WT/DS435/R/Suppl.1, WT/DS441/R/Suppl.1  
WT/DS458/R/Suppl.1, WT/DS467/R/Suppl.1  
 
28 June 2018 
(18-4052) Page: 1/150 
  Original: English  
 
 
 
 
AUSTRALIA – CERTAIN MEASURES CON CERNING TRADEMARKS, 
GEOGRAPHICAL INDICAT IONS AND OTHER PLAIN  PACKAGING 
REQUIREMENTS APPLICA BLE TO TOBACCO PRODU CTS AND PACKAGING  
REPORTS OF THE PANEL S 
Appendices  
SCI redacted, as indicated [[***]]  
 
This supplement contains Appendices A to E to the Reports of the Panels to be found in document 
WT/DS435 /R, WT/DS441/R, WT/DS458/R, WT/DS467/R.   
 
 
_______________  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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Table of Contents  
 
APPENDIX  A: POST -IMPLEMENTATION EVIDENCE ON NON -BEHAVIOURAL 
OUTCOMES OF THE TPP MEASURES  ................................ ................................ ...............  A-1 
1  EVIDENCE RELATING TO  THE APPEAL OF TOBACC O PRODUCTS SINCE THE  ENTRY 
INTO FORCE OF THE TPP MEASURES  ................................ ................................ ..................  A-2 
2  EVIDENCE RELATING TO  THE EFFECTIVENESS OF G HWS SINCE THE ENTRY INTO 
FORCE OF THE TPP MEASURES  ................................ ................................ ..........................  A-7 
3  EVIDENCE RELATING TO  THE ABILITY OF TOBAC CO PACKAGING TO MISL EAD 
CONSUMERS ABOUT THE HARMFUL EFFECTS OF S MOKING SINCE THE ENT RY INTO 
FORCE OF THE TPP MEASURES  ................................ ................................ ........................  A-16 
4  OVERALL CONCLUSION O N POST -IMPLEMENTATION EVIDE NCE ON 
NON-BEHAVIOURAL OUTCOMES  ................................ ................................ ......................  A-18 
APPENDIX  B: EVIDENCE ON QUITT ING-RELATED OUTCOMES AND  OTHER DISTAL 
OUTCOMES SINCE THE E NTRY INTO FORCE OF T HE TPP MEASURES  ..............................  B-1 
1  EVIDENCE RELATING TO  QUITTING -RELATED COGNITIONS S INCE THE ENTRY INTO 
FORCE OF THE TPP MEASURES  ................................ ................................ ..........................  B-2 
2  EVIDENCE RELATING TO  PACK CONCEALMENT AND  MICRO -INDICATORS OF CONCER N 
SINCE THE ENTRY INTO  FORCE OF THE TPP MEASURES  ................................ .......................  B-9 
3  EVIDENCE RELATING TO  QUIT ATTEMPTS SINCE THE ENTRY INTO FORCE  OF THE 
TPP MEASURES  ................................ ................................ ................................ ..............  B-17 
4  EVIDENCE RELATING TO  THE PREDICTIVE RELAT IONSHIPS BETWEEN PRO XIMAL 
OUTCOMES AND DISTAL OUTCOMES SINCE THE E NTRY INTO FORCE OF T HE 
TPP MEASURES  (NATIONAL TOBACCO PL AIN PACKAGING TRACKI NG SURVEY)  ......................  B-22 
5  OVERALL CONCLUSION O N POST -IMPLEMENTATION EVIDE NCE ON 
QUITTING -RELATED OUTCOMES AND  OTHER DISTAL OUTCOME S ................................ ........  B-25 
APPENDIX  C: EVIDENCE ON SMOKI NG PREVALENCE FOLLOW ING THE ENTRY 
INTO FORCE OF THE TPP MEASURES  ................................ ................................ .............  C-1 
1  WHETHER SMOKING PREV ALENCE DECREASED FOL LOWING THE IMPLEMENT ATION OF 
THE TPP MEASURES  ................................ ................................ ................................ .........  C-2 
2  WHETHER THE REDUCTIO N OF SMOKING PREVALE NCE ACCELERATED FOLL OWING 
THE IMPLEMENTATION O F THE TPP MEASURES  (ROY MORGAN SINGLE S OURCE)  ..................  C-18 
3  WHETHER THE TPP MEASURES  CONTRIBUTED TO THE R EDUCTION IN SMOKING 
PREVALENCE  ................................ ................................ ................................ .................  C-22 
4  OVERALL  CONCLUSION ON POST -IMPLEMENTATION EVIDE NCE ON SMOKING 
PREVALENCE  ................................ ................................ ................................ .................  C-38 
APPENDIX  D: EVIDENCE RELATING  TO TOBACCO PRODUCT S ALES AND 
CONSUMPTION FOLLOWIN G THE ENTRY INTO FOR CE OF THE TPP MEASURES  .............  D-1 
1  WHETHER CIGARETTE SA LES VOLUMES DECREASE D FOLLOWING THE 
IMPLEMENTATION OF TH E TPP MEASURES  ................................ ................................ ..........  D-2 
2  WHETHER THE REDUCTIO N OF CIGARETTE SALES  VOLUMES ACCELERATED AFTER 
THE ENTRY INTO FORCE  OF THE TPP MEASURES  ................................ ...............................  D-13 
3  WHETHER THE TPP MEASURES  CONTRIBUTED TO THE R EDUCTION IN CIGARETT E 
SALES VOLUMES AND CO NSUMPTION  ................................ ................................ ..............  D-20 
4  EVIDENCE RELATING TO  THE EVOLUTION OF IMP ORTS OF CIGARS  ................................ .. D-36 
5  OVERALL CONCLUSION O N POST -IMPLEMENTATION EVIDE NCE ON TOBACCO 
PRODUCT SALES VOLUME S ................................ ................................ .............................  D-39 WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/D S458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  APPENDIX  E: POST -IMPLEMENTATION EVIDE NCE ON DOWNWARD 
SUBSTITUTION IN THE CIGARETTE MARKET  ................................ ................................ . E-1 
1  WHETHER DOWNWARD SUB STITUTION IN CIGARET TES INCREASED FOLLOW ING THE 
IMPLEMENTATION OF TH E TPP MEASURES  ................................ ................................ ..........  E-2 
2  WHETHER DOWNWARD SUB STITUTION IN CIGARET TES ACCELERATED AFTE R THE 
ENTRY INTO FORCE OF THE TPP MEASURES  ................................ ................................ ........  E-8 
3  WHETHER THE TPP MEASURES  CONTRIBUTED TO DOWNW ARD SUBSTITUTION IN 
CIGARETTES  ................................ ................................ ................................ .................  E-15 
4  OVERALL CONCLUSION O N POST -IMPLEMENTATION EVIDE NCE ON DOWNWARD 
SUBSTITUTION IN CIGA RETTES  ................................ ................................ .......................  E-19 
 
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  LIST OF FIGURES  
Figure  Page  
Figure B. 1: Event Study of Calls to the Quitline  B-20 
Figure C.1: Smoking Prevalence Based on RMSS Data  C-3 
Figure C.2: Smoking Prevalence Based on OECD Dataset on Non -Medical Determinants in Australia and 
Selected OECD Countries   C-4 
Figure C.3: Smoking Prevalence Based on OECD Dataset on Non -Medical Determinants in Australia and 
Selected European Countries  C-5 
Figure C.4: Smoki ng Prevalence Based on NDSHS Data  C-6 
Figure C.5: Youth Smoking Prevalence Based on NDSHS Data  C-6 
Figure C.6: Youth Smoking Prevalence with Confidence Interval Based on NDSHS Data  C-7 
Figure C.7: Smoking Prevalence Based on NHS Data  C-8 
Figure C.8: Youth Smoking Prevalence Based on ASSAD Data  C-9 
Figure C.9: Smoking Behaviour Based on Roy Morgan Research Data  C-10 
Figure C.10: New South Wales Consumer Smoking Behaviour Based on CITTS Data  C-11 
Figure C.11: Smoking Prevalence in New South Wales Bas ed on CINSW Survey Data  C-12 
Figure C.12: Smoking Prevalence Among Youth in New South Wales Based on SSHBS Data  C-13 
Figure C.13: Smoking Prevalence in South Australia Based on SAHOS Data  C-14 
Figure C.14: Smoking Prevalence in South Australia Based on South  Australia  Survey  Data C-14 
Figure C.15: Smoking Prevalence in Victoria Based on VSHS Data  C-15 
Figure C.16: Smoking Prevalence in Victoria Based on NDSHS Data  C-16 
Figure C.17: Smoking Prevalence in Australia  C-17 
Figure C.18: Smoking Prevalence and Linear Trend  C-19 
Figure C.19: Smoking Prevalence and Pre - and Post -TPP Trends  C-21 
Figure C.20: Tobacco Price and Linear Trend  C-34 
Figure D.1: Monthly Cigarette Sales Volumes Based on IMS/EOS Data  D-3 
Figure D.2: Annual Cigarette Sales Volumes Ba sed on IMS/EOS Data  D-4 
Figure D.3: Average Monthly Cigarette Sales Volumes Based on IMS/EOS Data  D-5 
Figure D.4: Per Capita Monthly Cigarette Sales Volumes Based on IMS/EOS Data  D-6 
Figure D.5: Cigarette Sales Volumes Based on Nielsen Data  D-7 
Figure D.6: Per Capita Monthly Cigarette Sales Volumes Based on Aztec Scanner Data  D-8 
Figure D.7: Quarterly Cigarette Sales Volume based on IMS/EOS, Nielsen and Aztec Data  D-9 
Figure D.8: Household Expenditure on Tobacco and Cigarettes based on ABS Data  D-10 
Figure D.9: Monthly Cigarette Sales Volumes Based on IMS/EOS, Nielsen and Aztec Data  D-11 
Figure D.10: Indexes of Cigarette Sales Volumes Based on IMS/EOS, Nielsen and Aztec Data  D-12 
Figure D.11: Per Capita Cigarette Sales Volumes Based on IMS/EOS, Nielsen and Aztec Data  D-13 
Figure D.12: Event Study of Per Capita Cigarette Sales Volumes Based on IMS/EOS Data  D-17 
Figure D.13: Alternative Event Study of Per Capita Cigarette Sales Volumes Based on IMS/EOS Data  D-19 
Figure D.14: Cigarette Sales Volumes Pre - and Post-TPP Trends  D-20 
Figure E.1: Monthly Sa les Volumes of Higher - and Low -Priced Sticks Based on IMS/EOS Data  E-2 
Figure E.2: Monthly Sales Volumes Ratio of Higher - to Low -Priced Sticks and Ratio of Average H igher to 
Low Prices Based on IMS/EOS Data  E-3 
Figure E.3: Weekly Sales Volumes Ratio of Higher - to Low -Priced Sticks Based on Aztec Data  E-4 
Figure E.4: Month ly Brand Preference for Higher -Priced versus Low -Priced Brands and Ratio of Average 
Higher to Lo w Prices Based on RMSS Data  E-5 
Figure E.5: Graphical Assessment of Monthly Sales Volumes Ratio of Higher - to Low -Priced Sticks 
Based on IMS/EOS and Aztec Data  E-6 
Figure E.6: Graphical Assessment of Brand Preference Based on RMSS Data  E-7 
Figure E.7: Graphical Assessment of Difference in Brand Preference Based on RMSS Data  E-7 
Figure E.8: Trend Assessment of Monthly Sales Volumes Ratio of Higher - to Low -Priced Sticks and Ratio 
of Average Higher to Low Prices Based on IMS/EOS Data   E-8 
Figure E.9: Event Study on Sales Volumes Ratio of Higher - to Low -Priced Sticks Based on IMS/EOS 
Data E-9 
Figure E.10: Event Study on Sales Volumes Ratio of Higher - to Low -Priced Sticks Based on Aztec Data  E-10 
Figure E.11:  Monthly Preference for Higher -Priced versus Low -Priced Brands and Ratio of Average 
Higher to Low Prices Based on RMSS Data  E-11 
Figure E.12: Preference for Higher -Priced versus Low -Priced Brands Pre - and Post -TPP Trends Based on 
RMSS Data  E-12 
Figure E. 13: Sales Volumes Ratio of Higher - to Low -Priced Sticks Pre - and Post -TPP Trends Based on 
IMS/EOS Data  E-13 
Figure E.14: Ratio of Average Higher to Low Prices and Linear Time Variable Based on RMSS Data  E-14 
 
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  APPENDIX  A: 
  
POST -IMPLEMENTATION EVIDE NCE  
ON NON-BEHAVIOURAL OUTCOMES  OF THE TPP MEASURES  
 
1.  In these proceedings , the parties submitted  as exhibits a number of peer-reviewed studies 
investigating the post-implementation impact of the TPP measures  and enlarged GHWs  on 
non-behavioural proximal outcomes , namely : (i) reduction in the appeal of tobacco products ; 
(ii) increased effectiveness of GHWs ; and ( iii) reduction in the ability of the pack to mislead  
consumers about smoking harm s.1 This Appendix  reviews and discusses this evidence, in the light 
of the relevant expert reports submitted by the parties.  
2.  Australia submits that the available post -implementation empirical studies on non -behavioural 
outcomes confirm that TPP and enlarged GHWs  have (i) reduc ed appeal, (ii)  increas ed the 
effectiveness of GHWs , and (iii)  reduc ed the ability of packaging to mislead  consumers about the 
harmful effects of tobacco products .2  
3.  Based on the review of these peer -reviewed papers, and in some cases the re-analysis of the 
data used in the se papers,  the Dominican  Republic , Honduras and Indonesia  argue that the 
TPP measures  have not had the expected effects on the antecedents of behaviour posited in 
Australia 's conceptual framework  of the TPP measures .3 In particular, they contend that beyond 
the obvious findings that the pack is less visually appealing and people more often notice the 
larger GHWs  first, empirical evidence shows little or no effects of the policies on the antecedents of 
behaviour . They further claim that th e variables relating to beliefs, attitudes and intentions 
towards smoking were almost entirely unaffected by the TPP measures .4  
4.  In addition, the experts of the Dominican  Republic  and Indonesia argue that some of the 
published empirical studies on Australi a's TPP measures  provide an inaccurate picture of the 
empirical evidence.  They state that  some of these papers failed to report the results for more than 
half of all the variables available in the survey dataset, which were overwhelmingly not statistically  
significant, suggesting no impact by plain packaging on these variables. The Dominican  Republic  
and Indonesia contend that the authors of some of these published studies also failed to explain 
that a number of the reported statistically significant effects had vanished by the end of the first 
year of Australia's implementation of the TPP measures  as a result of wear -out effects.  The 
Dominican  Republic  and Indonesia  further criticize these papers for failing to report the magnitude 
of the statistically significant effects. According to their experts, most of the reported statistically 
significant effects are small, suggesting that the TPP measures  have little importance in shifting 
behaviour.5  
5.  Each peer -reviewed empirical pap er discussed by the parties either addresses different 
questions or is based on specific survey data , or both.  We discuss , for each proximal  outcome, 
each survey data and corresponding paper separately , before turning to an overall assessment.  
We approach this assessment on the basis that our task  is not  to conduct our own econometric 
assessment of the TPP measures ' impact  on the proximal outcomes  identified above but rather to 
                                                
1 Some of these papers also analyse more distant varia bles, such as beliefs, attitudes and intentions 
towards smoking and quitting as well as quitting attempts. These papers are also discussed in Appendix  B. 
2 See Australia's first written submission, paras.  201-205; and comments on the complainants' 
responses  to Panel question No. 146, para. 7. 
3 See Ajzen et al. Data Report,  (Exhibit DOM/IDN -2); Ajzen et al. Second Data Report,  (Exhibit 
DOM/IDN -4); Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6); Ajzen et al. Second Data Rebuttal 
Report , (Exhibit DOM/IDN -8); Klick Supplemental Rebuttal Report , (Exhibit HND -122); and Klick Second 
Supplemental Rebuttal Report , (Exhibit HND -165).  
4 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  10-22. 
5 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  23-27. WT/DS435/R/Suppl.1 • WT/DS44 1/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  examine , on the basis of the evidence before us,  the overall robustness of the econometric 
evidence submitted by the parties  in this respect.6 
1  EVIDENCE RELATING TO  THE APPEAL OF TOBACCO PRODUCTS SIN CE THE ENTRY INTO 
FORCE OF THE TPP MEASURES  
6.  Four peer-reviewed papers have analysed empirically the impact  of Australia's TPP measures  
on the appeal of tobacco products : (i)  Wakefield  et al. 2015; (ii)  Dunlop et al. 2014; 
(iii) White  et al. 2015a; and (iv)  Miller et al. 2015.7  
7.  Different survey data were used by several of these published papers. Most survey d ata cover 
adult smokers, with the exception of a survey of students attending secondary schools .8 Most of 
these peer -reviewed papers analyse only cigarette smokers, although  some of these survey 
datasets  also include information on cigar smokers. Only one peer -reviewed stud y analyse s 
appeal -related outcomes in relation to cigar and cigarillo smokers.9  
1.1  Datasets and related studies  
1.1.1   National Tobacco Plain Packaging Tracking Survey  
8.  In order to track the effect o f the TPP measures , Australia 's Department of Health and Ageing  
funded the National Tobacco Plain Packaging Tracking Survey (NTPPTS), a nationwide  tracking 
survey conducted by the Cancer Council Victoria  (CCV) . The NTPPTS is a continuous 
cross-sectional ba seline survey of about 100 interviews per week of current smokers and recent 
quitters aged 18 to 69 years, conducted from 9 April 2012 to 30 March  2014. A follow -up survey of 
baseline participants then took place approximately four weeks after the initial survey, with 
follow -up surveys conducted from 7  May 2012 to 4  May 2014.10 The NTPPTS data ha ve been used 
in several peer -reviewed papers published in the supplement to the Tobacco Control journal in 
2015.11 
9.  Wakefield et al. 2015 use the NTPPTS data to investigate among adult smokers the impact of  
Australia's TPP measures  on its three specific mechanisms, namely ( i) the appeal of tobacco 
products, ( ii) the effectiveness of GHWs , and ( iii) the ability of packaging to mislead about 
smoking harms.12 The auth ors estimate a logistic model, using baseline survey weights and 
controlling  for individual characteristics , such as sex, age, highest educational attainment, nicotine 
dependence and socio -economic status .  
10.  Overall, Wakefield et al. 2015 conclude that Australia's TPP measures  have statistically 
reduced the appeal of tobacco products for adult cigarette smokers. This statistically significant 
effect  was sustained up to 12  months after implementation . In particular, the authors report a 
statistically sign ificant increase in the proportion of adult smokers that disliked their pack , 
perceived lower pack appeal,  lower cigarette quality , lower satisfaction  and lower value, and 
disagreed that brands differed in prestige.  However, the authors find that there was  no statistical ly 
significant  change in the proportion of adult smokers that perceived differences in the taste of 
different brands.  
11.  The Dominican  Republic  and Indonesia submit ted an expe rt report by Ajzen et al.13, also 
relied upon by Honduras14, which review s the accuracy and completeness of the findings reported 
                                                
6 For a similar approach, see Panel Reports, US – COOL (Article 21.5 – Canada and Mexico) , para. 7.183 
(citing Panel Reports, US – COOL , para. 7.539).  
7 See Wakefield et al. 2015, (Exhibits  AUS-206, DOM -306); Dunlop et al. 2014, (Exhibits AUS-207, 
HND-132, DOM -199); White  et al. 2015a, (Exhibit s AUS-186, DOM -235); Miller et al. 2015, (Exhibits AUS -102, 
DOM-315).  
8 See White et al. 2015a , (Exhibit s AUS-186, DOM -235); and White et al. 2015b,  (Exhibits HND -135, 
DOM-236, DOM -288).  
9 See Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
10 See Dominican  Republic's  second written submission, paras.  380-429.  
11 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), para. 6. 
12 See Wakefield et al. 2015, (Exhibits  AUS-206, DOM -306).  
13 Ajzen et al. Data Report, (Exhibit DOM/IDN -2). WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  in Wakefield et al. 2015. They reconsider the NTPPTS dataset and present the results of a logistic 
model for dichotomized outcome variables, a linear model for continuous outcome variables , and 
an ordered logit model for categorical outcome variables, using baseline survey weights and 
controlling for individual characteristics.  
12.  The Dominican Republic argues that the published studies greatly underreport the results of 
the NTPPTS survey, with a p attern of underreporting unfavourable results.15 Ajzen et al. argue that 
Wakefield et al. 2015 failed to report the results of three other appeal -related outcome variables 
that were not statistically significant . According to Ajzen et al., the authors also failed to address 
the small magnitude of the observed statistically significant effects .16 More generally, the 
Dominican  Republic  considered Australia's argument that the NTPPTS was much broader in scope 
than Wakefield et al. 2015 to be surprising, as this message was not expressed in Wakefield et al. 
2015 or in the journal's editorial  and the papers were presented as the first comprehensive 
evaluation of the TPP measures .17  
13.  Ajzen et al. conclude that the TPP measures  have had very little impact on the mecha nisms 
posited to underlie change in smoking behaviours  because  the most notable changes were  only in 
pack appeal, with the effect on pack dislike moderate to strong, but the impact on product dislike, 
brand loyalty and identification was much smaller  or statistically not significant . In particular, the 
authors find that the increase in the proportion of adult smokers that  perceived lower pack appeal 
was statistically moderate to large but with partial evidence of wear -out effect . Ajzen et al. also 
report that the effects on perceived lower cigarette quality and satisfaction were statistically  
positive but small and without any wear -out effect . Similarly, they find that the effect s on 
perceived lower value and brands' prestige were statistically very sm all but without any wear -out 
effect.  They further confirm Wakefield et al.'s 2015 finding  that there was no statistical ly 
significant  change in the proportion of adult smokers that  perceived differences in the taste of 
different brands . They reach a s imilar conclusion  for three other variables , not reported by 
Wakefield et al. 2015, namely whether the smoker w ould stay loyal to a regular brand if the store 
ran out of it; agreed that they felt connected to other s smoking their regular brand , and (very) 
often noticed others with their regular brand in the past month.18 
14.  Honduras submitted an expert report by Professor  Klick, which examines  the NTPPTS data on 
the effect of the TPP measures  on the appeal of smoking.19 Professor  Klick submits that ther e are a 
host o f items relating to the appeal of smoking that appear to have worse ned following the 
introduction of the TPP measures , but which have been ignored by Wakefield et al. 2015.20  
15.  Professor  Klick presents the results of an ordered probit model, which controls f or the 
TPP measures  (early TPP period and formal TPP period), gender, age , education, socio-economic 
status and a linear time trend.21 He finds that the TPP measures  are not associated with a 
decrease in the reported frequency of thoughts about enjoying smoking.22 
16.  According to Australia, t he survey data are most suited to assessing changes in the specific 
mechanisms of the TPP measures . In that context, Australia contends that the positive findings 
reported by Ajzen et al. are completely consistent with Wakefield  et al. 2015's findings, i.e. that 
                                                                                                                                                  
14 See Honduras's second written submission, paras.  171-185. We note that Cuba states, "Cuba did not 
submit [this] expert report prepared by Professor  Ajzen, and therefore no assumptions can be made as to 
Cuba's position c oncerning the effectiveness of plain packaging on the basis of that report." Cuba's response to 
Panel question No. 146. 
15 Dominican Republic's comments on Australia's response to Panel question No. 198, paras. 700 -709. 
16 See Ajzen et al. Data Report, (Exhi bit DOM/IDN -2), paras.  98-101. 
17 Dominican  Republic' s comments on Australia 's response to Panel question No. 198, para. 705. 
18 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  89-97, 148 -150, Appendix  A, pp. 78-80. 
19 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  54-73.  
20 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  61-63. 
21 Professor  Klick explains that, unlike Wakefield et al. 2015, he omits the measure of exposure to mass 
media anti -smoking message s, cigarette costliness and heaviness of smoking index, because these variables 
are endogenous. He further explains that the inclusion of these variables does not change the results he 
presents. See Klick Supplemental Rebuttal Report , (Exhibit HND -122), fn  35.  
22 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  66-68. We note that 
Professor  Klick considers the questions "how important is quitting to the person" and "how frequently people 
think about quitting" relevant to the appeal of tobac co. The results of these questions are discussed in 
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  Australia's TPP measures  reduce the appeal of tobacco products.23 Australia further argues that 
because the scope of the NTPPTS wa s much broader than the specific and limited focus of 
Wakefield et al. 2015, the results of the study in question  were reported appropriately and 
consistently . Australia also  contends that the complainants' implication that unfavourable results 
were not reported is directly contradicted by the facts.24  
1.1.2   Cancer Institute New South Wales Tracking Survey  
17.  The Cancer Institute New South Wales Tobacco Tracking Survey (CITTS) is a weekly tracking 
telephone survey of smokers and recent quitters (who quit in the p ast 12 months) involving 
approximately 50 interviews conducted per week throughout the year. The survey monitors 
smoking -related thoughts and behaviours among adult smokers and recent quitters in New South 
Wales.  
18.  Dunlop et al. 2014 uses the  CITTS data  to investigate the impact of Australia's TPP measures  
on two of the specific mechanisms : (1)  decreasing the promotional appeal of packaging and 
(2) increasing the impact of health warnings.25 The analysis covers 15,375 randomly selected adult 
smokers between April 2006 and May 2013 (i.e. six months after the introduction of the 
TPP measures ). Adjusting for background trends, seasonality, antismoking advertising activity and 
cigarette costliness, the authors  estimate autoregressive integrated moving average ( ARIMA) 
models .  
19.  Overall, Dunlop et al. 2014 conclude that Australia's TPP measures  have had an early 
statistically significant effect in reducing the promotional appeal of the packaging among adult 
smokers.26 In particular, the authors find a significant increase in the proportion of adult smokers 
strongly disagreeing that t he look of their cigarette pack is attractive , says something good about 
them, influences the brand they buy, makes their pack stand out, is fashionable  and matches their 
style.  Accordi ng to Dunlop et al. 2014, c hanges in these appeal -related outcomes were maintained 
six months following the TPP measures ' implementation . 
1.1.3   Australian Secondary Students Alcohol Smoking and Drug Survey  
20.  The 2013 Australian Secondary Students Alcohol Smoking and Drug (ASSAD) survey 
extension is a follow -up survey of students attending secondary schools that participated in the 
2011 ASSAD survey in Victoria and Queensland. In total 82 schools across both states 
participated. The 2013 survey extension was design ed to compare attitudes to cigarette packaging 
before and after the introduction of Australia's TPP measures , and included questions about beliefs 
and attitudes about cigarette packaging, ratings of popular cigarette brands, noticing health 
warnings on cig arette packs, awareness of the specific harms of tobacco use, and perceptions of 
the prevalence of smoking and intention to smoke.27 
21.  White  et al. 2015a use the responses from the ASSAD survey extension to analyse , among 
other things, the impact of plain packaging on the appeal of cigarette packs and brands  among 
students aged 12 -17 years.28 The authors estimate generali zed linear regression models and 
multinomial logistic regression models controlling for smoking status, age, sex, schoo l education 
sector and state . 
22.  Overall,  White et al. 2015a conclude that the TPP measures  have reduced the appeal of 
cigarette packs among adolescents . In particular, they found a statistically significant decrease in 
the proportion of students, who had see n a cigarette pack in the previous six months, that rated 
positively the brand character and cigarette pack. The authors note that the effect on brand 
character and cigarette pack was even larger among younger smokers. White et al. 2015a also 
                                                
23 Australia's comment s on the complainants ' responses to Panel question No. 146, para. 7. 
24 Australia's response to Panel question No.  198, paras.  298-303. 
25 See Dunlop et al. 2014, (Exhibits  AUS-207, HND -132, DOM -199).  
26 See Tobacco Plain Packaging PIR , (Exhibit AUS -624), paras.  77-80. 
27 See, e.g. Dominican  Republic 's second written submission, paras.  443-456. 
28 See White  et al. 2015a, (Exhibit s AUS-186, DOM -235). WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  report a stat istically significant increase in the proportion of students, who had seen a cigarette 
pack in the previous six months, rat ing negatively cigarette pack s.29  
23.  The Dominican  Republic  and Honduras argue that , in the absence of full access to the ASSAD 
survey d ata it requested , it is impossible to make an objective assessment of the findings in White 
et al. 2015a. The Dominican  Republic  submits  that as its analysis of the NTPPTS data showed, the 
published results in White et al. 2015a may provide an unduly positive and inaccurate impression 
of the full dataset. The Dominican  Republic  argues that although the study concludes that there is 
a change in the visual appeal of packs, that reduced appeal does not have any meaningful impact 
on perceptions of the harmfulness of smoking, quit intentions and secondary indicators of 
quitting.30 Professor  Ajzen , in an expert report submitted by  the Dominican  Republic , Honduras 
and Indonesia,  submits that the impact of Australia's TPP measures  on visua l appeal  of tobacco 
products reported in White et al. 2015a  and defined as "modest" by their authors  makes it difficult 
for the change in appeal to carry all the way through the posite d chain of effects to behaviour .31 
1.1.4   Cigar and cigarillo smoker s survey s 
24.  Miller  et al. 2015 conducted individual interviews with ten  regular premium cigar smokers, as 
well as two focus groups with premium cigarillo smokers and occasional premium cigar smokers  
(with a total of 14 smokers) , and four focus groups with non -premium cigarillo smokers  (with a 
total of 28 smokers) , in February  and March  2014, 15 months after the TPP measures  became 
mandatory . In addition, in February  and March  2014 the authors  conducted an online survey of 
current cigar and cigarillo smokers. Of the ori ginal 56,589 people contacted, only 268 met all 
inclusion criteria, one of these criteria  being  current smokers of these products.32 Rather than 
undertaking an econometric analysis, the authors present descriptive statistics of the results of 
these intervie ws, focus groups and the online survey.  
25.  According to Miller et al. 2015, there was incomplete exposure to the TPP measures  on cigar 
and cigarillo  smokers during the first 15 months following the ir implementation , with many 
premium cigar smokers purchasing  fully branded cigars in boxes duty free or online and singles in 
non-compliant packaging. R eported exposure was seemingly highest among non -premium cigarillo 
smokers. However, the authors  note that when exposure occurred, the TPP measures  reduced 
perceived packaging appeal . In particular, they find that although changes in perceived taste, 
harm and value were minimal for experienced premium cigar smokers, they indicated some fear of 
being equated with cigarette smokers. Miller et al. 2015 also find that occasional premium cigar 
and premium cigarillo smokers with higher plain packaging exposure (gained by purchasing boxes 
rather than singles  cigars ) perceived  that cigar/package appeal and value had declined.  Similarly, 
they report  that more non-premium cigarillo smokers affirmed that the  perceived appeal, quality, 
taste, enjoyment and value  had decreased . They also find that online survey participants stated 
that packaging appeal ha d diminished  since the implementation of the TPP measures .33  
26.  Ajzen et al., in their expert report submitted by  the Dominican  Republic  and Indonesia,  
contend  that the results  reported by Miller et al. 2015 suffers from several methodological 
shortcomings, such as the non -representativeness of survey participants, unsuitability of focus 
groups and interviews to draw causal inferences, failure to control for exposure to anti -smoking 
campaigns and changes in tobacco prices, and absence of "baseline" information collected before 
the implementation of the TPP measures . According to Ajzen et al., these methodological 
shortcomings severely limit any conclusions that can be drawn from the results .34 
27.  Ajzen et al. claim  that even if Miller et al.'s 2015 results were taken at face value, the study 
revealed a few  notable effects  of the TPP measures  that were clearly to be expected and unlikely 
to influence actual smoking behaviour, namely the changes in the appeal of the package, 
                                                
29 See White  et al. 2015a, (Exhibit s AUS-186, DOM -235). 
30 See Dominican  Republic 's second written submission, paras.  443-456; and comment s on Australia's 
response to Panel question No. 196, para. 390. 
31 See Ajzen Report , (Exhibit DOM/HND/IDN -3), paras.  174-178. 
32 See Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
33 See Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
34 See Dominican  Republic's  second written submission, paras.  457-462. See Ajzen et al. Data Report, 
(Exhibit DOM/IDN -2), paras.  251-262. WT/DS435/R/Suppl.1 • WT/DS44 1/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  increased noticeability of the health warnings, and perceived less value for money. However, 
accordin g to Ajzen et al., the fact that tobacco products were seen as less value for money may 
have been due to the rise in their cost as a result of the December  2013 tax increase and other 
factors.  In addition, they argue  that Miller et al. 2015 failed to  mention that the participants also 
reported no change  with respect to smoking enjoyment. More generally , Ajzen et al. contend  that 
smoking cigarettes and smoking cigars (or cigarillos) are different behaviours, and their 
determinants are also likely to di ffer. They conclude that consequently  whatever effects the 
TPP measures  are, or are not, found to have on cigarette -related cognitions and behaviours, such 
findings cannot be generalized to cigars.35 
1.2  Analysis by the Panel  
28.  We note that among the peer -review ed papers discussed by the parties, four studies analyse 
the impact of the TPP measures , as applied together with enlarged GHWs , on the appeal of 
tobacco products.  
29.  A careful review of Wakefield et al. 2015 and Dunlop et al. 2014 and the econometric 
evidence submitted by the Dominican  Republic , Honduras and Indonesia leads us to conclude that 
there is some empirical evidence suggest ing that the TPP measures  have reduced the appeal of 
tobacco products among adult cigarette smokers , in terms of pack dis like, product dislike, 
perceived lower quality, satisfaction and value, lower brand s' prestige , and connection  and 
identification .36  
30.  We further note that the Dominican  Republic  and Indonesia qualify th e finding s reported in 
Wakefield et al. 2015 by highlig hting that for most of the appeal -related outcomes, although  
statistically significant, the impact is small, or very small in the case of perceived lower value and 
brand prestige, but without any evidence of wear-out effects. Only the impact on perceived lower 
pack appeal , which  is found to be statistically moderate , shows  some partial evidence of wear -out 
effect.37 We also note that  Ajzen et al.'s claim that Wakefield et al. 2015 did not report the results 
of three other outcome variables38, which were not statistically significant, is actually only valid for 
the variable related to brand loyalty39 and to a lesser extent to the variable related to brand 
connection . In fact, Ajzen et al. also find in the ordered logistic regression of the variable on brand 
connection a statistically significant increase in the proportion of adult smokers that disagree they 
feel connected to others smoking their regular brand. Similarly, Ajzen et al. report a decrease , 
albeit small,  in the proportion of adult smokers that (very)  often noticed others with their regular 
brand in the past month, which is statistically significant at 10% level in the logistic regression or 
5% level in the linear regression and ordered logistic regression .40  
31.  We note that the empirical evidence available to us on  the impact of the TPP measures  on the 
perception of tobacco appeal  among adolescents is limited to one peer -reviewed study  by White 
et al. 2015a . In particular , White et al. 2015a suggest that the reduction in the appeal of cigarette 
packs and brands to adolescents , though modest , was statistically significant  seven to 12  months 
after the introduction of the TPP measures . This result  is consistent with th e findings  reported in 
Wakefield et al. 2015 and Dunlop et al. 2014.  
                                                
35 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  251-262. 
36 See Wakefield et al. 2015, (Exhibits  AUS-206, DOM -306); Dunlop et al. 2014, (Exhibits AUS -207, 
HND-132, DOM -199); and Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  89-97, 148 -150, Appendix  A, 
pp. 78-80. We note that in his review of Dunlop et al.'s 2014 analysis, Professor  Klick did not discuss and 
re-analyse the questions of the CITTS related to appeal. We also note that Professor  Klick did not mention in 
his reports whether the commissioned Roy Morgan Research Survey also asked questions related to the appeal 
of tobacco products.  
37 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  89-97, 148 -150, Appendix  A, pp. 78-80.  
38 We are also not persuaded that the variable "thought about enjoying smoking" referred to by 
Professor  Klick is directly relevant to assess the impact of the appeal of tobacco products. See para. 15 above. 
In fact, we note that this variable was discussed by Ajzen et al.  Data Report, (Exhibit DOM/IDN -2) in the 
context of the balance between smoking enjoyment and concern . See Appendix  B. 
39 We note that Ajzen et al.  did not discuss the fact that in some specifications, such as the logistic 
regression of the brand loyalty variable, only three explanatory variables are statistically significant (besides 
the constant). See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), bac k-up material.  
40 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), Appendix  A, pp. 78-80. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  32.  Similarly, we note that specific empirical evidence before us on the impact of the 
TPP measures  on appeal of cigars and cigarillos  is limited to the peer -reviewed paper by Miller 
et al. 2015, in which a descriptive statistics analysis finds that occasional premium ci gar and 
premium cigarillo smokers with higher TPP exposure, non -premium cigarillo smokers, and online 
survey participants reported reduced perceived appeal since the implementation of the 
TPP measures .41 We note that many of the criticisms raised by Ajzen et al. are actually 
acknowledged by Miller et al. 2015. Specifically, the authors recognize that the primary limitations 
of the study are the representativeness of the samples and the accuracy of self -report measures, 
most notably recall. In the absence of other relevant data or study on cigars, it is however unclear 
to what extent the results would have changed if Miller et al. 2015 had explicitly accounted for 
exposure to anti -smoking campaigns and changes in tobacco prices or applied a different 
methodolo gy. In that context, we note that although Ajzen et al. submit that the conclusions about 
the impact of the TPP measures  on cigarettes cannot be generalized to cigars, they also recognize 
themselves that the impact of the TPP measures  on appeal reported in  Miller et al. 2015 was to be 
expected.  In fact, we note that Miller et al.'s findings are consistent with the findings published in 
the peer-reviewed studies on adult cigarette smokers and adolescents reviewed above . We 
therefore see no basis to reject in its entirety Miller et al.'s study on the basis of Ajzen et al.'s 
criticism of it.42 
2  EVIDENCE RELATING TO  THE EFFECTIVENESS OF GHWS  SINCE THE ENTRY INTO  
FORCE OF THE TPP MEASURES  
33.  Based on different datasets, five peer-reviewed pape rs have empirically investigated the 
impact of Australia's TPP measures  on the effectiveness of GHWs: (i) Wakefield et al. 2015; 
(ii) Yong et al. 2015; (iii) Dunlop et al. 2014; (i v) White et al. 2015b ; and ( v) Miller et al. 2015.43 
An expert report prepared by Professor  Klick and submitted by  Ukraine  also contains an analys is of 
the impact of the TPP measures  on the effectiveness of GHWs.44  
2.1  Datasets and related studies  
2.1.1   National Tobacco Plain Packaging Tracking Survey  
34.  In addition to analysing the im pact on tobacco products appeal, Wakefield et al. 2015 use the 
NTPPTS data to investigate the impact of Australia's TPP measures  on GHW effectiveness among 
adult smokers .45 The authors estimate a logistic model, using baseline survey weights and 
controlling for individual characteristics.  
35.  Overall, Wakefield et al. 2015 conclude that Australia's TPP measures  have had a statistically 
significant effect  among adult cigarette s mokers , generally sustained  for up to 12  months after 
implementation, on increasing health warning effectiveness.  In particular, the authors report a 
statistically significant increase in the proportion of adult smokers who noticed GHWs, attributed 
more motivation to quit ting to GHWs , avoided specific GHWs when purchasing  and covered their 
pack. However, they find that there was no statistical ly significant  change in the proportion of 
adult smokers who perceived exaggeration of harms.46 
36.  Ajzen  et al., in their expert report submitted by  the Dominican  Republic  and Indonesia, argue 
that Wakefield et al. 2015's conclusion that the TPP measures  are associated with consistent 
improvement in health warning effectiveness outcomes cannot withstand careful examination . 
                                                
41 See Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
42 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  255-256. 
43 See Wakefield et al. 2015, (Exhibits  AUS-206, DOM -306); Yong et al. 2015, (Exhibit DOM -382); 
Dunlop et al. 2014, (Exhibits AUS -207, HND -132, DOM -199); White et al. 2015b , (Exhibits HND -135, 
DOM-236, DOM -288); Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
44 See section 1.6. 6 in the main body of these Reports for a description of Ukraine's participation in 
these proceedings.  
45 See para. 8 above for a description of the NTPPTS data. S ee Wakefield et al. 2015, 
(Exhibits  AUS-206, DOM -306).  
46 As discussed in Appendix  B, we also note that Durkin et al. 2015 use the NTPPTS data to analyse the 
impact of the TPP measures on quitting -related variables and report greater increases in pack concealment and 
stubbing out cigarettes because of thoughts about the harm of smoking. See Appendix  B and Durkin et al. 
2015, (Exhibits AUS -215 (revised), DOM -305).  WT/DS435/R/Suppl.1 • WT/DS44 1/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  According to Ajzen  et al., Wakefield et al. 2015 underreport ed the results of seven questions 
related to knowledge about diseases that were not statistically significant, did not pay attention to 
the magnitude of the statistically significant effects and  failed to mention vanishing effects of some 
of these small effects.47 The Dominican  Republic  considered Australia's claim that the NTPPTS was 
much broader in scope than Wakefield et al. 2015 to be surprising, as this message was not 
expressed in Wakefield et al. 2015 or in the journal's editorial in which the study was published.48 
Ajzen et al. reconsider the NTPPTS data and present the results of a logistic model for 
dichotomized outcome variables, linear model for continuous outcome variables and ordered l ogit 
model for categorical outcome variables, using baseline survey weights and controlling for 
individual characteristics.  
37.  Ajzen  et al. conclude  that the TPP measures  have had a statistically moderate effect on the 
attention paid to the enlarged GHWs , but the impact of the TPP measures  on concealing packs and 
requesting packs with different  GHWs  was statistically small. They also f ind that the increase in the 
proportion of adult smokers that attributed more motivation to quit ting to GHWs  was statistically 
small and subject to a wear -out effect. However, Ajzen et al. find that the TPP measures  had no 
impact on most beliefs about the health risks of smoking , many of which were not published in 
Wakefield et al. 2015. In particular, Ajzen et al. report a statistically significant small increase in 
the proportion of adult smokers that freely recalled a disease on a current GHW and agreed that 
smoking causes blindness . For the remaining outcome variables related to beliefs about the health 
risks of smoking , Ajzen et al. find that there is no statistically significant change in the p roportion 
of adult smokers that perceived exaggeration of harms  and that agreed that  there are diseases 
caused by smoking , that smoking causes harm to unborn babies , that lung cancer is an old age 
disease, and that smoking causes stroke, mouth cancer, bladder cancer, and gangrene .49  
38.  Similarly, Ajzen et al. argue that Wakefield et al. 2015 failed to report the results on the 
balance between smoking enjoyment and concern. In their view, this is all the more surprising 
given that, in Brennan et al. 2015, the same six authors use the NTPPTS data and hypothesize 
that the balance between sm oking enjoyment and concern is "influenced by cigarette appeal, 
graphic health warning [GHW] effectiveness and perceived harm".50 Ajzen et al. find no 
statistically significant change in the proportion of adult smokers that thought about enjoyment of 
smokin g several/many times in the past month, were very/extremely concerned that smoking may 
affect health, and experienced more concern than enjoyment from/of smoking.51 Overall, Ajzen 
et al. contend that the weakening of the policy across the chain of effects d oes not reflect a 
limitation of the NTPPTS dataset, as argued by Professor  Chaloupka, but the theoretically expected 
decline  in the impact of TPP across the chain of effects from pack appeal to behaviour.52  
39.  Professor  Klick, in his expert report submitted b y Honduras, reviews the NTPPTS data relating 
to the effect of the TPP measures  on the effectiveness of GHWs.53 Professor  Klick contends  that a 
large number of outcomes in the NTPPTS data, not reported by Wakefield et al. 2015,  show that 
the TPP measures  have not improved the effectiveness of GHWs .54  
40.  Professor  Klick presents the results of an ordered probit model  and a logistic model , which 
control for the TPP measures  (early TPP period and formal TPP period), gender, age , education, 
socio-economic status and  a linear time trend.55 He finds that the TPP measures  had no 
statistically significant impact on the concerns about the effect of smoking on health  but had a 
                                                
47 See Ajzen et al. Data Report, (Exh ibit DOM/IDN -2), paras.  115-122. 
48 Dominican  Republic' s comments on Australia 's response to Panel question No. 198, para. 705. 
49 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  102-114, 151 -155, Appendix  A, pp. 81-83. 
50 See para. 8 above for a description of the NTPPTS data. Ajzen et al. Data Report, (Exhibit 
DOM/IDN -2), paras.  138-142. 
51 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras. 132-137, 159 -162, Appendix  A, pp.  87-89. 
52 Ajzen et  al. Data Rebuttal Report , (Exhibit DOM/IDN -6), para. 11 and Table 1 . 
53 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  74-81.  
54 See Klick Supplemental Rebuttal Report , (Exhibit HND-122), paras.  74-75. 
55 Professor  Klick explains that unlike Wakefield et al. 2015 he omits the measure of exposure to mass 
media anti -smoking messages, cigarette costliness and heaviness of smoking index, because these variables 
are endogenous. He furth er explains that the inclusion of these variables does not change the results he 
presented. See Klick Supplemental Rebuttal Report , (Exhibit HND -122), fn 35.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  negative and statistically significant in respondents' awareness of the causal relationship betwee n 
smoking and mouth cancer .56 
41.  Professor  Chaloupka, in an expert report submitted by  Australia, contends that the pattern of 
results reported by Ajzen et al. is consistent with the strengths and limitations of the NTPPTS data. 
Australia further claims that t he results of Wakefield et al. 2015, whose focus is more specific and 
limited than the much broader scope of the NTPPTS data, were reported appropriately and 
consistently . According to Australia the complainants' implication that unfavourable results were 
not reported is directly contradicted by the facts.57 In particular, Professor  Chaloupka argues that, 
as expected, Ajzen et al. found consistent and statistically significant effects for the impact of the 
TPP measures  on the most proximal outcomes, such as noticing and avoiding health warnings , but 
the impact is smaller, less statistically significant and less consistent as the focus shifts to less 
proximal outcomes, such as health knowledge and perceptions of the health risks , when looking at 
the impact in the overall sample of smokers and recent quitters.58 Professor  Chaloupka further 
contends  that the NTPPTS data cannot be used to assess the impact of TPP on the population most 
likely to be influenced by the measure, namely, never users who might have taken up tobacco use 
in the absence of TPP. According to Professor  Chaloupka, the NTPPTS data  can also not measure 
the impact of TPP on relapse among former smokers who are not categorised as "recent 
quitters".59 
2.1.2   International Tobacco Control Policy Evaluation Project  
42.  The International Tobacco Control (ITC) Policy Evaluation Project (ITC Project) is a 
longitudinal cohort survey to assess the impact, and identif y the determinants of, effective tobacco 
control policies in more than 20 countries, including Australia. The ITC Project covers a number of 
issues related to GHWs , including attention to health warnings, salience of health warnings and the 
effect of healt h warnings on consumers ' thoughts, behaviours and intentions to quitting.  The wave 
survey prior to the implementation of the TPP measures  was conducted between September  2011 
and February  2012, while the wave after the implementation was conducted between February  and 
May 2013.  
43.  Yong et al. 2015 use data from the Australian component of the ITC Project to assess the 
impact of the TPP measures ' GHW effectiveness. The authors estimate various generalised 
estimating equation (GEE) models controlling for age, sex, income, education, cigarettes per day, 
past year quit attempts, survey mode (phone vs. web) and wave of recruitment.60  
44.  Yong et al. 2015 find a statistically significant increase in the proportion of adult smokers who 
increased their attentional orient ation towards health warning labels, noticed them more, 
experienced cognitive reactions with respect to health warning labels and avoided health warning 
labels. However, the authors report no statistical ly significant  change in the proportion of adult 
smok ers who read health warning labels and for ego cigarettes. Yong et al. 2015 further find that 
the subgroup of respondents that switched from initially focusing away to focusing on the health 
warning labels following the introduction  of the TPP measures , noticed and read the health warning 
labels more, thought more about the harmful effects of smoking and avoided health warning 
labels, but did not for ego cigarettes. Conversely, Yong et al. 2015 show that the subgroup of 
respondents wh o chose to focus away fro m the health warning labels, noticed them less, 
experienced less cognitive reactions, and avoided  the health warning labels  less.61 
45.  Ajzen et al., in their expert report submitted by  the Dominican  Republic  and Indonesia, claim 
that they were unable to presen t a comprehensive assessment of the ITC dataset, including 
                                                
56 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  74-78 and 80-81. We note that  
Professor  Klick considers the question "how often the person stub out due to thoughts about the harm of 
smoking" to be relevant to the effectiveness of GHWs. The results of this question are discussed in Appendix  B.  
57 Australia's response to Panel questi on No.  198, paras.  298-303. 
58 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 9; and Chaloupka Third Rebuttal Report, 
(Exhibit AUS -604), paras.  2-7. 
59 Chaloupka Rebuttal Report, (Exhibit AUS -582), para.3.  
60 See Yong et al. 2015, (Exhibit DOM -382).  
61 Yong et al. 2015 (Exhibit DOM -382) note that the mechanism for this apparent reactance, i.e. the 
minority of smokers stimulated to shift from initially focusing on to focusing away from the warnings and 
reporting a reduction in avoidance, is not clear.  WT/DS435/R/Suppl.1 • WT/DS44 1/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  correcting for the possibility of false positive findings due to multiple hypothesis testing (i.e. 
statistically significant results might have occurred by chance), controlling for anti -smoking 
advertising in mass media and testing for wear -out effects, because they only had access to a 
small subset of the data.62 Similarly, Ajzen et al. criticise Yong et al. 2015 for failing to justify their 
selection of outcome variables available in the ITC datase t and having chosen not  to report the 
results of downstream variables and actual smoking behaviour and other questions related to 
warning labels. According to Ajzen et al., Yong et al. 2015 also failed to report effect sizes, explore 
wear-out effects and correct for multiple hypothesis testing.63 Ajzen et al. replicate the analysis of 
Yong et al. 2015 by re -estimating GEE models controlling for the survey mode (phone vs. web) 
and wave of recruitment, as well as respondents ' age, sex, income, education, ciga rettes per day 
consumed and past year quit attempts.  
46.  Overall, Ajzen et al. conclude that the results based on the ITC data are similar to th ose based 
on the NTPPTS dataset, namely that the TPP measures  have had a mixed and overall weak impact 
on GHW effectiveness. In particular, Ajzen et al. find that , although the TPP measures  have had a 
moderate positive and statistically significant effect on increasing smokers' attentional orientation 
towards health warning labels and a statistically significant small positive effect on the noticeability 
of the enlarged GHWs , smokers did not actually read the GHWs  more. Similarly, they report that 
the TPP measures  have had a statistically significant small positive impact on cognitive reactions 
and a statistically signi ficant moderate positive impact on avoiding health warning labels.64  
47.  Australia contends that Ajzen et al. correctly conclude that the TPP measures  have 
significantly increased attention paid to GHWs , noticeability of GHWs , cognitive reactions to GHWs , 
and avoidance of GHWs.65 Professor  Chaloupka further submits that Ajzen et al. fail to recognize 
that the impact of plain packaging should be smaller for the less proximal outcomes, such as 
knowledge about the health consequences of tobacco use, when one looks at the impact in the 
overall sample of smokers and recent quitters, becau se one would not expect that a smoker whose 
likelihood of noticing health warnings did not increase following plain packaging would show any 
change in his/her knowledge about the health consequences of smoking.66 
48.  Ajzen et al. argue that Australia and its ex perts do not contest the accuracy of the analytical 
approach they adopted or the results they obtained and do not challenge their serious criticisms of 
Yong et al. 2015.67 They further contend that Professor  Chaloupka's assertion  that the more distal 
outcom es will be less affected by the policy than the most proximal outcomes is unfounded. In 
their view, this weakening of the policy across the chain of effect does not reflect a limitation of 
the data, but the theoretically expected decline in the impact of p lain packaging across the chain 
of effect from pack appeal to behaviour.68 
2.1.3   Cancer Institute New South Wales Tobacco Tracking Survey  
49.  As well as analysing the impact of the TPP measures  on the appeal of tobacco products, 
Dunlop et al. 2014 use the CITTS data  to investigate the ir impact on GHW effectiveness among a 
large group of  randomly selected adult smokers between April 2006 and May 2013.69 The authors 
present the results of ARIMA models controlling for background trends, seasonality, anti -smoking 
advertising ac tivity and cigarette costliness.  
50.  Overall , Dunlop et al. 2014 conclude that Australia's TPP measures  have had an early 
statistically significant effect on increasing effectiveness of health warnings among adult 
                                                
62 See Dominican  Republic 's comment s on Australia's response to Panel question No. 196, 
paras.  409-414; and Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  12-19. 
63 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  30-37 and 53-58. 
64 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  22-27. We note that Ajzen et al. 
use the terms "intermediate", "moderate", and "medium" interchangeably to interpret effect sizes of their 
estimates. See, e.g. Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras. 90 and 119, and Appendix B, 
pp. 100-102. 
65 See Australia's response to Panel question No. 196, paras.  225 and 237.  
66 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 4. 
67 See Ajzen et al. Second Data Rebutta l Report , (Exhibit  DOM/IDN -8), paras.  13-16. 
68 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  39-45. 
69 See para. 17 above for a description of the CITTS data. See Dunlop et al. 2014, (Exhibits AUS -207, 
HND-132, DOM -199).  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  smokers.70 In particular, the aut hors report that two to three months following the introduction of 
the TPP measures , the absolute proportion of adult smokers having strong cognitive  ("graphic 
warnings encourage me to stop smoking") , emotional ("with the graphic warnings, each time I get 
a cigarette out I worry that I should not be smoking") and avoidant ("they make me feel that I 
should hide or cover my packet from the view of others") responses to on -pack GHWs  has 
increased. They find, however, that the impact of the TPP measures  on smok ers' responses to the 
salience of GHWs ("the only thing I notice on my cigarette pack is the graphic warnings")  was 
positive but statistically not significant.  
51.  Professor  Klick, in an expert report submitted by  Honduras,  re-examine s the impact of the 
TPP measures  on GHW effectiveness using more recent  CITTS data . Unlike Dunlop et al. 2014, 
Professor  Klick restrict s the sample to be more evenly spread between the pre - and 
post-implementation periods, namely from January  2009 to December  2014. In additio n, rather 
than looking only at "strong agreement" with a statement, as Dunlop et al. 2014 did, 
Professor  Klick also analyses "strong disagreement" with a statement. Professor  Klick present s the 
results of a logistic regression  controlling for annual time t rend, week of survey and individual 
characteristics, and submits that comparable results may be found using the ARIMA models.  
52.  Professor  Klick finds t hat the TPP measures  have had a positive and statistically significant 
impact on adult smokers' cognitive,  emotional, avoidant and salience responses  when the outcome 
variables are defined as "strong agreement" with  a given  statement. However, when the outcome 
variables are defined as "strong disagreement" with a given statement, the results are reversed 
and t he impact of the TPP measures  on adult smokers' cognitive, emotional, avoidant and salience 
responses is found to be negative and statistically significant. Professor  Klick submits  that this 
situation of contradictory outcomes likely results from consumer perceptions and intentions being 
ill-conceived, in a context where there is no cost to providing inaccurate or even inconsistent 
answers.71  
53.  Professor  Klick further submits that Dunlop et al. 2014 have cherry -picked questions to 
analyse GHW effectiveness  and failed to examin e other equally relevant questions , whose results 
contradict the authors' conclusions.  In particular, Professor  Klick finds that the TPP measures  had a 
positive and statistically significant impact on the probability that the respondent s trongly agrees 
with the statements " I do not look at the warnings each time the smoker gets a cigarette out " and 
"the graphic warnings are exaggerated ". In addition, Professor  Klick finds a negative but not 
statistically significant impact of the TPP measures  on the probability that the respondent strongly 
agrees with the statement "I have read the detailed information on the warning labels ". 
54.  Australia's expert Professor  Chaloupka submits that the CITTS dataset has features, including 
many of the s ame features of the NTPPTS data, which limit its utility in fully assessing the impact 
of plain packaging on the proximal and distal outcomes that are likely to be affected by the 
TPP measures .72 Professor  Chaloupka claims  that the CITTS dataset does not in clude young people 
and never smokers and, therefore, cannot assess  the impact of the TPP measures  on the 
population most likely to be influenced by the measure . Professor  Chaloupka  further  submits that 
any analys is that use s responses to questions, which a re only asked of smokers, is  likely to be 
considerably understating the effects of the TPP measures  because recent quitters , who seem 
most likely to have responded positively to these questions and to have already been influenced by 
the TPP measures , are not included in the analys is. Professor  Chaloupka contends also that 
Professor  Klick's analyses fail to appropriately account for significant change s in the CITTS 's 
sampling methods implemented in 2013 , resulting in an increase in the share of the sam ple 
accounted for by younger people and by men.  
2.1.4   Australian Secondary Students Alcohol Smoking and Drug Survey73 
55.  In another paper, White et al. 2015b use the 2013 ASSAD survey dataset to examine the 
impact of Australia's TPP measures  on the effectiveness of GHWs  among students aged  
                                                
70 See Tobacco Plain Packaging PIR , (Exhibit AUS -624), paras.  77-80. 
71 See Klick Second  Supplemental Rebuttal Report, (Exhibit HND -165), paras.  35-58. 
72 See Chaloupka Second Rebuttal Report , (Exhibit AUS -590), paras.  24-30. 
73 See Dominican  Republic's  second written submission, paras.  443-456. WT/DS435/R/Suppl.1 • WT/DS44 1/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  12-17 years  in Victoria and Queensland .74 The authors estimate linear and logistic regression 
models controlling for individual characteristics, such as age, sex, school type, state and smoking 
status .  
56.  Overall, White et al. 2015b conclude that Australia's TPP measures  have increased awareness 
among adolescents of bladder cancer, blindness and smoking as leading cause of death. However, 
the authors  find that the TPP measures  had no impact on adolescents' other health beliefs and 
cognitive processing of warning information.  In particular, they find no change over time in 
responses to the statements that smoking is addictive, is toxic (from tobacco smoke), clogs 
arteries, harms unborn babies, increases the risk of having a heart attac k, doubles the risk of 
stroke, and causes mouth cancer, diseases of the gums, kidney disease, lung cancer, emphysema, 
and diseases in toes and fingers (gangrene) .75 Similarly, the authors report that there is no 
statistical ly significant  change in the propo rtion of adolescents that read GHWs , paid close 
attention to GHWs , though t about GHWs , and talked about GHWs .76 
57.  The Dominican  Republic  argues  that without having  full access to the data, it is impossible to 
make an objective assessment of the findings  reported  in White et al. 2015b . The 
Dominican  Republic  submits that, as the analysis of the NTPPTS data showed, the published 
results in W hite et al. 2015b  may provide an unduly positive and inaccurate impression of the full 
dataset.77 Professor  Ajzen , in an expert report submitted by  the Dominican  Republic , Honduras 
and Indonesia,  further submits that the change in knowledge about bladder cancer could very well 
be attributable to a confounding factor, namely new information contained in new health 
warnings .78 More generally, the Dominican  Republic  notes that White et al. 2015b conclude that a 
period of one year following the implementation of the TPP measures  was not too short to detect 
effects on adolescents . The Dominican  Republic  also submit  that White et al. 2015b recognize that 
a "process of habituation" means that these initially weak effects are likely to weaken further over 
time.79 
2.1.5   Cigar and cigarillo smoker s survey s 
58.  As part of the ir analysis of cigar and cigarillo smokers, Miller  et al. 2015 review the responses 
to questions related to GHW effectiveness obtained from individual interviews, focus groups and an 
online survey  conducted 15 months after the introduction of the TPP measures .80 
59.  Miller et al. 2015 find that exposure of cigar and cigari llo smokers to the TPP measures  was 
incomplete  during the first 15 months following the implementation of the TPP measures  because 
they purchase d fully branded cigars in boxes duty free or online and singles in non -compliant 
packaging.  They note, however, that when exposure occurred, the TPP measures  increased the 
noticeability of health warnings . In particular, the authors report that premium cigar smokers who 
were exposed had noticed and were concerned by the health warnings, tried to avoid them and felt 
more like "dirty smokers". Similarly, they find that occasional premium cigar and premium ciga rillo 
smokers with higher plain packaging exposure (gained by purchasing boxes rather than singles) 
and online survey participants reported having  noticed GHWs  more. They also note that 
non-premium cigarillo smokers reported high plain packaging exposure, somewhat increased 
perceived harm, as well as greater noticeability of GHWs and concealment of packs.  
60.  Ajzen et al., in their expert report submitted by  the Dominican  Republic  and Indonesia,  claim 
that the results reported by Miller et al. 2015 suffer from several serious methodological 
shortcomings, including the non-representativeness of survey participants, impossibility of drawing 
causal inferences, failure to control for confounding factors , and absence of information collected 
                                                
74 See White et al. 2015b , (Exhibits HND -135, DOM-236, DOM -288). See para. 20 above for a 
description of the ASSAD survey.  
75 We note that White et  al. 2015b report a statistically significant at 10% level increase  in responses to 
the statement that smoking causes mouth cancer.  
76 See White et al. 2015b , (Exhibits HND -135, DOM-236, DOM -288). 
77 See Dominican  Republic's  second written submission, paras.  443-456; and comment s on Australia's 
response to Panel question No. 196, para. 390. 
78 See Ajzen Report , (Exhibit DOM/HND/IDN -3), para. 178. 
79 See Dominican  Republic's  second written submission, paras.  451-455. 
80 See para. 24 above for a description of the cigar and cigarillo smokers surveys data. See Miller et al. 
2015, (Exhibits AUS -102, DOM -315).  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  during the pre -implementa tion period of the TPP measures , which severely limit s any conclusions 
that can be drawn from the analysis.81 
61.  According to Ajzen et al., even if the results published by  Miller et al. 2015 are taken at face 
value, the few notable effects of  the TPP measures  revealed in the paper, including the increased 
noticeability of health warnings, are clearly to be expected and unlikely to inf luence actual smoking 
behaviour . Ajzen et al. further claim  that Miller et al. 2015 did not mention that the participants 
also r eported no change with respect to concern s that smoking may damage health , stubbing out 
cigars or cigarillos  and stopping smoking. More generally, Ajzen et al. contend that w hatever 
effects the TPP measures  are, or are not, found to have on cigarette -related cognitions and 
behaviours, such findings cannot be generalized to cigars . This, they submit, is because smoking 
cigarettes and cigars (or cigarillos) are different behaviours, and their determinants are also likely 
to differ.82 
2.1.6   Commissioned Roy Morgan Re search  Survey (Australia and New Zealand ) 
62.  Roy Morgan Research data set, commissioned by Professor  Klick, is a survey of individuals who 
were current or former (in the past 12 months) smokers in both Australia and New Zealand  
undertaken using random digit dialling sampling techniques. The first wave of the survey was 
completed prior to the implementation of Australia's TPP measures  between 2 November  2012 and 
26 November  2012 in Australia and between 8 November  2012 and 1 December 2012 in 
New Zealand . Subsequent waves were carried out at three -month intervals up until 
February  2014. The survey probed the respondents ' experience with attempts to quit and their 
intention to do so in the future as well as other attempts to change some aspect of their smoking 
behaviour.83  
63.  Professor  Klick uses the Roy Morgan Research data to estimate a difference -in-difference logit 
model that explains non -behavioural outcomes related to GHWs in Australia and New Zealand , 
controlling for the TPP meas ures, an Australian baseline variable, a common baseline variable and 
a post -TPP implementation time -period.  
64.  Overall, Professor  Klick concludes that the TPP measures  have had no statistically significant 
effect on smokers' beliefs about the health effects of smoking and the degree to which they notice 
warnings on their cigarette packages in Australia relative to New Zealand .84 In particular, 
Professor  Klick find s there was no statistically significant TPP impact in Australia relative to 
New Zealand  on the likelihood that the respondent answered positively on whether smoking is a 
major issue, a minor or major issue, and harmful to the heart, stomach, mouth, bladder, throat, 
sight, skin, or teeth. In addition, Professor  Klick find s that the TPP measures  have had no 
statistically significant impact in Australia relative to New Zealand  on placing a cover over the 
cigarettes, placing the cigarettes in a different container and kee ping the pack out of sight.85  
65.  Although Australia's expert, Dr  Chipty, do es not address directly Professor  Klick's analysis of 
non-behavioural outcomes based on the Roy Morgan Research data, a number of criticisms raised 
by Dr  Chipty regarding Professor  Klick's difference -in-difference analysis of smoking incidence also 
apply to the analysis of non -behavioural outcomes. Dr  Chipty argues that Professor  Klick's analysis 
of the Roy Morgan Research data is invalid because Professor  Klick's commissioned Roy Morga n 
survey does not contain a pre -period and is incapable of distinguishing which respondents had 
noticed plain packaging. Furthermore, Dr  Chipty considers  that New Zealand  is an invalid 
counterfactual for the purposes of studying the effects of plain packag ing, because of 
New Zealand 's January  2013 excise tax increase, one month after the introduction of 
TPP measures .86  
                                                
81 See Dominican  Republic's  second written submission, paras.  457-462; and Ajzen et al. Data Report, 
(Exhibit DOM/IDN -2), paras.  251-262. 
82 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  251-262. 
83 See Klick Report , (Exhibit UKR -5), pp. 6-8. See section 1.6.6 in the main body of these Reports for a 
description of Ukraine's participation in these proceedings.   
84 See Klick Report , (Exhibit UKR -5), pp. 18, 47 -54. 
85 See Klick Report , (Exhibit UKR -5), pp. 18, 54 -56. 
86 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  54-71. WT/DS435/R/Suppl.1 • WT/DS44 1/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  2.2  Analysis by the Panel  
66.  We note that a slightly large r number of peer -reviewed studies  before us ( six in total)  analy se 
the impact of the TPP measures  and enlarged GHWs on outcome variables related to GHW 
effectiveness , compared to the number of studies before us addressing  the impact on appeal of 
tobacco products .  
67.  A careful review of Wakefield et al. 2015 and Yong et al. 2015 and the econo metric evidence 
submitted by the Dominican  Republic , Honduras and Indonesia leads us to conclude that there is 
some empirical evidence that suggests that the TPP measures  have improved  the GHW 
effectiveness  among adult cigarette smokers by increasing  the noticeability  of GHWs , attention 
toward s them, avoidance of health warnings labels, pack concealment, request for a pack with a 
different GHW and attribution  to the motivation to quit to GHWs  (cognitive responses) .87 We note 
that although Ajzen et al. qualify these impacts as small or moderate in the case of a ttention and 
avoidant responses, they  are still  statistically sign ificant, with no evidence of wear-out effect s, 
except in the case of the cognitive responses .88  
68.  However , we note that the empirical evidence on the impact of the TPP measures  on 
knowledge about health  risks is more nuanced  and statistically not significant as regards  the 
balance between smoking enjoyment and concern . Ajzen et al. and Professor  Klick contend that 
the impact of  the TPP measures  on GHW effectiveness is mixed because the impact s on reading 
the GHW, perceived exaggeration of harms and knowledge about specific risks are not statistically 
significant.89 We note in this respect that while the analysis suggests that the  TPP measures  seem 
to have a limited impact on recalling specific smoking risks, the results also suggest that the 
TPP measures  have had a  small  but positive  and statistically significant impact on recalling a 
disease on a current GHW and on believing that  smoking causes blindness without evidence of a 
wear-out effect .90 In that context, w e find that Ajzen et al.'s claim that Wakefield et al. 2015 
underreport ed non -statistically significant results should be qualified .91 First, we note that 
Wakefield et al. 2015 did not report  some results . However, following their own analysis of the 
unreported results with respect to questions assessing whether the TPP measures  and enlarged 
GHWs increased knowledge about diseases caused by smoking , Ajzen et al. acknowledge  that the 
TPP measures  had a "very small effect" on respond ents' ability to freely recall a disease on a 
current GHW and their belief that smoking causes blindness.92 Second, Ajzen et al. also find an 
increase, albeit very small, in the proportion of adult smokers who believe smoking causes bladder 
cancer , which is statistically significant at the 10% level in the logistic regression . Similarly, 
Ajzen  et al. report in the linear regression and ordered logistic regression a v ery small but 
statistically significant (at the 10% level ) increase in the proportion of adult smokers who disagree 
that lung cancer is a disease smokers only get in old age.93 Third, and more generally, we agree 
with Professor  Chaloupka  that the impact of the TPP measures  is likely to be smaller for the less 
proximal outcomes , when looking at the impact in an overall survey sample composed of smokers 
and recent quitters.94 
69.  A careful review of the analysis of the CITTS data reported by Dunlop et al. 2014 and 
Professor  Klick confirms the findings reported in Wakefield et al. 2015 and Yong et al. 2015 that 
the TPP measures  had, in the two to three months following the ir introduction , a positive and 
                                                
87 See Wakefield et al. 2015, (Exhibits  AUS-206, DOM -306); Dunlop et al. 2014, (Exhibits AUS -207, 
HND-132, DOM -199); Yong et al. 2015, (Exhibit DOM -382); and Ajzen et al. Data Report, (Exhibit 
DOM/IDN -2), paras.  89-97, 148 -150, Appendix  A, pp. 78-80. We also note that in his review of Dunlop et al. 
2014's analysis, Professor  Klick did not discuss and  re-analyse the questions of the CITTS related to appeal. 
We also note that Professor  Klick did not mention in his reports whether the commissioned Roy Morgan 
Research survey also asked questions related to the appeal of tobacco products.  
88 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  102-114, 151 -155, Appendix  A, pp. 81-83; 
and Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  22-27. 
89 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  102-114, 151 -155, Appendix  A, pp. 81-83. 
See also Ajzen et al. Second Data Re port, (Exhibit DOM/IDN 4), para . 22. 
90 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), Appendix  A, pp. 81-83. 
91 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), para. 116. 
92 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  112 and 116 -117. 
93 See Ajzen et al. Data Report,  (Exhibit DOM/IDN -2), pp. 81-83. We also note that Ajzen et al. report in 
the logistic regression results table a very small but statistically significant at the 10% level decrease in the 
proportion of adult smokers that agree that smoking causes mouth cancer.  
94 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 9. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  statistically significant impact on adult smokers' cognitive, em otional and avoidant reactions to 
GHWs .95 We are not persuaded that the econometric results presented by Professor  Klick can be 
taken at face value  and provide sufficient basis to dismiss Dunlop et al.'s results. A comparison 
between Professor  Klick's re -analysis with Dunlop et al. 2014 is not straightforward , not only  
because the sample period is different but more importantly because the estimation method is 
different. Professor  Klick submits that using Dunlop  et al. 2014 would yield similar results.96 Yet, 
Professor  Klick report s a statistically significant impact of the TPP measures  on smokers' responses 
to GHW salience , while in Dunlop et al. 2015 the impact is found to be not significant.97 It is 
therefore unclear to what extent Professor  Klick's fin dings are the result of his model specification 
(i.e. not controlling for exposure to advertising and tobacco costliness) or a different sample period  
or both . It is also unclear why Professor  Klick decided to discard data from April 2006 to 
December  2008.  Likewise, it is unclear if Professor  Klick's findings are affected by the changes in 
the survey's sampling methods. Professor  Klick also did not provide an explanation as to why the 
TPP measures  would decrease GHW effectiveness, as suggested by some of hi s counter -intuitive 
results.  
70.  As noted above in our review of the post -implementation studies before us on appeal, only 
one peer -reviewed study by White et al. 2015b reports empirical evidence of the impact of the 
TPP measures  on adolescents . In the context of GHW effectiveness, we note that White et al. 
2015b suggest  that one year after their implementation , the TPP measures  have had a limited 
impact on adolescents ' beliefs about the health risks of smoking and no impact on their cognitive 
processing of the GHW information .98 The authors report that acknowledgement of negative health 
effects of smoking among Australian adolescents  remain s high. This could explain why the 
TPP measures  did not increase  adolescents ' health beliefs , except as rega rds bladder cancer, 
mouth cancer, blindness and smoking as a leading cause of death.  
71.  Post-implementation empirical evidence  on cigar and cigarillo  smokers  is also limited to a 
single peer -reviewed paper , by Miller et al. 2015, who present a descriptive statistics analysis of 
various  personal interviews, focus groups and an online survey.  The authors find  that 15 months 
after the introduction of the TPP measures , cigar and cigarillo smokers exposed to plain packaging 
reported greater noticeab ility of the GHWs and in a few  cases greater concerns about the health 
warnings , avoidance of graphic health labels and pack concealment.99 As pointed out by Ajzen 
et al., the evidence on cigar and cigarillo smokers' health beliefs and cognitive responses a re more 
mixed. As explained in our review of the post -implementation studies on appeal, many  of the 
criticisms raised by Ajzen et al. regarding Miller et al.'s methodology , such as the 
representativeness of the samples and accuracy of self -report measures , have been identified as 
limitations by the authors themselves . It is however  unclear to what extent the results would have 
change d if Miller et al. 2015 had explicitly accounted for confounding factors or applied a different 
methodology , noting that no ot her relevant data on cigars  have been provided by the parties. That 
being said, we note that although Ajzen et al. submit that conclusions about the impact of the 
TPP measures  on cigarettes cannot be generalized to cigars, they  also recognize that the impa ct of 
the TPP measures  on increased noticeability of the health warnings on cigars was to be 
expected.100 Therefore, we see no basis to reject in its entirety Miller et al.'s study on the basis of 
Ajzen et al.'s. criticism of it, noting that the overall findings reported in Miller et al. 2015 are to 
some extent in line with the results reported in the other peer -reviewed papers analysing the 
impact of GHW effectiveness on adult cigarette smokers reviewed above.  
72.  Finally, after a careful review , we question the robustness  of Professor  Klick's analysis of the  
commissioned  Roy Morgan Research data. We note that unlike in the context of his empirical 
analysis of smoking incidence based on the Roy Morgan Research data , Professor  Klick did not 
re-estimate his model specification to address some of the criticisms raised by Dr  Chipty.101 We 
also question the validity of Professor  Klick's difference -in-difference analysis , for two main 
                                                
95 See para. 17 above for a description of the CITTS data. See Dunlop et al. 2014, (Exhibits AUS -207, 
HND-132, DOM -199). 
96 See Klick Second Supplemental Rebuttal  Report, (Exhibit HND -165), para. 42. 
97 See Klick Second Supplemental Rebuttal Report, (Exhibit HND -165), p p. 18 and 21-23. 
98 See White et al. 2015b, (Exhibits HND -135, DOM-236, DOM -288). 
99 See Miller et al. 2015,  (Exhibits AUS -102, DOM -315).  
100 See, Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  255-256. 
101 We are aware that most of Dr Chipty's critics referred to Professor  Klick's analysis of smoking 
prevalence, but some of these critics apply to the difference -in-difference methodology in general.  WT/DS435/R/Suppl.1 • WT/DS44 1/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  reasons. First , the structure of the comm issioned data prevents Professor  Klick from accurately 
identifying the respondents who had noticed plain packs in the pre -period . This is because  the 
question about noticing changes in the packaging was not asked to all respondents , making the 
pre-period  covered by the commissioned data , in our view, very questionable .102 Second, i t is 
unclear how controlling for the excise tax increase that took place in New Zealand  between Waves 
1 and 2 and Waves 5 and 6 of the commissioned survey would have changed the results.  
3  EVIDENCE RELATING TO  THE ABILITY OF TOBACCO PACKAGING  TO MISLEAD 
CONSUMERS ABOUT THE HARMFUL EFFECTS OF S MOKING SINCE THE ENTRY INTO  
FORCE OF THE TPP MEASU RES 
73.  Two peer-reviewed papers analyse empirically the impact of Australia's TPP measures  on the 
ability of the pack of tobacco products to mislead consumers  among adult cigarette smokers and 
adolescents, respectively : (i) Wakefield et al. 2015; and (ii)  White et al. 2015a .103  
3.1  Datasets and related studies  
3.1.1   National Tobacco Plain Packaging Tracking Survey  
74.  In addition to analysing the impact of the TPP measures  on appeal and GHWs effectiveness, 
Wakefield et al. 2015 uses the NTPPTS data to investigate the ir impact among adult smokers on 
tobacco packaging 's ability  to mislead consumers about smoking harms.104 The authors present 
the results of a logistic model, using baseline survey weights and controlling for individual 
characteristics.105  
75.  Wakefield et al. 2015 find that, 12 months after their implementation , the TPP measures  have 
had a positive and statistically significant effect  on the proportion of adult smokers who believed 
that brands do not differ in harmfulness. However, the authors report no statistical ly significant  
change in the proportion of adult smokers who rated  their current cigarette or tobacco as more 
harmful  compared to a year ago and who believed brand variants do not differ in strength.106 
76.  Ajzen et al. in their expert report submitted by the Dominican  Republic  and Indonesia,  submit 
that although Wakefield et al. 2015 acknowledge s that the impact of the TPP measures  on 
reducing the ability of packaging to mislead was mixed, the picture they presented must be 
considered incomplete because they failed to mention an important wear -out effect and to report 
statistically not significant  result s.107 In particular, Ajzen et al. find that the increase in the 
proportion of adult smokers who believed that brands did not differ in harmfulness was very small 
and showed a wear -out effect. In addition, Ajzen et al. report no statistically significant change in 
the proportion of adult smokers that perceived their cigarettes  are more harmful compared to a 
year ago, believed that brand variants do not differ in strength and agreed they had trouble 
believing that their regular brand of cigarettes is harmful .108 More generally, the 
Dominican  Republic  considered Australia's claim that the NTPPTS was much broader in scope than 
Wakefield et al. 2015 to be surprising, as  this message was not expressed in Wakefield et al. 2015 
or in the journal's editorial in which the study was published.109 
77.  Professor  Klick, in his expert report submitted by Honduras, reviews the NTPPTS data relating 
to the effect of the TPP measures  on the ability of packaging to mislead consumers about the harm 
of smoking .110 Professor  Klick contends that there are other  outcomes in the NTPPTS data, not 
                                                
102 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  54-62. 
103 See Wakefield et al. 2015, (Exhibits  AUS-206, DOM -306); and White et al. 2015a, (Exhibit s 
AUS-186, DOM -235).  
104 See para. 8 above for a description of the NTPPTS data. See Wakefield et al. 2015, 
(Exhibits  AUS-206, DOM -306).  
105 See para. 8 above for a description of the NTPPTS data.  
106 See para. 8 above for a description of the NTPPTS dat a. See Wakefield et al. 2015, 
(Exhibits  AUS-206, DOM -306).  
107 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  128-132. 
108 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  123-127 and 156-158, Appendix  A, 
pp. 84-86. 
109 Dominican  Republic's  comments on Australia 's response to Panel question No. 198, para. 705. 
110 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  82-86.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  reported by Wakefield et al. 2015, which go against their conclusion that the TPP measures  are 
achieving t heir goal regarding the ability of packaging to mislead consumers about smoking  
harms.111  
78.  Professor  Klick presents the results of an ordered probit model, which control s for the 
TPP measures  (early TPP period and formal TPP period), gender, age , education, socio-economic 
status and a linear time trend.112 He finds that the TPP measures  had no statistically significant 
impact on the respondents' belief about the harmfulness of the regular brand .113 
79.  Australia contends that the findings reported by Ajzen et al. are completely consistent with 
the findings of Wakefield et al. 2015 regarding the impact of the TPP measures  on reducing the 
ability of packaging to mislead  consumers about the harmful effects of smoking .114 More generally, 
Australia argues that the result s of Wakefield et al. 2015 were reported appropriately since the 
scope of the NTPPTS was much broader than the specific and limited focus of Wakefield et al. 
2015. Australia further claims that the complainants' implication that unfavourable results were 
not reported is directly contradicted by the facts.115 
3.1.2   Australian Secondary Students Alcohol Smoking and Drug Survey  
80.  In addition to  assessing  the impact of Australia's TPP measures  on the appeal of tobacco 
products, White  et al. 2015a employ  the 2013 ASSAD survey extension to examine  the impact of 
the TPP measures  on the ability of tobacco product packaging to mislead about smoking harms 
among students aged 12 -17 years.116 The authors present the results of several generali zed linear 
regression  models and multinomial logistic regression models controlling for individual  
characteristics.  
81.  Overall, White et al. 2015a conclude that the impact of Australia's TPP measures  on reducing 
the ability of cigarette packaging to mislead young smokers regardin g the harmful effects of 
smoking is mixed. In particular , the authors report a statistically significant increase in the 
proportion of students who had seen a cigarette pack in the previous six months  and disagreed 
that some brands are more addictive than others  and that some cigarette brands contain more 
harmful substances than others.  However, the authors find that the number of students agreeing 
that some cigarette brands are easier to smoke than others  has increased, while there was no 
change over tim e in responses to the statement "some cigarette brands are easier to quit than 
others".  White et al. 2015a conclude that further research is needed to determin e whether 
continued exposure to standardi zed packs lead s adolescent s to develop more uncertainty or 
disagreement regarding brand differences in ease of smoking and quitting, perceived addictiveness 
and harms.117 
82.  As explained previously, t he Dominican  Republic  argues that i n the absence of full access to 
the dataset, it is im possible to make an objective assessment of the findings in White et al. 2015a. 
According to t he Dominican  Republic , the published results in White et al. 2015a may provide an 
unduly positive and inaccurate impression of the full dataset.118 The Dominican  Republic  notes  that 
White et al. 2015a acknowledge that the impact of plain packaging and enlarged GHWs on 
                                                
111 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), para. 84. 
112 Professor  Klick explains that , unlike Wakefield et al. 2015, he omits the measure of exposure to mass 
media anti -smoking messages, cigarette costliness and heaviness of smoking index, because these variables 
are endogenous. He further explains that the inclusion of these variables does  not change the results he 
presented. See Klick Supplemental Rebuttal Report , (Exhibit HND -122), fn 35.  
113 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  85-86. We note that in 
Professor  Klick's model specification with an early TPP peri od and a formal TPP period, the impact of the early 
TPP period variable is positive and statistically significant, suggesting that the respondents are not more 
convinced that their regular brand is harmful.  
114 Australia's comments on the complainants' responses  to Panel question No. 146, para. 7. 
115 Australia's response to Panel question No.  198, paras.  298-303. 
116 See para. 20 above for a description of the ASSAD survey dataset. See also White et al. 2015a, 
(Exhibit s AUS-186, DOM -235). 
117 See White et al. 2015a, (Exhibit s AUS-186, DOM -235). 
118 See Dominican  Republic's  second written submission, paras.  443-456; and comment s on Australia's 
response to Panel question No. 196, para. 390. WT/DS435/R/Suppl.1 • WT/DS44 1/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  deception are "mixed"  and that the authors refrain from concluding that the pack changes have 
reduced deception .119 
3.2  Analysis by the Panel  
83.  Among the vari ous peer -reviewed studies discussed by the parties, two assess  the impact of 
the TPP measures  and enlarged GHWs on the ability of the packaging  of tobacco products to 
mislead consumers  about the harmfulness of smoking  among adult cigarette smokers and 
adolescents . 
84.  A careful review of Wakefield et al. 2015 paper  and the econometric evidence submitted by 
the Dominican  Republic  and Indonesia suggests that the impact of the TPP measures  on the ability 
of the pack to mislea d is much more mixed.  Wakefield et al. 2015 only find a statistically 
significant impact of the TPP measures  in reducing the belief that brands differ in harmfulness, but 
no impact on the belief that there is no difference in strength level across brands a nd that the 
current tobacco product is perceived as more harmful than a year ago.120 While Ajzen et al. 
confirm these results, they also qualify the impact on the belief about difference in harmfulness 
across brands as being small and subject of wear -out.121 Ajzen et al. and Professor  Klick further 
claim that Wakefield et al. 2015 failed to report the result associated with the question on the 
harmfulness of their own brand , which according to them is statistically not significant. We note, 
however, that the r esults of the linear regression and ordered logistic regression suggest  a small 
decrease in the proportion of adult smokers who do not have trouble believing that their brand is 
harmful , which is  statistically significant at the 10% level.122 
85.  We note that th e empirical evidence reported in Wakefield et al. 2015 regarding the mixed 
impact of the TPP measures  on the packaging ability to mislead among adult smokers is supported  
by White et al. 2015b in the case of adolescents.  A review of White et al. 2015b sugg ests that , one 
year after their implementation , the TPP measures  have had some  impact in reducing adolescents' 
belief s in difference in addiction and harmfulness across brands . However, the authors find that 
the TPP measures  have ha d no impact on adolescents' belief that some brands are easier to quit 
than others  and, surprisingly , a positive impact on the belief that some cigarette brands are easier 
to smoke than others .123 
4  OVERALL CONCLUSION ON POST -IMPLEMENTATION EVIDE NCE ON 
NON-BEHAVIOURAL OUTCOM ES 
86.  Overall, b ased on the studies and expert reports before us and discussed above , the empirical  
evidence available to us regarding  the impact of the TPP measures , together with  enlarged GHWs , 
since their entry into force, on the proximal outcomes  of interest  suggests  that: 
a. The TPP measures  and enlarged GHWs have statistically significantly reduced the appeal 
of cigarettes  among adult smokers .  
b. The TPP measures  and enlarged GHWs have statistically significantly increased GHWs ' 
effectiveness on the noticeability of health warnings, avoidance of graphic health labels 
and pack concealment among adult cigarette smoker , albeit modestly for some 
outcomes , while the impact of the TPP measures  and enlarged GHWs on adult cigarette 
smokers' health beliefs is relatively more limited and nuanced.  
c. The TPP measures  and enlarged GHWs have had a more mixed and limited impact on 
the ability of the pack to mislead adult cigarette smokers about the harmful effects of 
smoking.  
                                                
119 See Dominican  Republic's  comment s on Australia's response to Panel question No. 200, 
paras.  793-794; and Ajzen Report , (Exhibit DOM/HND/IDN -3), paras.  174-178. 
120 See Wakefield et al. 2015, (Exhibits AUS -206, DOM -306).  
121 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  123-127, 156 -158, Appendix  A, 
pp. 84-86. 
122 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), Appendix  A, pp. 85-86. 
123 See White et al. 2015b , (Exhibits HND -135, DOM-236, DOM -288). WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  d. While t he TPP measures  (together with  enlarged GHWs) have contributed statistically 
significantly in reducing  the appeal of cigarettes among adolescents , the impact of the 
TPP measures  (with enlarged GHWs) on adolescents' health beliefs and cognitive 
processing of warning information on cigarettes packs is much more limited.  Similarly, 
the impact of the TPP measures  (with enlarged GHWs) on the ability of the pack to 
mislead adolescents about the harmful effects of smoking is more mixed and limited.  
e. There has been a decrease in perceiv ed packaging appeal when cigar and cigarillo 
smokers were exposed to the TPP measures  (and enlarged GHWs) . In addition, t here has 
been an increase in the noticeability of health warnings and pack concealment among 
cigar and cigarillo smokers but the eviden ce is mixed regarding health beliefs.  
87.  No post -implementation empirical evidence has been presented to us on the impact of the 
TPP measures  on the ability of the pack to mislead cigarillo and cigar smokers about smoking 
harms.  
 WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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APPENDIX  B:  
 
EVIDENCE ON QUITTING -RELATED OUTCOMES AND  OTHER DISTAL  OUTCOMES  SINCE 
THE ENTRY INTO FORCE  OF THE TPP MEASURES  
 
1.  Earlier in th ese Report s, we referred to behaviours  such as calling a Quitline and concealing a 
pack in public as "smoking -related behaviours".  Australia's experts h ave referred to changes in 
quit intentions and quit attempts  as "distal" outcomes  of the TPP measures .1 The 
Dominican  Republic  and Indonesia have similarly referred to quit intentions, secondary quit 
indicators, and quit attempts as "distal" outcomes  and " antecedents of smoking behaviour".2 We 
focus our discussion in this Appendix  on the post -implementation evidence submitted by the 
parties with respect to these variables.  
2.  Australia submits that several peer -reviewed studies , which focus on quitting -related  
cognitions, pack concealment, and quit attempts,  confirm that the TPP measures  have resulted in 
increased calls to Quitline and the number of quit attempts.3 Australia further submits that the 
features of certain survey data are most suited to detecting c hanges in proximal outcomes (i.e. 
tobacco products appeal, GHW effectiveness, and ability of packaging to mislead) than in more 
distal variables, such as intentions and quitting -related behaviours.4 
3.  The Dominican  Republic  and Indonesia submit that the TPP measures  have not had the 
expected effects on the antecedents of behaviour posited by Australia's conceptual framework of 
the TPP measures . In particular, the Dominican  Republic  and Indonesia contend that beyond the 
obvious findings that the pack is less v isually appealing and people more often notice the larger 
GHW first, empirical evidence shows little or no effects of the policies on the antecedents of 
behaviour. The Dominican  Republic 's, Honduras' s and Indonesia's experts further argue that the 
empirica l evidence shows that the TPP measures  have had no impact on variables relating to 
quitting and relapse.5 The Dominican  Republic  and Indonesia submitted expert reports dedicated 
to reviewing a series of peer -reviewed papers assessing the impact of the TPP measures  on 
quitting -related outcomes. In some cases, the experts of the Dominican  Republic , Honduras and 
Indonesia also re -analysed the data used in the studies.6  
4.  In addition, the experts of the Dominican  Republic  and Indonesia contend that some of the 
published empirical studies relied upon by Australia provide an inaccurate picture of the empirical 
evidence. According to the m, some of these papers failed to report the results for more than half 
of all variables available in the  survey dataset, which were overwhelmingly not statistically 
significant, suggesting no impact of plain packaging on these variables. The Dominican  Republic  
and Indonesia contend that the authors of some of these studies failed also to explain that a 
numbe r of the reported statistically significant effects had "vanished" by the end of the first year of 
the TPP measures ' implementation as a result of wear -out effects. The  Dominican  Republic  and 
Indonesia further criticize these papers for failing to report t he effects size of the statistically 
significant effects. According to their experts, most of the reported statistically significant effects 
are small, suggesting that they have little importance in shifting behaviour. The 
Dominican  Republic  and Indonesia also criticize the authors of one of the studies for having 
removed the effects of a non -existent daily trend in survey responses, which has distorted the 
analysis by finding wrongly statistically significant effects.7  
                                                
1 See Chaloupka Rebuttal R eport, (Exhibit AUS -582), para. 2; and NTPPTS Technical Report, (Exhibits 
AUS-570, HND -124, DOM -307), p p. 6 and 21.  
2 Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  27 and 35.  
3 Australia's second written submission, para. 464. 
4 Australia' s comments on the complainants ' responses to Panel question No. 197, paras.  371-375. 
5 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  10-22. 
6 See Ajzen et al. Data Report,  (Exhibit DOM/IDN -2); Ajzen et al. Second Data Report,  (Exhibit 
DOM/IDN -4); Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6); Ajzen et al. Second Data Rebuttal 
Report , (Exhibit DOM/IDN -8); and Klick Report , (Exhibit UKR -5). 
7 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  23-27. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  5.  For each main type of outcome, namel y quit intention, pack concealment and quit attempt, we 
discuss the survey data and corresponding papers separately, before turning to an overall 
assessment of the evidence before  us. As in respect of the evidence relating to proximal outcomes 
addressed in  Appendix  A, we approach this assessment on the basis that our task is not to conduct 
our own econometric assessment of the impact of the TPP measures  on the  relevant outcomes but 
rather to examine, on the basis of the evidence before us, the overall robus tness of the 
econometric evidence submitted by the parties in this respect.8 
1  EVIDENCE RELATING TO  QUITTING -RELATED COGNITIONS S INCE THE ENTRY INTO 
FORCE OF THE TPP MEASURES  
6.  Four peer -reviewed papers empirically analyse the impact of Australia's TPP measure s on 
quitting -related cognitions: (i)  Durkin et al. 2015; (ii)  Yong et al. 2015; (iii)  White et al. 2015b; 
and (iv)  Miller et al. 2015.9 An expert report prepared by Professor  Klick, submitted by  Ukraine, 
also contains a study analy sing the impact on quitting -related cognitions.10 
1.1  Datasets and related studies  
1.1.1   National Tobacco Plain Packaging Tracking Survey  
7.  As described in Appendix  A, the NTPPTS, funded by Australia's Department of Health and 
Ageing, is a nationwide  tracking survey conducted from 9  April 2012 to 30  March  2014 with a 
follow -up survey of baseline participants from 7  May 2012 to 4  May 2014.11 Durkin et al. 2015 
employ the NTPPTS data to examine the effects of the TPP measures  on short -term changes in qui t 
intentions. The authors estimate various logistic models based on the respondents' experiences 
regarding quit intentions over the one -month follow -up period for the cohorts surveyed before the 
implementation of the TPP measures , over the transition period to TPP, and during the first year of 
implementation . The authors adjusted the models for baseline levels of the outcome and controlled 
for the date of the follow -up survey, number of days between baseline and follow -up surveys,  
anti-smoking television advertising in the three months prior to the follow -up survey, change in 
cigarette costliness, sex, age, education, socio -economic status, and addiction level.12 Durkin et al. 
2015 also present the results of unadjusted models, wher e the only control variable is the baseline 
response.  
8.  Durkin et al. 2015 find that the TPP measures  were associated with increased rates of quitting 
cognitions among adult cigarette smokers. In particular, compared to the referent group of 
smokers having c ompleted their follow -up survey in the pre -TPP period, smokers who were 
followed -up with in the late transition period reported greater increases in their intentions to quit 
in the next month. However, the authors find that there was no statistically signi ficant change in 
the proportion of adult smokers who were followed -up with in the first year of implementation of 
the TPP measures  who thought daily about quitting in the past week, intended to quit in the next 
month or set a firm date to quit in the next month compared with the pre -TPP period.  
9.   Ajzen et al., in their expert report submitted by the Dominican  Republic  and Indonesia, use the 
NTPPTS data to review the findings reported in Durkin et al. 2015. They argue that Durkin et al.'s 
2015 conclusions are  unwarranted and contradicted by the data. According to Ajzen et al., Durkin 
et al. 2015 overstate their findings because the TPP measures  have had no impact on the majority 
of the quitting -related measures.13 More generally, Ajzen et al. contend that Durki n et al. 2015 
have adopted a very different and unorthodox comparison methodology compared to Wakefield 
et al. 2015, despite being the same six authors using the same dataset.  
                                                
8 For a similar approach, see Panel Reports, US – COOL (Article 21.5 – Canada and Mexico) , para. 7.183 
(citing Panel Reports, US – COOL , para. 7.539).  
9 See Durkin et al. 2015, (Exhibit s AUS-215 (revised) , DOM-305); Yong et al. 2015, (Exhibit DOM -382); 
White et al. 2015b, (Exhibits HND -135, DOM -236, DOM -288); and Miller et al. 2015, (Exhibits AUS -102, 
DOM-315).  
10 See section 1.6.6 in the main body of these Reports  for a description of Ukraine's participation in 
these proceedings.  
11 Dominican  Republic 's secon d written submission, paras.  380-429.  
12 See Durkin et al. 2015, (Exhibit s AUS-215 (revised) , DOM-305).  
13 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  174-179. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  10.  Ajzen et al. submit  that Durkin et al.'s analytical approach suffers from three serious 
methodological shortcomings. First, unlike Wakefield et al. 2015, Durkin et al. 2015 control for a 
non-existent daily trend that distorts the estimates of the impact of the TPP measures  by 
conflating the co ntribution to behavioural change due to the daily trend on the one hand, and the 
TPP measures  on the other. When the daily trend is removed from Durkin 's own analysis, each of 
the significant results reported in Durkin et al. 2015 disappears.14 Second, Durk in et al. 2015 failed 
to show that the statistically significant results experienced wear -out effects, with none of the 
results still significant in the final quarter of the first year following the introduction of the 
TPP measures .15 Third, Durkin et al. 2015 did not correct for multiple significances tests that would 
have shown that none of the effects reported as being statistically significant by Durkin et al. 2015 
remain statistically significant.16 Ajzen et al. further argue that Durkin et al.'s claim t hat relying on 
changes in participants' responses from month to month minimizes the influence of sampling 
variation and increase the power of the statistical tests has been mathematically proven to be 
wrong.17 
11.  Ajzen et al. present the results of a logistic model for dichotomized outcome variables, linear 
model for continuous outcome variables and ordered logit model for categorical outcome variables, 
controlling for the same covariates as Durkin et al. 2015 except for the date of the follow -up 
interview. The y find no statistically significant change in the proportion of adult smokers who were 
followed -up in the first year of the TPP measures  who thought daily about quitting in the past 
week, intended to quit in the next month or set a firm date to quit in the  next month.18 In 
addition, Ajzen et al. claim that Durkin et al. 2015 failed to report the result showing that the 
TPP measures  did not bring about any increase in respondents ' ability to perceive the importance 
of staying quit.19 
12.  Professor  Klick, in his ex pert report submitted by Honduras, looks at the NTPPTS data on the 
effect of the TPP measures  on quitting -related cognitions  and intentions .20 Professor  Klick claims 
that Wakefield et al. 2015 did not present the results of some variables related to quitting that did 
not improve or might have even gotten worse with the TPP measures .21  
13.  Professor  Klick presents the results of an ordered probit model, which controls for the 
TPP measures  (early TPP period and formal TPP period), gender, age , education, socio -economic 
status and a linear time trend.22 He finds that the re is no evidence that the  TPP measures  
increased the importance of quitting in respondents' mind . He reports, however, a negative and 
statistically significant impact of the  TPP measures  on the respondents'  thoughts about quitting .23 
14.  Professor  Klick further contends that Durkin et al.'s 2015 results of the unadjusted models, 
which show that none of the quitting -related cognition variables are statistically distinguishable 
from the pre -TPP period, must be given appropriate weight and considered as at least equally valid 
compared with the results of the adjusted models , for various reasons .24 First, Professor  Klick 
claims that accounting for the respondent's characteristics does not seem necessary, because they 
should be captured by the individual's baseline response. Second, he  argues that the variables for 
the individual's heaviness of smoking and cigarette p rice are likely to be endogenous, which could 
bias the estimates of the TPP measures . Third, he claims that the variable for the exposure to 
mass media anti -smoking messages, which is computed over a fixed three -month time -period, 
measures different things  for different respondents and controlling for days between interviews 
                                                
14 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  188-192.  
15 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  193-195. 
16 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  196-198. 
17 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  184-185. 
18 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  165-173, Appendix  A, pp. 90-92. 
19 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), para. 179. 
20 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  69-73, 88 -100.  
21 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  61-63. 
22 Professor  Klick explains that unlike Wakefield et al. 2015 he omits the measure of exposure to mass 
media anti -smoking messages, cigarette costliness and heaviness of smoking index, because these variables 
are endogenous. He further explains that the inclu sion of these variables does not change the results 
presented. See Klick Supplemental Rebuttal Report , (Exhibit HND -122), fn 35.  
23 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  69-73. We note that 
Professor  Klick considers these two qu estions to be relevant to the appeal of tobacco.  
24 Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  91-100. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  does not address this problem. Finally, Professor  Klick argues that Durkin et al. 2015 do not 
explain what adjusting the models for the date of the follow -up survey means.25  
15.  Professor  Chaloupka, Australia's expert, contends that Ajzen et al.'s analysis suffers from 
several limitations, in part resulting from the particular features of the NTPPTS data. As a result, 
this analysis creates more confusion than it provides help in understandin g whether Australia is 
achieving the specific and broad objectives of the TPP measures .26 In his view, the fact that there 
are inherent limitations to any data and analysis is the primary reason for considering the overall 
weight of the evidence based on a variety of data and methods, rather than relying on any one set 
of data or analysis.27 Professor  Chaloupka argues that the NTPPTS data cannot be used to assess 
the impact of the TPP measures  on the population most likely to be influenced by TPP, namely 
individuals who might have taken up tobacco use in the absence of the TPP. Professor  Chaloupka 
further submits that because of its cross -sectional nature, the NTPPTS data limit the ability of 
analysts to follow the impact of the TPP measures  through the pathwa y from its impact on the 
most proximal outcomes, like perceived appeal and noticing of the labels, through less proximal 
outcomes, such as increased interest in quitting, to the most distal outcomes, such as actual 
tobacco use behaviour. Professor  Chaloupk a is of the view that a true longitudinal survey tracking 
the impact of the TPP measures  over a number of years on the same sample of current tobacco 
users and recent quitters would allow for the type of sequential analysis that would be more 
helpful in fu lly understanding how the TPP measures  affect the more and less proximal outcomes 
they are expected to influence, as well as to more fully understand their impact on actual tobacco 
use behaviour.28 
16.  According to Professor  Chaloupka,  Ajzen et al. fail to reco gnize that the power to detect 
statistically significant changes will fall for outcomes that are increasingly distal. The analysis of 
distal outcomes requires relatively large sample sizes to detect these increasingly smaller effects 
when it is based on al l current tobacco users and recent quitters, and not just the subsample of 
users for whom more proximal outcomes were influenced by the TPP measures .29 
Professor  Chaloupka further submits that given that the questions about quitting -related 
behaviours were only asked of smokers, any analysis that uses these as outcomes are likely to 
considerably understat e the effects of the TPP measures  on quitting ‐related intentions and 
behaviour. This is especially so given that the recent quitters whose intentions and behaviour are 
likely to have already been influenced by the TPP measures  are not included in the analysis. 
Instead, analyses that employ these outco mes focus on the sample of smokers that are least likely 
to have been influenced by the TPP measures , making it less than surprising that the findings on 
the impact of the TPP measures  on quitting -related behaviour variables are relatively weak.30  
17.  Overall,  Professor  Chaloupka contends that the pattern of results reported by Ajzen et al. is 
consistent with the strengths and limitations of the NTPPTS data. As expected, Ajzen et al. found 
consistent and statistically significant effects for the impact of the TPP measures  on the most 
proximal outcomes. The impact is smaller, less statistically significant and less consistent as the 
focus shifts to less proximal outcomes, such as health knowledge and perceptions of the health 
risks. Likewise, the impact is smalle r, less significant and less consistent as the focus shifts to 
more distal outcomes, including intentions and other quit ‐related measures.31 
18.  Ajzen et al. respond that Professor  Chaloupka's assertion  that the more distal outcomes will 
be less affected by the  policy than the more proximal outcomes is unfounded. In their view, this 
weakening of the policy across the chain of effect does not reflect a limitation of the NTPPTS data, 
but the theoretically expected decline in the impact of the TPP measures  across t he chain of effect 
                                                
25 Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  96-99. 
26 See Australia's response to Panel question No. 196, para. 236; and Australia's comments on the 
complainants' responses  to Panel question No. 197, paras.  369-376. 
27 See Chaloupka Rebuttal Report , (Exhibit AUS -582), paras.  2 and 10 ; Chaloupka Second Rebuttal 
Report, (Exhibit AUS -590), para.  12; and Chaloupka Third Reb uttal Report, (Exhibit AUS -604), para.  7. 
28 See Chaloupka Rebuttal Report , (Exhibit AUS -582), paras.  2-5. 
29 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 6; and Chaloupka Third Rebuttal Report, 
(Exhibit AUS -604), paras.  4-5. 
30 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 7; Chaloupka Second Rebuttal Report , 
(Exhibit AUS -590), para. 20; and Chaloupka Third Rebuttal Report , (Exhibit AUS -604), para. 6. 
31 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 9; and Chaloupka Third Re buttal Report , 
(Exhibit AUS -604), paras.  2-7. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  from pack appeal to behaviour.32 Ajzen et al. further contend that Professor  Chaloupka's assertion  
that the NTPPTS data cannot reveal longer -term effects of the TPP measures  because of its 
cross-sectional nature is unfounded. According to  them, a cross -sectional design is widely used 
and accepted. In addition, the results found in the NTPPTS data are confirmed by the findings 
based on the longitudinal International Tobacco Control (ITC) Policy Evaluation Project (ITC 
Project).33 Likewise, A jzen et al. argue that Professor  Chaloupka's assertion  that the NTPPTS 
dataset has enough statistical power to detect small changes in the most proximal outcomes but 
not in more distal outcomes is unfounded. Ajzen et al. claim that the statistical power of  the 
NTPPTS data to detect small changes in proximal and distal outcomes is very similar.34 Similarly, 
Ajzen et al. contend that Professor  Chaloupka's assertion  that the NTPPTS data underestimate 
changes in some measures of intention because recent quitters  who gave up smoking because of 
the TPP measures  have not been asked is unfounded because the TPP measures  did not increase 
quitting behaviours in the short term.35 
1.1.2   International Tobacco Control  Policy Evaluation Project  
19.  As described in Appendix  A, the ITC Project is a longitudinal cohort survey on the 
determinants of tobacco control policies in more than 20  countries, including Australia. The ITC 
Project covers a number of questions related to GHWs, including on consumers ' thoughts, 
behaviours and intention s towards quitting.  
20.  The Australian component of the ITC Project used by Yong et al. 2015 was conducted between 
September  2011 and February  2012 for the pre -implementation period and between February  and 
May 2013 for the post -implementation period.  
21.  Yong et al. 2015 analyse the relationship between health warning label reactions and quit 
intention s. The authors present the results of various GEE models controlling for age, sex, income, 
education, cigarettes per day, past year quit attempts, survey mode (phone  vs. web) and wave of 
recruitment.36 
22.   Yong et al. 2015 find that the TPP measures  have led to a statistically significant increase in 
the proportion of adult smokers thinking more about smoking health risks and quitting as a result 
of the GHWs. In particula r, they report a statistically signi ficant increase in the proportion  of 
respondents who did not focus on health warning labels first, but who now focus on them first, and 
thought more about quitting as a result of the health warning labels. Conversely, th e subgroup of 
respondents wh o chose not to focus on the health warning labels experienced less cognitive 
reactions and thought less about quitting. In addition, Yong et al. 2015 find that adult smokers, 
who had been stimulated by health warning labels to t hink about the harm caused by smoking and 
about quitting, were more motivated to quit smoking in the future. In that context, the authors 
argue that the cognitive reactions serve as an important pathway through which the effects of 
more upstream reactions to the health warning labels exert their influence on quit intentions. Yong 
et al. 2015 explain, however, that given that the prediction of quit intentions was based on 
cross-sectional data, caution needs to be exercised in interpreting the finding as caus al. The 
authors note that while intentions are logically subsequent to reported past reactions, it is possible 
that the person 's intentional state may affect their recall of past reactions.37 
23.   Ajzen et al., in their expert report submitted by  the Dominican  Republic  and Indonesia, 
review Yong et al.'s analysis and submit that given that they only had access to a small subset of 
the ITC dataset, they were unable to present a comprehensive assessment of data, including 
correcting for the possibility o f false positive findings due to multiple hypothesis testing (i.e. 
statistically significant results might have occurred by chance), controlling for anti -smoking 
advertising in mass media and testing for wear -out effects.38 Ajzen et al. further contend that  
                                                
32 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  39-45. 
33 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  46-49, Appendix  I. 
34 See Ajzen et al. Data Rebuttal Report, (Exhi bit DOM/IDN -6), paras.  50-54, Appendix  II. 
35 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  55-62, Appendix  III. 
36 See Yong et al. 2015, (Exhibit DOM -382).  
37 See Yong et al. 2015, (Exhibit DOM -382).  
38 See Dominican  Republic 's comments on Australia's response to Panel question No. 196, 
paras.  409-414. See also  Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  12-19. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  Yong et al. 2015 failed to report effect sizes, explore wear -out effects, correct for multiple 
hypothesis testing and justify their selection of outcome variables available in the ITC dataset. In 
particular, they criticise Yong et al. 2015 for not reporti ng the statistically significant or 
non-significant impact of the TPP measures  on certain downstream variables.39 
24.  Ajzen et al. find that although the TPP measures  have had a small positive and statistically 
significant impact on thinking about quitting as a  result of the GHWs, there was also a small but 
statistically significant decrease in the proportion of adult smokers that reported interest in 
quitting and intentions to quit. According to Ajzen  et al., Yong et al. 2015 did not report these two 
last resul ts, which are in the "wrong direction" for the TPP measures .40  
25.  Australia contends that Ajzen et al. correctly conclude that the TPP measures  have 
significantly increased cognitive reactions to GHWs.41 However, Australia is of the view that  Ajzen 
et al., whe n concluding that interest in and intentions to quit decreased post -plain packaging, do 
not acknowledge or appear to appreciate that questions relating to quit intentions were not asked 
of recent quitters – the cohort whose intentions and behaviours were m ost likely to have been 
influenced by the TPP measures .42 Australia concludes that consequently the sample Ajzen et al. 
used to analyse quit intentions was negatively biased.  According to Ajzen et al., Australia and its 
experts do not contest the accuracy of their analytical approach or their results, and do not 
challenge their "serious criticisms" of Yong et al. 2015.43 They submit  that Australia 's sole criticism 
regarding the ITC analysis seeks to deni grate the quality of the ITC dataset itself, claiming that it 
provides a "biased" sample to measure the impact on quit intentions and quit interests. According 
to Ajzen et al., Australia 's argument assumes that the TPP measures  led smokers to quit shortly 
after their introduction, and that these "recent quitters" were subsequently excluded from 
responding to questions on quit intentions and quit interests in the ITC survey. However, Ajzen 
et al. submit  that the data show that no additional quit attempts wer e made post -implementation , 
which contradict Australia's argument . Further, Ajzen et al. consider it surprising to hear (for the 
first time) from Australia that the ITC dataset is "biased " in this regard because it was developed 
by the tobacco control comm unity to measure the real -world impact of tobacco control measures, 
such as plain packaging, on smoking -related outcomes, including the impact of the TPP measures  
on quit intentions.44 Ajzen et al. argue  that it is only after having demonstrated that quit intentions 
have not increased post -implementation that Australia claims that the ITC sample is biased in 
relation to this particular measure.45 
1.1.3   Australian Secondary Students Alcohol Smoking and Drug Survey  
26.  As described in Appendix  A, the 2013 ASSAD survey e xtension is a survey of students in 82 
secondary schools in Victoria and Queensland tracking their beliefs and attitudes about cigarette 
packaging, ratings of popular cigarette brands, noticing health warnings on cigarette packs, 
awareness of the specific harms of tobacco use, and perceptions of the prevalence of smoking and 
intention to smoke.46 
27.  White et al. 2015b employ the ASSAD survey data to examine the impact of the 
TPP measures  on students aged 12 -17 years. The authors estimate a logistic regression m odel of 
youth smokers' experience with quit intentions controlling for age, sex, school type, state and 
smoking status.47 
28.  White et al. 2015b find that the TPP measures  have had no impact in the proportion of 
students who , having seen a cigarette pack in the  previous six months , thought about quitting 
smoking.  The authors conclude that the data suggest that the introduction of the TPP measures 
                                                
39 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  30-37 and 53 -58. 
40 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  24 and 28.  
41 See Australia's response to Panel question No. 196, paras.  225 and 237.  
42 Australia's response to Panel question No.  196, para.  237. 
43 See Dominican  Republic's  comments on Australia's response to Panel question No. 196, 
paras.  409-414. See also Ajzen et al. Second Data Rebuttal Report , (Exhibit  DOM/IDN -8), paras.  13-16. 
44 See Ajzen et al. Second Data Rebuttal Report , (Exhibit  DOM/IDN -8), paras.  15-16. 
45 See Ajzen et  al. Second Data Rebuttal Report, (Exhibit DOM/IDN -8), para.  14. 
46 See Dominican  Republic's  second written submission, paras.  443-456. 
47 See White et al. 2015b , (Exhibits HND -135, DOM-236, DOM -288). WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  did not induce adolescent to attend to and process warnings on cigarette packs to a greater extent 
than when GHWs cov ered 30% of the front of a fully branded pack.48 
29.  According to the Dominican  Republic , the results published in White  et al. 2015b may provide 
an unduly positive and inaccurate impression of the full dataset, but without full access to the 
ASSAD survey data, it cannot make an objective assessment of White et al.'s findings.49 The 
Dominican  Republic  further contends that although  in another study White et al. 2015a conclude 
that there is a change in the visual appeal of packs among adolescents50, that reduced appeal does 
not have any meaningful impact on quit intentions.51 
1.1.4   Cigar and cigarillo smokers surveys  
30.  Miller  et al. 2015 conducted , in February  and March  2014, individual interviews with regular 
premium cigar smokers, as well as two focus groups with premium cigarillo smokers and 
occasional premium cigar smokers, four focus groups with non -premium cigarillo smokers, an d an 
online survey of current cigar and cigarillo smokers.52 The interviews took place 15 months after 
the TPP measures  became mandatory. The authors present descriptive statistics of the responses 
of these interviews, focus groups and the online survey.  
31.  Miller et al. 2015 find that non -premium cigarillo smokers reported high plain packaging 
exposure and more contemplation of quitting.  
32.  Ajzen et al., in their expert report submitted by  the Dominican  Republic  and Indonesia, argue 
that the conclusions that ca n be drawn from the results reported by Miller et al. 2015 are limited 
by several methodological shortcomings, such as the non -representativeness of survey 
participants, the unsuitability of focus groups to draw causal inferences, failure to control for 
exposure to anti -smoking campaigns and changes in tobacco prices, and absence of "baseline" 
information collected before the implementation of the TPP measures .53 They further claim that 
Miller et al. 2015 did not mention that the cigar and cigarillo smokers participating in the online 
survey reported no change in thinking about quitting. According to Ajzen et al., the TPP measures  
have had no impact on reported changes in thoughts about quitting among cigar and cigarillo 
smokers, because the TPP measures  did not affect their ratings of the appeal, taste or quality of 
the products they currently smoked, their enjoyment of smoking or its perceived health risks. More 
generally, Ajzen et al. contend that smoking cigarettes and smoking cigars (or cigarillos) are 
different behaviours, with potentially different determinants, which implies that the findings about 
the TPP measures  on cigarette -related cognitions and behaviours cannot be generalized to 
cigars.54 
1.1.5   Commissioned Roy Morgan Research Survey (Australia and New Zealand ) 
33.  Roy Morgan Research dataset, commissioned by Professor  Klick, is a survey of current or 
former (in the past 12 months) smokers in both Australia and New Zealand . The first wave of the 
survey was completed prior to the implementation of Australia's TPP measures  between 
2 November  2012 and 26  November  2012 in Australia and between 8  November  2012 and 
1 December  2012 in New Zealand . Subsequent waves were carried out  at three -month intervals 
up until February  2014.55 Professor  Klick employs the Roy Morgan Research data to estimate a 
difference -in-difference logit model that explains the respondents ' experience with their intention 
to quit in Australia and New Zealand , controlling for the TPP measures , an Australian baseline 
variable, a common baseline variable and a post -TPP implementation time -period.  
                                                
48 See White et al. 2015b, (Exhibits HND -135, DOM -236, DOM -288), p. ii56.  
49 See Dominican  Republic's  second written submission, para. 445. 
50 See White  et al. 2015a, (Exhibits AUS -186, DOM-235).  
51 See Dominican  Republic's  second written submission, paras.  443-456; and Dominican  Republic's  
comments on Australia's response to Panel question No. 196, para. 390. 
52 See Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
53 See Dominican  Republic's  second written submission, paras.  457-462. See also Ajzen et al. Data 
Report, (Exhibit DOM/IDN -2), paras. 251-262. 
54 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  251-262. 
55 See Klick Report , (Exhibit UKR -5), pp. 6-8. See section 1.6.6 in the main body of these Reports for a 
description of Ukraine's participation in these proceedings.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  34.  Professor  Klick finds that the TPP measures  have had no statistically significant effect on 
smokers' quit intention s and expectations about future smoking in Australia relative to 
New Zealand . In particular, he reports no statistically significant impact of the TPP measures  in 
Australia relative to New Zealand  on the likelihood that the respondents seriously considered 
quitting smoking, had the desire, even slightly, to give up smoking, or had the intention to try to 
quit smoking in the next six months.56 Similarly, Professor  Klick's finds no statistically significant 
impact of the TPP measures  on the likelihood that the re spondents were thinking about increasing 
future smoking, smoking just as much, trying and easing up future smoking, changing to a low tar 
brand or making a definitive attempt to quit.57 
35.  As explained in Appendix  A, Australia's expert, Dr  Chipty, does not ref er directly to 
Professor  Klick's analysis of quitting -related cognitions outcomes based on the Roy Morgan 
Research data. However, a number of general criticisms formulated by Dr  Chipty regarding 
Professor  Klick's difference -in-difference analysis of smoking incidence are also relevant to the 
analysis of quitting -related cognitions outcomes. Dr  Chipty submits that Professor  Klick's analysis 
of the Roy Morgan Research data is invalid because the commissioned Roy Morgan survey does 
not include a pre -period and does not allow for distinguishing which respondents had noticed in 
plain packaging. Dr  Chipty contends also that New Zealand  is an invalid counterfactual for the 
purposes of studying the effects of plain packaging, because New Zealand  increased the excise tax 
on cigarettes in January  2013 one month after the introduction of the TPP measures .58  
1.2  Analysis by the Panel  
36.  We note that only four peer -reviewed studies papers assess the impact of Australia's 
TPP measures  and enlarged GHWs on quitting -related cognitions among adult cigarette smokers, 
cigar and cigarillo smokers and adolescents.  
37.  A careful review of the Durkin et al. 2015 and Yong et al. 2015 papers and the econometric 
evidence submitted by the Dominican  Republic , Honduras and Indonesia suggests that the impact 
of the TPP measures  on quitting intentions among adult smokers is limited and mixed.  
38.  We note that Durkin et al. 2015 only find some evidence that the TPP measures  have had a 
positive and statistically significant impact on the intention to  quit during the late transition period 
of the TPP. They report no statistically significant impact of the TPP measures  on daily thoughts 
about quitting, intention to quit and setting a firm date to quit among adult smokers in the first 
year of the TPP.59 We note that Ajzen et al., applying an alternative estimation methodology, 
which consists of re-estimating the model without the daily trend, confirm most of Durkin et al.'s 
results. We note, however, that the results of the logistic model reported by Ajzen  et al. suggest 
that the TPP measures  have had a positive and statistically significant (at the 10% level) impact on 
the likelihood of adult smokers reporting having set a firm date to quit in the next month. The 
results of the linear regression also sugge st that the TPP measures  have had a negative and 
statistically significant (at the 10% level ) impact on quitting importance.60 More generally, we note 
that Australia did not rebut Ajzen et al.'s and Professor  Klick's  alternative estimation methodology 
and a ssociated results.  We are, however, not persuaded by Professor  Klick's claim that unadjusted  
model s, which do not control for individual characteristics , addiction level  and other tobacco 
control policies ( exposure to anti -smoking television advertising an d cigarette costliness) , should 
be considered at least equally valid compared with adjusted models  that do  control for these 
variable s. We note that Ajzen et al. focused their analysis on the adjusted models. We further note 
that the econometric results fo r quitting -related variables (i.e. quitting importance, thoughts about 
quitting) reported by Professor  Klick are also based on adjusted models that control for the 
respondent's individual characteristics.  Professor  Klick further acknowledges  that the resul ts he 
reported do not change when the variables for addiction level, exposure to anti -smoking television 
advertising and cigarette costliness  are included in the model specification , which would suggest 
that the risk of endogenous bias might be limited . 
                                                
56 See Klick Report , (Exhibit UKR -5), pp. 18 and 37 -44. 
57 See Klick Report , (Exhibit UKR -5), pp. 18 and 37 -47. 
58 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  54-71. 
59 See Durkin et al. 2015, (Exhibit s AUS-215 (revised), DOM -305). 
60 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  165-173, Appendix  A, pp. 90-92. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  39.  Unlike Durkin et al. 2015, Yong et al. 2015 find relatively more evidence of a positive impact 
of the TPP measures  on quitting -related cognitions. In particular, Yong et al. 2015 report a 
statistically significant impact of the TPP measures  on thinking mor e about quitting as a result of 
health warnings among adult smokers who switched from initially focusing away to focusing on 
health warning labels. They further find that adult smokers, having been stimulated by health 
warning labels to think about the har ms of smoking and about quitting, reported being more 
motivated to quit smoking in the future.61 We note that Ajzen et al. confirm that the TPP measures  
have had a positive and statistically significant impact on thinking about quitting but qualify it as 
small.62 Ajzen et al. further report a small and statistically significant decrease in the proportion of 
adult smokers reporting their interest in quitting and intention to quit.63 We note that Ajzen et al. 
do not offer an explanation as to why the TPP measure s would have decreased  smokers' interest in 
quitting and intention to quit. We note that it is conceivable that these  findings could  partly  result 
from the fact that, as observed by Australia, questions on quitting intention were not asked of 
recent quitte rs, contrary to Ajzen et al.'s claim that the question was asked to both smokers and 
recent quitters , although it is not clear, in the absence of specific evidence relating to the number 
of recent quitters, to what extent this circumstance may account for the results . 
40.  We observe that the conclusion that the impact of the TPP measures  on quitting intentions is 
limited and mixed is confirmed by the two other peer -reviewed studies on adolescent and cigar 
and cigarillo smokers. White et al. 2015b suggest that t he TPP measures  have had no impact on 
thinking about quitting smoking among adolescents, which is consistent with the findings reported 
in Durkin et al. 2015. Conversely, the descriptive statistics analysis of Miller et al. 2015 suggests 
that the share of non-premium cigarillo smokers contemplating quitting increased.64 As explained 
in our review of the post -implementation studies before us on proximal outcomes65, we see no 
basis to reject Miller et al.'s findings on the basis of Ajzen et al.'s criticism, noting that the result 
on quitting intentions reported in Miller et al. 2015 is in line with the results reported in Durkin 
et al. 2015. We note, however, that Miller et al. 2015 provide no empirical evidence on quitting 
intentions among (premi um or non -premium) cigar smokers.  
41.  Finally, as explained in our review of Professor  Klick's analysis of GHW effectiveness and 
smoking incidence based on the commissioned Roy Morgan Research data, we question the 
robustness of his results. We question the va lidity of  the pre -period of the commissioned data , 
because it corresponds to the TPP measures  transition period , during which plain packs could 
already be sold on the Australian market. In addition, Professor  Klick's analysis does not control 
for New Zeala nd's excise tax increase one month after the introduction of the TPP measures , which 
leads us to question the use of New Zealand  as a counterfactual.66 
2  EVIDENCE RELATING TO  PACK CONCEALMENT AND  MICRO -INDICATORS OF CONCER N 
SINCE THE ENTRY INTO  FORCE OF THE TPP MEASURES  
42.  Six peer -reviewed papers analyse empirically the impact of Australia's TPP measures  on distal 
outcomes related to quitting: (i)  Durkin et al. 2015; (ii)  Yong et al. 2015; (iii)  Zacher et al. 2014; 
(iv) Zacher et al. 2015; (v)  White et al. 2015b ; and (v i) Miller et al. 2015.67 Professor  Klick, in his 
expert report submitted by Ukraine, also assess es the impact of the TPP measures  on pack 
concealment and related variables.68 
                                                
61 See Yong et al. 2015, (Exhibit DOM -382).  
62 We note that Ajzen et  al. only replicate one part of the analysis of Yong et al. 2015 and do not 
analyse the relationship of changes in a ttentional orientation response pattern with changes in GHW reactions 
and the association of GHWs with quit intentions.  
63 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  24 and 28.  
64 See Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
65 See Appendix  A, paras.  32 and 71 above . 
66 See Appendix  A, para. 72 above . 
67 See Durkin et al. 2015, (Exhibit s AUS-215 (revised) , DOM-305); Yong et al. 2015, (Exhibit 
DOM-382); Zacher et al. 2014, (Exhibits AUS -222 (revised), JE -24(68), DOM -286); Zacher et al. 2015, 
(Exhibits AUS -223 (revised), DOM -287); White et al. 2015b, (Exhibits HND -135, DOM -236, DOM -288); and 
Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
68 See section 1.6.6 in the  main body of these Reports  for a description of Ukraine's participation in 
these proceedings.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  2.1  Datasets and related studies  
2.1.1   National Tobacco Plain Packaging Tracking Survey  
43.  Durkin et al. 2015 use the NTPPTS data to analyse the impact of the TPP measures  on pack 
concealment and micro -indicators of concern.69 The NTPPTS Technical Report measured two 
micro -indicators of concern about smoking, namely stubbing out a tobacco product before finishing 
due to thoughts about the harms of smoking, and stopping oneself from smoking despite an urge 
to smoke.70 The authors estimate logistic models of the respondents' experiences regarding pack 
concealment and other related behaviours b y adjusting for baseline levels and controlling for the 
date of the follow -up survey, number of days between baseline and follow -up survey, anti -smoking 
television advertising in the three months prior to the follow -up survey, change in cigarette 
costlines s, addiction level and other individual characteristics.71 Durkin et al. 2015 also present the 
results of unadjusted models, where the baseline response is the only control variable . 
44.  Durkin et al. 2015 find that the TPP measures  were associated with increas ed rates of pack 
concealment and micro -indicators of smoking concern among adult cigarette smokers.72 In 
particular, they find that compared to the referent group of smokers having completed their 
follow -up survey in the pre -TPP period, smokers who were fol lowed -up in the late transition period 
showed greater increases in pack concealment, amounting to several or many times in the 
previous month. Similarly, they find that smokers who were followed -up in the first year of the 
TPP measures  reported greater inc reases  in pack concealment and stubbing out their cigarettes 
before finishing them because they thought about the harm of smoking.73 
45.  Ajzen et al., in their expert report submitted by the Dominican  Republic  and Indonesia, claim 
that Durkin et al.'s conclusions are unwarranted and contradicted by the data, because the 
TPP measures  have had no impact on the majority of the quitting -related measures.74 They further 
contend that Durkin et al. 2015 have adopted a very different and unorthodox comparison  
methodology compared to Wakefield et al. 2015, despite being the same six authors using the 
same dataset, including analysing the same variable on pack concealment. According to 
Ajzen  et al., Durkin et al.'s 2015 analytical approach suffers from serious m ethodological 
shortcomings, including controlling for a non -existent daily trend, failing to investigate wear -out 
effects and not correcting for multiple significances tests.75 According to Ajzen et al., Durkin 
et al.'s 2015 assertion that analysing changes  in the participants' responses from month to month 
minimizes the influence of sampling variation and increase the power of the statistical tests has 
been mathematically proven to be wrong.76 
46.  Based on the NTPPTS data, Ajzen et al. estimate a logistic model for dichotomized outcome 
variables, linear model for continuous outcome variables and ordered logit model for categorical 
outcome variables with the same specification considered by Durkin et al. 2015 but without the 
variable for date of the follow -up inte rview. They find a statistically significant increase in the 
proportion of adult smokers, who were followed -up in the first year of TPP, who concealed their 
pack several or many times. However, they report no statistically significant change in the 
proport ion of adult smokers who were followed -up in the first year of TPP, that stubbed out and 
foregone cigarettes several or many times.77 Ajzen et al. further argue that Durkin et al. 2015 
failed to report the result showing that the TPP measures  has had no imp act on respondents ' 
ability to limit their consumption of cigarettes.78 
                                                
69 See Appendix  A, para. 8 for a description of the NTPPTS data.  
70 NTPPTS Technical Report, (Exhibits AUS -570, HND -124, DOM -307), p. 52. 
71 See Durkin et al. 2015, (Exhibit s AUS-215 (revised), DOM -305). 
72 As discussed in Appendix  A, Wakefield et al. 2015 used the NTPPTS data  and concluded also that 
there was a statistically s ignificant increase in smokers covering their packs . See Wakefield et al. 2015, 
(Exhibit s AUS-206, DOM -306).  
73 See Durkin et al. 2015,  (Exhibit s AUS-215 (revised), DOM -305). 
74 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  174-179. 
75 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  188-198. 
76 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  184-185. 
77 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  165-173, Appendix  A, pp. 90-92. 
78 See Ajzen et al. Data Report, (Exhib it DOM/IDN -2), para. 180. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  47.  Professor  Klick, in his expert report submitted by Honduras, analyses the NTPPTS data on the 
effect of the TPP measures  on quitting -related variables.79 Professor  Klick claims that Wakef ield 
et al. 2015 did not present the results of some variables related to quitting that did not improve or 
might have even gotten worse with the TPP measures .80  
48.  Professor  Klick presents the results of an ordered probit model  control ling for the 
TPP measures  (early TPP period and formal TPP period), gender, age , education, socio -economic 
status and a linear time trend.81 He finds that the TPP measures  had no statistically significant 
impact on  stubbing out cigarettes because of thoughts about smoki ng harms .82 
49.  Professor  Klick further contends that Durkin et al.'s 2015 results of the unadjusted models, 
which show that none of the variables related to pack concealment and micro -indicators of 
concerns are statistically distinguishable from the pre -TPP pe riod, must be given appropriate 
weight and considered as at least equally valid compared with the results of the adjusted models 
for various reasons.83  
50.  As explained above, Australia's expert  Professor  Chaloupka  argues that Ajzen et al.'s analysis 
suffer fr om several limitations, in part due to the fact that the NTPPTS data do not track 
non-smokers who might have taken up tobacco use in the absence of the TPP measures  and are 
cross-sectional.84 In that context, Professor  Chaloupka submits that Ajzen et al. fail to recognize 
that given the analysis considers all current tobacco users and recent quitters, and not just the 
users for whom the TPP measures  have influenced their more proximal outcomes, relatively large 
sample sizes are required to detect the incr easingly smaller effects of more distal outcomes. 
According to Professor  Chaloupka, it is therefore not surprising that by focusing on the sample of 
smokers least likely to have been influenced by the TPP measures , the findings on the impact of 
the TPP measures  on quitting -related behaviour variables are relatively weak.85  
51.  Ajzen et al. contend that , contrary to what Professor  Chaloupka submits, the weakening of the 
TPP measures  across the chain of effect from pack appeal to behaviour is not explained by the  
NTPPTS data's limitation, but by the theoretically expected decline in the impact of the 
TPP measures .86 They further argue that the findings based on the NTPPTS, whose cross -sectional 
nature is widely used and accepted, are supported by those based on the  longitudinal ITC survey 
data.87 Ajzen et al. also claim that the NTPPTS dataset has enough statistical power to detect 
proximal and distal outcomes.88 Likewise, Ajzen et al. disagree with Professor  Chaloupka and 
argue that the NTPPTS data do not underestima te changes in some measures of secondary 
indicators because the TPP measures  have had no impact on quitting behaviours in the short 
term.89 
2.1.2   International Tobacco Control Policy Evaluation Project  
52.  Yong et al. 2015 also use the ITC data to investigate the imp act of the TPP measures  on pack 
concealment and foregoing smoking behaviours. The authors present the results of a GEE model 
                                                
79 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  69-73 and 88-100.  
80 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  61-63. 
81 Professor  Klick explains that , unlike Wakefield et al. 2015, he omits the measure of exposure to mass 
media anti -smoking messages, cigarette costliness and heaviness of smoking index, because these variables 
are endogenous. He further explains that the inclusion of these variables do not change the results he 
prese nted. See Klick Supplemental Rebuttal Report , (Exhibit HND -122), fn 35.  
82 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  74-78 and 80-81. We note that in 
one of Professor  Klick's specification, the impact of the early TPP period variabl e on stubbing out is negative 
and statistically significant.  
83 See para. 14 above for a full summary of Professor  Klick's argument and Klick Supplemental Rebuttal 
Report , (Exhibit HND -122), paras.  91-100.  
84 See para. 16 above for a full summary of Professor  Chaloupka's arguments; and Chaloupka Rebuttal 
Report , (Exhibit AUS -582), paras.  2-5 and 10.  
85 See Chaloupka Rebuttal Report , (Exhibit AUS -582), paras.  6-7 and 9.  
86 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  39-45. 
87 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  46-49, Appendix  I. 
88 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  50-54, Appendix  II. 
89 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  55-62, Appendix  III. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  controlling for age, sex, income, education, cigarettes per day, past year quit attempts, survey 
mode (phone vs. web) and wave of r ecruitment.90  
53.  Yong et al. 2015 find a statistically significant increase in the proportion of adult cigarette 
smokers that avoided health warning labels but no statistically significant change in the proportion 
of those foregoing cigarettes. Similarly, Yon g et al. 2015 find that the subgroup of respondents 
that switched from initially focusing away to focusing on the health warning labels following the 
TPP measures ' introduction avoided health warning labels, but did not forego cigarettes. 
Conversely, the s ubgroup of respondents, which chose to focus away from the health warning 
labels, avoided fewer health warning labels, but did not forego cigarettes.91 
54.  As explained in the review of post -implementation studies on quit intention s, Ajzen et al., in 
their expert report submitted by  the Dominican  Republic  and Indonesia, argue that they could not 
undertake a comprehensive assessment of the ITC dataset, because they only had access to a 
small subset of the data.92 They further claim that Yong et al. 2015 did no t discuss effect sizes, 
analyse wear out effects and account for multiple hypothesis testing. They also criticise Yong et al. 
2015 for failing to justify the outcome variables available in the ITC dataset they selected for their 
analysis and to report the results of some variables. Ajzen et al. replicate the analysis of Yong 
et al. 2015 by re -estimating GEE models controlling for the survey mode (phone vs. web) and 
wave of recruitment, as well as respondents ' age, sex, income, education, cigarettes per day 
consumed and past year quit attempts.93  
55.  Ajzen et al. find that although the TPP measures  have had a moderate positive and 
statistically significant impact on avoiding health warning labels, the TPP measures  did not prompt 
smokers to forego cigarettes.94  
56.  Australia contends that Ajzen et al. correctly conclude that the TPP measures  have 
significantly increased avoidance of GHWs.95 However, Australia argues that  when Ajzen et al., 
conclude that interest in and intentions to quit decreased post -plain packaging, they do not 
acknowledge or appear to appreciate that questions relating to quit intentions were not asked of 
recent quitters, which are the cohort whose intentions and behaviours were most likely to have 
been influenced by the TPP measures .96 Australia concludes that consequently the sample Ajzen 
et al. used to analyse quit intentions was negatively biased.  The Dominican  Republic  disagrees 
with Australia's argument. According to Ajzen et al., the exclusion of recent quitters could not have 
produced a biased sample because the ITC data show that the number of quitters was about the 
same before and after implementation of the TPP measures , implying that Australia's argument is 
contradicted by the data .97 Further, Ajzen et al. consider it surprisin g to hear (for the first time) 
from Australia that the ITC dataset is "biased " in this regard because it was developed by the 
tobacco control community to measure the real -world impact of tobacco control measures, such as 
plain packaging, on smoking -relate d outcomes, including quit intentions.98 
2.1.3   Personal pack display dataset  
57.  CCV undertook an observational survey of the prevalence of cigarette pack display and 
smoking in outdoor venues in Victoria and South Australia between October  2011 and April 2012, 
and a gain between October  2012 and April 2013 and between January  and April 2014. The survey 
provides information on active smoking rates and personal display of cigarette packs on tables 
observed among patrons of public venues with outdoor seating (visible from the footpath) before 
and after the introduction of Australia TPP meas ures. Two peer -reviewed papers employed the 
personal pack display data.  
                                                
90 See Yong et al. 2015, (Exhibit DOM -382).  
91 See Yong et al. 2015, (Exhibit DOM -382).  
92 See Dominican  Republic's  comments on Australia's response to Panel question No. 196, 
paras.  409-414. See also Ajzen et al. Second Data Report , (Exhibit DOM/IDN -4), paras.  12-19. 
93 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  30-37 and 53 -58. 
94 See Ajzen et al. Second Data Report , (Exhibit DOM/IDN -4), paras.  22-27. 
95 See Australia's response to Panel question No. 196, paras.  225 and 237.  
96 Australia's response to Panel question No.  196, para.  237. 
97 See Ajzen et  al. Second Data Rebuttal Report, (Exhibit DOM/IDN -8), paras.  15-16. 
98 See Ajzen et  al. Second Data Rebuttal Report, (Exhibit DOM/IDN -8), para.  6.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  58.  Zacher et al. publish ed two papers assessing empirically  the impact of the TPP measures  on 
pack display, smoking and pack orientation. Zacher et al. 2014 use the personal pack display 
dataset to analyse the rates of pack display, smoking and pack orientation between October  and 
April 2011-2012 (pre -TPP period) and 2012 -2013 (post -TPP).99 The authors report the results of a 
multi-level Poisson regression analysis. Zacher et al. 2014 find that the TPP measures  reduced 
active smoking in outdoor areas of cafés, restaurants and bars, reduced personal pack display on 
tables, and increased steps taken by smokers to conceal packs that would otherwise be visible. In 
particular, the authors find th at the decrease of pack display was stronger in venues with children 
present and limited to mid - and high - socio-economic status areas. Conversely, the decrease in 
packs orientated face -up was found to be stronger in low socio -economic status areas.  
59.  Zache r et al. 2015 re -analyse the rates of pack display, smoking and pack orientation by 
extending the period of analysis with a longer post -implementation period, between January  and 
April 2012 (pre -TPP period), 2013 (early post -TPP period) and 2014 (one year post-TPP period).100 
The authors conclude that after one year Australia's TPP measures  have reduced visibility of 
tobacco products and active smoking in public venues, particularly in the presence of children. In 
particular, the authors report a statisticall y significant decrease in pack display from pre -TPP to 
early post -TPP that remained low after one year following the introduction of the TPP measures . 
That being said, Zacher et al. 2015 find that the statistically significant change from pre -TPP to 
early post-TPP was not sustained one year post -TPP for packs orientated face -up, packs concealed 
by telephones, wallets or other items and for the use of external case.  
60.  Ajzen et al., in their expert report submitted by the Dominican  Republic  and Indonesia, 
reviewed the accuracy and completeness of the findings reported in Zacher et al. 2015. According 
to Ajzen et al., Zacher et al. 2015 failed to report or discuss effect sizes.101 Ajzen et al. further 
argue that Zacher et al.'s explanation that pack changes may ha ve made smokers less inclined to 
smoke in public is hard to reconcile with the finding that pack display did not decline among 
smokers, who continued to smoke at outdoor venues, and that smokers' pack avoidant behaviours 
vanished within a year. Ajzen et al. contend that Zacher et al.'s alternative explanation, according 
to which the small decline observed in outdoor smoking could reflect the overall declining trend in 
smoking in Australia, seems more consistent with the data. According to Ajzen et al., Zach er et al. 
2015 acknowledge that the Personal Pack Display dataset is unable to establish whether the small 
decline observed in outdoor smoking was caused by the implementation of the TPP measures .102 
Ajzen et al. replicated Zacher et al's 2015 analytical app roach and conclude that although there 
was a small decrease in packs displayed and active smoking at outdoor venues, pack -avoidant 
behaviours such as packs orientated face -up, packs concealed and use of external case, "had 
entirely vanished" one -year after  the implementation of the TPP measures .103 
61.  Australia submits that there is no evidence before the Panel to support a finding that the 
impact of the TPP measures  will wear out. Australia argues that Professor  Ajzen relies on the two 
studies by Zacher et al. 2014, 2015 to support the claim of wear out, although Ajzen et al. 
concede that Zacher et al. 2014, 2015 demonstrate that there was a statistically significant decline 
in active smoking at outdoor venues after the introduction of tobacco plain packaging, a n effect 
which was enhanced over time. Similarly, Australia argues that while the Dominican  Republic  and 
Indonesia contend that changes in the way packs are displayed at outdoor venues wore out over 
the course of the study, Ajzen et al. concede that there was a statistically significant and lasting 
decline in the total number of packs displayed.104 
62.  The Dominican  Republic  disagrees with Australia's claim that a statistically significant decline 
in outdoor smoking was enhanced over time and that the TPP measures  have already been 
successful in reducing smoking prevalence. The Dominican  Republic  argues that outdoor smoking 
initially declined and then increased again, although it did not return to its earlier level. The 
Dominican  Republic  further submits that Zacher et al. 2015 themselves acknowledge that the 
finding on the level of outdoor smoking cannot be attributed to the TPP measures , because they 
                                                
99 See Zacher et al. 2014, (Exhibits  AUS-222 (revised), JE -24(68), DOM -286).  
100 See Zacher et al. 2015, (Exhibits  AUS-223 (revised), DOM -287).  
101 See Dominican  Republic's  second written submission, para. 487; response to Panel question No. 126, 
paras.  294-297; and comment s on Australia's response to Panel question No. 196, paras.  416 and 419 -423. 
102 See Ajzen et al. Second Data Report , (Exhibit DOM/IDN -4), paras.  42 and 45 -47. 
103 See Ajzen et al. Second Data Report , (Exhibit DOM -IDN-4), paras.  38-47 and 59 -60. 
104 See Australia's response to Panel question No. 196, paras.  246-247. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  did not control for a host of unrelated factors that could explain the decline in outdoor smok ing 
levels.105  
2.1.4   Australian Secondary Students Alcohol Smoking and Drug Survey  
63.  White et al. 2015b use the ASSAD survey data to examine the impact of the TPP measures  on 
foregoing behaviours by students aged 12 -17 years. The authors estimate a logistic regress ion 
model controlling for age, sex, school type, state and smoking status.106 
64.  White et al. 2015b find that the TPP measures  have had no impact on the proportion of 
students, who had seen a cigarette pack in the previous six months, and that did not have a 
cigarette because of the health warnings.  The authors conclude that the data suggest that the 
introduction of the TPP measures did not induce adolescent s to attend to and process warnings on 
cigarette packs to a greater extent than when GHWs covered 30% of t he front of a fully branded 
pack.107 
65.  The Dominican  Republic  submits that it could not make an objective assessment of White 
et al.'s findings without full access to the ASSAD survey data. The Dominican  Republic  further 
argues that although in a different stu dy White et al. 2015a conclude that the TPP measures  have 
reduced the visual appeal of packs among adolescents108, that reduced appeal does not have any 
meaningful impact on quit intentions and secondary indicators of quitting.109 
2.1.5   Cigar and cigarillo smokers surveys  
66.  Miller et al. 2015 use the responses from a series of interviews, focus groups and an online 
survey of current cigar and cigarillo smokers and find that premium cigar and cigarillo smokers, 
who were exposed to the TPP measures , tried to avoid the he alth warning labels by decanting the 
individual cigars and cigarillos from the box to a humidor or an unbranded tin. Similarly, they 
report an increase in pack concealment among non -premium cigarillo smokers.110  
67.  Ajzen et al., in their expert report submitte d by the Dominican  Republic  and Indonesia, 
consider that the conclusions that can be drawn from Miller et al.'s results are limited by several 
methodological shortcomings, such as the non -representativeness of survey participants, 
unsuitability to draw cau sal inferences from focus groups and interviews, failure to control for 
confounding factors, and absence of "baseline" information collected before the TPP measures ' 
implementation. They further argue that Miller et al. 2015 failed to report that the onlin e survey 
participants in the online survey reported no change in stubbing out cigars or cigarillos and in 
stopping smoking. More generally, Ajzen et al. submit  that any findings about the TPP measures  
on cigarette -related cognitions and behaviours cannot b e generalized to cigars because smoking 
cigarettes and smoking cigars are different behaviours, with potentially different determinants.111 
2.1.6   Commissioned Roy Morgan Research Survey (Australia and New Zealand ) 
68.  Professor  Klick uses the Roy Morgan Research data to estimate a difference -in-difference logit 
model that explains the respondents ' experiences concealing their packs in Australia and 
                                                
105 See Ajzen et al. Second Data Rebuttal  Report , (Exhibit DOM/IDN -8), paras.  17-21; 
Dominican  Republic's  second written submission, para. 487; Dominican  Republic's  response to Panel question 
No. 126, paras.  294-297; and Dominican  Republic's  comments on Australia's response to Panel question 
No. 196, paras.  416 and 419 -423. 
106 See White et al. 2015b, (Exhibits HND -135, DOM-236, DOM -288). 
107 See White et al. 2015b, (Exhibits HND -135, DOM -236, DOM -288), p. ii56.  
108 See Appendix  A, paras.  20-22 and 80-81 (review ing White et al. 2015a, (Exhibits AUS -186, 
DOM-235)). 
109 See Dominican  Republic's  second written submission, paras.  443-456; and comments on Australi a's 
response to Panel question No. 196, para. 390. 
110 See Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
111 See Dominican  Republic's  second written submission, paras.  457-462. See also Ajzen et al. Data 
Report, (Exhibit DOM/IDN -2), paras.  251-262. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  New Zealand , controlling for the TPP measures , an Australian baseline variable, a common 
baseline variable and a post -TPP implementation time -period.112 
69.  Professor  Klick concludes that the TPP measures  have had no statistically significant effect on 
smokers' preferences or feelings about being seen with a plain pack in Australia relative to a 
non-plain pack in New Zealand .113 In particular, Professor  Klick finds no statistically significant 
impact of the TPP measures  in Australia relative to "regular" packs in New Zealand  on the 
likelihood of respondents reporting they had placed a cover over the cigarettes, placed the 
cigaret tes in a different container or kept the pack out of sight.114 Professor  Klick further reports 
no statistically significant impact of the TPP measures  in Australia relative to New Zealand  on the 
likelihood the respondents successfully giving up smoking for m ore than a month, switching to a 
brand with lower tar or nicotine, reducing the number of cigarettes smoked in a day, or recently 
stopping smoking for 24  hours at least once during the last three months. In addition, he reports 
no statistically significant  impact on the likelihood of the respondents increasing the number of 
cigarettes smoked, unsuccessfully trying to switch to a brand with lower tar or nicotine or 
unsuccessfully trying to reduce the number of cigarettes smoked in a day.115  
70.  Although Australia 's expert Dr  Chipty does not address directly Professor  Klick's analysis of 
pack concealment behaviours based on the Roy Morgan Research data, she raises several 
criticisms of Professor  Klick's difference -in-difference analysis of smoking incidence, which also 
apply to his analysis of pack concealment behaviours. Dr  Chipty contends that Professor  Klick's 
analysis of the Roy Morgan Research data is invalid because the Roy Morgan survey does not 
contain a pre -period and is unable to distinguish which responde nts had noticed plain packaging. 
Dr Chipty further argues that New Zealand  is an invalid counterfactual for the purposes of studying 
the effects of plain packaging, because New Zealand  increased its excise tax in January  2013, one 
month after the introduct ion of the TPP measures .116  
2.2  Analysis by the Panel  
71.  The parties submitted five peer -reviewed papers that investigate empirically the impact of the 
TPP measures  and enlarged GHWs on pack concealment and micro -indicators of concern. While 
four of these studies  use responses of survey data on adult smokers, cigar and cigarillo smokers or 
adolescents, the two papers by Zacher et al. 2014, 2015 analyse actual observed behaviours of 
pack concealment among adult smokers. In addition, an expert report  prepared by Professor  Klick, 
submitted by  Ukraine,  contains a study assess ing the impact of the TPP measures  on pack 
concealment.117 
72.  A careful assessment of Durkin et al. 2015, Yong et al. 2015 and Zacher et al. 2014, 2015 
and the econometric evidence submitted by the Dominican  Republic , Honduras and Indonesia 
suggests that the TPP measures  have increased pack concealment among adult cigarette smokers. 
However, empirical evidence of the impact of the TPP measures  on stubbing out cigarettes before 
finishing them due to th oughts about the harms caused by smoking and stopping smoking among 
adult cigarette smokers is much more limited and mixed.  
73.  We note that Durkin et al. 2015 find some evidence that the TPP measures  have had a 
positive and statistically significant impact o n pack concealment and stubbing out cigarettes but no 
impact on stopping smoking among adult cigarette smokers in the first year of implementation of 
the TPP measures .118 Ajzen et al., applying an alternative estimation methodology and correcting 
for multipl e testing bias, reverse the results reported in Durkin et al. 2015 and find that the 
TPP measures  have had no impact on pack concealment, stubbing out or stopping smoking.119 
                                                
112 See Appendix  A, paras.  62-63 and Appendix  B, para. 33 for a description of the Roy Morgan 
Research data.  
113 See Klick Report , (Exhibit UKR -5), pp. 18 and 54 -56. 
114 See Klick Report , (Exhibit UKR -5), pp. 18 and 54 -56. 
115 See Klick Report , (Exhibit UKR -5), pp. 18 and 37 -44. 
116 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  54-71. 
117 See section 1.6.6 in the main body of these Reports  for a description of Ukraine's participation in 
these proceedings.   
118 See Durkin et al. 2015, (Exhibit s AUS-215 (revised) , DOM-305).  
119 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  188-198. We note that a comparison of 
the results with and without the trend variable shows that the coefficient of the constant variable is very larg e 
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  Similarly, Professor  Klick, using a different model specification , finds that the TPP measures  had no 
impact on stubbing out. We note that Australia did not challenge Ajzen et al.'s and 
Professor  Klick's alternative estimation methodology and results , but generally considers that the 
structure of the NTPPTS is likely to be more suited to  detecting changes in proximal outcomes than 
in more distal variables, such as quitting -related behaviours .120 As explained in our review of the 
evidence on quitting -related cognition, we are not persuaded by Professor  Klick's claim that 
unadjusted models, which do not control for individual characteristics and tobacco control policies, 
should be considered at least equally valid compared to adjusted models, noting that Ajzen et al. 
focused their analysis on adjusted mod els and Professor  Klick presented econometric results for 
stubbing out based on an adjusted model that control s for the respondent's individual 
characteristics.121 
74.  We observe that the results presented in Yong et al. 2015 are partially in line with those in 
Durkin et al. 2015. Yong et al. 2015 report a positive and statistically significant impact of the 
TPP measures  on avoiding the health warning labels and a statistically non -significant impact on 
foregoing among adult smokers.122 We note that Ajzen et al. confirm that the TPP measures  have 
had a positive and statistically significant impact on avoiding GHWs and that they qualify it as a 
medium effect.123 
75.  The empirical evidence regarding the positive impact of the TPP measures  on smokers' 
avoidant responses publ ished in Durkin et al. 2015 and Yong et al. 2015 is to some extent 
corroborated by Zacher et al.'s 2014, 2015  papers , who suggest that one year after the 
introduction of the TPP measures , the display of personal pack in outdoor areas of cafés, 
restaurants and bars has decreased, particularly in the presence of children.124 Zacher et al. 2015 
find, however, that the reduction in the proportion of packs oriented face -up and the increase in 
concealed packs by telephones, wallets or other items and in the use of external cases was not 
sustained one year after the introduction of the TPP measures . We note that Ajzen et al.'s analysis 
of the Personal Pack Display dataset confirms all the findings reported in Zacher et al. 2015 but 
that they qualify the impact for bo th packs displayed and active smoking at outdoor venues as 
small.125 
76.  Similarly, the limited available evidence on adolescents and cigar and cigarillo smokers 
corroborate s part of the findings reviewed above. Although White et al. 2015b provide no empirical 
evidence on pack concealment among young smokers, they find that the TPP measures  have had 
no statistically significant impact on the frequency of not having a cigarette because of the health 
warnings126, which is in line with the findings on foreg oing smoking  reported in Durkin et al. 2015 
and Yong et al. 2015. The descriptive statistics analysis by Miller et al. 2015 suggests that the 
share of premium cigar and cigarillo smokers and of non -premium cigarillo smokers reporting 
decanting the cigar fr om the boxed to a humidor or concealing their pack have increased127, which 
is partially in line with the results reported in Durkin et al. 2015, Yong et al. 2015 and Zacher et al. 
2014, 2015. As explained in more detail in Appendix  A, we see no basis to rej ect entirely Miller 
et al.'s findings on the basis of Ajzen et al.'s criticism.128  
77.  Finally, as explained above and in our review of Professor  Klick's analysis of GHWs 
effectiveness and smoking incidence based on the commissioned Roy Morgan Research data, we  
question the validity of the pre -period of the commissioned data and the use of New Zealand  as a 
                                                                                                                                                  
when the trend variable is included in the model specification. The coefficient value of the other variables is 
usually marginally affected by removing the trend variable.  
120 See Australia's comments on the complainants' responses  to Panel question No. 197, 
paras.  371-375.  
121 Professor  Klick further acknowledges that the results he reported do not change when the variables 
for addiction level, exposure to anti -smoking television advertising and cigarette costliness  are included in the 
model specification , which would suggest that the risk of endogenous bias might be limited.  
122 See Yong et al. 2015, (Exhibit DOM -382).  
123 See Ajzen et al. Second Data Report , (Exhibit DOM/IDN -4), paras.  22-27. 
124 See Zacher et al. 2014, (Exhibits AUS -222 (revised), JE -24(68), DOM-286); and Zacher et al. 2015, 
(Exhibit  AUS-223 (revised), DOM -287).  
125 See Ajzen et al. Second Data Report , (Exhibit DOM/IDN -4), para. 44. 
126 See White et al. 2015b , (Exhibits HND -135, DOM-236, DOM -288). 
127 See Miller et al. 2015, (Exhibits AUS -102, DOM -315).  
128 See Appendix A, paras.  32 and 71 above.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  counterfactual, and therefore the overall robustness of Professor  Klick's results  based on these 
data.129  
3  EVIDENCE RELATING TO  QUIT ATTEMPTS SINCE THE ENTRY IN TO FORCE OF THE 
TPP MEASURES  
78.  Two peer-reviewed papers investigate empirically the impact of Australia's TPP measures  on 
quit attempts: (i)  Durkin et al. 2015 and Young et al. 2014.130 The expert report by 
Professor  Klick, submitted by Ukraine,  also contains an analysis of the impact of the TPP measures  
on quitting.131 
3.1  Datasets and related studies  
3.1.1   National Tobacco Plain Packaging Tracking Survey  
79.  Durkin et al. 2015 use the NTPPTS data to assess the impact of the TPP measures  on 
short-term changes in quit ting-related behaviours. The authors estimate various logistic models of 
respondents' experiences with quit attempts by adjusting for baseline levels and controlling for the 
date of the follow -up survey, number of days between baseline and follow -up survey , anti-smoking 
television advertising in the three months prior to the follow -up survey, change in cigarette 
costliness, addiction level and demographic characteristics.132 Durkin et al. 2015 also present the 
results of unadjusted models, where the only cont rol variable is the baseline response.  
80.  Durkin et al. 2015 find that the TPP measures  were associated with increased rates of quit 
attempts among adult cigarette smokers. In particular, the authors report that compared to the 
referent group of smokers who c ompleted their follow -up survey in the pre -TPP period, smokers 
who were followed -up in the early transition period showed significantly greater increases in quit 
attempt in the past month. Similarly, smokers who were followed -up in the first year of TPP 
showed greater increases  in quit attempt in the past month.133 
81.  Ajzen et al., in their expert report submitted by  the Dominican  Republic  and Indonesia, claim 
that Durkin et al.'s conclusions are unwarranted and contradicted by the data. According to Ajzen 
et al., Durkin et al. 2015 overstate their findings because they failed to report the results showing 
that the TPP measures  did not bring about any increase in respondents ' attempts to ever quit, to 
quit more than once, and to quit for more than one week betwee n baseline and follow -up.134 More 
generally, Ajzen et al. criticize Durkin et al. 2015 for having adopted a very different and 
unorthodox methodology than in Wakefield et al. 2015, despite being the same six authors using 
the same dataset. In their view, Durkin et al.'s analytical approach suffers from three serious 
methodological shortcomings, namely controlling for a non -existent daily trend, not investigating 
wear-out effec ts and not correcting for multiple significances tests.135 Ajzen et al. further argue 
that, contrary to Durkin et al.'s claim, relying on changes in the responses of participants from 
month to month does not minimize the influence of sampling variation and i ncrease the power of 
the statistical tests.136 
82.  Ajzen et al. estimate a logistic model for dichotomized outcome variables, a linear model for 
continuous outcome variables and an ordered logit model for categorical outcome variables, which 
include the same cov ariates considered by Durkin et al. 2015 except for the dates of the follow -up 
interviews. They find that the TPP measures  have had virtually no significant effect on quit 
attempts among adult cigarette smokers. In particular, they find no statistically si gnificant change 
in the proportion of adult smokers who were followed -up in the first year of TPP that attempted to 
                                                
129 See Appendix  A, para. 72 above.  
130 See Durkin et al. 2015, (Exhibit s AUS-215 (revised) , DOM-305); Young et al. 2014, (Exhibits 
AUS-214, JE -24(67), DOM -285).  
131 See section 1.6.6 in the m ain body of these Reports  for a description of Ukraine's participation in 
these proceedings.   
132 See Durkin et al. 2015, (Exhibit s AUS-215 (revised) , DOM-305).  
133 See Durkin et al. 2015, (Exhibit s AUS-215 (revised) , DOM-305).  
134 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  174-180. 
135 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  188-198. 
136 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  184-185. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  ever quit, attempted more than once to quit, and attempted to quit for more than one week, which 
Durkin et al. 2015 failed to report. The on ly exception is a positive and statistically significant but 
short-lived effect of the TPP measures  on calls to Quitline to help with the last quit attempt, which 
was also not published in Durkin et al. 2015. Ajzen et al. further find that for the quit -related 
variables considered in Durkin et al. 2015, the TPP measures  have statistically increased the 
proportion of adult smokers who attempted to quit in past month in the linear and ordered logistic 
regressions, but in the logistic regression the TPP measur es have reduced their attempts to quit in 
past month.137 
83.  Professor  Klick submits that the results of the unadjusted models, which show that none of 
the variables related to quit attempts are statistically distinguishable from the pre -TPP period, 
must be give n appropriate weight and considered as at least equally valid compared with the 
results of the adjusted models for various reasons.138  
84.  As mentioned in the review of quitting -related cognitions and pack concealment, 
Professor  Chaloupka, Australia's expert, submits that Ajzen et al.'s analysis suffers from several 
limitations that are partly related to the structure of the NTPPTS data, which do not include 
non-smokers who might have taken up tobacco use in the absence of the TPP measures  and are 
cross-sectiona l.139 In that context, Professor  Chaloupka argues that Ajzen et al. do not recognize 
that relatively large sample sizes are required to detect the increasingly smaller effects of more 
distal outcomes, because the sample includes all current tobacco users and recent quitters, and 
not just the users influenced by the TPP measures  in terms of more proximal outcomes. 
Professor  Chaloupka is of the view that it is not surprising that the findings on the impact of the 
TPP measures  on quitting -related behaviour variables are relatively weak when one considers the 
sample of smokers , who are least likely to have been influenced by the TPP measures .140  
85.  Ajzen et al. disagree with Professor  Chaloupka and claim that the declining impact of the 
TPP measures  across the chain of effect is not due to the NTPPTS data's limitation but to the 
theoretically expected decline in the impact of the TPP measures .141 They further contend that the 
findings based on the NTPPTS, whose cross -sectional nature is widely used and accepted, are 
corroborated by those obtained using the longitudinal ITC survey data .142 Ajzen et al. are also of 
the view that the NTPPTS dataset has enough statistical power to detect proximal and distal 
outcomes.143 Ajzen et al. claim that given the TPP measures  have had no impact on quitting 
behaviours in the short term, the NTPPTS data d o not underestimate changes in quit attempts.144 
3.1.2   International Tobacco Control Policy Evaluation Project  
86.  In their review of Yong et al. 2015, who use the ITC data to analyse whether the 
TPP measures  are associated with increased desirable reactions towards t he health warning labels, 
Ajzen et al., in their expert report submitted by  the Dominican  Republic  and Indonesia, criticise the 
authors for not reporting the results of actual smoking behaviour. They reconsider the ITC data 
and estimate a GEE model of the decision to attempt to quit in the last 12 months controlling for 
the survey mode (phone vs. web) and wave of recruitment, as well as the respondents ' ages, sex, 
income, education, cigarettes per day consumed and past year quit attempts.145  
                                                
137 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  165-173, Appendix  A, pp. 90-92. 
138 See para. 14 above for a full summary of Professor  Klick's argument and Klick Supplemental Rebuttal 
Report , (Exhibit HND -122), paras.  91-100.  
139 See para. 15 above for a full summary of Professor  Chaloupka's arguments; and Chaloupka Rebuttal 
Report , (Exhibit AUS -582), paras.  2-5 and  10.  
140 See Chaloupka Rebuttal Report , (Exhibit AUS -582), paras.  6-7 and 9; and Chaloupka Third Rebuttal 
Report, (Exhibit AUS -604), paras. 2 -7. 
141 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  39-45. 
142 See Ajzen et al. Data Rebuttal Rep ort, (Exhibit DOM/IDN -6), paras.  46-49, Appendix  I. 
143 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  50-54, Appendix  II. 
144 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  55-62, Appendix  III. 
145 See Ajzen et al. Second Data Report , (Exhibit DOM/IDN -4), paras.  30-37 and 53 -58. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  87.  Ajzen et al. find no statistically significant change in the proportion of adult smokers that 
attempted to quit in the last 12 months. They note that this result was not reported in Yong et al. 
2015.146  
88.  Professor  Chaloupka is of the view that Ajzen et al. do not recognize that the impact of the 
TPP measures  should be smaller for more distal outcomes, when one looks at the impact in the 
overall sample of smokers and recent quitters, because a smoker, whose likelihood of noticing 
health warnings did not increase following the introduction of the TPP measures , would not be 
expected to show any change in his/her tobacco use behaviour.147 
89.  Ajzen et al. argue that Professor  Chaloupka does not contest the accuracy of their analytical 
approach and results, and does not question their serious criticisms of Yong et al. 2015.148 They 
state that Professor  Chaloupka 's sole criticism regarding the ITC analysis seeks to denigrate the 
quality of the ITC dataset itself, claiming that it provides a "biased" sample to measure the impact 
on quit intentions and quit interests. Accordin g to Ajzen et al., Professor  Chaloupka's argument 
assumes that the TPP measures  led smokers to quit shortly after their introduction, and that these 
"recent quitters" were subsequently excluded from responding to questions on quit intentions and 
quit inter ests in the ITC survey. However, they state that the question on "quit attempt in the last 
12 months" was asked of smokers and recent quitters, and, moreover, the data show that no 
additional quit attempts were made post -implementation.149 
3.1.3   Quitline calls 
90.  The Quitline calls dataset reports the weekly number of calls to the quit smoking hotline 
Quitline in New South Wales and the Australian Capital Territory between 1 March  2005 and 7 
April 2013.150 Young et al. 2014 use the Quitline calls data to investigate the impact of the 
introduction of the TPP measures  on Quitline calls by comparing this number to the nationwide 
introduction of GHWs on cigarette packaging in 2006. The authors estimate an autoregressive 
integrated moving average (ARIMA) model controlling for seasonal variation, anti -smoking 
advertising activity, number of smokers in the population and cigarette costliness.151  
91.  Young et al. 2014 find a sustained increase in calls to the Quitline, which occurred four  weeks 
after the introduction of the TPP measures  and lasted for 43 weeks. The authors further report that 
the positive impact of the TPP measures  on calls to the Quitline has continued for a longer period 
than for the 2006 GHWs.  
92.  Ajzen et al. re-analyse the Quitline Calls data by applying a differen t methodology from the 
one used by Young et al. 2014. They present the results of a graphical analysis as well as an 
"event study" analysis comparing the "actual" volume of calls to  the Quitline with the "forecast" 
volume of calls in the pre -implementation  period obtained by estimating a model controlling for 
seasonal variation, anti -smoking advertising, number of smokers and cigarette costliness.  
93.  Ajzen et al. find that, as reported in  Figure B.1 , there was a statistically significant increase 
in the number of calls to the Quitline after the introduction of the TPP measures , which occurred 
approximately three weeks before the sale of plain packs with enlarged GHWs became mandatory. 
However, they report that the increase in the number of calls was only significant in the first 13 
week period following the introduction of the TPP measures . In the second 13 week period, the 
level of calls  dropped quickly to that of the calls level prevailing in the pre -implementation period. 
Ajzen et al. argue that Young et al. 2014 came to qualitatively similar conclusions using an 
alternative empirical strategy and controlling for the same confounding fa ctors. They posit that, 
based on Young et al.'s findings, by the week of mandatory implementation (1  December  2012), 
the level of calls had dropped by more than 36%; by the end of 2012, the level of calls had 
                                                
146 See Ajzen et al. Second Data Report , (Exhibit DOM/IDN -4), paras.  24 and 28.  
147 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 4. 
148 See Dominican  Republic's  comments on Australia's response to Panel question No. 196, 
paras.  409-414; and Ajzen et al. Second Data Rebuttal Report , (Exhibit  DOM/IDN -8), paras.  13-16. 
149 See Ajzen et al. Second Data Rebuttal Report , (Exhibit  DOM/IDN -8), paras.  15-16. 
150 See Dominican  Republic's  second written submission, paras.  434-442. 
151 See Young et al. 2014, (Exhibits AUS -214, JE -24(67), DOM -285).  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  dropped 65% compared with the peak week; and by  the end of July 2013, there was no longer 
one extra call per week left compared to the pre -implementation period.152 
Figure B. 1: Event Study of Calls to the Quitline153 
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source:  Ajzen et al. Data Report, (Exhibit  DOM/IDN -2), p. 62. 
 
94.  Professor  Chaloupka argues that Ajzen et al.'s conclusion that calls to the Quitline rose 
sharply following the implementation of the TPP measures , and then eventuall y returned to 
pre-implementation levels, does not mean that the effect of the TPP measures  has "worn out". 
Referring to two recent econometric analyses that report strong statistically significant effects of 
tobacco tax increases in driving increased calls  volume in the United States, Professor  Chaloupka 
submits  that the decline in call volume in the months following a tax increase does not imply that 
the effects of tax and price increases on tobacco use "wear out" over time. According to 
Professor  Chaloupka, the extensive economic research that has looked at the short - and long ‐run 
effects of tax and prices on tobacco use concludes that estimates for the long ‐run impact of tax 
and price increases exceed estimates for the short ‐run impact, implying t hat the effects grow over 
time. Professor  Chaloupka is of the view that rather than "wearing out" over time, the effects of 
the TPP measures  are likely to grow over time as new cohorts of young people are less likely to 
take up tobacco use in the absence o f branded packaging.154 
95.  Ajzen et al. counter that Professor  Chaloupka draws a faulty analogy with the effect of a tax 
increase on smoking. Ajzen et al. submit that for a change in smoking behaviour to persist after 
Quitline calls have receded to prior levels , the intervention must reduce smoking behaviour in the 
first place. In the case of the TPP measures , Ajzen et al. contend that given that the TPP measures  
                                                
152 See Ajzen et al. Data Report , (Exhibit DOM/IDN -2), paras.  237-245. 
153 We note that Figure 8 in Ajzen et al. Data Report , (Exhibit DOM/IDN -2, p. 62) includes the vertical 
line representing the TPP measures is set to 1 October  2012.  
154 See Australia's response to Panel question No. 196, paras.  238 and 245; Australia's comments on 
the complainants' responses  to Panel question No. 197; and Chaloupka Re buttal Report , (Exhibit AUS -582), 
para. 15. 
250350450550650750850
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  have had no impact on consumption, quitting, relapse, or prevalence, there is no change in 
behaviour  that could persist over time, after the increase in calls to the Quitline has vanished.155 
3.1.4   Commissioned Roy Morgan Research Survey (Australia and New Zealand ) 
96.  Professor  Klick uses the Roy Morgan Research data to estimate a difference -in-difference logit 
model of quit -related behaviours in Australia and New Zealand , controlling for plain packaging, an 
Australian baseline, a common baseline and a post plain packaging implementation time -period.  
97.  Professor  Klick reports no statistically significant impact of th e TPP measures  in Australia 
relative to New Zealand  on the likelihood that the respondents recently attempted to quit 
smoking.156  
98.  According to Dr  Chipty , Professor  Klick's analysis of the Roy Morgan Research data is invalid 
because the Roy Morgan survey does not include a pre -period and does not make it possible to 
distinguish which respondents noticed plain packaging. Dr  Chipty further  submits  that 
New Zealand  is an invalid counterfactual for the purposes of studying the effects of the 
TPP measures , beca use of New Zealand 's excise tax increase implemented one month after the 
introduction of the TPP measures .157  
3.2  Analysis by the Panel  
99.  We note that only three peer -reviewed studies analyse empirically the impact of the 
TPP measures  and enlarged GHWs on quit a ttempts among adult smokers. In addition, the expert 
report  prepared by Professor  Klick, submitted by Ukraine,  investigates the impact on quit 
attempts.158 We note that none of the peer -reviewed papers that focus on adolescents or cigar and 
cigarillo smokers  provide post -implementation evidence on quit attempts.  
100.  A careful review of Durkin et al. 2015, Yong et al. 2015 and Young et al. 2014 studies and 
the econometric evidence submitted by the Dominican  Republic  and Indonesia suggests that 
although the TPP measures  have increased calls to the Quitline, empirical evidence of the impact 
on quit attempts is very limited and mixed.159 
101.  We note that , based on the NTPPTS data , Durkin et al. 2015 report evidence that the 
TPP measures  have had a positive and statistically significant impact on quit attempts among adult 
smokers in the first year of the TPP.160 Ajzen et al., applying an alternative estimation 
methodology and correcting for multiple testing bias, reverse the results reporte d in Durkin et al. 
2015 and find that the TPP measures  have had no impact on attempting to ever quit, attempting 
to quit more than once and attempting to quit for more than a week.161 We note, however, that 
very few explanatory variables, and sometimes only two variables, are statistically significant at 
5% and 10% in some of the model specifications for the variables quitting more than once and 
quitting for more than a week. We further note that Ajzen et al.'s own results of the linear and 
ordered logistic r egressions confirm Durkin et al.'s finding of a positive and statistically significant 
impact on quit attempts. Ajzen et al. qualify this impact as small without evidence of any wear -out 
effect. Conversely, Ajzen et al.'s results of the linear regression s uggest that the TPP measures  
have reduced quit attempts. We note that Ajzen et al. did not provide any rationale that would 
explain why the TPP measures  would lead to reduced quit attempts.162 Using the ITC dataset, 
                                                
155 See Dominican  Republic's  response to Panel question No. 126, para. 293; Dominican  Republic's  
second written submission, paras.  411, 434 -442 and 447; Dominican  Republic's  comments on Australia's 
response to Pane l question No. 196, paras.  424-425; and Ajzen et al. Data Rebuttal Report, (Exhibit 
DOM/IDN -6), paras.  73-74. 
156 See Klick Report, (Exhibit UKR -5), pp. 18 and 37 -44. 
157 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  54-71. 
158 See section 1.6.6 in the main body of these Reports for a description of Ukraine's participation in 
these proceedings.   
159 See Ajzen et al. Second Data Report , (Exhibit DOM/IDN -4), paras.  24 and 28.  
160 See Durkin et al. 2015, (Exhibit s AUS-215 (revised) , DOM-305).  
161 See Ajzen  et al. Data Report, (Exhibit DOM/IDN -2), paras.  165-173, Appendix  A, pp. 90-92. 
162 As explained in paras.  38 and 73  we are not persuaded by Professor  Klick's claim that unadjusted 
models, which do not control for individual characteristics and tobacco cont rol policies, should be considered at 
least equally valid compared with adjusted models.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  Ajzen et al. also report a non -statistical ly significant impact of the TPP measures  on quit attempts. 
A review of this result shows, however, that very few explanatory variables in that specification 
are statistically significant at 5 % and 10%.163 As noted previously , Australia did not challenge 
Ajzen et al.'s alternative estimation methodology and results based on the NTPPTS and ITC 
data.164 Australia generally submits, however, that the structure of both NTPPTS and ITC data are 
likely to be less suited to detecting changes in more distal variables, s uch as quitting -related 
behaviours.165  
102.  As explained previously in our review of Professor  Klick's analysis of GHW effectiveness and 
smoking incidence based on the commissioned Roy Morgan Research data, it is unclear how robust 
Professor  Klick's results are given the issues regarding the validity of the pre -period of the 
commissioned data and the use of New Zealand  as a counterfactual.166  
103.  We note that , unlike the impact on quit attempts, the empirical evidence on the impact of 
the TPP measures  on calls to the Quitline is unambiguous. Both Young  et al. 2014 and Ajzen et al. 
find that there was a statistically significant increase in calls to the Quitline after the introduction 
of the TPP measures .167 The only main difference between the results reported in Young et al. 
2014 and Ajzen et al. is that in Young et al. 2014 the estimated TPP impact on calls to the Quitline 
lasted 43 weeks and was considered by "sustained" by the authors, while in Ajzen et al. the 
estimated TPP impact was found to last 13 weeks and quali fied as "short -lived". We note that none 
of the explanatory variables in Ajzen et al.'s ARIMA model specification are statistically significant 
at 5% or 10%, except the New Year variable and the first -order autoregressive term.168 We further 
note that in the  pre-implementation period most of the predicted Quitline calls obtained from the 
ARIMA model are not close to the actual level of Quitline calls and tend to lag behind the observed 
level of calls. This could explain why Ajzen et al. find that the increase  in Quitline calls occurred 
three weeks before the mandatory implementation of the TPP measures . In any event , we are not 
persuaded  that a decline in the volume of Quitline calls following an increase in calls immediately 
after the introduction of the TPP measures  would necessarily imply that the impact of the 
TPP measures  on tobacco use would wear out , since such Quitline calls reflect effects of the 
TPP measures  on existing  smokers, and would not inform  their effect on those would -be smokers 
who abstain f rom tobacco use as a result of the TPP measures .  
4  EVIDENCE RELATING TO  THE PREDICTIVE RELAT IONSHIPS BETWEEN PRO XIMAL 
OUTCOMES AND DISTAL OUTCOMES SINCE THE E NTRY INTO FORCE OF T HE 
TPP MEASURES  (NATIONAL TOBACCO PL AIN PACKAGING TRACKI NG SURVEY)  
4.1  Datasets and  related studies  
104.  Brennan et al. 2015 use the NTPPTS data to examine the predictive relationships between 
proximal outcomes (i.e.  tobacco appeal, GHW effectiveness and pack misleading) and distal 
                                                
163 We note that in their review of Scollo et al. 2015b (Exhibit CUB -80), Ajzen et  al. also present the 
results of several logistic, linear, and ordered logit models for  various measures related to quitting and relapse. 
They find that there was no statistically significant change in the proportion of adult smokers that quitted for 
more than one month or successfully quitted between baseline and follow -up. Similarly, they find that there 
was no statistically significant change in the proportion of adult ex -smokers who relapsed, still abstained from 
smoking at follow -up or stayed quit for more than one week at follow -up. We note that in several of these 
results, only a few e xplanatory variables in the model specification are statistically significant. In some cases, 
such as the linear and ordered logistic models for the relapse variable, none of the explanatory variables are 
statistically significant, which suggests that the model might be misspecified given the low coefficient of 
determination. The results of the logistic model also suggest that the TPP measures have had a negative and 
statistically significant change at 10% in the proportion of adult smokers that quit for mo re than one month, 
did not relapse and still remained quit. See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  221-224, 
Appendix  A pp. 95-97 and backup material.  
164 A comparison of the results with and without the trend variable shows that the coeffi cient of the 
constant variable is very large when the trend variable is included in the model specification. The coefficient 
value of the other variables is usually marginally affected by removing the trend variable.  
165 See Australia's response to Panel qu estion No. 196, para. 237; and Australia's comments on the 
complainants' responses  to Panel question No. 197, paras.  371-375. 
166 See Appendix  A, para. 72 above.  
167 See Young et al. 2014, (Exhibit AUS -214, JE-24(67), DOM -285); and Ajzen et al. Data Report, 
(Exhibit DOM/IDN -2), paras.  237-245. 
168 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), backup material.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  outcomes (i.e. quitting -related thinking and behaviours).169 The authors present the results of a 
logistic regression analysis testing whether baseline measures of cigarette appeal, GHW 
effectiveness, perceived harm and concern/enjoyment predicted each of seven follow -up measures 
of quitting -related cognitions and behaviours, adjusting for baseline levels of the outcome and 
controlling for the date of the follow -up survey, number of days between the baseline and 
follow -up survey, anti -smoking television advertising, change in cigarette costliness, sex, age, 
educatio n, socio -economic status and addiction level.  
105.  Brennan et al. 2015 find that some of the appeal -related variables, namely pack dislike and 
lower satisfaction, are prospectively associated with thoughts about quitting. Similarly, the authors 
find that severa l indicators of GHW effectiveness, such as noticing GHWs first, believing dangers of 
smoking are not exaggerated, and attributing much more motivation to quit to GHWs, have 
positively and significantly predicted the likelihood that smokers reported thinkin g daily about 
quitting, intending to quit and setting a firm date to quite. Similarly, they report a statistically 
significant association between concealing packs and daily thought about quitting as well as 
between feeling more smoking -related concern tha n enjoyment and daily thoughts about quitting 
and intention to quit. However, the authors find no statistically significant association between 
lower pack appeal, lower quality and lower value for money, on the one hand, and quitting -related 
cognition vari ables, on the other hand. They also report no statistically significant association 
between brand perception variables and quitting -related cognition variables.  
106.  Turning to pack concealment and micro -indicators of concern, Brennan et al. 2015 find that 
amon g all the appeal -related variables, only lower satisfaction is statistically associated with 
stubbing out and stopping smoking. The authors further find that several measures of GHWs 
effectiveness, namely noting the GHW first, attributing much more motivat ion to quit to graph 
health warning, concealing packs and requesting different GHWs, positively and significantly have 
predicted the likelihood that smokers at the following -up reported stubbing out. Similarly, they find 
a statistically significant associa tion between not believing dangers of smoking are exaggerated 
and attribution of much more motivation to quit to GHW, on the one hand, and stopping oneself 
from smoking on the other hand. They also report that stubbing out and stopping smoking are 
predicte d by feeling more smoking -related concern than enjoyment. However, the authors find 
that none of the proximal outcomes variables, such as disliking packs, lower pack appeal, lower 
quality, lower value for money, believing brands do not differ in prestige, not believing dangers of 
smoking are exaggerated, and attributing much more motivation to quit to GHWs, have predicted 
pack concealment.  
107.  Finally, Brennan et al. 2015 report that only two measures of GHW effectiveness, namely 
attributing much more motivatio n to quit to GHWs and requesting different GHWs, have positively 
and significantly predicted that smokers reported having attempted to quit. The authors find that 
the other proximal outcomes related to appeal, perceived harm and balance between smoking 
enjoyment and concern have not predicted quit attempts.  
108.  Ajzen et al. argue that Brennan et al.'s conclusion that quitting -related cognitions and 
behaviours are prospectively predicted by the more proximal beliefs and perceptions and that, 
among adults, GHWs a re likely to be particularly influential in driving quitting behaviour is 
unfounded, reflecting a basic misconception of the logic inherent in correlation analysis. They 
consider that Brennan et al.'s analysis is unable to establish that the TPP measures  have changed 
quit intentions/secondary indicators. According to Ajzen et al., if there is no evidence that the 
intervention had an effect on the outcome (quit intentions/secondary indicators), a mediation 
analysis cannot be used to establish that the interv ention did have such an effect. They contend 
that contrary to the requirements for a mediation analysis, Brennan et al. 2015 mostly explored 
correlations between assumed mediators (e.g. appeal -related variables) and outcome measures 
(quit intentions and se condary indicators), for which at least one, and often both of the variables 
involved in the correlation analysis had not been found to have changed in a statistically significant 
way as a result of the TPP measures . For instance, Ajzen et al. argue that not believing that 
dangers of smoking are exaggerated, smoking enjoyment, smoking concern and balance between 
smoking enjoyment and concern are mechanism (mediator) variables for which there are no 
statistically significant changes reported in Wakefield et al. 2015. Similarly, they claim that daily 
thoughts about quitting, intending to quit, setting a firm date to quit and refraining from smoking 
                                                
169 See Brennan et al. 2015, (Exhibit s AUS-224, DOM-304).  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  are quit intention/secondary indicator variables for which there is no statistically significant cha nge 
reported in Durkin et al. 2015.170 
109.  Professor  Chaloupka argues that limiting the analysis of more distal measures to continuing 
smokers effectively forces the estimates to suggest that the effects of the TPP measures  are 
wearing out over time, when the op posite may actually be the case. Professor  Chaloupka submits  
that while there is relatively little evidence of wear out for the most proximal outcomes, such as 
appeal and noticing/avoiding GHWs, most wear out evidence is obtained for the more distal 
outcom es, such as quitting -related measures. According to Professor  Chaloupka rather than 
wearing out over time, the impact of the TPP measures  on overall population attitudes, beliefs, and 
behaviours are likely to grow over time as young people, who might other wise have taken up 
tobacco use, are discouraged from doing so, while younger current users are encouraged to 
quit.171 
110.  Professor  Chaloupka further contends that neither Brennan et al. 2015 nor Ajzen et al. use 
the NTPPTS data to assess directly the impact of the TPP measures  on proximal intermediate 
and/or distal tobacco -related outcomes. Professor  Chaloupka argues that several measures on 
appeal, not included in Brennan et al. 2015 but analysed by Ajzen et al., are questionable, at best, 
measures of appeal. S imilarly, several quit -related measures, not analysed in Brennan et al. 2015, 
are questionable measures of quitting. According to Professor  Chaloupka, Ajzen et al. do not asses 
the relationship between other proximal outcomes and quitting -related outcomes,  or between 
intermediate outcomes, which are found to have stronger associations. Professor  Chaloupka 
argues that Ajzen et al. do not report other quitting -related measures (e.g. having daily thoughts 
about quitting in the past). Professor  Chaloupka furthe r submits  that Ajzen et al. are using a much 
more stringent criterion for defining statistical significan ce than that used by Brennan 
et al. 2015.172  
111.  Ajzen et al. respond that the NTPPTS data provide no empirical basis for the assertion that 
there is a stro ng correlation between the appeal of tobacco production and smoking behaviour. 
Using the NTPPTS data, they replicate Brennan et al.'s analysis for appeal -related variables and 
correct for multiple hypothesis testing. They find that of the 130 potential cor relations between 
appeal variable and downstream variables relating to quit intentions, quit attempts, secondary quit 
indicators and smoking behaviours, 129 showed no significant correlation.173  
112.  Ajzen et al. further contend that Professor  Chaloupka formulates a series of unsubstantiated 
and unfounded criticisms regarding the NTPPTS data and their correlational analysis. In particular, 
they argue that the correlational analysis measures the association among variables but does not 
assess the  impact of the TPP measures  on proximal, or distal outcomes by using the longitudinal 
component of the NTPPTS. They further claim that the NTPPTS technical report underscores the 
importance of the appeal and downstream variables, considered as inappropriat e or questionable 
by Professor  Chaloupka. They submit that Professor  Chaloupka fails to understand that the 
correlation analysis only focuses on the appeal mechanism and not on GHW effectiveness and pack 
ability to deceive in order to address Professor  Fong's and Australia's core argument that the 
appeal of tobacco products is "very highly" correlated with smoking behaviour. According to Ajzen 
et al., Professor  Chaloupka's comment regarding the criterion for defining statistical significance 
shows his failu re to understand the importance of correcting for multiple hypothesis testing. They 
also argue that Professor  Chaloupka's assertion  that the NTPPTS data underestimate changes in 
some measures of intention and secondary indicators by not asking these questi ons to recent 
quitters is unfounded because the TPP measures  did not increase quitting behaviour. They further 
disagree with Professor  Chaloupka's assertion  that some appeal variables do not measure change 
over time, because the NTPPTS data do measure chan ge over time for these variables. According 
to the authors, the NTPPTS data show that although the TPP measures  did increase pack dislike 
there were no changes in quit -related outcomes. Finally, Ajzen et al. argue that 
Professor  Chaloupka's assertion  that the NTPPTS  data do not measure the impact of initiation by 
                                                
170 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  200-213. 
171 See Chaloupka Rebuttal Report, (Exhibit AUS -582), paras. 12 -14. 
172 See Chaloupka Second Rebuttal Report, (Exhibit AUS -590), paras. 16 -23. 
173 See Ajzen Rebuttal Report , (Exhibit DOM/HND/IDN -5), paras.  128-130 and 207-212, p. 44. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  mirror is unwarranted because Australia and CCV have been unwilling to share the results of the 
2013 schools -based survey.174 
4.2  Analysis by the Panel  
113.  We note that Brennan et al. 2015 is the only peer -reviewed study analysing the association 
between proximal outcomes and distal outcomes based on the NTPPTS  data.  
114.  A careful review of Brennan et al. 2015 suggests that there is a positive and statistically 
significant association between several outcomes r elated to GHW effectiveness and quitting 
cognitions and behaviour among adult smokers. The empirical evidence of the association between 
appeal variables and quitting -related thinking and behaviour outcomes is much more mixed and 
limited. Similarly, Brenna n et al. 2015 report no statistically significant association between the 
perceived harm variable and any of the quitting -related thinking and behaviour outcomes.175 
115.  We note that Ajzen et al. did not replicate completely Brennan et al.'s 2015 analysis of the  
predictive relationships between proximal outcomes and quitting -related cognitions and 
behaviours. Ajzen et al. only replicate the analysis for appeal -related variables. They find that 
there was no significant correlation between the appeal of tobacco products and quit intention, 
secondary indicators and actual quitting behaviours, except between lower values and making 
more than one quit attempt. More g enerally, Ajzen et al. submit  that Brennan et al.'s (2015) 
analysis is unable to establish that the TPP measures  have changed quit intentions and secondary 
indicators, because Brennan et al. 2015 mostly explore correlations between assumed mediators 
and ou tcome measures, for which at least one, and often both of the variables involved in the 
correlation analysis have not been found to have changed in a statistically significant way as a 
result of the TPP measures .176 
116.  We note that Ajzen et al.'s results confir m to a large extent the findings of Brennan et al.'s 
findings related to appeal -related variables. Brennan et al. find no statistically significant 
association between most of the appeal variable and quitting -related cognitions and behaviours , 
while noting  that further studies would be needed to explore this relationshi p. However, in many 
estimation results obtained with the resampled data based on the multiple testing procedure, 
Ajzen et al. find that none or only one or two explanatory variables (besides the variable of 
interest) are statistically significant, which could suggest that the resample data are subject to 
multicollinearity.  Multicollinearity arises when two (or more) explanatory variables convey the 
same information . As a result, the coefficien t estimates may become very sensitive to minor 
changes in the model specification or data and their confidence interval may increase.  We further 
note that , as mentioned above,  Ajzen et al. did not replicate the analysis for the variables related 
to GHW eff ectiveness, perceived harm and balance between enjoyment and concern. Brennan 
et al. themselves acknowledge that further mediation analyses and controlled experimental studies 
are required to establish if appeal, GHW effectiveness, perceived harm and enjoy ment/concern 
variables are causally responsible for the observed changes in quitting -related outcomes.177 
5  OVERALL CONCLUSION O N POST -IMPLEMENTATION EVIDE NCE ON 
QUITTING -RELATED OUTCOMES AND  OTHER DISTAL  OUTCOMES  
117.  As discussed above , the parties have referred to several peer -reviewed studies analysing 
empirically the impact of the TPP measures  and enlarged GHWs on quitting -related cognitions, 
pack concealment and quit attempts. T he Dominican  Republic , Indonesia and Honduras also 
provided several expert reports reviewing , and in some cases replicating , the results reported in 
these published papers. In response, Australia discussed the features of some of the survey 
datasets used in these peer -reviewed papers, but did not provide its own econometric analysis, 
unlike in the discussion on smoking prevalence and cigarette consumption.  
118.  At the outset, we note that  the survey data used in the se studies , may, as suggested by 
Australia, be more suited to analysing the impact of the TPP measures  and enlarged GHWs on 
                                                
174 See Ajzen et al. Second Data Rebuttal Report , (Exhibit DOM/IDN -8), paras.  22-59. 
175 See Brennan et  al. 2015, (Exhibits AUS -224, DOM -304).  
176 See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  200-213. 
177 Brennan et  al. 2015, (Exhibits AUS -224, DOM -304).  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- B-26 - 
 
  proxim al outcomes, such as appeal, GHWs and ability of the pack to mislead than more distal 
outcomes, such as quitting intentions and quit attempts. Questions on quit intentions and quit 
interests were not asked to "recent quitters". In addition, none of the sur vey data sets discussed 
above track non -smokers who might have taken up smoking in the absence of the TPP measures  
and enlarged GHWs .  
119.  We also note that the parties disagree on the extent to which the variables related to appeal, 
GHW effectiveness, perceive d harm and enjoyment/concern variables may be considered to be 
predictive of smoking and quitting behaviours . The authors of the peer -reviewed study analysing 
the predictive relationships between proximal outcomes and quitting -related outcomes  
acknowledge that further empirical  analyses and experimental studies are required to establish 
causality.  
120.  With this in mind , and based on the studies and expert reports before us and discussed 
above, the empirical evidence available to us regarding quitting -related ou tcomes and other distal  
outcomes , which is sometimes scarce, suggests that:  
a. The impact of the TPP measures  and enlarged GHWs on adult cigarette smokers' quitting 
intention and quitting -related cognition reactions is limited and mixed.  
b. The TPP measures  and enlarged GHWs have had a statistically significant positive impact 
on avoidant behaviours, such as pack concealment, among adult cigarette smokers , 
while the ir impact on stubbing out and stopping smoking is much more limited and 
mixed.  
c. Although the TPP measures  and enlarged GHWs have statistically significantly increased 
calls to the Quitline, the observed impact of the TPP measures  and enlarged GHWs on 
quit attempts is very limited and mixed.  
d. The empirical evidence of the impact of the TPP measures  and enlarged GHWs on 
adolescents' quitting -related outcomes is limited. This evidence suggests that  the impact 
of the TPP measures  and enlarged GHWs on adolescents' refraining from smoking 
cigarette s and thoughts about quitting  is statistically not significa nt. No empirical 
evidence has been submitted to us on pack concealment among adolescent smokers.  
e. The empirical evidence of the impact of the TPP measures  and enlarged GHWs on cigar 
and cigarillo smokers' quitting -related outcomes is limited. This evidence suggests that 
the share s of premium cigar and cigarillo smokers and of non -premium cigarillo smokers 
reporting having decanted the cigars and cigarillos from their boxes to a humidor or an 
unbranded tin or concealed their pack have increased  and there has been an increase in 
the share of non -premium cigarillo smokers contemplating quitting.  
121.  No post -implementation empirical evidence has been presented to us on the impact of the 
TPP measures  on quit attempts among adolescent smokers and cigar a nd cigarillo smokers.  
 WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-1 - 
 
   
APPENDIX  C:  
 
EVIDENCE ON SMOKING PREVALENCE  
FOLLOWING THE ENTRY INTO FORCE OF THE TPP MEASURES  
 
1.  A number of expert reports  submitted by the parties  are dedicated in part or in whole to an 
assessment of the contribution of the TPP measures  to reducing smo king prevalence .1 These 
expert reports rely on  different databases, statistical analysis and econometric methods to 
determine whether TPP and enlarged GHW s have contributed to a reduction in smoking 
prevalence.  
2.  One of the only points of agreement among the parties in the discussion on the impact of the 
TPP measures  on smoking prevalence is that the empirical econometric studies they submitted do 
not assess separately the impact of TPP and the impact of the enlarg ed GHW s, because both 
measures were implemented at the same time.2 Unless specified otherwise, in this Appendix, 
references to the impact of the TPP measures  therefore refer to the impact of the TPP measure s 
and the enlarged GHWs implemented simultaneously . 
3.  The complainants argue that the overall empirical statistical and econometric studies carried 
out by their experts conclude that the TPP measures  have failed to reduce cigarette and cigar 
smoking prevalence.3 The complainants also initially suggested tha t the TPP measures  "backfired" 
by increasing youth smoking prevalence4, although they did not pursue this argument in later 
stages of the proceedings . 
4.  Notwithstanding its position that, in the early stages of introduction of the measures, the most 
appropri ate way to discern their effects is to rely on experiments and surveys which co nsider 
drivers of choice, attitudes, and ultimately, the elicitation of behavioural intentions5, Australia 
engaged in estimating econometrically the impact of the TPP measures  on smoking prevalence , in 
response to the submissions  of the Dominican  Republic , Honduras and Indonesia . Australia argues 
that using the most appropriate dataset available and correcting for flaws in the econometric 
models put forward by the experts  of the Dominican  Republic , Honduras and Indonesia , the results 
show that the TPP measures  have already contributed to reducing cigarette and cigar smoking 
prevalence.6 
                                                
1 See Chipty Report, (Exhibit AUS -17); Chipty Supplementary Report, (Exhibit AUS -511); Chipty 
Rebuttal Report , (Exhibit AUS -535) (SCI) ; Chipty Surrebuttal Report, (Exhibit AUS -586); Chipty Second 
Rebuttal Report, (Exhibit AUS -591); Chipty Third Rebuttal Report, (Exhibit AUS -605); Chaloupka Rebuttal 
Report, (Exhibit AUS -582); Chaloupka Third Rebuttal Report , (Exhibit AUS -604); List Report, (Exhibit 
DOM/IDN -1); List Rebuttal Report , (Exhibit DOM/IDN -3); List Second Supplemental Report, (Exhibit 
DOM/IDN -5); List Third Supplemental Report, (Exhibit DOM/IDN -7); List Summary Report, (Exhibit 
DOM/IDN -9); IPE Report , (Exhibit DOM -100); IPE Updated Report , (Exhibit DOM -303); IPE Second Updated 
Report , (Exhibit DOM -361); IPE Third Updated Report , (Exhibit DOM -375); IPE Summary Report , (Exhibit 
DOM-379); Klick Report , (Exhibit UKR -5); Klick Rebuttal Report , (Exhibit HND -118); Klick Supplemental 
Rebuttal Report , (Exhibit HND -122); Klick Second Supplemental Rebuttal Repor t, (Exhibit HND -165); Klick 
Third Supplemental R ebuttal Report, (Exhibit HND -166); and Klick Fourth Supplemental Rebuttal Report , 
(Exhibit HND -169).  
2 See Australia's first written submission, para. 518; Honduras's response to Panel question No. 8; 
Dominican  Republic's  response to Panel question No. 8, para. 61; and Indonesia's response to Panel question 
No. 8, para. 8. 
3 See Honduras's second written submission, paras.  56-60; Dominican  Republic 's comments on 
responses to Panel questions following th e second substantive meeting, paras.  681-682; Cuba's second written 
submission, paras.  276-277; and Indonesia's second written submission, para. 192. 
4 See Honduras's first written submission, para. 395; Dominican  Republic 's first written submission, 
para. 523; Cuba's first written submission, para. 163; and Indonesia's first written submission, para. 412. 
5 See Australia's first written submission, paras.  147 and 670. See also the discussion reflected at 
section 7.2.5.3.3. in the main body of these Reports . 
6 See Australia's comment s on complainants' response to Panel question No. 197, para. 214. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-2 - 
 
  5.  Overall, we note that the approaches proposed by the parties to analyse the trends in smoking 
prevalence evolved over the course of the proceedings . They address the following three main 
aspects, that we will review in turn : 
 First, the parties have submitted economic figures and descriptive statistics analyses 
aimed at determining whether smoking prevalence has decreased following the 
implementation of the TPP measures ; 
 Second, Australia, the Dominican  Republic , Honduras and I ndonesia have submitted 
statistical analyses to determine whether there was a break in the trend in smoking 
prevalence following the implementation of the TPP measures , and in particular, whether 
the reduction of smoking prevalence has accelerated followin g the implementation of the 
TPP measures ; 
 Finally, Australia, the Dominican  Republic , Honduras and Indonesia have submitted 
econometric analysis to determine whether the TPP measures  have contributed to a 
reduction in smoking prevalence by isolating and qu antifying the different factors that 
can explain the evolution of smoking prevalence.  
1  WHETHER SMOKING PREV ALENCE DECREASED FOL LOWING THE IMPLEMENT ATION OF 
THE TPP MEASURES  
6.  The parties have submitted different data sources tracking smoking prevalence in Aus tralia. 
Each dataset is presented separately. We consider each in turn before turning to an overall 
assessment.  
1.1  Datasets and related analyses  
1.1.1   Roy Morgan Single Source  
7.  The Roy Morgan Single Source (RMSS), submitted first by the Dominican  Republic , is a larg e 
survey dataset based on more than 50,000 interviews conducted each year with randomly selected 
individuals across Australia. The dataset is based on a representative survey of the Australian 
population and solicits responses from respondents regarding so cio-economic and demographic 
characteristics, as well as consumer behaviour such as smoking status and brand choices. The 
same individuals are however not surveyed over time. Monthly data are available for the period 
January  2001 through September  2015.  
8.  As shown in  Figure C.1 , the RMSS data reveal a downward trend in smoking prevalence that 
has accelerated since July 2006. In 2001, the smoking prevalence was around 24%. In 2006, 
smoking prevalence was slightly low er at 23%. In 2015, the level of smoking prevalence was 18%.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-3 - 
 
  Figure C. 1: Smoking Prevalence Based on RMSS Data  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  RMSS data ( January  2001 – September  2015) . 
 
1.1.2   Organisation for Economic Co -operation and Development Dataset on Non -Medical 
Determinants  
9.  The Organisation for Economic Co -operation and Development (OECD) Dataset on Non -Medical 
Determinants is a panel dataset on various smoking behaviours, including yearly smoking 
prevalence rates covering all 34 OECD countries from 1960 through 2014 (2013 in the case of 
Australia).  
10.  The IPE Report submitted by the Dominican  Republic  contend s that there is a secular 
downward trend in smoking preva lence in Australia and other high income countries, which are 
presumably, at least in part due to a combination of demographic shifts (change in the 
composition of population, education, etc.) as well as other factors entirely unrelated to tobacco 
control interventions (such as a general trend towards a healthier lifestyle and away from 
smoking).7 
                                                
7 See IPE Updated Report , (Exhibit DOM -303), paras.  43-46; and IPE Third Updated Report , (Exhibit 
DOM-375), paras.  193-201. 
151719212325
Jan-01
Jun-01
Nov-01
Apr-02
Sep-02
Feb-03
Jul-03
Dec-03
May-04
Oct-04
Mar-05
Aug-05
Jan-06
Jun-06
Nov-06
Apr-07
Sep-07
Feb-08
Jul-08
Dec-08
May-09
Oct-09
Mar-10
Aug-10
Jan-11
Jun-11
Nov-11
Apr-12
Sep-12
Feb-13
Jul-13
Dec-13
May-14
Oct-14
Mar-15
Aug-15Share of daily smokers (aged 14+) 
in population (%)
YearTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-4 - 
 
  Figure C. 2: Smoking Prevalence Based on OECD Dataset on Non -Medical Determinants  in 
Australia and Selected OECD Countries  
 
Source :  IPE Updated R eport, (Exhibit DOM -303), p. 24 
 
11.  Professor  Chaloupka, in an expert report submitted by  Australia, disagrees that (1)  tobacco 
use has been falling consistently in all OECD countries, (2)  this decline has been largely linear over 
time and (3)  these downward trends are expected to continue into the future regardless of what 
happens in these co untries. According to Professor  Chaloupka trends in tobacco use differ 
considerably across OECD countries and that assuming a linear downward trend over time is overly 
simplistic and fails to fully capture the role of tobacco control policies (or lack ther eof) in 
accelerating (decelerating) any downward trend in tobacco use.8 He further argues that the 
differences in trends in smoking prevalence between Australia and other OECD countries are more 
pronounced when one looks at countries, such as Germany or It aly, that have not been included in 
the figures shown in the IPE Report , such as in  Figure C.2 .9 According to Australia and as shown 
in Figure C.3 , the assertion that there is a se cular downward trend in smoking across all OECD 
countries is belied by the rising trend in prevalence in Greece, which is largely attributable to the 
weak tobacco control policies the country has implemented (29 th out of 34 European countries in 
the 2013 t obacco control scale).10 
                                                
8 See Chaloupka Rebuttal Report , (Exhibit AUS -582), paras.  37-44; and  Chaloupka Third Rebuttal 
Report , (Exhibit AUS -604), paras.  20-28. 
9 See IPE Updated Report , (Exhibit DOM -303), p. 24. 
10 Chaloupka Rebuttal Report, (Exhibit AUS -582), para. 44. 
101520253035404550Share of daily smokers (aged 15+) 
in population (%)
Year
Australia Canada
Denmark New Zealand
United States All OECD Countries without AustraliaWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-5 - 
 
  Figure C. 3: Smoking Prevalence Based on OECD Dataset on Non -Medical Determinants  in 
Australia and Selected European Countries  
 
Source :  Chaloupka Rebuttal Report, (Exhibit AUS -582), pp. 37-38. 
 
1.1.3   National Drug Strategy Household Survey  
12.  The National Drug Strategy Household Survey (NDSHS) is a nationally representative survey 
run by the Australian Government approximately every two or three years. At the time of these 
proceedings, t he most recent wave of the NDSHS had been  undertaken in 2013, and was the only 
wave of the NDSHS to have been undertaken since  the introduction of the TPP measures .  
13.  The Dominican  Republic  note that the last eight NDSHS reports indicate, as shown in 
Figure  C.4, that smoking prevalence (both overall smoking prevalence and daily smoking) has 
decreased along a roughly linear trend since 1993. The most recent NDSHS survey reveals that 
smoking rates in 2013, the first year after the implementation of TPP, have evolved according to 
this trend without "break", "shift" or "kink" in the trend line that could be attributable to the 
TPP measures .11  
                                                
11 Dominican  Republic's  first written submis sion, para. 523. 
1015202530354045Share of daily smokers (aged 15+) 
in population (%)
Year
Australia Greece ItalyWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-6 - 
 
  Figure C. 4: Smoking Prevalence Bas ed on NDSHS Data  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  Dominican  Republic 's first written submission, p. 157. 
Figure C. 5: Youth Smoking Prevalence Based on NDSHS Data  
 
Note:   The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source:   Gibson Report, (Exhibit DOM -92), p. 22. 
05101520253035
1993 1995 1998 2001 2004 2007 2010 2013Share of smokers (aged 14+) 
in population (%)
Year
Daily smoker SmokerTPP
00.511.522.533.54
2010 2013Share of smokers (aged 12 -17 years)
in population (%)
Year
Daily smokers Occassional smokersTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-7 - 
 
  14.  According to the Dominican  Republic , Honduras and Indonesia the most recent NDSHS data 
show an increase in smoking prevale nce in certain segments of the Australian population. For 
instance, as shown in Figure C.5 , prevalence of daily smoking in the 12 –17 year old group has 
increased from 2.5% in 2010 to 3.4% in 2013, marking the first increase in prevalence rates after 
years of decline for this category, from 5.2% in 2004 to 3.2% in 2007 to 2.5% in 2010.12 
15.  According to Australia and its expert Dr Chipty, there were signif icant reductions in daily and 
overall smoking prevalence reported in the most recent wave of the NDSHS data. In particular, 
between 2010 and 2013, rates of daily smoking among people aged 18 years or older dropped 
from 15.9% to 13.3%. In 2013, 12.8% of peo ple in Australia aged 14 or older were daily smokers, 
declining from 15.1% in 2010.13  
16.  Australia, however, notes that given the small sample sizes, particularly for certain 
subgroups, like adolescents or residents of specific Australian states, trend lines can be difficult to 
interpret. Australia argues that, for example, one cannot conclude from these data that daily 
smoking increased in the youth population following TPP. This is because actual youth daily 
smoking prevalence among the underlying population  may, in reality, be flat or decreasing given 
the small sampling error associated with these estimates, as shown in Figure C.6 .14 Australia's 
Post-Implementation Review Tobacco Plain Packaging 2016 further explains that the NDSHS report 
states that this rise in the number of 12 -17 year olds smoking in the 2010 -2013 reporting period is 
not statistically significant and should be interpreted with caution.15 
Figure C. 6: Youth Smoking Prevalence with Confidence Interval Based on NDSHS Data  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  Chipty Report, (Exhibit AUS -17), p. 46. 
                                                
12 Honduras's first written submission, paras.  395-396; Dominican  Republic's  first written submission, 
para. 523; Indonesia's first written submission, para. 412; and Gibson Report, (Exhibit DOM -92), p.22.  
13 See Australia's first written su bmission, para. 36; and Chipty Report, (Exhibit AUS -17), paras.  77-84. 
14 See Chipty Report, (Exhibit AUS -17), paras.  77-84; and Australia's comments on the complainants' 
responses  to Panel question No. 197, para. 387. 
15 See Australia's first written submission, Annexure E , para. 77; and Tobacco Plain Packaging PIR , 
(Exhibit AUS -624), para. 119. 
01234567
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013Share of daily smokers (aged 12 -17 years) 
in population (%)
Year
Prevalence Prevalence 95% Confidence IntervalTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-8 - 
 
  1.1.4   National Health Survey  
17.  The National Health Survey (NHS) is a nationally representative survey, released by the 
Australian Bureau of Statistics  (ABS) . The latest NHS covered the period 2014 -2015 and surveyed 
approximately 19,000 respondents. Previous surveys release s covered the period 1995, 2001, 
2004-2005, 2007 -2008 and 2011 -2012.  
18.  Australia notes that according to the first results of the 2014 -2015 NHS, daily smoking among 
Australians aged 18 and over was 14.5% in 2014 -2015, down from 16.1  % in 2011 -2012, as 
shown in Figure C.7 .16 Australia further recognizes that the specific results of the NDSHS and NHS 
are not directly comparable due to differences in methodolo gy, age cohorts, timing and sample 
sizes (including across age cohorts).  
Figure C. 7: Smoking Prevalence Based on NHS Data  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source:   NHS Results, (Exhibit AUS -622), p. 30. 
 
1.1.5   Australia Secondary Students' Alcohol and Drug survey  
19.  The Australian Secondary Students ' Alcohol and Drug (ASSAD) survey is a triennial national 
survey of secondary school students ' use of licit and illicit substances. Th is survey assesses, 
among others, their use of alcohol and tobacco and was conducted collaboratively by Cancer 
Councils across Australia, commencing in 1984.  
20.  According to Australia and in contrast to assertions of the Dominican  Republic , Honduras and 
Indon esia with respect to the youth smoking findings in the NDSHS, more recent data from the 
                                                
16 See Australia's comments on the complainants' responses  to Panel question No. 197, para. 389; NHS 
Results, (Exhibit AUS -622), p. 30; and Tobacco Plain Packag ing PIR , (Exhibit AUS -624), para. 126.  
0510152025303540
1995 2001 2004-05 2007-08 2011-12 2014-15Share of daily smokers (aged 18+) 
in population (%)
Year
Males FemalesTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-9 - 
 
  ASSAD survey shows statistically significant declines in current smoking prevalence between 2011 
and 2014 for students aged 12 to 17 years, as depicted in  Figure C.8.17 
Figure C. 8: Youth Smoking Prevalence Based on ASSAD Data  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  CCV 2014 Survey, (Exhibit AUS -621), pp. 33 and 37.  
 
1.1.6   Commissioned Roy Morgan Research Survey (Australia and New Zealand ) 
21.  Roy Morgan Research data, commissioned by Honduras's expert Professor  Klick, is a survey of 
individuals who were current or former (in the past 12 months) smokers in both Australia and 
New Zealand  undertaken using random digit dialling sampling techniques. The first wave of the 
survey was completed prior to the introduction of the TPP measures  in December  2012 between 
2 November  2012 and 26 November  2012 in Australia and between 8 November  2012 and 
1 December  2012 in New Zealand . Subsequent waves have been carried out at three -month 
intervals: Wave  2 between 28 February  2013 and 19 March  2013; Wave  3 between 30 May 2013 
and 20 June 2013; Wave 4 between 8 August  2013 and 26 August  2013; Wave 5 between 
8 November  2013 and 24 November  2013 and Wave 6 between 7 February  2014 and 
28 February  2014.  
22.  Professor  Klick notes, as shown in Figure C.9 , that the change in Australian respondents 
reporting a daily smoking status from before the TPP measures  (72.0%) to after the TPP measures  
(69.6%) was 2.4% points (averaged across the post -TPP waves), while for New Zealand , the 
decline was 3.6% points (before 70.5% vs. after 66.9%). Similarly, the decline in occasional 
smoking status in Australia was 6.2% and 7.1% point decline observed in New Zealand .18 
                                                
17 See Australia's comments on the complainants' responses  to Panel question No. 197, para. 390; C CV 
2014 Survey, (Exhibit AUS -621), Table 6.1; Tobacco Plain Packaging PIR , (Exhibit AUS -624), para. 126; and  
Dessaix et al. 2016, (Exhibit AUS -623), p. 1. 
18 See Klick Report , (Exhibit UKR -5), pp. 8-10. 
05101520253035404550
1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014Share of students having smoked in past month (%)
Year
12 to 15 years old smoker 16 to 17 years old smokerTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-10 - 
 
  Figure C. 9: Smoking Behaviour Based on Roy Morgan Research Data  
 
Source :  Klick Report, (Exhibit UKR -5), pp. 8-10. 
 
23.  Australia's expert, Dr Chipty, notes that the "smoking incidence", defined by Professor  Klick as 
the share of c urrent smokers and individuals who have been smokers at some point during the 
past 12  months, is different from "smoking prevalence", which is the share of the entire population 
that is smoking.19 Dr Chipty further submits  that daily smoking incidence fell more in Australia 
after the introduction of the TPP measures  (5% between Wave 1 and 6, 5% between Wave 2 and 
6) than in New Zealand  (3% between Wave 1 and 6, 0% between Wave 2 and 6). In addition, a 
higher proportion of New Zealand  respondents cited costs as the primary reason for quitting as 
compared to Australian respondents, while a higher proportion of Australian respondents cited 
health as the primary reason for quitting, as compared to New Zealand  respondents.20 
1.1.7   State -level smoking prevalence datasets  
24.  In their first written submissions, the complainants presented data for four Australian States, 
namely New South Wales  (NSW) , South Australia, Queensland, and Victoria, suggesting that 
smoking prevalence had increased after the implementation of the TPP measures .21 Most of these 
datasets were not discussed by the complainants in later submissions, except Honduras and Cuba 
for some datasets.22 Each state -level dataset is reviewed next.  
1.1.7.1   Cancer Institute New South Wales Tobacco Tracking Survey  
25.  The Cancer Institu te New South Wales Tobacco Tracking Survey (CITTS) is a weekly tracking 
telephone survey of smokers and recent quitters (in the past 12 months) based in N SW. The data 
                                                
19 See Chipty Report, (Exhibit AUS -17), fn 13. 
20 See Chipty Report, (Exhibit AUS -17), paras.  25-31, Appendix  C. 
21 See Honduras's first written submission, para. 396; Dominican  Republic 's first written submission, 
paras.  525-527; Indonesia's first written submission, para. 23; and Cuba's first written submission, paras.  164, 
251. 
22 See Honduras's response to Panel question No. 199, p p. 46-47 (referring to previous analy sis of the 
CITTS and NDSHS data); and Cuba's response to Panel question No. 199, p p. 20-21 (referring to previous 
analysis of the NDSHS, RMSS and CITTS data, among others).  
60657075808590
Australia New Zealand Australia New Zealand
Daily smoking Occasional or daily smokingShare in smokers and recent quitters surveyed (%)
Before the TPP measures After the TPP measuresWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-11 - 
 
  discussed by the Dominican  Republic , Honduras and Indonesia cover the years 2012, 2013 and 
2014.  
26.  The Dominican  Republic , Honduras and Indonesia refer to the Gibson Report, which was 
prepared at the request of British American Tobacco UK and submitted to a UK government 
consultation process on the introduction of the TPP measures . As shown in  Figure C.10 , the 
Gibson Report presents the CITTS data showing that the proportion of smokers surveyed, who 
smoke on a daily basis, actually increase d from 70% in 2012, the year before the implementation 
of the TPP measures , to 77% in 2013 and remained above the 2012 levels in 2014. Similarly, the 
proportion of people smoking over 11 cigarettes a day increased from 62% in 2012 to 64% in 
2014.23 
Figure C .10: New South Wales Consumer Smoking Behaviour Based on CITTS Data  
 
Source :  Gibson Report, (Exhibit DOM -92), p. 20. 
 
27.  Australia considers that the Gibson Report's analysis is fundamentally flawed because the 
figures reported are incorrectly labelled as representing the "proportion of smokers" smoking on a 
daily basis, while they represent the proportion of the entire samp le (including both smokers and 
recent quitters), who are, or in the case of recent quitters were, daily smokers. Accordingly, 
Australia submits  that since the CITTS is a survey of smokers and recent quitters, and not a 
population survey, it is not designed  to measure (and indeed is not capable of measuring) changes 
in smoking prevalence in the entire population.24 
28.  Australia further considers that the RMSS data, collected monthly, is better suited to 
comparing more accurately, including by states, smoking rat es immediately prior to and following 
the introduction of the TPP measures . According to RMSS data, overall smoking prevalence in 
New South Wales has fallen significantly in the 12 months following the introduction of the 
                                                
23 Honduras's first written submission, para. 396; Dominican  Republic's  first writte n submission, 
para. 525; Indonesia's first written submission, para. 23; and Gibson Report, (Exhibit DOM -92), p.  22. 
24 See Australia's first written submission, Annexure E, paras.  60-61; and C INSW Rebuttal  of BATA 
Analysis of CITTS Data , (Exhibit AUS -504).  
50556065707580
2012 2013 2014Share in smokers and recent quitters surveyed (%)
Year
Daily smokers in NSW Daily smokers smoking over 11 cigarettes per day in NSWWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-12 - 
 
  TPP measures .25 Australia's Post -Implementation Review Tobacco Plain Packaging 2016 also 
reports a reduction in daily smoking prevalence in New South Wales based on the NSW survey 
data (data up to 2014) for individuals aged 16 years and over, as shown in Figure C.11, and the 
NDSHS (data up to 2013) for individuals aged 14 years and over.26  
Figure C. 11: Smoking Prevalence in New South Wales Based on C INSW Survey Data  
 
Source :  Tobacco Plain Packaging PIR, (Exhibit AUS -624), p. 42. 
 
1.1.7.2   New South Wales School Students Health Behaviours Survey  
29.  The New South Wales School Students Health Behaviours Survey (SSHBS) asked students 
aged 12 –17 years a range of questions on alcohol, demograp hics, height and weight (including 
perception of body mass), injury, nutrition, physical activity, psychological distress, sedentary 
behaviour, substance use, sun protection (including sunburn experience and solarium use), and 
tobacco.  
30.  Australia submitted  a recent study by Dessaix et al. 2016 based on SSHBS data showing, as 
highlighted in Figure C.12 , the proportion of adolescents reporting current smoking as 6.7% in 
2014, down from 23.5% in 1996.27 
                                                
25 See Australia's first written submission, Annexure E, paras.  82-86. See also Chipty Report, (Exhibit 
AUS-17), paras.  80-81. 
26 See Tobacco Plain Packaging PIR , (Exhibit AUS -624), para. 128. 
27 See Australia's comments on the complainants' responses  to Pan el question No. 197, para. 390; and 
Dessaix et al. 2016, (Exhibit AUS -623), p. 1. 
1012141618
2011 2012 2013 2014Share of daily smokers (aged 16+) 
in population (%)
YearWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-13 - 
 
  Figure C. 12: Smoking Prevalence Among Youth in New South Wales Based on SSHBS 
Data  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  Dessaix et al. 2016, (Exhibit AUS -623), p. 1. 
 
1.1.7.3   South Australian Health Omnibus Survey  
31.  The South Australian Health Omnibus Survey (SAHOS) is a representative, cross -sectional 
survey that has been in operation since 1990. The data discussed by the Dominican  Republic  cover 
the years 2004 to 2013.  
32.  According to the Dominican  Republic , the SAHOS data show, as depicted in Figure C.13 , that 
smoking prevalence of the responding population has increased, rather than decreased, in South 
Australia between 2012, the year prior to the implementation of the TPP measures , and 2013.28 
33.  Australia considers that the RMSS data allow a more accurate comparison of smoking rates 
immediately prior to and following the introduction of the TPP measures . Based on the RMSS data, 
overall smoking prevalence in South Australia reduced significantly in the 12  months following the 
introduction of the TPP measures .29 Australia's Post -Implementation Review Tobacco Plain 
Packaging 2016 also reports a reduction in daily smoking prevalence in South Australia based on 
SAHOS (data up to 2014) for individuals aged 15 years and over, as shown in Figure C.14, and 
the NDSHS (data up to 2013) for individuals aged 14 years and over.30  
                                                
28 See Dominican  Republic's  first written submission, para. 526.  
29 See Australia's first written submission, Annexure E, paras.  82-86; and Chipty Report, (Exhibit 
AUS-17), paras.  80-81. 
30 See Tobacco Plain Packaging PIR , (Exhibit AUS -624), para. 128. 
0510152025303540
1996 1999 2002 2005 2008 2011 2014Share of adolescents who are current smokers (%)
YearTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-14 - 
 
  Figure C. 13: Smoking Prevalence in South Australia Based on SAHOS Data  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  SAHOS data, (Exhibit DOM -93), p. 1. 
Figure C. 14: Smoking Prevalence in South Australia Based on South  Australia Survey  
Data 
 
Source :  Tobacco Plain Packaging PIR, (Exhibit AUS -624), p. 42. 
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Year
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YearWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-15 - 
 
  1.1.7.4   Victorian Smoking and Health Survey  
34.  The Victorian Smoking and Health Surveys (VSHS) are cross -sectional telephone surveys 
undertaken with representative samples of adults aged 18 years and over and residing in the 
general population of the Australian state of Victoria. The surveys were undertaken from 2  
November  to 5 December  2011 (inclusive), from 1 November  to 3 December  2012, and from 7  
November  to 11 December  2013.31 
35.  According to the Dominican  Republic , the VSHS data demonstrate, as depicted in 
Figure  C.15, that smoking prevalence of the responding population has increased, rather than 
decreased, in Victoria between 2012, the year prior to the implementation of the TPP measures , 
and subsequent periods.32 
36.  Australia claims that the VSHS  data does not allow for a proper before/after analysis with 
respect to the introduction of the TPP measures  because the 2012 survey was run from 1  
November  to 3 December  2012 when a majority of smokers were already using plain packaged 
products .33 Australia further argues that, based on the RMSS data, overall smoking prevalence in 
Victoria reduced significantly in the 12  months following the introduction of the TPP measures .34 
Australia's Post -Implementation Review Tobacco Plain Packaging 2016 also reports a reduction in 
daily smoking prevalence in Victoria based on the NDSHS (data up to 2013) for individuals aged 
14 years, as shown in Figure C .16.35  
Figure C. 15: Smoking Prevalence in Victoria Based on VSHS Data  
 
Note:  The VSHS  are conducted annually from  November to December . The vertical dashed line indicates 
the introduction of TPP and enlarged GHWs.  
Source :  Dominican  Republic 's first written submission, p. 159. 
                                                
31 See Scollo et  al. 2014, (Exhibits AUS -507, JE -24(57)).  
32 See Dominican  Republic's  first written submission, para. 526.  
33 See Australia's first written submission, Annexure E , para. 84. 
34 See Australia's first written submission, Annexure E, paras.  82-86; and Chipty Report, (Exhibit 
AUS-17), paras.  80-81. 
35 See Tobacco Plain Packaging PIR , (Exhibit AUS -624), para. 128. 
13.514.014.515.015.516.016.517.0
2011 2012 2013Share of daily smokers (aged 18+) in population (%)
YearTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-16 - 
 
  Figure C. 16: Smoking Prevalence in Victoria Based on NDSHS Data  
 
Note:  The vertical dashed line indicates the introduct ion of TPP and enlarged GHWs.  
Source :  Tobacco Plain Packaging PIR, (Exhibit AUS -624), p. 43. 
 
1.1.7.5   Cancer Council Queensland Survey  
37.  Referring to a news item published in an Australian website, the Dominican  Republic  noted 
that while prevalence levels decreased for some subsets of the population, there had been a sharp 
increase in prevalence among Queenslanders aged between 25 and 34 after the implementation of 
the TPP measures .36 
38.  Australia submits  that according to th e RMSS data, overall smoking prevalence in Queensland 
decreased significantly  in the 12  months following the introduction of the TPP measures .37 More 
recently, Australia's Post -Implementation Review Tobacco Plain Packaging 2016 reports a 
reduction in daily smoking prevalence in Queensland based on Queensland survey (data up to 
2014) for individuals aged 18 years and over and the NDSHS (data up to 2013) for individuals 
aged 14 years and over.38  
1.2  Analysis by the Panel  
39.  We note at the outset the usefulness of relying on  the most recent available (i.e. 2014 and 
early 2015) and comparable data to analyse trends in smoking prevalence. This is particularly 
important because the different datasets before us and presented above do not always cover the 
same period. For i nstance, the RMSS data continuously cover the period 
January  2001-September  2015, while the NDSHS covers the period 1993 -2013 with data available 
every two or three years. We also note the importance of distinguishing between smoking 
prevalence, which meas ures the proportion of smokers in the population, and smoking incidence, 
which measures the proportion of smokers in a population of smokers and recent quitters. Unless 
                                                
36 See Dominican  Republic's  first written submission, para. 527; and ABC News 2014, (Exhibit DOM -96). 
37 See Australia's first written submission, Annexure E, paras.  82-86; and Chipty Report, (Exhibit 
AUS-17), paras.  80-81. 
38 See Tobacco Plain Packaging PIR , (Exhibit AUS -624), para. 128. 
10121416182022
1998 2001 2004 2007 2010 2013Share of daily smokers (aged 14+) in population (%)
YearTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-17 - 
 
  specified otherwise, we focus on smoking prevalence because , unlike smoking incidence , which 
ignores individuals who never smoked, smoking prevalence is based on the entire population (i.e. 
smokers, recent quitters and non -smokers).  
40.  After a careful review of the datasets described above, we observe that smoking prevalence 
fluctuates, even m ore when the unit of measure is disaggregated (monthly vs. yearly or state -level 
vs. country -level observations). We agree with Australia that in the presence of small sample 
sizes, in particular for subgroups such as youth and specific Australian states, it can be particularly 
difficult to interpret trends. That being said, we see, as depicted in Figure C.17 , that despite 
different estimates and fluctuations of smoking prevalence, most of the datasets described above, 
including the RMSS data, OECD Dataset on Non -Medical Determinants, and NHS, sho w continuing 
declines in smoking prevalence at the national level in the period following the introduction of the 
TPP measures .39  
41.  While the most recent available data on smoking prevalence confirm that smoking prevalence 
in Australia continued to decrease following the introduction of the TPP measures , simply 
observing the existence of the trend  does not inform , however, whether this downward trend in 
smoking prevalence has accelerated . This question is reviewed next.  
Figure C. 17: Smoking Prevalence  in Australia  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  RMSS, NHS , NDHS  and OECD data based on Chipty Third Rebuttal Report, (Exhibit AUS -605); 
Tobacco Plain Packaging PIR, (Exhibit  AUS-624); NHS Results , (Exhibit AUS -622); and IPE Updated 
Report, (Exhibit  DOM-303).  
 
 
                                                
39 We note that the smoking p revalence rates reported by the RMSS data are higher than the ones 
reported by the NHS and OECD data. These differences could be due to different methodology, timing and 
sample sizes. See Chipty Third Rebuttal Report, (Exhibit AUS -605); NHS Results, (Exhib it AUS -622); Tobacco 
Plain Packaging PIR , (Exhibit AUS -624); C CV 2014 Survey, (Exhibit AUS -621); and IPE Updated Report , 
(Exhibit DOM -303).  
051015202530
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Annual OECD data (15 aged +) Annual NHS (aged 18+)TPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-18 - 
 
  2  WHETHER THE REDUCTIO N OF SMOKING PREVALE NCE ACCELERATED FOLL OWING 
THE IMPLEMENTATION O F THE TPP MEASURES  (ROY MORGAN SINGLE S OURCE)  
42.  As discussed above, the majority of  the most recent datasets presented to us show continuing 
declines in smoking prevalence in Australia in the period following the introduction of the 
TPP measures . Rather than assessing directly the TPP measures ' impact on smoking prevalence, 
which will be  discussed in detail next, the Dominican  Republic 's experts initially investigated 
whether there was a shift in smoking prevalence in the post -TPP implementation period. In other 
words they assess ed whether the reduction of smoking prevalence accelerated o r slowed down 
following the implementation of the TPP measures . According to the m, if the reduction in smoking 
prevalence follows the same pre -existing downward trend after the introduction of the 
TPP measures , this implies that the TPP measures  have not reduced smoking prevalence.  
2.1  Datasets and related studies  
43.  The Dominican  Republic  first submitted, through IPE, a statistical trend analysis of smoking 
prevalence using the RMSS dataset. The trend analysis consists of (1)  estimating the time trend  of 
smoking prevalence for the pre -TPP implementation period (before December  2012); 
(2) predicting the prevalence rate that would have been obtain in any given month following the 
implementation of the TPP measures  on 1 December  2012, in the absence of th e TPP measures  
using the pre -TPP implementation trend; and (3)  determining whether the difference between the 
observed prevalence and the estimated counterfactual prevalence is different from zero by 
computing confidence intervals.40  
44.  The trend analysis is undertaken by estimating either a quadratic time trend for the 
January  2001-March  2014 period or a linear trend model for the January  2006-March  2014 period. 
In both cases, IPE concludes that there is no statistical difference between observed smoking 
prevalence of the full population and the estimated counterfactual prevalence of the full population 
with the exception of the month of December  2012, implying overall that the post -implementation 
trend did not shift. Similar results are found when the analysi s focuses only on minor population 
and young adult population.41 
                                                
40 See IPE Report , (Exhibit DOM -100), p p. 26-27. 
41 See IPE Report , (Exhibit DOM -100), p p. 28-35, 105 -116, 119 -156, an d 181 -199. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-19 - 
 
  Figure C. 18: Smoking Prevalence and Linear Trend  
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs. The black and red 
lines represent the linear trends.  
Source :  RMSS data, based on IPE Report, (Exhibit DOM -100), p. 28.  
 
45.  Australia's expert, Dr Chipty, rejects the IPE Report 's results on the grounds, inter alia, that 
(1) IPE asserts without support that historical trends will continue into the future in the absence of 
new regulatory measures; (2)  IPE does not attempt to evaluate the extent to which past policies 
contributed to the trend in prevalence; and (3)  IPE's model design makes it less likely, and 
sometimes impossible, to  find a policy effect.42 Australia posits that trends in available data show 
that overall prevalence in Australia is declining over time, including following the TPP measures . 
However, given the small sample sizes for certain subgroups, like adolescents or residents of 
specific Australian states, trends in prevalence can be difficult to interpret.  
46.  Australia also submits another expert report by Professor  Scharfstein, who further argues that 
(1) IPE's assumption that smoking prevalence would have continued t o decline at the same rate 
after December  2012, even if the TPP measures  had never been introduced, is entirely 
unsupported without assumptions or a valid natural experiment; (2)  IPE's date restriction 
(i.e. January  2006) in the linear trend model is deriv ed by simply looking at the data; (3)  IPE's 
statistical trend analysis lacks statistical rigor by not specifying a null hypothesis to evaluate 
whether there is a TPP measures ' effect; and most importantly (4)  IPE's statistical trend analysis 
has low statis tical power and is inadequate to detect important declines in smoking prevalence 
after the introduction of the TPP measures .43  
47.  Professor  Scharfstein submits  that IPE's methodology applied to the excise tax increase 
introduced by Australia in April 2010 doe s not identify a reduction in smoking prevalence after the 
tax increase, although the complainants have argued that excise taxes, in general, are an effective 
                                                
42 See Chipty Report, (Exhibit AUS -17), paras.  40-43. 
43 See Scharfstein Report, (Exhibit AUS -20), paras.  11-12, 35, and 37 -64.  
161718192021222324
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YearTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-20 - 
 
  tool to discourage smoking. Professor  Scharfstein further argues that monthly data from the RMSS 
data cannot reasonably rule out important declines in smoking prevalence in the post -TPP period.44 
48.  The Dominican  Republic 's and Indonesia's expert, Professor  List, disagrees with 
Professor  Scharfstein and argues that according to Borland (2010) the RMSS data have power to 
detect small effects. Professor  List further argues that the justification for Scharfstein 's linear and 
quadratic time trends starting in 2001 and 2006, respectively, are u nsubstantiated. Given the 
nature of the data, especially the seasonality, the start date chosen will affect the estimate of the 
downward trend absent of the TPP measures , and therefore change the null hypothesis used. 
According to Professor  List, Professor  Scharfstein should have simultaneously considered a gradual 
descent and a step down of smoking prevalence. Since the only significant decrease in prevalence 
is December  2012 when the TPP measures  were introduced, it is possible that there is a large 
initial deviation in smoking prevalence followed by a return to the pre -implementation trend (mean 
regression).45 
49.  More generally, Professor  List submits  that abstracting from the general downward trend in 
smoking prevalence, there is no sustained change in the p reviously existing rate of prevalence 
following the vertical dashed line, depicted in a figure similar to Figure C.18 , that denotes the 
start of the TPP measures  in Australia.46 
50.  Australia's expert, Dr Chipty, contests Professor  List's claim that the RMSS data have "power 
to detect small effects". In Dr Chipty's view, using the classification system in Borland (2010), 
IPE's methodology does not have sufficient power to detect "small" (less than 0.5 standard 
deviations of trend), "medium" (between 0.5 and 1), or even most "large" (greater than 1) 
effects.47 
51.  Dr Chipty further contends that, unlike Professor  List's claim of no sustained change in the 
smok ing prevalence trend following the introduction of the TPP measures , allowing the trend line 
to be different before and after the TPP measures  shows, as depicted in Figure C.19 , a break in 
the trend of smoking prevalence after the TPP measures ' implementation, about one percentage 
point lower relative to where it would have been by June 2015.48, 49 
                                                
44 See Scharfstein Report, (Exhibit AUS -20), paras.  12, 51 -55, and 65 -68. 
45 See List Report, (Exhibit DOM/IDN -1), paras.  109-112. 
46 See List Report, (Exhibit DOM/IDN -1), paras.  22-23. 
47 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  4 and 8.  
48 See Australia's comments on the complainants' responses  to Panel question No. 146, para. 15; and 
Chipty Second Re buttal Report, (Exhibit AUS -591), paras.  8-12. A similar graphic for the period 
January  2001-September  2015 is included in the Tobacco Plain Packaging PIR  (Exhibit AUS -624), p. 35. 
49 See Australia's comments on the complainants' responses  to Panel question  No. 146, para. 15. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-21 - 
 
  Figure C. 19: Smoking Prevalence and Pre - and Post -TPP Trends   
 
Note:  The vertical dashed line indicates the introduction of TPP and enlarged GHWs. The dashed line and 
the dotted line denote, respectively, the pre -TPP linear trend and the post -TPP linear trend.  
Source :  RMSS data, based on Chipty Second Rebuttal Report, (Exhibit AUS -591), p. 10.  
 
52.  A similar figure for the period January  2001-September  2015 is included in the 
Post-Implementation Review Tobacco Plain Packaging 2016, with which the Dominican  Republic  
took issue. According to the Dominican  Republic , the figure is misleading, for at least three 
reasons: (1)  it glosses over the clear break in trend that occurred in June 2006, as demonstrated 
by IPE50; (2) October, November, and December  2012 are omitted in the construction of the 
pre-TPP trend, thus artificially making the pre -implementation trend line less steep; (3)  the 
post-implementation trend is inconsistent with previous visualizations adduced by Dr Chipty during 
the WTO proceedings. The Dominican  Republic  submits  that given Dr Chipty 's failure to provide 
back-up material for her analysis, this inconsistency is difficult to explain.51 
2.2  Analysis by the Panel  
53.  We note at the outset that the parties have discussed extensively whether there is a secular 
and long -term downward trend in smoking prevalence in Australia and how to specify the smoking 
prevalence trend (e.g. linear or quadratic) in different contexts related to the contribution of the 
TPP measures . This will be discussed more extensively in the next subs ection, which reviews the 
econometric studies aimed at assessing the impact of the TPP measures  on smoking prevalence 
and smoking incidence.  
54.  We further note that , although more recent data were available over the course of the 
proceedings, IPE did not upda te the results of its statistical trend analysis. Instead, in reply to 
some of the criticism raised by Australia's experts, IPE proposed a "modified trend analysis", which 
acknowledges that the original statistical trend analysis does not control for other  relevant 
                                                
50 See IPE Report , (Exhibit DOM -100), p. 109; and IPE Third Updated Report , (Exhibit DOM -375), 
paras.  32-49. 
51 See Dominican  Republic's  comments on Australia's Post -Implementation Review, paras.  69-70 and 
fn 85. 
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- C-22 - 
 
  variables explaining the evolution of smoking prevalence beyond the trend. The "modified trend 
analysis" is based on a n entirely  different methodology discussed in the next subsection.  
55.  In this context, we consider that the results of the origina l trend analysis provided by the IPE 
Report  are not informative, not only because it fails to control for other relevant variables affecting 
smoking prevalence but also because it is unclear if the results of the trend analysis would have 
changed with the more recent data  made available to us .  
56.  Overall, b ased on the most recent available RMSS data, we note that smoking prevalence in 
Australia has not only continued to decrease following the introduction of the TPP measures , but 
that the downward trend in smoking prevalence has accelerated with a steeper slope of the 
smoking prevalence trend between December  2012 and September  2015 (latest available 
observations submitted by the parties) compared to the pre -TPP periods.  
57.  That being sai d, this change in the smoking prevalence trend following the introduction of the 
TPP measures  does not necessarily imply  that the TPP measures  are having a statistically 
significant impact, to the extent that other factors could explain such evolution, including  other 
tobacco control policies. Indeed , most of the discussion among the parties' experts focused on 
assessing  econometrically the impact of the TPP measures  on smoking prevalence by controlling 
for other factors. This is reviewed next.  
3  WHETHER THE TPP MEASURES  CONTRIBUTED TO THE R EDUCTION IN SMOKING 
PREVALENCE  
58.  The parties disagree on whether the TPP measures  contributed to reducing smoking 
prevalence, i.e. had a negative impact on smoking prevalence. This issue gave rise to detailed 
technical exchan ges between IPE for the Dominican  Republic , Professor  List for the 
Dominican  Republic  and Indonesia, Professor  Klick for Honduras,  and Dr Chipty for Australia, who 
each proposed different econometric methods to estimate the TPP measures ' impact on smoking 
prevalence or smoking incidence. As mentioned above, all parties, however, recognize that the 
empirical econometric evidence on smoking prevalence submitted does not  distinguish between 
the impact of TPP and the impact of enlarged GHW s, because both measur es were implemented at 
the exact same time.52 
59.  Australia  has argued  that the impacts of the TPP measures on prevalence may not fully 
manifest in short term datasets53 and that it is inappropriate to seek to judge the efficacy of the 
TPP measures on the basis of limited short term datasets .54 First, reduc ing smoking prevalence is a 
long-term objective.55 Second, large changes in the root behaviours (i.e. initiation, cessa tion, and 
relapse) stemming from the TPP measures  are likely masked in smoking prevalence because of the 
stock of current smokers whose behaviours may not be as affected by the TPP measures .56 
Notwithstanding this position, Australia re -estimated the impact  of the TPP measures  on smoking 
prevalence , in response to the submissions of the Dominican  Republic , Honduras and Indonesia.  
During the course of the proceedings  and as more prevalence -related  data became available , 
Australia argue d that using the most a ppropriate dataset available and correcting for flaws in the 
econometric models put forward by the experts of the Dominican  Republic , Honduras,  and 
Indonesia, the results show that the TPP measures  have already contributed to the reduction of 
cigarette and  cigar smoking prevalence.57 
                                                
52 See List Report, (Exhibit DOM/IDN -1), para. 113. 
53 See Australia's response to Panel questions No. 126 and 200 and Australia's first written submission, 
para. 670.  
54 See Australia's first written submission, para. 17.  
55 See Australia's first written subm ission, para. 670. Instead Australia claimed that the TPP measures' 
impact should  be investigated through its mechanisms by looking at its impact on non -behavioural outcomes, 
that is, (1) reduction in the appeal of tobacco products, (2) increased effective ness of health warnings, and (3) 
reduction of the ability of the pack to mislead. The evidence on these non -behavioural outcomes is considered 
in Appendix  A. 
56 See Chipty Report, (Exhibit AUS -17), paras.  32-39; Scharfstein Report, (Exhibit AUS -20), para. 68. 
57 See Australia's opening statement at the second hearing of the Panel, paras.  110-111; and comments 
on the complainants' responses  to Panel question No. 197, para. 214. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- C-23 - 
 
  60.  A particular feature of the exchange between the parties on this issue is that , on several 
occasions , the experts of the Dominican  Republic , Honduras and Indonesia proposed in their 
rebuttal reports new models or methodologies , or both , that sometimes contradict some of the 
approaches taken in their earlier reports and invalidate the results reported in th ose reports.58 For 
this reason, the description of the approaches and results below is based primarily on the most 
recent expe rt reports submitted by the parties.59 
3.1  Datasets and related studies  
3.1.1   Roy Morgan Single Source  
61.  The RMSS data were used by the experts  of the Dominican  Republic , Honduras , Indonesia,  
and Australia to assess whether the TPP measures  have contributed to the redu ction in smoking 
prevalence.  
62.  Australia and its expert Professor  Scharfstein consider that the RMSS data covering 15 post -
implementation  months (December 2012 to March 2014) cannot rule out important declines in 
smoking prevalence in the post -policy period.60 Australia's expert Dr Chipty nonetheless considers 
the RMSS data , which is a nationally representative dataset available from January 2001 to 
September 2015,  to be her "preferred data source" for the analysis of smoking prevalence .61 
3.1.1.1   IPE Report s 
63.  The Dominican  Republic  submitted five reports prepared by IPE aimed at estimating 
econometrically the TPP measures ' impact on, among other things, smoking prevalence using the 
RMSS data. Throughout these IPE Report s, different econometric approaches have bee n proposed: 
(1) statistical trend analysis62; (2)  two-stage micro -econometric analysis; (3)  modified trend 
analysis; (4)  autoregressive integrated moving average with explanatory variable (ARIMAX) 
model; and (5)  one-stage micro -econometric analysis.63 The fi rst two approaches were only 
presented in the first IPE Report .64 The second and subsequent IPE Reports only focused on the 
                                                
58 For instance, as discussed in detail below, IPE initially proposed to control fo r excise tax increases by 
including (dummy) indicator variables for each excise tax increase ( IPE Updated Report , (Exhibit DOM -303)), 
but subsequently contended that a more appropriate measure to capture the excise tax increases is the 
weighted average pri ce per cigarette in Australia ( IPE Second Updated Report , (Exhibit DOM -361)). Similarly, 
Professor  List and IPE initially applied the STATA software command ivreg2 in order to calculate standard 
errors that are robust to heteroscedasticity and serial corre lation using the automatic bandwidth selection 
procedure by Newey and West 1994 . IPE Updated Report, (Exhibit DOM -303); and List Report, (Exhibit 
DOM/IDN -1). Subsequently, both Professor  List and IPE applied an alternative way of calculating standard 
errors, that, according to them, is adjusted to reflect more accurately the original suggestion by Newey and 
West (1994) . IPE Second Updated Report , (Exhibit DOM -361); and List Rebuttal Report, (Exhibit DOM/IDN -3). 
59 We note that we have nonetheless consid ered all the relevant evidence before us, including all the 
expert reports, including the methodologies and models contained therein.  
60 Australia's first written submission, Annexure E, para. 45; and Scharfstein Report, (Exhibit AUS -20), 
para. 68.  
61 See Ch ipty Third Rebuttal Report, (Exhibit AUS -605), para. 70.  
62 As described above, given that the statistical trend analysis does not specify explicitly the impact of 
the TPP measures, we consider it to be different from the remaining approaches, which explici tly control for the 
TPP measures and other relevant variables beyond the trend.  
63 See IPE Report , (Exhibit DOM -100); IPE Updated Report , (Exhibit DOM -303); IPE Second Updated 
Report , (Exhibit DOM -361); IPE Third Updated Report , (Exhibit DOM -375); and IPE S ummary Report , (Exhibit 
DOM-379).  
64 The two -stage micro -econometric analysis initially proposed but then set aside by IPE was the object 
of several criti ques raised by Australia's expert, Professor  Scharfstein. Professor  Scharfstein argues that the 
analysi s misinterprets the constant terms in the first -stage model by considering the estimated likelihood of 
smoking for a specific nonsensical subgroup of individuals: males, age zero, with zero years of education, who 
are positioned at the very top of the inco me distribution. In Professor  Scharfstein's view, this misinterpretation 
is important because these constant terms serve as the critical input to IPE's second -stage analysis and are the 
basis of IPE's conclusions about the effects of the TPP measures. Professor  Scharfstein submits that the results 
of IPE 's two -stage micro -econometric analysis would show evidence of a TPP effect if different demographic 
subgroups were considered by redefining ("centering") the variables in the first -stage model . See Scharfst ein 
Report, (Exhibit AUS -20), paras.  73-84.  
 WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  last three approaches, which to some extent have been adopted to address some of the criticisms 
raised by Australia's experts, Dr Chi pty and Professor  Scharfstein. As well as using different 
estimation techniques, these approaches differ also in terms of model specifications, that is the set 
of explanatory variables used to explain the evolution of smoking prevalence and that are includ ed 
explicitly in the model, such as tobacco policies and demographic variables. The only variable 
common to all econometric approaches is a variable capturing the smoking prevalence trend, 
although the trend is assumed to be linear in some cases and quadra tic (i.e. curved) in others 
depending on the sample period covered. The most recent econometric analysis presented in the 
IPE Report  covers the period July 2006 to September  2015.  
64.  Overall, IPE concludes that the TPP measures  had no statistically significa nt effect on general 
smoking prevalence and on cigar smoking prevalence.65 Other factors explain the reduction in 
smoking prevalence, such as the overall declining trend. According to IPE, these results are robust 
across different specifications (e.g. diffe rent TPP measures ' starting date: October, November  and 
December; controlling for the weighted average price of cigarettes and/or tax policy change, 
population sample weighting changes by Roy Morgan Research, extending the sample period back 
to January  2001-September  2015).  
65.  Australia's expert, Dr Chipty, rejects the econometric results of the IPE Report s on various 
technical grounds. First, according to Dr Chipty, there is no credible justification for excluding data 
prior to July 2006 and the analysis should cover the 2001 -2015 period.66 Second, Dr Chipty rejects 
IPE's assertion that the STATA software command, ivreg2, used to estimate standard errors robust 
to "heteroscedasticity"67 and "autocorrelation"68 (Newey -West standard errors) is wrong, noting 
that IPE used the same STATA command, before Professor  List claimed he found an error in the 
STATA programming code.69 Third, Dr  Chipty argues that controlling for prices inclusive of tax 
while attempting to measure the effects of a tax hike ignores the TPP measures ' effect on price, 
leading the TPP indicator variable to capture only a partial effect of the TPP measures , and the 
price variable capturing the rest of its effect. Dr  Chipty further notes that IPE initially controlled for 
excise tax increase with in dicator variables in its model specification but then decided to replace it 
with a price variable.70 Fourth, and similarly, Dr  Chipty submits  that the use of single tax level 
variable, as proposed by IPE, is only valid under the proportionality assumption ( i.e. the effect of 
tax changes on prevalence is proportional to the size of the tax change), which may only be 
satisfied in some specifications (for instance, the model of cigar smoking prevalence does not 
satisfy this assumption).71 Finally, Dr  Chipty argu es that the inability of IPE to measure a negative 
and statistically significant effect of the TPP measures  on prevalence stems from challenges 
associated with the inclusion of a time trend: (a)  the inclusion of a linear trend (for the 
                                                                                                                                                  
IPE argues in its report that Professor  Scharfstein 's analysis is misspecified, and that his findings are 
entirely driven by this misspecification, which attributes the effects of the secular downward trend to the TPP 
measures . See IPE Updated Report , (Exhibit DOM -303), paras.  69-74. 
Professor  List criticises the fact that Professor  Scharfstein's analysis suffers from the same issues 
Professor  Scharfstein argues affect the constructed constant term in the IPE Report by constructing the 
constant term for individuals that do not exist in the data and failing to construct the constant term for some 
individuals. Professor  List further argues that Professor  Scharfstein's reanalysis overstates the importance of 
the TPP  measures' impact for two reasons. First, the statistical analysis does not account for the fact that this 
is a case of multiple hypothesis testing, which increases the probability of at least one incorrect rejection. 
Second, the statistical analysis does not account in the second stage analysis for all background changes not 
related to the policy, such as tax increases and macroeconomic factors . See List Report, (Exhibit DOM/IDN -1), 
paras.  113-122. 
Professor  Scharfstein  contends that both IPE and Professor  List have misinterpreted his critiques of the 
two-stage micro -econometric analysis, confusing his demonstration of its flaws with an affirmative opinion 
about the effect of the TPP measures. In his view, the two -stage micro -econometric analysis, even afte r the 
modification he made to it, remains flawed and should not be used to assess the impact of the TPP measures. 
See Scharfstein rebuttal report, (Exhibit AUS -587), paras.  12-19. 
65 See IPE Summary Report , (Exhibit DOM -379), paras.  11-24, Appendix  6. 
66 See Chipty Surrebuttal Report, (Exhibit AUS -586), para. 9; and Chipty Third Rebuttal Report, (Exhibit 
AUS-605), paras.  34-35. 
67 Heteroscedasticity arises when the regression errors variances are not constant across observations . 
W. H. Green, Econometric Analy sis, 5th edn  (Prentice Hall, 2002).  
68 Autocorrelation or serial correlation of the disturbances arises when the disturbances are correlated 
across periods . W. H. Green, Econometric Analysis , 5th edn  (Prentice Hall, 2002). 
69 See Chipty Second Rebuttal Report, (Exhibit AUS -591), paras.  13-31. 
70 See Chipty Surrebuttal Report, (Exhibit AUS -586), para. 12. 
71 See Chipty Third Rebuttal Report, (Exhibit AUS -605), paras.  22-26 and 29 -32. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  July 2006-September  2015 sample) ; or (b) allowing the trend line to both shift and change slop e 
at July 2006 (for the January  2001-September  2015) . In each case, Dr Chipty notes  that the time 
trend absorbs all policy effects, noting that in most specifications the impact of e xcise tax (or 
tobacco price), considered by all complainants as one of the most effective tobacco control 
measure s, is not statistically significant.72  
3.1.1.2   Professor  List's reports  
66.  The Dominican  Republic  and Indonesia's expert Professor  List reconsiders the RMSS data and 
estimates a two -stage micro -econometric model. The first stage estimates the likelihood of a 
representative person being a smoker for each month controlling for demographic characteristics 
(e.g. age, fourth order polynomials73 of gender, educa tion, and income). The second stage 
conducts a before and after analysis on the likelihood for each month computed in the first stage 
by estimating a linear probability model controlling for the TPP measures , price and/or linear 
trend, and weighting change s by Roy Morgan Research. The most recent econometric analysis 
presented in Professor  List's report covers the period from July 2006 to September  2015.  
67.  Overall, Professor  List concludes that the TPP measures  had no statistically significant effect 
on the likelihood of a representative Australian smoker or of a representative Australian minor and 
young adult smoking.74 According to Professor  List, these results are robust across different 
specifications (e.g. different TPP starting date: October, November  and December). The results are 
also robust to an alternative way of calculating the explanatory variables' standard errors that are 
robust to heteroscedasticity and autocorrelation and correct compared to the STATA software 
package ivreg2 used by Dr Chipty. The standard error of the explanatory variables, including the 
TPP measures , is important to determine whether the respective variable is statistically different 
from zero or not. According to Professor  List, his new procedure to compute standards errors 
follows exactly the procedure described in the seminal article of Newey and West (1994) in order 
to select the maximum amount of time that the data can be correlated over time (maximum lag 
selection). The same method was also used in the latest IPE Reports.  
68.  Australia's expert, Dr  Chipty, submits  that the econometric results on smoking prevalence of 
Professor  List are flawed for many of the same reasons formulated with respect to IPE Reports. In 
particular, Dr  Chipty contests restricting the sample to the per iod 2006 -2015; using a price 
variable without correcting for the TPP measures ' effect on price; including a trend variable that 
absorbs all policy effects, and the assertion that the STATA software command ivreg2, used to 
estimate robust standard errors, i s wrong. In addition, Dr Chipty considers Professor  List's 
attempts to correct for the sample re -weighting contained in the RMSS data to be unsound, noting 
that this was an entirely new concern about the RMSS data that had not been raised before in any 
of the expert debate.75  
3.1.1.3   Professor  Klick's reports  
69.  Honduras's expert Professor  Klick also reconsiders the RMSS data and estimates a two -stage 
micro -econometric model. The first stage estimates the TPP measures ' impact on tobacco price 
controlling for excise ta x indicators. The second stage estimates the TPP measures ' impact on the 
likelihood a respondent is a smoker by estimating a linear probability model controlling for the 
TPP measures , the logarithm of tobacco price instrumented by excise tax indicators in the first 
stage, quadratic trend, 2006 GHW and demographic characteristics (e.g. sex, married status, 
urban status, age, income, education, territory and job category). The TPP measures ' impact 
corresponds to the sum of the direct effect of TPP measures  on the probability a respondent is a 
smoker and the indirect effect of the TPP measures  defined as the product of the TPP measures ' 
effect on price and the effect of price change on the probability a respondent is a smoker.76 The 
most recent econometric analy sis presented in Professor  Klick's Report covers the period from 
January  2001 to June 2015.  
                                                
72 See Chipty Third Rebuttal Report, (Exhibit A US-605), paras.  36-42. 
73 A fourth order polynomial of a given variable x corresponds to x1, x2, x3 and x4. 
74 See List Third Supplemental Report, (Exhibit DOM/IDN -7), paras.  78-80. 
75 See Chipty Second Rebuttal Report, (Exhibit AUS -591), paras.  32-38. 
76 See Klick Third Supplemental Rebuttal Report , (Exhibit HND -166), para. 21. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  70.  Overall, Professor  Klick concludes that the TPP measures  had no statistically significant effect 
on the likelihood that a respondent is a smoker.77 Professor  Klick further re -estimates his model 
focusing on young people (14 -24 years old). While the TPP measures ' impact is not statistically 
significant for the age groups 14 -17 and 18 -19, the TPP measures ' impact is positive and 
statistically significant for the age gr oup 20 -24.78 According to Professor  Klick, these results are 
robust across different specifications (e.g. different TPP starting date: October, November  and 
December).  
71.  Dr Chipty rejects Professor  Klick's use of a quadratic time trend variable, because it ab sorbs 
virtually all of the variation in smoking prevalence and leaves no room for any other explanatory 
variables, including price, to have a measurable effect on smoking prevalence.79 In addition, 
Dr Chipty argues that Professor  Klick's two -steps instrumen t variables approach does not yield 
reliable estimates for the standard error and confidence interval of the TPP measures ' total 
effect.80 
3.1.1.4   Dr Chipty's reports  
72.  Dr Chipty c onsiders the RMSS data to be her  preferred  data for assess ing the TPP measures ' 
impact on smoking prevalence because of its large sample size , sufficient pre -period , and national 
representativeness . However, as explained above, Dr Chipty rejects the econometric results of the 
reports by IPE, Professor  List and Professor  Klick on various tech nical grounds. Dr Chipty 
addresses these critics by re -estimating the models of smoking prevalence developed by IPE 
(one-stage micro -econometric analysis and modified trend analysis)  by extending the period of 
analysis from January  2001 to September  2015, controlling for a linear trend, a 2006 GHW 
dummy, a set of excise tax indicators and a set of socio -demographic characteristics, and 
correcting for robust standard errors (when necessary). Dr Chipty also re -estimates the model of 
smoking prevalence developed by Professor  List (two -stage micro -econometric analysis) by 
correcting for robust standard errors . Similarly, Dr Chipty re -estimates Professor  Klick's two -stage 
instrument variables micro -econometric anal ysis by replacing the quadratic linear variable with a 
linear trend.  
73.  Overall, Dr Chipty concludes that the TPP measures  had a negative and statistically significant 
effect on smoking prevalence.81 Most of the results show statistically significant declines  in 
smoking prevalence even when using Professor  List's own standard error calculation procedure. 
The negative and statistically significant impact of the TPP measures  on smoking prevalence is also 
robust to controlling for the reweighting of the RMSS data . Similarly, replacing the tax indicator 
variables with a single tax level variable produces similar point estimates of the TPP measures ' 
effect.  
74.  IPE, Professor  List and Professor  Klick raise a number of criticisms of Dr  Chipty's econometric 
approaches. Ac cording to IPE, Dr Chipty's model specifications covering the 
January  2001-September  2015 period fail to account for two different linear downward trends in 
smoking prevalence: one for the January  2001-June 2006 period and another for the 
July 2006-Septemb er 2015 period. As a result, Dr Chipty overestimates the downward trend in 
smoking prior to June 2006, while underestimating it afterwards.82  
75.  IPE further contends that the use of tax hike dummies, as proposed by Dr Chipty, are inferior 
control variables co mpared to cigarette prices and tax levels for three reasons: (i)  consumers base 
their choices on what cigarettes cost; (ii)  it is important to control for, by how much a certain price 
increase affects prevalence, and not only whether it affects prevalence;  and (iii)  tax hike dummies 
                                                
77 See Klick Third Supplemental Rebuttal Report , (Exhibit HND -166), paras.  11-23. 
78 See Klick Third Supplemental Rebuttal Report , (Exhibit HND -166), paras.  54-55. 
79 See Chipty Third Rebuttal Report, (Exhibit AUS -605), paras.  49-53. 
80 See Chipty Third Rebuttal Report, (Exhibit AUS -605), paras.  54-60. 
81 See Chipty Third Rebuttal Report, (Exhibit AUS -605), paras.  29-32, 52 -53 and 70 -73; and Chipty 
Second Rebuttal Report, (Exhibit AUS -591), paras.  28-38, 53 -54, Appendix  D. 
82 See IPE Summary Report , (Exhibit DOM -379), paras.  50-52. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  (or tax levels) do not control for changes in tobacco affordability other than the price changes 
resulting from the tax hikes themselves.83  
76.  Professor  List submits  that Dr Chipty's opposition to using control variables for reweig hting 
events of the population sample in the RMSS data may stem from the fact that an adjustment for 
reweighting would reverse Dr Chipty's estimates of the TPP measures ' effect.84 Failure to correct 
for reweighting changes may thus lead to misspecification.85  
77.  Professor  List, IPE and Professor  Klick argue that Dr Chipty computed incorrect standards 
errors by applying the STATA command ivreg2, which substantially deviates from the seminal 
article by Newey and West (1994). Professor  List further submits  that Dr  Chipty's method to 
compute standards errors assigns statistical significance nearly 400 % more frequently than it 
should. Applying the exact procedure proposed by Newey and West (1994), Professor  List and IPE 
conclude that most of Dr Chipty's specifications no longer exhibit a statistically significant TPP 
effect.86  
3.1.2   Commissioned Roy Morgan Research Survey (Australia and New Zealand ) 
78.  Honduras's expert Professor  Klick proposes comparing Australia's smoking behaviour before 
and after the introduction of the TPP measures  with another jurisdiction that has not implemented 
plain packaging during the same period. Professor  Klick posits that although Australia is unique  in 
many ways, it is reasonable to use New Zealand  as a reliable counterfactual jurisdiction, because 
(i) both countries share many similarities culturally, historically, and demographically; (ii)  both 
countries are in the same region and share the same se asonality (useful when dealing with 
subannual measures); (iii)  the governments of both countries themselves also recognize that they 
are especially comparable along dimensions such as health behaviour and socio -economic issues; 
(iv) tobacco prices, includi ng taxes, are comparable between both countries; and (v)  smoking 
rates in both countries are highly correlated (0.95 for the period 1964 -2012 based on OECD data 
on the fraction of residents ages 15 years and older who are daily smokers).87 Professor  Klick's  
analysis, defined as a difference -in-difference estimation, covers the period from November  2012 
to February  2014.  
79.  Overall, Professor  Klick concludes that the TPP measures ' impact on daily or occasional 
smoking in Australia relative to New Zealand  is not  statistically significant.88 Similar findings are 
obtained by using different estimators (linear probability model and logit model and fixed effects), 
restricting the sample to only individuals who answered the survey in the 6 waves (to mitigate 
attrition) , restricting the sample to only individuals who answered the survey at least in one 
post-PP waves (to mitigate attrition), restricting the sample to Wave 1 and Wave 6 (to not 
overweight immediate responses), restricting the sample to smokers planning to q uit during Wave 
1, and controlling for individual characteristics (income, unemployed, male, age).  
80.  Dr Chipty argues that Professor  Klick's difference -in-differences analysis of smoking incidence 
is invalid because Professor  Klick's commissioned Roy Morgan  survey does not contain a pre -period 
and is incapable of distinguishing which respondents had noticed plain packaging. Furthermore, Dr 
Chipty is of the view that New Zealand  is an invalid counterfactual for the purposes of studying the 
effects of the TPP measures , because of New Zealand 's January  2013 excise tax increase, a month 
after the TPP measures ' introduction.89 
                                                
83 See IPE Third Updated Report , (Exhibit DOM -375), para. 139; and IPE Summary Report , (Exhibit 
DOM-379), paras.  56-60. 
84 See List Third S upplemental Report, (Exhibit DOM/IDN -7), paras.  51-55.  
85 See IPE Summary Report , (Exhibit DOM -379), paras.  53-54. 
86 See List Third Supplemental Report, (Exhibit DOM/IDN -7), paras.  42-50; List Summary Report, 
(Exhibit DOM/IDN -9), paras.  83-98; IPE Summary Report , (Exhibit DOM -379), paras.  61-65; and Klick Fourth 
Supplemental Rebuttal Report , (Exhibit HND -169), paras.  16-20. 
87 See Klick Report , (Exhibit UKR -5), pp. 3-6. 
88 See Klick Report , (Exhibit UKR -5), pp. 23-32; and Klick Rebuttal Report , (Exhibit HND -118), 
paras.  19-38. 
89 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  54-71. In its third -party submission, 
New Zealand  similarly argues that Professor  Klick's study sets up a false and virtually impossible evaluation 
test by looking for a marke d short -term reduction in population smoking prevalence. New Zealand  also submits 
 WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  81.  Dr Chipty submits  that Professor  Klick's data show that Australia has experienced both a 
bigger absolute decline and faster rate of decline in daily smoking incidence than New Zealand , 
although there is no measurable decline in overall smoking, which is consistent with the possibility 
that the TPP measures  are having its intended effect.90 
3.1.3   New South Wales Population Health Survey  
82.  The New South Wales Population Health Survey (NSWPHS) reports yearly observation of daily 
smoking prevalence and smoking in general prevalence among men and women in NSW, the most 
populated state in Australia.  
83.  Professor  Klick estimates a model of (daily or overall) smok ing prevalence in NSW controlling 
for the TPP measures  and a linear time trend. The econometric analysis covers the period from 
2002 to 2014. Because the NSWPHS data are only available on an annual basis, the TPP variable is 
coded in different ways for the  year 2012: (i)  using the value of 0.25 (representing three months 
out of the year if an October  start date is assumed); (ii)  using the value of 0.08 (representing a 
single month if a December start date is assumed), or (iii)  using the value of zero (if it  is assumed 
that the vast majority of survey respondents would have answered the survey pre -TPP). 
84.  Overall, Professor  Klick concludes that the TPP measures  either had no statistically significant 
effect on daily smoking prevalence in NSW or had a positive a nd statistically significant impact on 
smoking prevalence in general in NSW.91 An analysis across age groups and/or by gender yields 
relatively similar results.  
85.  Dr Chipty considers that Professor  Klick's analysis of smoking prevalence in NSW should be 
disregarded in its entirety because of three basic problems. First, Dr Chipty argues that 
Professor  Klick is incorrect to assert  that Australia -wide data are not granular enough to credibly 
examine the TPP measures ' effects on smoking prevalence. Second, Dr Ch ipty is of the view that 
the NSWPHS data are incapable of providing a basis to study the TPP measures ' effects in NSW, 
because the estimate of the TPP effect is calculated from two to three data points and cannot be 
distinguished from the two excise tax in creases in 2013 and 2014. Finally, Dr Chipty asserts that 
there have been changes in the NSW survey methodology that led to a greater number of younger 
people and males in the survey sample; both of these groups have relatively higher smoking rates, 
leadin g to a higher overall reported rate of current smoking.92 
3.1.4   Cancer Institute New South Wales Tobacco Tracking Survey  
86.  Professor  Klick estimates a logit model of the likelihood that the respondent is a smoker, an 
ordered logit model of the smoking status, and a negative binomial model of the number of adults 
who are smokers in the household controlling for the TPP measures , annual time trend, gender, 
individual age fixed effects, week of survey fixed effects and location fixed effects. The 
econometric analysis c overs the period from January  2009 to December  2014.  
87.  Overall, Professor  Klick concludes that the TPP measures  either had no statistically significant 
effect on the likelihood of being a smoker in NSW and on the number of adult smokers in 
household or had a positive and statistically significant impact on the likelihood of being a daily 
smoker in NSW and on the smoking status.93 
88.  Australia posits that although Honduras  has presented analyses based on a range of other 
datasets, such as the CITTS data, these ar e not sources of smoking prevalence data.94 Australia's 
                                                                                                                                                  
that the use of New Zealand  as a comparison case is superficial and misleading, because Professor  Klick does 
not separately analyse the declining trends in smoking prevalence  in each country by taking into account the 
range and variety of tobacco control interventions taken in each country, including the 10% excise tax increase 
implemented in New Zealand  in January  2013, which was unique to New Zealand  during the relevant time 
period.  
90 See Chipty Report, (Exhibit AUS -17), paras.  25-31, Appendix  C. 
91 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  33-43. 
92 See Chipty Surrebuttal Report, (Exhibit AUS -586), paras.  78-86. 
93 See Klick Seco nd Supplemental Rebuttal Report , (Exhibit HND -165), paras.  15-24. 
94 See Australia's response to Panel question No. 196, para. 252. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  expert, Professor  Chaloupka, is further of the view that using these data to assess the 
TPP measures ' impact on the likelihood of being a smoker, as Professor  Klick does, is 
inappropriate. Professor  Chaloupka further argues that Professor  Klick's conclusion of no evidence 
of a decline in smoking associated with the TPP measures  is highly misleading, because the nature 
of the NSW Tracking Survey data does not allow one to use these data to assess the 
TPP measures ' impact on adult smoking prevalence given that the sample is not a representative 
sample of the NSW adult population. In addition, Professor  Chaloupka contends that 
Professor  Klick failed to appropriately account for the changes in the CITTS m ethodology that led 
to a greater number of younger people and males in the survey sample; both of these groups have 
relatively higher smoking rates, leading almost certainly to biased estimates towards showing an 
increase in smoking following the change in  method.95  
3.1.5   National Tobacco Plain Packaging Tracking Survey  
89.  As described in Appendix  A, Australia funded the National Tobacco Plain Packaging Tracking 
Survey (NTPPTS), a nationwide  cross-sectional baseline tracking survey conducted by CCV, to 
track the eff ects of the TPP measures . The results from the NTPPTS were published in April 2015 in 
the supplement to the Tobacco Control  journal dedicated to investigating the effects of Australia 's 
implementation of the TPP measures . 
3.1.5.1   Ajzen et al.'s reports  
90.  Ajzen et al. re-analysed part of Scollo et al. 2015a96, applying the approach in Wakefield et al. 
2015.97 Ajzen et al. estimated logistic, ordered logistic and linear regressions of the proportion of 
daily or weekly smokers, while controlling for age group, gender, edu cation group, socio -economic 
status group, potential exposure to televised anti -smoking advertising campaigns in the past three 
months and cigarette costliness.98  
91.  Overall, Ajzen et al. conclude that the TPP measures  had no statistically significant impact on 
the proportion of daily or weekly smokers.99 A similar finding is found with quarterly data.100 Ajzen 
et al. argue that, unlike Professor  Chaloupka's assertion  that the NTPPTS dataset has less power 
for detecting statistically significant changes in the mo re distal outcomes, such as actual tobacco 
use behaviour, the statistical power of the NTPPTS data to detect small changes in proximal and 
distal outcomes is very similar.101 
92.  Australia's expert, Professor  Chaloupka, argues that Ajzen et al.'s analyses of the  NTPPTS 
data fail to recognize that the TPP measures ' impact should be smaller for the less proximal 
outcomes when one looks at the impact in the overall sample of smokers and recent quitters, 
                                                
95 See Chaloupka Second Rebuttal Report, (Exhibit AUS -590), paras.  26-27. 
96 Ajzen et  al. argue that Scollo et al. 2015a 's conc lusion that the TPP measures had no significant effect 
on the average number of cigarettes consumed per day underreports additional results that were not 
statistically significant. According to Ajzen et  al., Scollo et al. 2015a reported on only one of the seven 
measures on smoking behaviours and the TPP measures' impact on each of the six unreported variables, 
dealing with the percentage of daily or weekly smokers, quitting, and relapse was not statistically significant . 
See Ajzen et al. Data Report, (Exhib it DOM/IDN -2), paras.  225-227. We note, however, that Ajzen et al. do not 
reassess the analysis by Scollo et al. 2015a of the TPP measures' impact and tax increase on type of tobacco 
products and price.  
97 Wakefield et al. 2015, (Exhibits AUS -206, DOM -306).  
98 We note that Ajzen et  al. also re -estimate their models by replacing the TPP measures dummies with 
a monthly time trend.  
99 Ajzen et  al. reach the same conclusion with respect to measures related to quitting and relapse, which 
were unreported by Scollo et al. 2015a. In particular, on quitting, Ajzen et al. conclude that there was no 
statistical change in the proportion of adult smokers that quit for more than one month or had successfully quit 
between baseline and follow -up. On relapse, Ajzen et al. conclude that there was no statistical change in the 
proportion of adult ex -smokers that relapsed, still abstained from smoking at follow -up or had stayed quit for 
more than one week at follow -up. See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  221-224, 
Appendix  A, pp. 95-97. 
100 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), para. 90. 
101 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  50-54, Appendix  II. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  given that smokers and recent quitters for whom the most proxim al outcomes were unaffected 
would not be expected to show any change in the less proximal outcomes.102  
3.1.5.2   Professor  Klick's report  
93.  Professor  Klick estimates a logistic regression of the likelihood the respondent is a daily 
smoker or a smoker in general or an o rdered logit model of the smoking status, controlling for the 
TPP measures , gender, age, education, socio -economic status and a linear time trend. The 
econometric analysis covers the period from 9 April 2012 to 4 May 2014.103  
94.  Overall, Professor  Klick conclu des that the TPP measures  had no statistically significant effect 
on the likelihood of being a smoker and on the smoking status during their first year of 
implementation.104 
95.  Australia posits that the NTPPTS data are not a source of smoking prevalence data.105 
Although Australia's experts do not specifically address Professor  Klick's results on smoking status 
based on the NTPPTS data,  Professor  Chaloupka generally argues that the NTPPTS is particularly 
useful in assessing the TPP measures ' impact on proximal out comes (appeal, noticeability of health 
warnings and misleading) but the largely cross ‐sectional nature of the survey does not allow one to 
track the TPP measures ' effects on more distal outcomes (e.g. interest in quitting) and on tobacco 
use behaviour (pre valence and consumption).106 Professor  Chaloupka  further claims that the 
impact of the TPP measures  on more distal outcomes should be smaller when the analysis is based 
on the overall sample of smokers and recent quitters, given that smokers and recent quitt ers for 
whom the most proximal outcomes were unaffected by the TPP measures  would not be expected 
to show any change in more distal  outcomes . 
3.2  Analysis by the Panel  
96.  As discussed  above , there is some evidence of an acceleration of the reduction in smoking 
prevalence since the entry into force of the TPP measures . The question before us at this stage of 
our analysis is whether this acceleration may, in part or in whole, be attributed to t he 
TPP measures . 
97.  We note that the evidence relied on by the parties in this part of the discussion is based on an 
econometric analysis of the evolution of smoking prevalence or smoking incidence aimed at 
distinguishing and assessing the impact of the TPP  measures and other determinants on the level 
of smoking prevalence or smoking incidence. In particular, the "dependent" variable, smoking 
prevalence or smoking incidence, is modelled as a function of a number of "explanatory" variables, 
including the TPP measures .107 The parties use different econometric estimators (namely the 
ordinary least square (OLS) estimator, the maximum likelihood estimator, the linear probability 
                                                
102 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 4. 
103 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  15-32. 
104 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  21-32. 
105 See Australia's response to Panel question No. 196, para. 252; and Chaloupka Second Rebuttal 
Report , (Exhibit AUS-590), para. 26. 
106 See Chaloupka Third Rebuttal Report , (Exhibit AUS -604), paras . 8-13. 
107 Explanatory variables ideally represent the full set of factors that have an impact on the dependent 
variable, and therefore contribute in "explaining" the behavio ur of the dependent variable. In general, 
explanatory variables are assumed to be independent with respect to the dependent variables. In other words, 
the dependent variable is assumed to have no (direct or indirect) impact on the explanatory variables tha t, in 
turn, have an impact on the dependent variable. For this reason, explanatory variables are often referred to as 
independent variables. A specific parameter is attached to each explanatory variable included in the 
econometric model, which represents t he impact that the associated explanatory variable might have on the 
dependent variable. Thus, when the econometric model is well specified with all the relevant explanatory 
variables, each parameter isolates the impact of the associated explanatory variab le on the dependent 
variable. In addition to the explanatory variables, the econometric model includes an error term, also known as 
the "residual" term, to capture the facts that no matter how well the model is specified (i) it is often impossible 
to accou nt for every factor that has an impact on the dependent variable, (ii) the actual relationship between 
the dependent variable and (some of) the explanatory variables may not be necessarily linear, (iii) data may 
suffer from measurement errors, and (iv) unp redicted – stochastic – effects can affect the dependent variable. 
Ultimately, econometric analysis consists of estimating each parameter of the explanatory variables specified in 
the model.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  estimator, and the logistic estimator) to estimate the parameters of the explanatory vari ables that 
best fit the relevant data. Each estimated parameter is assigned a standard error, which enables 
the evaluation of whether this estimated value of the parameter is statistically different from zero, 
i.e. statistically significant , at a given lev el of significance typically 1 %, 5% or 10% . The standard 
error provides information on the degree of confidence and reliability of the estimated value of 
each parameter considered in the model. As described above, the Dominican  Republic , Honduras 
and Indon esia submit  that the TPP measures ' impact on smoking prevalence or smoking incidence 
is statistically not different from zero, while Australia submits  that the impact of the TPP measures  
on smoking prevalence is negative and statistically different from ze ro. 
98.  At the outset, we note that  we approach this assessment on the basis that our task  is not to 
conduct our own econometric assessment of the impact of the TPP measures  on smoking 
prevalence , but rather to review the robustness of the econometric evidence  submitted by the 
parties  in this respect .  
99.  While we acknowledge that no data are perfect, we agree with Australia that the RMSS data is 
the most suited available data submitted by the parties to analyse the impact of the TPP measures  
on smoking prevalence , for two main reasons. First, the RMSS data provide an actual measure of 
smoking prevalence (based on a population of smokers, recent quitters and non -smokers). 
Second, the data are available monthly for a long period of time before and after the introduction 
of the TPP measures . The parties disagree with respect to the selection sample period. We concur 
with Australia that a large r number of observation s is likely to increase the precision of the 
estimates. In addition, we note that Professor  List, in his report submitted by th e 
Dominican  Republic  and Indonesia,  suggest s limiting the sample period to analyse smoking 
prevalence, but do es not propose the s ame restriction in the analysis of cigarette consumption.108  
100.  The other data sources considered by Professor  Klick suffer , in our view,  from a number of 
drawbacks in comparison with the RMSS data. In particular, the commissioned Roy Morgan 
Research Survey da ta collected in Australia and New Zealand  cover a short period prior to the 
introduction of the TPP measures  in December  2012, during which plain packs were already 
authorized for sale in the market. In comparison, the pre -TPP period of the RMSS data are 
available starting January  2001. In addition, the commissioned Roy Morgan Research Survey data, 
just like the CITTS and NTPPTS  datasets , do not actually measure smoking prevalence, because 
the sample is based only on smokers and recent quitters. Finally, al though the NSWPHS data 
provide information on smoking prevalence in NSW, the fact that they are only available yearly 
imply that the post -TPP period used to assess the impact of TPP measures  covers only two to three 
observations. This is extremely short in  comparison with the RMSS data encompassing up to 34 
post-TPP observations ( December  2012-September  2015).  
101.  Turning to the econometric results based on the RMSS data, we note at the outset that the 
different conclusions reached by the parties regarding the  impact of the TPP measures  on smoking 
prevalence stem from the fact that the parties' experts use different model specification (i.e. 
different explanatory variables included in the model), estimation approaches and in some cases 
sample periods. Even amon g the experts  of the Dominican  Republic , Honduras and Indonesia , 
different model specifications are used.109  
102.  On a number of occasions, the rebuttal reports of the Dominican  Republic 's, Honduras' s and 
Indonesia ' experts proposed new model specifications or methodologies or both , to address some 
of Australia's criticisms but also to take into account issues that the ir experts themselves 
highlighted. For instance, IPE initially proposed (in its analysis of cigarette sales volumes) 
controlling for excise tax in creases by including indicator variables for each excise tax increase in 
                                                
108 See List Third Supplemental Report, (Exhibit DOM/IDN -7), pp. 4-8. 
109 For instance, IPE initially (see IPE Updated Report , (Exhibit DOM -303)) and Professor  Klick (see Klick 
Third Supplemental Rebuttal Report , (Exhibit HND -166)) control for excise tax increases by specifying dummy 
variables for each excise tax hike imple mented during the sample period, while IPE later in the proceedings 
(see, e.g.  IPE Second Updated Report , (Exhibit DOM -361)) and Professor  List (see , e.g.  List Report, (Exhibit 
DOM/IDN -1)) consider the variable of cigarette price to be a better proxy for e xcise tax increases. Similarly, 
Professor  Klick applies the instrument variables estimator to address the potential endogeneity of the price 
variable, while IPE and Professor  List do not. Another difference among  the experts of the Dominican  Republic , 
Honduras, and Indonesia is the fact that IPE and Professor  Klick use monthly sample sizes as weights in the 
estimation, while Professor  List do es not, except in the first stage of his micro -econometric analysis.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  the sample period.110 However, it subsequently contended that a more appropriate measure to 
capture the excise tax increases was the average price per cigarette in Australia.111 Although the 
experts  of the Dominican  Republic , Honduras and Indonesia  ultimately reach the same conclusion 
when the changes they proposed are tak en into account, they explicitly or in some cases implicitly 
suggest ignoring or giving less weight to their previous r esults affected by the issues the ir experts 
themselves recognized or highlighted. As explained above, it is not our task to present a unified 
econometric analysis but rather assess the robustness of each report.  
3.2.1   IPE's and Professor  List's econometric resul ts 
103.  After a careful review of the econometric reports on smoking prevalence based on the RMSS 
data submitted by the Dominican  Republic 's and Indonesia's experts112, we are not persuaded that 
these econometric results can be taken at face value , mainly because  most of their model 
specifications are unable to detect the impact of tobacco costliness (including excise tax increases) 
on smoking prevalence. Yet, all parties consider tobacco excise tax to be one of the most effective 
tobacco control policies.113 To som e extent, the Dominican  Republic , Honduras and Indonesia are 
asking the Panel to conclude that the TPP measures  had no impact on smoking prevalence, 
because its effect is statistically not significant, but to disregard the fact that the same 
econometric re sults suggest that excise tax or price increase have also had no impact on smoking 
prevalence.  
104.  The manner in which the smoking prevalence trend is modelled with respect to the sample 
period considered (i.e. January  2001-September  2015 or July 2006-Septemb er 2015) has an 
important consequence on whether the econometric analysis is able to identify the impact of other 
variables. These variables can contribute, along with demographic shifts and other factors 
unrelated to tobacco control policies, to creating the smoking prevalence trend.114 This problem is 
defined as overfitting. For instance, the issue of overfitting associated with the trend variable is so 
severe in the ARIMAX models reported in the IPE Report s that even the lagged dependent variable 
is not statistically significant, suggesting that the level of smoking prevalence does not depend on 
the level of smoking prevalence in the previous month, which is in complete contradiction with the 
fact that smoking prevalence follows a downward trend, as agree d by all parties.115 Similarly, the 
results of Professor  List's two -stage micro -econometric shows how the inclusion of the secular 
(long-term) trend116 captures most of the explaining power making the price variable no longer 
significant in most of the specifi cations, while the price variable is always statistically significant 
when the trend variable is not included.117  
105.  In our view, it is important that the trend variable specified in the model avoids overfitting 
the data , to allow an identif ication of  the impa ct of other variables of interest, such as individual 
                                                
110 See IPE Report , (Exhibit DOM -100), p p. 67-69. 
111 See IPE Second Updated Report , (Exhibit DOM -361).  
112 Although the methodologies proposed by IPE and Professor  List differ, they share a number of 
similarities, including the sample period, the choice of the variable to control for tobacco price control po licies 
and the procedure to estimate the standard errors. That is why both experts' results are discussed together. 
See List Report, (Exhibit DOM/IDN -1); List Rebuttal Report, (Exhibit DOM/IDN -3); List Second Supplemental 
Report, (Exhibit DOM/IDN -5); List Third Supplemental Report, (Exhibit DOM/IDN -7); List Summary Report, 
(Exhibit DOM/IDN -9); IPE Report , (Exhibit DOM -100); IPE Updated Report , (Exhibit DOM -303); IPE Second 
Updated Report , (Exhibit DOM -361); IPE Third Updated Report , (Exhibit DOM -375); and IPE Summary Report , 
(Exhibit DOM -379).  
113 See Australia's first written submission, para. 719; Honduras's first written submission, para. 589; 
Dominican  Republic's  first written submission, paras.  758 and 1027; Cuba's first written submission, para. 276; 
and Indonesia's first written submission, para. 63. 
114 IPE considers a linear trend for the sample period July 2006-September  2015 and a quadratic trend 
for the sample period January  2001-September  2015. Similarly, Professor  List specifies a linear trend for the 
sample period July 2006-September  2015. Professor  Kick specifies a quadratic trend for the sample period 
January  2001-September  2015.  
115 See, e.g.  IPE Third Updated Report , (Exhibit DOM -375), p p. 34 and 106-108.  
116 See para. 11 above for a discussion on the secular trend.  
117 See, e.g. List Rebuttal Report, (Exhibit DOM/IDN -3), pp. 15 and 24; List Second Supplemental 
Report, (Exhibit DOM/IDN -5), pp. 32-33; and List Third Supplemental Report, (Exhibit DOM/IDN -7), pp. 18-19 
and 29 -30. In addition, we also question the validity of some of the results obtained by Professor  List in the 
first stage, where none of the explanatory variables are statistically significant (at 10%), not even the 
constant. Such results suggest that the associated model specification might be misspecified or affected by 
another econometric issue that Professor  List failed to address.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  tobacco control policies. Otherwise, one cannot rule out the possibility that the smoking prevalence 
trend included in the model accounts not only for the trend itself but potentially also reflects any 
tobacco control policies that contributed to its trend. We note that while the experts  of the 
Dominican  Republic , Honduras and Indonesia  discussed extensively the importance of accounting 
properly for the secular downward trend in smoking prevalence, they do not address the fact that 
in the vast majority of their results , the price variable was not statistically significant.  
106.  In this context, we also consider it important to specify the tobacco price control policy in the 
most appropriate manner. We note th at the Dominican  Republic 's experts' view on this issue has 
evolved throughout the proceedings. IPE was the first party to propose controlling for tobacco tax 
excise increases with indicator variables (in its analysis of cigarette sales discussed in Append ix D), 
but later changed its view when Professor  List used a price variable in his own analysis.118 IPE 
referred to the tobacco price variable as a measure for costliness of tobacco products (reflecting 
also the effect of tax increases). IPE also proposed th e level of tax as an alternative to the price 
variable. In our view, the three types of variables (dummy variables, tax level variable and price 
variable) are in theory complementary, each with advantages and disadvantages. The dummy 
variables are, by cons truction, exogenous and specific to each excise tax increase but do not 
specify the actual level of the tax increase. The tax level variable is also, by definition, exogenous 
and accounts for the actual level of the tax increase. However, as explained by A ustralia, it relies 
on the assumption that the effect of the tax increase on prevalence is proportional to the size of 
the tax increase. The price variable is a broader variable and accounts implicitly for all the factors 
that affect tobacco price, includi ng the excise tax increases but not only that. The TPP measures  
can also affect the price variable, as pointed by Dr Chipty and addressed by Professor  Klick.  
107.  In addition , we observe after a careful review, that there is, as shown in Figure C.20 , 
evidence of multicollinearity between the price variable and the linear trend variable, in particular 
when the sample period is restricted to July 2006 to September  2015.119 Multicollinearity arises 
when two (or more) explanatory variables convey the same information. In the presence of 
multicollinearity, the predictive power of the model remains unchanged, but the confidence 
interval of the coefficient estimates may increase. Moreover , the coe fficient estimates may become 
very sensitive to minor changes in the model specification or data. One way to mitigate 
multicollinearity is to increase the sample period. We note, however, that including a second linear 
trend specific to the July 2006-Septe mber 2015 period, as suggested by IPE, would not resolve 
this issue. We also note that unlike Professor  Klick, IPE and Professor  List do es not address the 
fact that the TPP measures  might affect the price variable. IPE and Professor  List's model 
specificat ions are unable to distinguish between the impact specific to the price variable and the 
TPP measures . Overall, given that neither IPE nor Professor  List address the issue of 
multicollinearity, and the potential impact of the TPP measures  on prices, we cal l into question the 
econometric results based on the price variable. We also note that the expert reports submitted by 
the Dominican  Republic , Honduras and Indonesia (and Australia) failed to mention that standard 
unit root tests suggest that the tax level  and the price variables are not stationary.120 Yet, 
econometric theory recommend s not estimating a model when the dependent variable 
(i.e. smoking prevalence) is stationary and one of the explanatory variable s (i.e. tax level or price) 
is not stationary in order to avoid spurious and biased results.  
108.  The parties' experts also disagree with the manner in which the population sampling 
correction is addressed in the RMSS data. We first note, as pointed out by Australia, that 
Professor  List did not consider the s ample reweighting in the RMSS data to be an issue in his first 
two reports. Similarly, IPE did not address the issue of reweighting in its first three reports.121 We 
recognize the importance of attempting to control for sample re -weighting events in the RMSS  
data. We note, however, that the inclusion of the three indicator variables to control for the 
reweighting correction in April 2009, July 2010, and April 2014, as suggested by Professor  List, 
increases the issue of multicollinearity, in particular when th e price (or tax level) and trend 
                                                
118 See IPE Updated Report , (Exhibit DOM -303), para. 150; and IPE Second Updated Report , (Exhibit 
DOM-361), para. 29. 
119 Evidence of multicollinearity is confirmed by the variance inflation factors statistic.  
120 A variable is said to be stationary, when its statistical properties, such as mean and variance are all 
constant  over time.  
121 We note that, unlike Professor  List and IPE, Professor  Klick does not address the sample reweighting 
corrections in the RMSS data in his analysis.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  variables are included in the specification.122 This problem is accentuated  when a fully flexible 
reweighting correction is adopted. For instance, none of the explanatory variables is statistically 
significant at 5% when the linear trend and price variables and the fully flexible reweighting 
correction are included in Professor  List's model specification for smoking prevalence among minor 
and young adult.123 Similar findings apply to IPE's modified trend analysis of overall smok ing 
prevalence, where the only significant variable is the dummy for the trend shift in July 2006.124 
Some results of IPE's modified trend analysis even suggest that the TPP measures  have led to a 
statistically significant increase in cigar smoking prevalenc e.125 The idea that the TPP measures  
"backfired" is rejected not only by Australia, but also by the Dominican  Republic 's and Indonesia's  
experts . Professor  List has explicitly questioned the possibility that the TPP measures  
"backfired".126 IPE explains also t hat it does not interpret the statistically significant and positive 
impact of the  TPP measures  on cigar smoking prevalence  as evidence that the TPP measures  led to 
an increase in cigar smoking prevalence, but rather as strong evidence to reject the claim of the 
intended negative TPP measures ' effect on cigar smoking prevalence.127 Yet, the 
Dominican  Republic 's and Indonesia's  experts do not explain  why such fin ding should be 
interpreted differently, without questioning the validity of the model specification that yields such 
result, especially when it relates to the main variable of interest of the econometric analysis. In 
fact, none of the Dominican  Republic 's and Indonesia's experts sought to explain why the 
TPP measures  would lead to an increase in the number of smokers. Overall, and based on the 
above, we have doubts about the reliability of the results obtained when the price variable, time 
trend and sample reweighting dummies are included in the model specifications.  
Figure C. 20: Tobacco Price and Linear Trend  
[[***]] 
 
Note:   Weighted average price per stick (in AUD) of factory -made cigarettes and roll -your-own tobacco 
(based on a  0.8 grams conversion rate of roll -your-own tobacco to cigarette sticks). The vertical 
dashed line indicates the introduction of TPP and enlarged GHWs. The dashed and dotted linear time 
trends correspond, respectively, to the sequence 1, 2, 3 … up to 177 o r the sequence 1, 2, 3, up to 
111. 
Source :  In-Market -Sales data and Coles and Woolworths data, based on data update and computer code and 
calculations supporting the IPE Updated R eport, (Exhibit DOM -373) (SCI); and List Second 
Supplemental Report , (Exhibit DOM/IDN -5).  
 
109.  Another technical issue that has been the object of extensive discussions among the parties 
is the choice of the procedure use d to compute the standard error of each of the estimated 
coefficients associated with the variables specifi ed in the econometric model.128 As explained 
earlier, statistical significance is essential because , as well as being the variable's estimated 
coefficient, it is also important to determine whether the coefficient's variable is statistically 
                                                
122 For instance, the results reported in columns (3) and (4) of Table  8 in List Second Supplemen tal 
Report, (Exhibit DOM/IDN -5), p. 43 suggest that the TPP measures' effect on smoking prevalence of minors 
and young adults is positive and statistically significant at 10%. In other more recent results on smoking 
prevalence among minor and young adult, presented in column  3 of Table  13 in List Third Supplemental 
Report, (Exhibit DOM/IDN -7), p. 32, the only variable, besides the constant, that is statistically significant is 
the trend when the price and time trend variables as well as reweighting correction dummies are included. We 
note, however, that the issue of multicollinearity is less severe when excise tax increase dummies or the real 
tax level variable are used.  
123 For instance, in the results on overall smoking prevalence presented in column  3 of Table  14 in List 
Third Supplemental Report, (Exhibit DOM/IDN -7), p. 33, the only variable, besides the constant, that is 
statistically significant is the trend when the price and time trend variables as well as fully flexible reweighting 
correction d ummies are included.  
124 Similar findings also apply to IPE's micro -econometric analysis, where the only significant variable is 
the dummy for the trend shift in July 2006, besides the constant and the socio -demographic variables . See IPE 
Third Updated Repor t, (Exhibit DOM -375), p. 38. We also note that IPE decided not to update the results of the 
ARIMAX model with the reweighting correction dummies.  
125 See the IPE Third Updated Report , (Exhibit DOM -375), p p. 48-50. 
126 See List Report, (Exhibit DOM/IDN -1), para. 106. 
127 See IPE Summary Report , (Exhibit DOM -379), fn 124. 
128 Heteroscedasticity and autocorrelation consistent standard errors are computed for the following 
models on smoking prevalence: IPE's modified trend analysis and ARIMAX models, and Professor  List 
two-stage micro -econometric analysis. Similarly, robust standard errors are computed for the following models 
on cigarette consumption: IPE's modified trend analysis and ARIMAX models, and Professor  List's event study 
analysis.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  different from z ero. Yet, a standard error is required to determine the estimated coefficient's level 
of statistical significance. We therefore recognize, like the parties, the importance of computing 
standard errors that are robust to heteroscedasticity and autocorrelati on.  
110.  We note, however, that the treatment of standard errors evolved over the course of the 
proceedings. Initially, Professor  List and IPE chose to apply the STATA software command ivreg2 
to calculate standard errors that are robust to heteroscedasticity a nd serial correlation using the 
automatic bandwidth selection procedure by Newey and West (1994).129 Subsequently, 
Professor  List, and later on IPE, appl ied an alternative way of calculating standard errors, that, 
according to Professor  List, is adjusted to reflect more accurately the original suggestion by Newey 
and West (1994).130 Technically speaking, the disagreement between Professor  List (as well as IPE 
and Professor  Klick) and Dr Chipty concerns the procedure to correct for autocorrelation, in 
particular  the choice of the maximum amount of time, defined as the maximum lag, that the data 
can be correlated over time. Professor  List proposes to set a smaller parameter value , resulting 
also in a smaller maximum lag than the one specified in the ivreg2 command . A careful review of 
the evidence and discussions  shows  that the choice of the maximum lag is not well established in 
the statistics and econometric literature , as pointed out by in an email exchange with STATA 
developers .131 As a result, it is unclear whether the results associated with Professor  List's 
procedure would have changed for a range of parameter values, taking into consideration the fact 
that the maximum lag should be able to take into account all lags until the serial correlation in the 
data van ishes.132  
111.  In sum, and based on the elements discussed above, we have reservations regarding IPE 
and Professor  List's methodologies133 and therefore question their results , based on these 
methodologies,  that suggest that the TPP measures  had no statistically significant impact on 
smoking prevalence.134 
                                                
129 See IPE Report  (Exhibit D OM-100); IPE Updated Report , (Exhibit DOM -303); List Report (Exhibit 
DOM/IDN -1); and List Rebuttal Report, (Exhibit DOM/IDN -3). 
130 See Second IPE updated report, (Exhibit DOM -361); IPE Third Updated Report , (Exhibit DOM -375); 
and IPE Summary Report , (Exhibi t DOM -379); List Second Supplemental Report, (Exhibit DOM/IDN -5); List 
Third Supplemental Report, (Exhibit DOM/IDN -7); and List Summary Report, (Exhibit DOM/IDN -9). 
131 See the correspondence between the parties and STATA developers in the IPE Summary Report , 
(Exhibit DOM -379), p. 70; and Chipty Second Rebuttal Report, (Exhibit AUS -591), p p. B1-B2. In the email 
exchange, the STATA software developers also explain that the automatic choice of the maximum lag in the 
command ivreg2 is in line with the criteria n ecessary for asymptotic optimality.  
132 Professor  List presents the results of simulation s to compare the frequency of so -called false 
positives using Professor  List's procedure and the ivreg2's automatic selection procedure. Professor  List 
concludes that th e STATA ivreg2's automatic selection procedure leads to  a wrong find ing of  a statistically 
significant result 16% of the time, instead of 5% (see List Summary Report, (Exhibit DOM/IDN -9), 
paras.  95-98). We note that the results are based on the sample size  of 111 observations 
(July 2006-September  2015), while Dr Chipty considers a larger sample period of 177 observations 
(January  2001-September  2015). It is therefore unclear to what extent Professor  List's results would change if 
the sample size increases, taking into account the fact that according to the STATA developers the formulae 
used in ivreg2 meet the criteria necessary for asymptotic optimality.  
133 We note that Gibson Report (Exhibit DOM -92) presents the main results of an econometric analysis 
of smo king prevalence of adolescents based on the RMSS data. The results suggest that the TPP measures and 
enlarged GHWs had no statistically significant impact on the smoking prevalence of 14 -17 yea r-old smokers of 
manufacturing cigarettes, RYO cigarettes, pipe s and cigars, respectively. We question however the validity of 
these results for some of the same reasons that apply to the econometric analysis of adult smoking prevalence 
reported by IPE, namely the use of the price variable and (quadratic) time trend.  
134 Professor  List proposes a framework to synthesize the diverse analyses, submitted by all the parties, 
on the TPP measures' impact on smoking prevalence and cigarette consumption ( see for instance List Second 
Supplemental Report, (Exhibit DOM/IDN -5), paras. 30-71). According to Professor  List, the probability that the 
TPP measures are working as intended is nearly zero whether just the studies of the experts of the 
Dominican  Republic , Honduras and Indonesia or the universe of the work of all the experts ar e considered . List 
Summary Report, (Exhibit DOM/IDN -9), paras.  167-173. Dr Chipty argues that Professor  List's framework for 
reweighing the evidence is both misleading and misguided because it amounts to nothing but a counting 
exercise that does not account for the interdependence of studies or the biases they may contain . Chipty Third 
Rebuttal Report, (Exhibit AUS -605), paras.  6-8. We acknowledge the usefulness of having a single number 
(Post-Study Probability) determining the likelihood that the TPP  measures have caused a reduction in smoking 
prevalence based on all available econometric studies. We note, however, that Professor  List assigns the same 
weight to all the results prepared by the experts of the Dominican  Republic , Honduras and Indonesia, even 
when Professor  List, himself, questions the validity of some of these results. For instance, Professor  List is not 
 WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  3.2.2   Professor  Klick's econometric results  
112.  Similarly, a review of the econometric results based on the RMSS data reported by 
Professor  Klick leads us to question their robustness.135 In particular,  as demonstrated by Dr 
Chipty, the use of a quadratic trend to capture the downward trend in smoking prevalence leads 
the predicted tobacco price variable to be not significant. As explained above, specifying a n 
excessively  flexible smoking prevalence tren d (i.e. quadratic trend) is likely to overfit the data on 
smoking prevalence and make redundant any other variables, such as individual tobacco control 
policies, that can potentially have also an impact on smoking prevalence. Finally, it is also unclear 
how the standard error and confidence interval of the total effect of the TPP measures , composed 
of the direct estimated impact of the TPP measures  on smoking prevalence obtained in the second 
stage of the procedure and the indirect estimated impact of the TPP measures  on cigarette price 
obtained in the first stage of the procedure through the impact of cigarette price on smoking 
prevalence, were calculated.  
113.  Our review of Professor  Klick's econometric analyses of the TPP measures ' impact on 
smoking prevalence and incidence based on the other datasets leads us also to question his 
results. With the exception of the NSWPHS data, the other datasets used smoking incidence, 
instead of smoking prevalence, by focusing only on smokers and  recent quitters. As a result, data 
on smoking incidence is, by definition, unable to measure the impact of TPP measures  on 
non-smokers. Therefore, the studies on smoking incidence are in our view less relevant than the 
studies focusing on smoking prevalen ce. 
114.  We question the validity of Professor  Klick's difference -in-difference analysis on smoking 
incidence based on the commissioned Roy Morgan Research Survey, because Professor  Klick is 
unable to accurately identify the respondents, who had noticed plain p acks in the pre -period given 
that the question about noticing changes in the packaging was not asked of all respondents. As a 
result, the pre -period is, in our view, not valid. In addition, when Professor  Klick attempts to 
address some of Dr Chipty's criti cs regarding the pre -period, several results find a positive and 
statistically significant TPP measures ' effect on the likelihood an individual reports being a smoker. 
Professor  Klick explains that he does not view these results as suggesting that smoking has surely 
increased under the TPP measures , because of the "multiple comparison problem", which implies 
that when "very many outcomes" are examined, there is a relatively high likelihood that one will 
find statistically significant results even by mere ch ance.136 Yet, Professor  Klick does not explain 
how ten different alternative specifications should be viewed as "very many outcomes".137 
Furthermore, Professor  Klick fails to account for the excise tax increase that took place in 
New Zealand  between Waves 1 an d 2 and Waves 5 and 6 of the commissioned survey, making any 
inference about the reduction in smoking incidence in Australia compared to New Zealand  
questionable.  
115.  We are also not persuaded by Professor  Klick's results based on an  analysis of the NSWPHS 
data on the ground that the nature of the data (i.e. yearly observations) limits the number of 
observations to two post -packaging observations (2013 and 2014), which prevents distinguishing 
between the TPP measures  and tobacco excis e tax increases in 2013 and 2014.   
116.  We question also Professor  Klick's results of the CITTS data, which, as explained above, do 
not analyse smoking prevalence, but smoking status. Unlike Dunlop et al. 2014, who also analyse 
the CITTS data but for a shorter period138, Professor  Klick does not explicitly account for other 
tobacco control policies (besides the TPP measures ), such as the respondents' level of exposure to 
anti-smoking advertising prior to their interview and changes in cigarette costliness. 
Profess or Klick includes an annual time trend, but the variable is actually never statistically 
significant. This result is at odd s with the view shared by all the experts  of the Dominican  Republic , 
                                                                                                                                                  
persuaded that the TPP measures "backfired" as suggested by Professor  Klick's difference -in-difference 
analysis. We are of the view that  a methodology that is unable to make a distinction between robust results 
and biased results is not informative.  
135 See Klick Third Supplemental Rebuttal Report , (Exhibit HND -166), paras.  11-23. 
136 See Klick Rebuttal Report , (Exhibit HND -118), fn 24. 
137 The ten specifications for daily smoker are reported in Table s 3 to 10 in Klick Rebuttal Report , 
(Exhibit HND -118).  The ten specifications for overall smoker s are reported in Table s 3 to 9 and Table  11 in 
Klick Rebuttal Report , (Exhibit HND -118).  
138 Dunlop et al. 2014, (Exhibits AUS -207, HND -132, DOM -199).  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  Honduras and Indonesia , including Professor  Klick, that smoking prevalence is characterized by a 
downward trend. Similarly, several results suggest that the TPP measures  "backfired" and led to 
an increase in the likelihood of a respondent reporting smoking daily and in general. It is unclear 
what such results can be at tributed to, and for that reason we cannot consider these results as 
relevant.  
117.  We also question the validity of Professor  Klick's results on smoking incidence and 
self-reported frequency of smoking based on the NTPPTS data. Professor  Klick chose  not to control 
for the exposure to tobacco -related media activity and tobacco costliness , on the grounds that the 
results do not change and both omitted variables are likely to be endogenous.139 We note that, 
unlike in his analysis of the RMSS data, Professor  Klick d id not attempt to address the potential 
endogeneity of cigarette costliness. Yet, failing to account for other tobacco control policies, in 
particular the December  2013 excise tax hike, might lead to biased results. We further note that 
although Professor  Klick refers to Durkin et al. 2015 and other articles in Tobacco Control , the 
explanatory variables considered by Professor  Klick are different to those in Durkin et al. 2015. For 
instance, Professor  Klick uses a single variable for age, while Durkin et al. 2015 considers a 
dummy variable for each age grou p. The same difference applies to the variable education. In 
addition, unlike the vast majority of the micro -econometric results submitted by the parties, 
Professor  Klick's econometric results suggest that  being a male has no statistically significant 
effect on the probability an individual reported being a (daily or in general) smoker and on the 
self-reported frequency of smoking. This finding contradicts econometric evidence submitted by 
the parties, including Professor  Klick, according to which men are more likely to smoke (daily) than 
women.140 This puzzling result raises questions about the validity of Professor  Klick's model 
specification.141 
118.  In sum, and based on the elements discussed above, we have reservations regarding 
Professor  Klick's methodologies and therefore question his contradictory results suggesting that 
the TPP measures  either had no sta tistically significant impact on smoking prevalence and/or 
smoking incidence or a positive and statistically significant impact on smoking prevalence and/or 
smoking incidence.  
3.2.3   Ajzen et al.'s econometric results  
119.  A careful review of Ajzen et al.'s analysis o f the proportion of daily or weekly smokers 
reported in the NTPPTS  data leads us to conclude that Ajzen et al.'s finding is in line with Scollo 
et al. 2015a, who find that daily cigarette consumption did not change during the first year of 
implementation o f the TPP measures .142 Like the results submitted by Professor  Klick, we note, 
however, that Ajzen et al. surprisingly find that gender has no statistically significant effect on the 
probability that an individual reported being a (daily or weekly) smoker.   
3.2.4   Dr Chipty's econometric results  
120.  Turning to the econometric results analysing smoking prevalence based on the RMSS data 
submitted by Australia's expert, Dr Chipty, we note that a number of concerns that we raised while 
reviewing the complainants' approaches  and results have been addressed by Dr Chipty. In 
particular, Dr Chipty acknowledges and addresses the issue of overfitting associated with a too 
flexible trend. Dr  Chipty's model specification also includes the excise tax increases dummy 
variables and thus avoids the problems of multicollinearity and endogeneity associated with the 
inclusion of the price variable (in combination with a quadratic trend variable). In addition, the use 
of the tax dummies avoids the issue of non -stationarity of the price or ta x level variables.  
                                                
139 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), fn 10.  
140 See NHS Results, (Exhibit AUS -622), p. 30; and Klick Supplemental Rebuttal Report , (Exhibit 
HND-122).  
141 We also note that only three out of the 54  variables are statistically significant in the model for the 
number of adults who are smokers in household . See Klick Supplemental Rebuttal Report , (Exhibit HND -122), 
backup material.  
142 We note that the model spe cification considered by Ajzen et al.  is different from the one developed 
by Professor  Klick. For instance, Ajzen et al.  include dummies variables for two age groups, while 
Professor  Klick includes a single age variable. Ajzen et al.  include also dummies v ariables for different  groups 
of education and socio -economic status, respectively, while Professor  Klick includes a single variable for 
education and another variable for socio -economic status.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  121.  A careful review of Dr Chipty's econometric results further shows that the negative and 
statistically significant impact of the TPP measures  on overall  smoking prevalence is robust to 
alternative specifications, including different TPP s tarting date (October, November  and 
December  2012), the use of an excise tax level variable (instead of the excise tax increase 
dummies) and sample reweighting dummies.143 In addition, the impact of the TPP measures  on 
overall smoking prevalence remains nega tive and statistically significant in most specifications 
when Professor  List's procedure to compute standard errors is implemented.144 
122.  Overall, based on the most recent econometric evidence submitted by Australia, there is 
econometric evidence suggesting  that TPP and enlarged GHWs contributed to the reduction in 
overall smoking prevalence in Australia.145 A similar conclusion applies also to cigar smoking 
prevalence in Australia.  
4  OVERALL  CONCLUSION ON POST -IMPLEMENTATION EVIDE NCE ON SMOKING 
PREVALENCE   
123.  Overall, based on the most recent data available and econometric evidence submitted by the 
parties, we find that:  
a. There is evidence that overall smoking prevalence in Australia continued to decrease 
following the introduction of the TPP measures . 
b. The downward  trend in overall smoking prevalence in Australia appears to have 
accelerated in the post -TPP period.  
c. Although it is impossible to distinguish between the impact of TPP and the impact of 
enlarged GHWs, there is some econometric evidence suggesting that the TPP measures , 
together with the enlarged GHWs implemented at the same time,  contributed to the 
reduction in overall smoking prevalence as well as in cigar smoking prevalence observed 
after their entry into force.  
124.   We note , however, that no post -implementa tion empirical evidence has been presented to 
us on the impact of the TPP measures  on cigarillos smoking prevalence.  
 
                                                
143 See Chipty Third Rebuttal Report, (Exhibit AUS -605), p. 22; and Chipty Second Rebuttal Report, 
(Exhibit AUS -591), p. D2. 
144 See Chipty Second Rebuttal Report, (Exhibit AUS -591), p. 33. 
145 See Chipty Third Rebuttal Report, (Exhibit AUS -605), p p. 22 and 51; and Chipty Second Rebuttal 
Report, (Exhibit AUS -591), p p. 33, D1 and D2.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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APPENDIX  D:  
 
EVIDENCE RELATING TO  TOBACCO PRODUCT SALES AND CONSUMPTIO N  
FOLLOWING THE ENTRY INTO FORCE OF THE TPP MEASURES  
 
1.  Similar to smoking pr evalence, the contribution of the TPP measures  to reducing tobacco 
consumption has been the object of extensive discussion between the parties. A number of expert 
reports are dedicated in part or in whole to this discussion.1 Different databases, statistic al 
analysis and econometric methods have been proposed to determine whether TPP and enlarged 
GHWs have contributed to the reduction in cigarette consumption.  
2.  Most studies use cigarette  sales volumes as a measure of cigarette consumption, with the 
exceptio n of a few other studies2, which use reported cigarettes consumption. Cigarette sales 
volumes are taken from market data, while data on cigarette consumption are reported in various 
surveys. The underlying assumption is that cigarette consumption (i.e. cigarette demand) can be 
proxied by cigarette sales (i.e. supply of cigarettes ). We note that none of the parties questioned 
this assumption. Where relevant, this Appendix will distinguish between cigarette consumption and 
cigarette sales.  
3.  As in respect of t he analysis of smoking prevalence, one of the only points of agreement among 
the parties is that the empirical econometric evidence on cigarette consumption submitted does 
not distinguish between the impact of TPP and the impact of enlarged GHW s on cigarette sales or 
consumption, because both measures were implemented at the exact same time.3 Unless specified 
otherwise, the impact of TPP in this Appendix therefore refers to the impact of TPP and enlarged 
GHWs. 
4.  The Dominican  Republic , Honduras and Ind onesia argue that all their experts' empirical 
statistical and econometric studies show t hat the TPP measures  failed to reduce cigarette sales 
volumes or consumption.4 The complainants even suggested initially that TPP measures  
"backfired" by increasing to bacco sales.5 This argument was  however  not developed  later in the 
proceeding s.  
5.  Notwithstanding its conten tion that it is too early to investigate the impact of TPP on tobacco 
consumption6, Australia submitted expert reports estimating the TPP measures ' impact on 
                                                
1 See Chipty Report, (Exhibit AUS -17); Chipty Supplementary Report, (Exhibit AUS -511); Chipty 
Rebuttal Report , (Exhibit AUS -535) (SCI) ; Chipty Surrebuttal Report, (Exhibit AUS -586); Chipty Second 
Rebuttal Report, (Exhibit AUS -591); Chipty Third  Rebuttal Report, (Exhibit AUS -605); List Report, (Exhibit 
DOM/IDN -1); List Rebuttal Report, (Exhibit DOM/IDN -3); List Second Supplemental Report, (Exhibit 
DOM/IDN -5); List Third Supplemental Report, (Exhibit DOM/IDN -7); List Summary Report, (Exhibit 
DOM/I DN-9); IPE Report , (Exhibit DOM -100); IPE Updated Report , (Exhibit DOM -303); IPE Second Updated 
Report , (Exhibit DOM -361); IPE Third Updated Report , (Exhibit DOM -375); IPE Summary Report , (Exhibit 
DOM-379); Klick Report , (Exhibit UKR -5); Klick Rebuttal Rep ort, (Exhibit HND -118); Klick Supplemental 
Rebuttal Report , (Exhibit HND -122); Klick Second Supplemental Rebuttal Report , (Exhibit HND -165); Klick 
Third Supplemental R ebuttal Report, (Exhibit HND -166); Klick Fourth Supplemental Rebuttal Report , (Exhibit 
HND-169); Ajzen et al. Data Report, (Exhibit DOM/IDN -2); and Ajzen et al. Second Data Report, (Exhibit 
DOM/IDN -4). 
2 See Klick Report , (Exhibit UKR -5); Klick Supplemental Rebuttal Report , (Exhibit HND -122); Klick 
Second Supplemental Rebuttal Report , (Exhibit  HND-165), Ajzen et al. Data Report, (Exhibit DOM/IDN -2); and 
Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4). 
3 See Australia's first written submission, para. 518; Dominican  Republic 's response to Panel question 
No. 8, para. 61; Honduras's responses to Panel question No. 8; and Indonesia's response to Panel question 
No. 8, para. 8. 
4 See Dominican  Republic 's comments on Australia's response to Panel question  No. 196, 
paras.  681-682; Honduras's second written submission, paras.  56-60; Indones ia's second written submission, 
para. 192; and Cuba's second written submission, paras.  276-277.  
5 See Indonesia's first written submission, para. 412; Cuba's first written submission, para. 163; 
Dominican  Republic 's first written submission, para. 523; a nd Honduras's first written submission, para. 395. 
6 See Australia's first written submission, para. 670. Australia considers  that, in the early stages of 
introduction of the measures, the most appropriate way to discern their effects was to rely on experi ments and 
surveys which concern drivers of choice, attitudes and, ultimately, the elicitation of behavioural intentions. 
Australia's first written submission, para. 147.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  cigarette sales, in response to the submissions  of the Dominican  Republic , Honduras and 
Indonesia . Australia contends that once the most appropriate dataset available (i.e. 
In-Market -Sales data) are used and the flaws of the econometric models put forward by the 
experts  of the Dominican  Republic , Honduras and Indonesia  are corrected, the econometric results 
show that TPP measures  have already contributed to their objectives by reducing cigarette sales 
volumes.7 
6.  Similar ly to the discussion on smo king prevalence, we note that the approaches  presented  by 
the parties to analyse cigarette sales volumes and consumption evolved over the course of the 
proceedings . Overall, t hese address  three main aspects , reviewed below  in sections 1 to 3 : 
 First, the pa rties have submitted economic figures and descriptive statistics analyses 
aimed at determining whether cigarette sales or consumption have decreased following 
the implementation of the TPP measures ;8 
 Second, Australia, the Dominican  Republic  and Indonesia have submitted statistical 
analyses to determine whether there was a break in the trend in cigarette sales following 
the implementation of the TPP measures , and in particular, whether the reduction of 
cigarette volumes sales has accelerated in the post -TPP period ; 
 Finally, Australia, the Dominican  Republic , Honduras and Indonesia have submitted 
econometric analysis to determine whether the TPP measures  have contributed to a 
reduction of cigarette sales or consumption by isolating and quantifying the different 
factors that can explain the evolution of cigarette sales or consumption.  
7.  The parties also presented and discussed a graphical and descriptive analysis of  cigar trade 
data. This is addressed  below in Section 4.  
1  WHETHER CIGARETTE SALES VOLUMES DECREA SED FOLLOWING THE 
IMPLEMENTATION OF TH E TPP MEASURES  
8.  Different market data sources tracking cigarette sales volumes in Australia have been 
submitted by Australia, the Dominican  Republic , Honduras and  Indonesia. We first present these 
datasets, before providing an overall analysis on the basis of these data.  
1.1  Main datasets and arguments  
1.1.1   In-Market -Sales/Exchange of Sales  
9.  Managed by InfoView Technologies, In -Market -Sales (IMS), also known as Exchange of Sales 
(EOS), is a dataset comprising monthly sales volume data at the Stock -Keeping Unit -level for 
factory -made cigarettes (FMC) and fine -cut tobacco covering the period from January  2000 
through September  2015. The data comprise monthly sales from manufacturers to wholesalers 
and retailers, as reported by the three largest tobacco companies in Australia - British American 
Tobacco Australia (BATA), Philip Morris Limited, and Imperial Tobacco Australia Limite d 
(ITA) - which collectively account for 99% of sales in the Australian market. The total tobacco 
sales volumes include  FMC and fine -cut tobacco converted to cigarette stick equivalents (CSE).  
10.  IPE notes, as depicted in Figure D.1 , that cigarette sales volumes based on the IMS/EOS 
data, as a proxy for cigarette consumption, are marked by strong seasonal patterns, with sales 
spikes at the end of each quart er (especially in December and June), followed by a trough 
immediately thereafter. IPE further argues that there is an observable overall downward trend in 
the total volume of cigarette sticks (FMC and CSE) sold in Australia over the period 2000 -2013, as 
                                                
7 See Australia's response to Panel question No. 196, para. 214. 
8 We note that the p arties also submitted data on the value and volume of Australian imports of 
tobacco, including cigar s and cigarillo s. See HoustonKemp Report, (Exhibit AUS -19) (SCI) ; 
Dominican  Republic 's response to Panel question No. 5.; Honduras's response to Panel question No. 5; Cuba's 
response to Panel question No. 5; and Indonesia's response to Panel question No. 5. These data are not 
reviewed here because they were not used in any of the econometric reports submitted by the parti es. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-3 - 
 
  depicted in Figure D.2 .9 IPE contends that the downward trend accelerated after the introduction 
of the 2010 excise tax increase. IPE further submits  that the data reveal an increase in the total 
volume of cigarett e sticks sold in 2013.  
Figure D. 1: Monthly Cigarette Sales Volumes Based on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax increases . The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  IPE Report, (Exhibit DOM -100), p. 67. 
 
                                                
9 See IPE Report , (Exhibit DOM -100), p p. 65-68. 
00.511.522.53
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Mar 2014Sales volume of FMC and CSE
(billions sticks per month)
YearTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-4 - 
 
  Figure D. 2: Annual Cigarette Sales Volumes Based on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick.  
Source :  IPE Report, (Exhibit DOM -100), p. 66. 
 
11.  Professor  Klick argues that while sales data are not equivalent to smoking incidence, market 
data are valuable because they do not suffer from the potential inaccuracies associated with 
self-reported survey responses, and captures even those smokers who would not be included in 
the survey sample such as underage smokers.10 Professor  Klick further submits  that there is some 
doubt regarding whether the TPP measures  are associated with a declin e in cigarette flows given 
that despite the steady decline in cigarette sales flows observed in the pre -TPP period, cigarette 
flows increased by 0.3% between 2012 and 2013, as depicted in Figure D.3 . In comparison, 
Professor  Klick argues that although the pre -December  2012 decline in average monthly cigarette 
sales was just as striking in New Zealand  as in Australia, the decline in cigarette sales continued 
into 2013 in New Zealand , unlike in Australia.11 In addition, Professor  Klick contends that, unlike 
Dr Chipty's claim of positive strategic inventory effects on sales in anticipation of the 
December  2013 tax increase in Australia , the decline in cigarette wholesale sales in Australia 
appears to have diminished with the introduction of the TPP measures  unlike in New Zealand .12 
                                                
10 See Klick Report , (Exhibit UKR -5), p. 12. 
11 See Klick Report , (Exhibit UKR -5), p. 16. 
12 See Klick Rebuttal Report , (Exhibit HND -118), paras.  66-68. 
26.4
25.425.9 26.1 26.0
25.124.8 24.6 24.7 24.9
23.0
21.8
21.0 21.1
1.6 1.7 1.9 1.9 2.0 2.0 2.0 2.0 2.1 2.2 2.2 2.2 2.3 2.3
051015202530
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013Sticks in billion per year
Sales volume of factory-made cigarettes sticks and cigarette stick equivalents from fine-cut
Sales volume of cigarette stick equivalents from fine-cutWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-5 - 
 
  Figure D. 3: Average Monthly Cigarette Sales Volumes Based on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick.  
Source :  Klick Report, (Exhibit UKR -5), pp. 17-18. 
 
12.  Unlike IPE and Professor  Klick, Professor  List considers the evolution of cigarette sales per 
capita, as shown in Figure D.4 , and argues that smoking consumption is characterized by a 
general downward trend in smoking consumption.13  
                                                
13 See List Report, (Exhibit DOM/IDN -1), p. 27; List Re buttal Report, (Exhibit DOM/IDN -3), p. 12; List 
Second Supplemental Report, (Exhibit DOM/IDN -5), p. 8; and List Third Supplemental Report, (Exhibit 
DOM/IDN -7), p. 35. We note that IPE presents also a graphical analysis of cigarette sales per capita in its 
second report, without updating it in its subsequent reports . IPE Updated Report , (Exhibit DOM -303), p. 57. 
2075
1915
1815
17361751 1756
273
261
237
220226
213
100200300400500
100012001400160018002000
2009 2010 2011 2012
(excl. Dec.)2012
(incl. Dec.)2013
Millions of sticks in New ZealandMillions of sticks in Australia
Australia's average monthly flows by year New Zealand's average monthly flows by yearWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  Figure D. 4: Per Capita Monthly Cigarette Sales Volumes Based on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  List Rebuttal Report, (Exhibit DOM/IDN -3), p. 12; and List Third Supplemental Report, (Exhibit 
DOM/IDN -7), p. 35. 
 
 
13.  Australia's expert Dr  Chipty argues that IPE's and Professor  Klick's graphical analysis is 
misleading and fails to account for strategic inventory management that likely took place on the 
eve of the December  2013 tax increase in the post -TPP period. Dr  Chipty is of the view that the 
presence of the anticipated tax r esponse at the end of December  2013 coupled with the fact that 
the TPP measures  went into effect in October  2012 makes the comparison of sales volume 
between 2012 and 2013 not meaningful. Dr  Chipty contends that a comparison of the year 
beginning October  before and after TPP is analytically sounder and shows a reduction in cigarettes 
sales volumes.14 
1.1.2   Nielsen Retail Sales (Australia and New Zealand ) 
14.  The Nielsen data reports actual sales of cigarettes, including "roll your own" equivalents, 
through all retaile rs in Australia and New Zealand 's markets except specialty tobacconist shops in 
Australia from February  2011 through December  2013. Professor  Klick also included in his analysis 
Nielsen processed data on the specialty tobacconist channel, which is collecte d by BATA and not 
available from any other source. According to Professor  Klick, the inclusion of this channel is 
preferred as the specialty tobacconist channel in Australia accounts for about 25% of the 
Australian market. The Nielsen data for Australia ar e available at monthly intervals, while they are 
available for New Zealand  on a four week rolling basis.15  
                                                
14 See Chipty Report, (Exhibit AUS -17), paras.  62-66. 
15 The four-week interval of the Nielsen data for New Zealand  does not align with months. 
Profes sor Klick notes that: "[t]o align the periods between the two countries, I allocated the New Zealand  4 
week periods to the months in which they were collected, using linear interpolation to account for periods that 
spanned two months" . See Klick Report , (Exhibit UKR -5), fn 35. 
406080100120140160
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Apr 2015Per capita sales volume of FMC and CSE
(per month)
YearTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-7 - 
 
  15.  Professor  Klick argues that there was a decline in sales post -TPP in Australia. Specifically, 
average monthly sales in Australia before TPP (1,720  million) fell to 1,719  million for a reduction of 
0.07%. However this reduction in cigarette sales is lower after the introduction of the 
TPP measures  than the drop of almost 6% in New Zealand  during the same period and without any 
TPP, as shown in Figure D.5 .16 
Figure D. 5: Cigarette Sales Volumes Based on Nielsen Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dashed line indicates  the 
introduction of TPP and enlarged GHWs.  
Source :  Klick Report, (Exhibit UKR -5), pp. 6 and 15.  
 
16.  Australia's expert Dr  Chipty is of the view that Professor  Klick's analysis is uninformative. She 
argues that even in the pre -TPP period, cigarette sales volume is trending down faster than in 
Australia. In her view, New Zealand  appears to be trending differently from Australia before and 
after the introduction of the TPP measures .17  
1.1.3   Aztec Scanner Retail Sales  
17.  The Aztec scanner data tracks sales on a weekly basis at the store - and stock -keeping 
unit-level, recording detailed product information on brand and variant, quantity, and price per 
package for factory -made cigarettes and fine -cut tobacco sold across Australia. The Aztec scanner 
dataset covers t he period 27 July 2008 through 27 September  2015.18 
18.  The experts of the Dominican  Republic , Honduras and Indon esia do not present a graphical 
analysis using the Aztec data. Instead, the y use the Aztec scanner data to estimate 
econometrically the TPP measures ' impact on (per capita) cigarette sales volumes, which will be 
                                                
16 Klick Report , (Exhibit UKR -5), p.15.  
17 See Chipty Report, (Exhibit AUS -17), paras.  45-48. 
18 As discussed below, Professor  Klick combines the Nielsen and Aztec data without the Convenience 
Independent sample when Nielsen data are missing.  
5.35.355.45.455.55.55
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Logarithm of sales volume of FMC and CSE in 
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Australia New ZealandTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  reviewed in detail below. In that context, Professor  List reports the evolution of per capita sales 
based on the Aztec data, as depicted in Figure D.6.19  
Figure D. 6: Per Capita Monthly Cigarette Sales Volumes Based on Aztec Scanner Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  List Rebuttal Report , (Exhibit DOM/IDN -3), p. 18. 
 
19.  Australia's expert, Dr Chipty, notes that the Aztec scanner data covers only a portion of total 
retail sales in Australia, as evident in a side -by-side comparison of the Aztec, Nielsen and IMS/EOS 
data, as depicted in Figure D.7 . Dr Chipty further argues that the (econometric) analysis of the 
Aztec scanner data is misleading because the share of total cigarette sales covered by the Aztec 
data has grown over time. Dr  Chipty submits  that these changes in the underlying data interfere 
with the ability to use them meaningfully to study changes in cigarette sales before and after the 
introduction of the TPP measures .20 
20.  Professor  Klick disagrees with Dr  Chipty and submits  that the Aztec dataset coverage of the 
retail market h as stayed substantially the same over the sample period, while noting that there are 
changes as some retail outlets close and others open (including within the convenience 
independent market segment). Professor  Klick argues that Dr  Chipty did not present d irect 
evidence demonstrating that the coverage of the Aztec sales data relative to total sales is growing 
over time. Professor  Klick further rejects Dr  Chipty 's indirect evidence of such a change, which 
can, according to Professor  Klick, be explained by the strategic inventory management that 
Dr Chipty identified.21 
 
                                                
19 See List Rebuttal Report, (Exhibit DOM/IDN -3), p. 18. We note, however, that unlike IPE, 
Professor  List does not include the sales of RYO tobacco in his analysis of the Aztec data.  
20 See Chipty Report, (Exhibit AUS -17), paras.  55-61. 
21 See Klick Third Supplemental Rebuttal Report , (Exhibit HND -166), paras.  33-34; and Klick Fourth 
Supplemental Rebuttal Report , (Exhibit HND -169), paras.  6-8 fn 4. 
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  Figure D. 7: Quarterly Cigarette Sales Volume based on IMS/EOS, Nielsen and Aztec Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The verti cal dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  Chipty Report , (Exhibit AUS -17), p. 33. 
 
1.1.4   Australian Bureau of Statistics Household Expenditure  
21.  Australia's Post -Implementati on Review Tobacco Plain Packaging 2016 reports the evolution of 
estimated household expenditure on tobacco and cigarettes released by the Australian Bureau of 
Statistics (ABS), as shown in Figure D.8 . According to the ABS, although there was a rise in 
estimated consumption expenditure in the June 2013 and September  2013 quarters compared 
with the previous quarters, estimated consumption expenditure on tobacco and cigarettes has 
been declining in the March  2013 quarter and in all other quarters since implementation.22  
 
                                                
22 See Tobacco Plain Packaging PIR , (Exhibit AUS -624), paras.  132-134. The Tobacco Plain Packaging 
PIR also refers to a 2014 Euromonitor Report on Tobacco, which shows a continued decline in tobacco sales, 
although limited information about the source s of the data and methodological processes used is provided in 
the report . Ibid. para. 135. Similarly, the Tobacco Plain Packaging PIR  refers to the Australian Taxation Office 
and Customs clearance data showing a reduction in tobacco clearances in stick eq uivalent terms (including 
excise and customs duty) between calendar year 2012 and calendar year 2014.  
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  Figure D. 8: Household  Expenditure on Tobacco and Cigarettes based on ABS Data  
 
Note:  The vertical dotted lines indicate excise tax hikes. The vertical dashed line indicates the introduction 
of TPP and enlarged GHWs.  
Source :  Tobacco Plain Packaging PIR, (Exhibit AUS -624), p. 45. 
 
1.2  Analysis by the Panel  
22.  As with smoking prevalence, we acknowledge the importance of analysing the trends in 
cigarette sales with the most recent available data. We further recognize, as pointed out by IPE, 
that there is no perfect dataset for a sales  analysis in terms of market coverage, frequency 
(weekly, monthly or annually) and period covered.23  
23.  The IMS/EOS data cover sales from manufacturers to wholesalers and retailers, while both 
Aztec and Nielsen data cover sales from retailers to consumers. Si milarly, both Aztec and Nielsen 
data are only available for February  2011 to December  2013, and 27  July 2008 to 27  
September  2015, respectively, while the IMS/EOS data cover the larger sample period, from 
January  2000 to September  2015. The Nielsen data an d the IMS/EOS data cover, respectively, 
almost 100 % and 99% of the Australian market, while the Aztec data cover 67% of the Australian 
market.24 We also note that the experts of the Dominican  Republic , Honduras and Indonesia used 
different definition s of cigarette sales, namely level of cigarette sales and per capita cigarette 
sales. We further note that survey datasets on cigarette consumption have been used by some of 
the experts of the Dominican  Republic , Honduras and Indonesia to analyse the impact of the 
TPP measures . These will be reviewed in detail when discussing the econometric analysis.  
                                                
23 See IPE Updated Report , (Exhibit DOM -303), para. 137. 
24 See IPE Summary Report , (Exhibit DOM -379), paras.  131-133. 
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  Figure D. 9: Monthly Cigarette Sales Volumes Based on IMS/EOS, Nielsen and Aztec Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  IPE Summary Report, (Exhibit DOM -379), back -up material.  
 
24.  We note, at the outset, that neither IPE nor Professor  Klick updated their graphical analysis of 
cigarette sales volume with more recent data  in the course of the proceedings . The 
Dominican  Republic , Honduras and Indonesia no longer refer red to their initi al assertion that 
cigarette sales volumes increased in the post -TPP period. After a careful review of the most recent 
available IMS/EOS and Aztec datasets, we note that despite fluctuating, cigarette sales volumes 
follow a downward trend in the period foll owing the introduction of the TPP measures , as depicted 
in Figure D.9 .25 However, the downward trend is more pronounced in the IMS/EOS data than in 
the Aztec scanner data. As pointed out by Australia and acknowledged by Professor  List and IPE26, 
the share of total cigarette sales covered by the Aztec data has grown over time, which would 
explain, at least partially, why the downward trend is less pronounced in the Aztec data.27  
                                                
25 The weekly Aztec data were aggregated to monthly data by assuming that each weekly cigarette 
quantity can be evenly split for each day of the week.  
26 See List Rebuttal Report, (Exhibit DOM/IDN -3), fn 15; and IPE Third Updated Report , (Exhibit 
DOM-375), para. 171. 
27 We note that Professor  Klick is the only one of the complainants' expert s to reject the claim that the 
Aztec dataset's market coverage has increased. Professor  Klick argues that the upward trend of the ratio 
between the retail and wholesale data  is the result of strategic inventory management . See Klick Fourth 
Supplemental Rebuttal Report , (Exhibit HND - 169), paras . 33-34. Dr Chipty disagrees with Professor  Klick's 
claim and argues that strategic inventory management cannot explain the upward tre nd of the ratio beyond 
the 2012 and 2014 excise tax increase . See Chipty Third Rebuttal Report, (Exhibit AUS -605), fn 148. We note 
that Professor  Klick does not provide in his reports any evidence that would suggest that the retail market 
coverage has stay ed substantially the same over the sample period. In fact, a review of the underlying Aztec 
data reporting the associated store count for each sales channel shows that the number of stores covered by 
the data increased from 6,605 in January  2012 to 9,437 c overed stores in September  2015. See Klick Fourth 
Supplemental Rebuttal Report , (Exhibit HND -169), back up material. We also note that a comparison of the 
Aztec data to tax statistics suggests that the market share covered by the Aztec has increased over t ime. The 
same conclusion applies with a comparison of the Aztec data to the IMS/EOS data . See IPE Report , (Exhibit 
DOM-100), p p. 101-103. 
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  25.  We will review in the next subsections all the econometric evidence submitted to us based on 
the IMS/EOS, Nielsen and Aztec  data. However, we consider the IMS/EOS data to be the most 
appropriate available market data for ana lysing the impact of the TPP measures  on cigarette sales, 
for a number of reasons. First, the IMS/EOS data are available for the longest period, which is 
more likely to yield more accurate estimates. Second, although the IMS/EOS data do not cover 
sales fro m retailers to consumers, the correlation between the IMS/EOS data and the Nielsen data, 
which  do cover sales from retailers to consumers, is relatively high, with a correlation coefficient of 
0.58, as shown in Figure D.10.28 The correlation coefficient is even higher when the unit of 
analysis is quarter ly sales, with a correlation coefficient equal to 0.85.29  
Figure D. 10: Inde xes of Cigarette Sales Volumes Based on IMS/EOS, Nielsen and Aztec 
Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TPP  and enlarged GHWs. Each data 
are normalized to its respective cigarette sales in January  2011.  
Source :  IPE Summary Report, (Exhibit DOM -379), back -up material.  
 
                                                
28 According to the English Oxford Dictionary, the correlation coefficient is a number between -1 and 1 
calculated so a s to represent the linear interdependence of two variables . Shorter Oxford English Dictionary , 
5th edn, W.R. Trumble and A. Stevenson (eds.) (Oxford University Press, 2002), Vol. 1, p. 524.  
29 We note that Professor  Klick submits that for the March  2012-December  2013 period the correlation 
coefficient between the Nielsen data and the Aztec data is 0.985 if the Convenience Independent sample is 
included in the Nielsen data, and 0.999 if the Convenience Independent sample is omitted . See Klick 
Supplemental Rebuttal Report , (Exhibit HND -122), para. 123. We note, however, that the monthly Aztec data 
considered by Professor  Klick differs significantly from the monthly cigarette sales constructed from the weekly 
Aztec data considered by IPE, Professor  List, and Dr Chipty. This explains why the correlation coefficient 
between the Nielsen data (including the Convenience Independent sample) and the Aztec data we obtained for 
the March  2012-December  2013 period is different and equal to 0.929. In addition, we note th at the correlation 
coefficient between the Nielsen data and the Aztec data for the February  2011-December  2013 period is 
smaller and equal to 0.84. In other words, the Nielsen data and the Aztec data are less correlated for the 
February  2011-February  2012 period than for the March  2012-December  2013 period, which is in line with the 
Aztec data's growing market coverage (given that the Nielsen data's market coverage is close to 100 %). The 
correlation coefficient is also smaller (0.756) when the data are aggr egated at the quarter level for the 
February  2011-December  2013 period.  
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26.  Although the Nielsen data cover sales from retailers to consumers, which represent a closer 
measure to cigarette consumption than the IMS/EOs data, they are only available for a short 
period, with only 13  post-implementation observations, which could make it more difficult to 
estimate accurately any impact on sales volumes. Similarly, although th e Aztec data have the 
advantage of covering sales from retailers to consumers, the share of total cigarette sales covered 
by the Aztec data has grown over time , unlike the general downward trend of cigarette sales in the 
Australian market , which  could make  it more difficult to identify the impact of any factors from the 
increasing market coverage.  
27.  The evolution of per capita cigarette sales volumes, as depicted in Figure D.11 , leads us to  
the same conclusion, namely that the evidence before us suggests that per capita cigarette sales 
have, on average, continued to decrease after the introduction of the TPP measure s. This finding is 
in line with the evolution of house expenditure on tobacco and cigarettes. Evidence before us on 
the extent  to which the downward trend in cigarette sales has accelerated or not in the post -TPP 
period is reviewed next.  
Figure D. 11: Per  Capita Cigarette Sales Volumes Based on IMS/EOS, Nielsen and Aztec 
Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  IPE Summary Report, (Exhibit DOM -379), back -up material.  
 
 
2  WHETHER THE REDUCTIO N OF CIGARETT E SALES VOLUMES ACCELE RATED AFTER THE 
ENTRY INTO FORCE OF THE TPP MEASURES  
28.  Having determined that the most recent market data show continuing declines in cigarette 
sales volumes in the period following the introduction of the TPP measures , we turn to wheth er 
there was a shift in cigarette sales volumes in the post -TPP implementation period. Instead of 
assessing directly the impact of the TPP measures  on cigarette sales, which we review next, the 
Dominican  Republic 's and Indonesia's expert Professor  List inv estigated whether there was a 
change in cigarette sales in the post -TPP implementation period. The underlying assumption is that 
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  if cigarette sales follow the same pre -existing pattern after the introduction of the TPP measures , 
then it follows that the TPP measures  failed to reduce cigarette sales.  
29.  Professor  List investigates this question using two distinct datasets: the IMS/EOS data and the 
Aztec scanner data.30 We describe Professor  List's results and Australia's criticisms before 
presenting our analysis  of this evidence . 
2.1  Main datasets and arguments  
2.1.1   In-Market -Sales/Exchange of Sales  
30.  Professor  List presents an event study analysing whether there has been a shift in the 
evolution of per capita cigarette sales following the introduction of TPP and enlarged GHWs. 
Specifically, a seasonally adjusted Autoregressive Integrated Moving Average (ARIMA) model and 
a dynamic model of per capita cigarette wholesales volumes are estimated controlling for per 
capita cigarette wholesales during the previous month, price during the previous month, a linear 
time trend and the 2006 GHWs.31 The most recent analysis covers the period from February  2002 
to June 2015.  
31.  Overall, Professor  List concludes that according to both mod els, there is no statistical 
difference between the observed per capita cigarette sales volumes and the estimated 
counterfactual per capita cigarette sales volumes, implying that the post -implementation 
downward trend in cigarette sales did not shift.32 
32.  In response, Australia's expert, Dr Chipty, argues that Professor  List's event study is 
fundamentally flawed. Dr Chipty contends that the estimates of Professor  List's first -stage 
consumption model are highly imprecise and many of the explanatory variables ar e statistically 
insignificant, sometimes with the wrong estimated coefficient sign, making the post -TPP 
projections unreliable. In her view, the estimated moving average parameters of the seasonal 
ARIMA model indicate that the model is not specified correctly and most likely over -differenced. 
According to Dr Chipty, this over -differencing would likely lead to large forecasting errors when the 
model parameters are used to predict consumption levels during the post -period. Dr Chipty further 
argues that Professor  List's analysis of the 2010 excise tax increase does not bolster confidence in 
Professor  List's conclusion that there is no shift in the downward trend in cigarette sales, because 
the result of the ordinary least square (OLS) model, intended to c orroborate the result for the 
TPP measures , predicts higher consumption with taxes than without.33  
33.  Dr Chipty also submits  that by controlling for prices in the pre -period model and using actual 
prices in the post -period forecasting, Professor  List's event study fails to account for the effect of 
tobacco control policies that work through price.34 According to Dr Chipty, failure to control for the 
2010 excise tax increase has the effect of crediting the trend with the effect of the tax increase. In 
her view, Professor  List implicitly assumes that the effect of the 2010 tax increase will continue in 
perpetuity.35 Dr Chipty reconsiders the dynamic model by controlling for the 2010 excise tax 
                                                
30 We note that Professor  List's event study is a trend -projection analysis that does not estimate directly 
the impact of the TPP measures, but rather assess es whether there is a differ ence between the counterfactual 
per capita cigarette sales in the absence of the TPP measures and the actual per capita cigarette sales. That is 
why we have decided to discuss Professor  List's event study under the subsection addressing whether there 
was a  change in (per capita) cigarette sales trend in the post -implementation period.  
31 An event analysis consists of (1) estimating the model of per capita cigarette sales during the pre -TPP 
period; (2)  forecasting the per capita cigarette sales that would hav e been prevailed in the absence of the TPP 
measures using the estimated model's parameters in the post -implementation period; and (3)  determining 
whether the difference between the observed per capital cigarette sales volumes and the estimated 
counterfactu al cigarette sales volumes is statistically different from zero . See List Report, (Exhibit DOM/IDN -1), 
paras.  123-132. 
32 See List Report, (Exhibit DOM/IDN -1), paras.  133-134; List Rebuttal Report, (Exhibit DOM/IDN -3), 
paras.  65-68; List Second Supplemental  Report, (Exhibit DOM/IDN -5), paras.  26, 72, 74 and 144 -154; and List 
Third Supplemental Report, (Exhibit DOM/IDN -7), paras.  26-28 and 56 -61. 
33 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  37-44; and Chipty Surrebuttal Report, 
(Exhibit AUS -586), paras.  30-33. 
34 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  33-44; and Chipty Surrebuttal Report, 
(Exhibit AUS -586), paras.  30-33. 
35 Chipty Third Rebuttal Report, (Exhibit AUS -605), paras.  61—67. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-15 - 
 
  increase and finds a statistically significant shift in the post -impleme ntation downward trend in 
cigarette sales. However, controlling for other problems, namely correcting the definition of the 
GHWs variable (from March  2006 onwards instead of between March  2006 and November  2012), 
accounting for all excise tax changes, and strategic inventory management associated with the tax 
changes, Dr Chipty concludes that the shift of the post -implementation downward trend in 
cigarette sales is economically significant (similar in magnitude to the estimates obtained in the 
preferred bef ore-after consumption model) but not statistically significant. More generally, 
Dr Chipty contends that Professor  List's conclusions regarding the statistical significance of the 
TPP measures ' effect are unreliable because Professor  List does not calculate  any standard error 
associated with the estimated policy effect in the first stage. Dr Chipty submits  that a before -after 
analysis, as discussed below, is preferable to Professor  List's event study analysis for determining 
statistical significance.36 
34.  Profes sor List counters that Dr Chipty does very little to engage with the event study as it 
pertains to TPP nor with the results reported but tears down an analysis of Australia's 2010  tax 
policy he never conducted. Professor  List submits  that when properly don e, an event study 
identifies a negative and statistically significant effect on cigarette consumption of Australia 's 
2010 tax increase. According to Professor  List, Dr Chipty confuses the interpretation of variables in 
a predictive model with the interpret ation of explanatory variables in a causal model. Unlike 
Dr Chipty's claim that the over -differencing in the ARIMA model would likely lead to large 
forecasting errors, Professor  List contends that the OLS model of cigarette sales does not suffer 
from this over-differencing problem. Professor  List submits  that although the predicted values are 
treated as if they were true, the hypothesis testing would actually be much wider if the uncertainty 
related to the predictors w ere taken into account. Professor  List concludes that when an event 
study on the TPP measures  finds no effect on cigarette sales, it is not because the data are too 
underpowered to detect changes induced by effective tobacco control policies, or because specific 
control variables have been  chosen, but because the TPP measures  are not working.37 
2.1.2   Aztec Scanner Retail Sales  
35.  Professor  List performs the same event  study using the Aztec scanner data. A seasonally 
adjusted ARIMA model and a dynamic model of per capita cigarette sales volumes are es timated 
controlling for per capita cigarette consumption during the previous month, price during the 
previous month, a linear time trend and the 2006 GHWs. The analysis covers the period from 
July 2008 to May 2015.  
36.  Professor  List concludes that there is no  statistical difference between observed per capita 
cigarette sales volumes and the estimated counterfactual per capita cigarette sales volumes, 
implying that the post -implementation downward trend in cigarette sales did not shift. However, 
one of Professo r List's specifications finds an upward and statistically significant trend in per capita 
cigarette sales, suggesting that per capital cigarette sales have increased in the post -TPP period. 
Professor  List explains that this result is reported for the sake of comprehensiveness but he does 
not place much emphasis on the finding, given that the Aztec market share is increasing over the 
relevant time period. 38 
37.  Australia's expert Dr Chipty submits  that the Aztec data should be disregarded because the y 
are confou nded by the growing coverage of the retail outlets included in the data. Dr Chipty 
submits  that given th is problem with the Aztec data, the analyses built on these data are also 
problematic.39 
38.  Professor  List counters that Dr Chipty favours discarding the Az tec dataset altogether without 
making any attempt to apply simple empirical tools available to deal with the alleged problem.40 In 
                                                
36 See Chipty Rebuttal Report , (Exhibit  AUS-535) (SCI), paras.  33-44; Chipty Surrebuttal Report, 
(Exhibit AUS -586), paras.  30-33; Chipty Second Rebuttal Report, (Exhibit AUS -591), paras.  39-42, 
Appendix  C; and Chipty Third Rebuttal Report, (Exhibit AUS -605), paras.  61-68. 
37 See List Second Supp lemental Report, (Exhibit DOM/IDN -5), paras.  151-154; and List Third 
Supplemental Report, (Exhibit DOM/IDN -7), paras.  26-28 and 56 -61. 
38 See List Third Supplemental Report, (Exhibit DOM/IDN -7), paras.  56-61 and 80.  
39 See Chipty Surrebuttal Report, (Exhibit AUS -586), para. 31. 
40 See List Summary Report, (Exhibit DOM/IDN -9), para. 107.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  particular, Professor  List referred to IPE 's propos al to benchmark quarterly Aztec data to IMS/EOS 
data in order to adjust for a growing market coverage of Aztec data.41  
2.2  Analysis by the Panel  
39.  As explained in our analysis of the contribution of the TPP measures  on smoking prevalence, 
we assess the evidence b efore us on the basis that our task is not to present a unified econometric 
analysis of this question but to assess the robustness of the results submitted by the parties. In 
addition, our conclusions  in this respect  relate exclusively to the data (includi ng the sample period)  
and econometric results submitted by the parties  in these proceedings , and are not intended to be 
generalized to other datasets or econometric studies.  
2.2.1   Professor  List's reports  
40.  After a careful review of the results of Professor  List's event study of the TPP measures ' 
impact on per capita cigarette sales, we question the validity of his results for a number of 
reasons, some of which are specific to one of the models considered by Professor  List.  
41.  We note that in most estimations of the ARIMA model for the pre -TPP period based on the 
IMS/EOS data that are used to forecast the value of per capita cigarette sale in the 
post-implementation period, none of the explanatory variables, including the constant, is 
statistically significant, beside s the moving averages parameters.42 In our view, the lack of 
statistically significant variables is surprising , given the relatively small number of explanatory 
variables included in the ARIMA model. We further note  that, as pointed out by Dr  Chipty, the 
estimated moving average parameters are not statistically different from -1, which would likely 
lead to large forecasting errors. This is, in our view, problematic because Professor  List's approach 
relies on the post -implementation forecasting errors to dete rmine whether there was a statistically 
significant change in the downward trend in per capita cigarette sales. We note that Professor  List 
recognized the issue of over -differencing but failed to address it or propose a solution. Instead, 
Professor  List suggests considering the dynamic model, which, according to him, does not suffer 
from this over -differencing problem.43  
42.  Yet, a visual inspection of the results of the ARIMA model and the dynamic model based on 
the IMS/EOS data shows, as depicted in Figure D.12 , that most of the estimated per capita 
cigarette sales associated with the dynamic model are not close at all to the actual values of the 
per cap ita sales in the pre -implementation period. In other words, the dynamic model does not fit 
well the per capita cigarette sales in the pre -TPP period. For instance, the predicted value of per 
capita sales in December  2010 given by the dynamic model is equal  to 100.6, while the actual 
value of per capita sales amounts to 147.7. Similarly, the dynamic model predicts a value of 95.6 
in February  2012, while the observed value  is 61.8. We therefore question how the dynamic model 
specification can be used to accur ately forecast the per capita cigarette sales that would have 
prevailed in the absence of the TPP measures  in the post -implementation period, when it already 
performs relatively poorly in the pre -implementation period.  
 
                                                
41 See IPE Third Updated Report , (Exhibit DOM -375), paras.  169-176. 
42 We note that the same issue applies to Professor  List's event study  of the 2010 tax change on 
cigarette sales, where most explanatory variables are not statistically significant, except for some of the 
moving average parameters . List Second Supplemental Report, (Exhibit DOM/IDN -5), backup material.  
43 See List Second Suppl emental Report, (Exhibit DOM/IDN -5), para. 49. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-17 - 
 
  Figure D. 12: Event Study of Per Capita Cigarette Sales Volumes Based on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TP P and enlarged GHWs.  
Source:  List Rebuttal Report, (Exhibit DOM/IDN -3), p. 16. 
 
43.  We further note that, similar to the ARIMA model, most explanatory variables in the estimated 
dynamic models using the IMS/EOS data are not statistically significant (except the constant) at 
5%. In particular, the results of the benchmark specification, wh ich includes the price variable in 
the previous month, suggest that per capita cigarette sales are not explained by the value of per 
capita sales in the previous month or the linear time trend. This result contradicts the fact that per 
capita sales follow a dynamic process and a downward trend, as acknowledge d by Professor  List.44 
While Professor  List explains that the predictive models he employ s are not designed to precisely 
describe every causal dynamic in Australia' s cigarette market, we note that he doe s not explain 
how this justifies the lack of statistically significant explanatory variables.45 In fact, the only 
explanatory variable (besides the constant) that is statistically significant is the time trend variable 
when the price variable is omitted or replaced by a tax level variable. This finding, as explained in 
the analysis of smoking prevalence, suggests that the price variable and the time trend might be 
collinear, that is both variables might convey the same information and one of them then become s 
redundant. As with the technical exchange between the experts of the Dominican  Republic , 
Honduras, Indonesia and Australia regarding smoking prevalence, they disagree on the use of the 
price variable. As explained in our review of the econometric studies  assessing the impact of the 
TPP measures  on smoking prevalence in Appendix  C, we question the results of the dynamic model 
specification with the price variable based on the IMS/EOS data.46 Finally, we note  that, as pointed 
out by Dr Chipty, Professor  List did not correctly define the March  2006 GHW variable and 
implicitly assumes that the GHW policy no longer had an effect on consumption as of the beginning 
                                                
44 See List Second Supplemental Report, (Exhibit DOM/IDN -5), para. 23.  
45 See List Second Supplemental Report, (Exhibit DOM/IDN -5), para. 149.  
46 We note that the price variable is also included in the ARIMA mo del but it is expressed in difference 
(i.e. the difference in price with respect to the previous year). Differentiating the data is often used to address 
the non -stationary (unit root) of the data. In fact, standard unit root tests suggest that price diffe rential 
variable is stationary. Therefore, the issue of non -stationary price variable does not apply to the results of 
Professor  List's ARIMA model.  
406080100120140
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Year
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Predicted per capita sales based on dynamic modelTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-18 - 
 
  December  2012, when the TPP measures  were fully implemented. It is also unclear to what extent 
defining correctly the dummy variable for the GHW policy would have changed the results.  
44.  Some of the issues we raised above also appl y to the results of Professor  List's event study 
based on the Aztec data. In particular, both the ARIMA model and the dynami c model include the 
price variable in the previous month, which as explained above, appears to be non -stationary and 
do not account for the potential impact of the TPP measures  on prices.47 In addition, the results of 
the dynamic model find a statistically significant upward trend in per capita cigarette sales. As 
acknowledged by Professor  List, Aztec 's market share has been increasing over the relevant time 
period.48 Yet, Professor  List does not control for this feature of the data, so it is unclear to what 
extent the results of an upward trend shift would prevail, if the increasing market share w as 
accounted for. In any event, we are not persuaded that we can simply ignore or down -weigh this 
contradict ory result, as Professor  List suggests , without questioni ng the model specification and 
data. Overall, in this context, we consider the results of Professor  List's event study to be of 
limited use in informi ng whether the TPP measures  led to a change in the downward trend of per 
capita cigarette sales.  
2.2.2   Dr Chipt y's reports  
45.  We note that Dr Chipty re -estimated Professor  List's dynamic model based on the IMS/EOS 
data by addressing some of the issue s we raised above. In particular, replacing the price variable 
with an excise tax increase dummy reverses Professor  List's conclusions and suggests that there 
was a statistically significant shift in the post -implementation downward trend in per capita 
cigarette sales. We note, however, that the shift is still negative but no longer statistically 
significant when the excise  tax changes, and strategic inventory management associated with 
these tax changes are taken into account in the post -implementation estimation. As shown in 
Figure D.13 , a visual inspection of the results of Dr Chipty's dynamic model specification based 
on the IMS/EOS data shows that, although Dr Chipty's specification, with a higher adjusted 
coefficient of determination, predicts slightly more accurately the values of per capita sales in the 
pre-implementation period than Professor  List, the dynamic model continues to perform relatively 
poorly in the pre -implementation period.49 As explained above, we continu e to have doubts about 
how the dynamic model specification can be used to accurately forecast the per capita cigarette 
sales that would have prevailed in the absence of the TPP measures  in the post -implementation 
period, when it already performs relatively  poorly in the pre -implementation period.  
 
                                                
47 We note that Professor  List decided to remove the observation associated with 3  August  2008 in his 
analys is without providing any explanation. We also note that the results of the ARIMA model show that the 
STATA software is unable to compute the standard error of the second lagged moving average coefficient. In 
addition, unlike the specification of the ARIMA model based on the IMS/EOS data, Professor  List removed the 
constant term, supposedly as a result of the procedure implemented by Professor  List to select the model 
specification by optimizing the information criteria of the model . See List Rebuttal Report , (Exhibit 
DOM/IDN -3), fn 14. 
48 See List Rebuttal Report, (Exhibit DOM/IDN -3), fn 15. 
49 The (adjusted) coefficient of determination measures the share of the variance in the dependent 
variable (e.g. per capita cigarette sales) is predictable from the indep endent variables included in the model 
(e.g. price, trend, …) . W. H. Green, Econometric Analysis , 5th edn (Prentice Hall, 2002). WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-19 - 
 
  Figure D. 13: Alternative Event Study of Per Capita Cigarette Sales Volumes  
Based on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source:  Chipty Third Rebuttal Report , (Exhibit AUS -605), para. 67. 
 
46.  That being said, we find that, according to a standard mean -compariso n test, the average 
cigarette sales volumes based on the IMS/EOS data in the post -implementation period are 
statistically significantly lower than in the pre -implementation period.50 This is confirmed by the  
fact that,  as described in  Figure D.14 , the cigarette sales trend in the post -implementation period 
has become steeper compared to the pre -implementation trend, implying that the fall in cigarette 
sales has accelerated in the post -implementation period. The same conclusion can be drawn based 
on the Aztec data. In any case, as for prevalence, the fact that the downward trend in sales from 
manufacturers to wholesalers and retailers has accelerated in the post -implementation period does 
not necessarily mean that the TPP measures  are having a statistically significant impact, given that 
other factors, unrelated to the TPP measures , could explain the trend shift. Evidence relating to 
the extent to which t he TPP measures  have an impact on cigarette sales or in some reports on 
cigarette consumption is reviewed next.  
                                                
50 For completeness sake, we note that the mean -comparison test applied to the Nielsen data concludes 
that there is no difference between the pre - and post -implementation period trends. However, the Nielsen data 
are only available for the February  2011-December  2013 period. When the mean -comparison test is applied to 
the IMS/EOS data for the same February  2011-December  2013 period, the test result suggests also that there 
is no shift in the pre - and post -trend, while the conclusion is reversed when the sample period is extended to 
September  2015. We, therefore, do not consider the result of the mean -comparison test applied to the Nielsen 
data to be relevant given that other more recent datasets are available and yield a different conclusion.  
406080100120140
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Jan 2011
Jul 2011
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Jul 2012
Jan 2013
Jul 2013
Jan 2014
Jul 2014
Jan 2015Per capita sales volume of FMC and CSE
(per month)
Year
Actual per capita sales
Predicted per capita sales based on Professor List's  dynamic model
Predicted per capita sales based on Dr. Chipty's dynamic modelTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-20 - 
 
  Figure D. 14: Cigarette Sales Volumes Pre - and Post -TPP Trends  
 
Note:  Conversion rate of 0.8 grams of fine -cut toba cco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of TPP and enlarged GHWs.  
Source :  IPE Summary Report , (Exhibit DOM -379), back -up material.  
 
3  WHETHER THE TPP MEASURES  CONTRIBUTED TO THE  REDUCTION IN CIGARETTE 
SALES VOLUMES AND CO NSUMPTION  
47.  As explained above, we have determined that the evidence presented to us shows that 
cigarette sales volumes in Australia have continued to experience a decline, which has accelerated 
in the post -TPP period. To the extent that there has been a greater reduction in cigarette sales 
volumes after the entry into force of the TPP measures , the question arises whether, and if so, to 
what extent, the TPP measures  contributed to reducing cigarette consumpt ion.  
48.  As for smoking prevalence, IPE (for the Dominican  Republic ), Professor  List (for the 
Dominican  Republic  and Indonesia), Professor  Klick (for Honduras) and Dr Chipty (for Australia) 
proposed different econometric methods to estimate the TPP measures ' impact on cigarette sales 
or reported cigarette consumption. As mentioned above, all parties recognize, however, that the 
empirical econometric results submitted do not distinguish between the impact of TPP and the 
impact of enlarged GHWs on cigarette sales and consumption, because both measures were 
implemented at the exact same time.51 
49.  Australia submit s that, with regard to prevalence, it is too early to look at cigarette 
consumption to assess the contribution of the TPP measures , for two main reasons. Fir st, reduction 
in cigarette consumption through smoking prevalence is a long -term objective.52 Second, 
                                                
51 See Australia's first written submission, para. 518; Dominican  Republic's  response to Panel question 
No. 8, para. 61; List Report, ( Exhibit DOM/IDN -1), para. 113; Honduras's response to Panel question No. 8; 
and Indonesia's response to Panel question No. 8, para. 8.  
52 See Australia's first written submission, para. 670. Australia considers that  in the early stages of 
introduction of t he measures, the most appropriate way to discern their effects is to rely on experiments and 
surveys which consider drivers of choice, attitudes, and ultimately, the elicitation of behavioural intentions  
(Australia's first written submission, para. 147).  
0.71.21.72.22.7
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YearTPPWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-21 - 
 
  significant changes in the root behaviours (i.e. initiation, cessation, and relapse) stemming from 
TPP are likely masked in cigarette consumption because o f the stock of current smokers whose 
behaviours may not be as affected by TPP.53 Instead Australia considered that the impact of TPP 
should  be investigated through its three mechanisms , i.e. appeal, GHW effectiveness, and the 
packs' ability to mislead. Aust ralia referred to a series of peer -reviewed studies published in the 
Tobacco Control  journal. Notwithstanding this position, Australia engaged in estimating the 
TPP measures ' impact on cigarette sales in response to the Dominican  Republic 's, Honduras' s and 
Indonesia 's submissions , and found on that basis that the TPP measures  have already contributed 
to the reduction of cigarette sales volumes .54 
50.   Just as with the empirical results submitted in the context of prevalence, new methodologies  
or new  model sp ecifications or both were proposed by the experts of the Dominican  Republic , 
Honduras and Indonesia in the course of the proceedings in response to the exchange of 
arguments between the parties. In some cases, the new models proposed invalidate some of the  
previous estimations (even though they yielded the same conclusion).55 For this reason, the 
approaches and results discussed below are drawn mostly from the most recent expert reports 
submitted by the parties.56 Similar to the review of the econometric stud ies on smoking 
prevalence, we first describe the relevant results and related discussions by dataset, before 
presenting our analysis.  
3.1  Datasets and related studies  
3.1.1   In-Market -Sales/Exchange of Sales  
51.  The IMS/EOS data were used by several of the Dominican  Republic 's and Honduras' s experts 
to estimate econometrically the impact of the TPP measures  on cigarette wholesale volumes.  
3.1.1.1   IPE Report s 
52.  The Dominican  Republic  submitted several reports prepared by IPE, estimating 
econometrically the TPP measures ' impact on the logarithm of cigarette sales using the 
IMS/EOS  data. Throughout the IPE Report s submitted, different econometric approaches and 
model specifications have been proposed: (1)  time series regression analysis of cigarette sales; 
(2) modified trend analysis of per capita cigarette sales; and (3)  ARIMAX model of per capita 
cigarette sales.57 The first approach was only presented in the first IPE Report  and is based on a 
model specification of the logarithm of cigarette sales that includ es at least a dummy variable for 
the TPP measures , dummy variables for the 2010 and 2013 excise tax increase, month fixed 
effects and a trend (in some specifications). The second and subsequent IPE Report s only focused 
on the last two approaches, which to some extent were adopted to address some of the critiques 
raised by Australia's expert, Dr Chipty. Under these two approaches, the model specification was 
modified to focus on the logarithm of per capita cigarette sales and to include at least a 
TPP measur es dummy variable, a tobacco price variable, a 2006 GHW dummy, dummy variables 
for strategic inventory and a linear trend. The most recent econometric analysis reported in the 
IPE Report  covers the period January  2001 through August  2015 (for the model spe cifications 
                                                
53 See Chipty Report, (Exhibit AUS -17), paras.  32-39. 
54 See Australia's response to Panel question No. 196, para. 214. 
55 For instance, as in the review of the econometric studies on smoking prevalence, IPE initially 
proposed to control for excise tax increases by including (dummy) indicator variables for each excise tax 
increase ( IPE Updated Report , (Exhibit DOM -303)), but subsequently contended that a more appropriate 
measure to capture the excise tax increases is the weighted average price per cigarette in Australia.  IPE 
Second Updated Report , (Exhibit DOM -361). Similarly, Professor  List and IPE initially applied the STATA  
software command ivreg2 in order to calculate standard errors that are robust to heteroscedasticity and serial 
correlation using the automatic bandwidth selection procedure by Newey and West (1994) . IPE Updated 
Report , (Exhibit DOM -303); and List Report, (Exhibit DOM/IDN -1). Subsequently, both Professor  List and IPE 
applied an alternative way of calculating standard errors, that, according to them, is adjusted to reflect more 
accurately the original suggestion by Newey and West (1994) . IPE Second Updated R eport (Exhibit DOM -361); 
and List Rebuttal Report, (Exhibit DOM/IDN -3). 
56 We note that we nonetheless considered all the relevant evidence before us, including all the expert 
reports, including the methodologies and models contained therein.  
57 See IPE Repo rt, (Exhibit DOM -100), p p. 67-73 and 201 -210; and IPE Updated Report , (Exhibit 
DOM-303), paras.  135-175 and 290 -326. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-22 - 
 
  without the price variable) or February  2002 through August  2015 (for the model specifications 
with the price variable).58 
53.  Overall, IPE concludes that the TPP measures  had no statistically significant effect on cigarette 
sales and per capita cigarette sales. According to IPE, these results are robust across different 
specifications (e.g. different TPP starting date: October, November  and December; excluding the 
October  and November  2012 observations; controlling for the weighted average price of tobacco, 
tax levels or tax policy change; and strategic inventory management). The results are also robust 
to Professor  List's procedure to compute the explanatory variables' robust standard errors, which 
is different from the STATA software package ivreg2  used by Dr Chipty.59 However, when excise 
tax dummy variables are included in the model specification, some of the results of the modified 
trend analysis suggest that the TPP measures  had a negative and statistically significant impact on 
cigarette wholesa les and per capita cigarette wholesales.60 
54.  Australia's expert, Dr Chipty, rejects the econometric results of the IPE Report s on various 
technical grounds. Dr Chipty is of the view that the analysis should be extended to the 2000 -2015 
period, instead of restricting the sample to the period 2001 -2015 or 2002 -2015, noting that there 
is no reason for ignoring available data.61 For similar reasons as for the IPE Report s and 
Professor  List's econometric studies on smoking prevalence, Dr Chipty disagrees with Professor  List 
and IPE's claim that the Stata command, ivreg2, used to estimate standard errors robust to 
"heteroscedasticity" and "autocorrelation" (Newey -West standard errors) is wrong, noting that 
both IPE and Professor  List used the same Stata command, b efore Professor  List argued he found 
an error in the Stata programming code.62 Similarly, Dr Chipty submits  that controlling for tobacco 
prices inclusive of tax while attempting to measure the effects of a tax hike ignores the effect of 
the TPP measures  on price, leading the TPP measures  indicator variable to capture only a partial 
effect of the TPP measures , and the price variable capturing the rest of its effect. Dr Chipty further 
notes that IPE initially controlled for excise tax increase with indicator v ariables in their model 
specification.63 Dr Chipty further submits  that the use of a single tax level variable, as proposed by 
IPE, is only valid under the proportionality assumption (i.e. the effect of tax changes is 
proportional to the size of the tax cha nge), which may only be satisfied in some specifications, and 
is inappropriate in models of consumption/sales.64 Dr Chipty argues that IPE's consumption 
analyses rely heavily on the use of time trends by assuming trends in consumption exist in a 
vacuum with out addressing the issue of whether any of the changes in consumption with the time 
trends around the TPP measures  should themselves be interpreted as the TPP measures ' effects.65 
3.1.1.2   Professor  Klick's reports  
55.  Like his analysis of smoking prevalence, Honduras's  expert, Professor  Klick, proposes 
comparing Australia's cigarette sales before and after the introduction of the TPP measures  relative 
with another jurisdiction that has not implemented TPP during the same period. Professor  Klick 
posits that although Aust ralia is unique in many ways, it is, notwithstanding Dr Chipty's criticisms, 
reasonable to use New Zealand  as a reliable counterfactual jurisdiction, because (i)  both countries 
share many similarities culturally, historically, and demographically; (ii)  both countries are in the 
same region and share the same seasonality (useful when dealing with sub -annual measures); 
(iii) the governments of both countries acknowledge that they are comparable in areas such as 
health behaviour and socio -economic issues; (iv)  tobacco prices, including taxes, are comparable 
between both countries; and (v)  smoking rates in both countries are highly correlated (0.95 for 
                                                
58 The difference between the two sample periods stem from the fact that the price variable is not 
available prior to February  2002.  
59 IPE R eport , (Exhibit DOM -100), p p. 67-73 and 201 -210; IPE Updated Report , (Exhibit DOM -303), 
paras.  143-155, 290 -295; IPE Second Updated Report , (Exhibit DOM -361), paras.  26-31; IPE Third Updated 
Report , (Exhibit DOM -375), paras.  117-145; and IPE Summary Report , (Exhibit DOM -379), paras.  123-150. 
60 See IPE Summary Report , (Exhibit DOM -379), paras.  144-145 and backup material.  
61 See Chipty Surrebuttal Report, (Exhibit AUS -586), para. 9; and Chipty Third Rebuttal Report, (Exhibit 
AUS-605), paras.  34-35. 
62 See Chip ty Second Rebuttal Report, (Exhibit AUS -591), paras.  13-31. 
63 See Chipty Surrebuttal Report, (Exhibit AUS -586), paras.  12, 45 and 65 . 
64 See Chipty Third Rebuttal Report, (Exhibit AUS -605), paras.  22-26 and 29 -32. 
65 See Chipty Surrebuttal Report, (Exhibit A US-586), paras.  68-70. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-23 - 
 
  the period 1964 -2012 based on the OECD data on the fraction of residents ages 15 years and 
older who are daily smokers).66  
56.  Professor  Klick reconsidered the IMS/EOS data for Australia and New Zealand  and estimated a 
difference -in-difference model that explains the logarithm of cigarette sales in Australia relative to 
New Zealand  controlling for a TPP measures  dummy variable, the logarithm of tobacco price, 
country fixed effects, time -period fixed effects and country -specific trends. In Professor  Klick's first 
submission, the model only controlled for a TPP measures  dummy variable, time -period fixed 
effects and  differential intercept term for New Zealand . Professor  Klick subsequently modified his 
model specification to address some of Dr Chipty's criticisms. In Professor  Klick's first report, a 
differential trends model was also estimated controlling for a TPP measures  dummy variable, an 
Australia monthly trend, and a New Zealand  monthly trend. The most recent econometric analysis 
covers the period February  2011 to September  2015.67  
57.  Professor  Klick considers it unlikely that prices may be endogenous to cigarette sales, in other 
words prices may be determined by cigarette sales, a concern raised by Dr Chipty. This is because 
tobacco taxes make up the bulk of tobacco prices, and are, theoretically, less likely to be 
determined endogenously to cigarette sales, at lea st on a month -to-month basis, since taxes are 
the result of political decisions that take significant time to reach and implement. Nevertheless, 
Professor  Klick implements an instrument variable (IV) estimation procedure to address the 
theoretical possibil ity of an endogeneity bias of the tobacco price variable. The IV estimation 
procedure involves (1) estimating a model of tobacco price that includes a TPP measures  dummy 
variable, an excise tax dummy variable, country fixed effects and time fixed effects ( and 
country -specific trends in some specifications); and (2) reconstructing the tobacco price variable 
using the estimated parameters of the model obtained in the first stage. This constructed 
(instrumented) price variable replaces the original price varia ble in the model of cigarette sales.68 
The overall impact of the TPP measures  corresponds to the sum of the impact of the TPP measures  
on cigarette sales and the impact of the TPP measures  on cigarette price multiplied by the impact 
of cigarette price on cigarette sales. In addition, Professor  Klick contends that New Zealand 's 2013 
excise tax increase does not invalidate it as a comparator to Australia, because taxes influence 
behaviour through prices and the model specification controls for price and accoun ts for its 
potential endogeneity through the instrumental variables technique.69 
58.  Overall, Professor  Klick concludes that the TPP measures  have not resulted in a decline in 
cigarette sales in Australia relative to sales in New Zealand .70 However, Professor  Klick's most 
recent estimations find a positive and statistically significant impact of the TPP measures  on 
cigarette sales, suggesting that the TPP measures  led to an increase in cigarette sales in Australia 
relative to New Zealand .71  
59.  Dr Chipty contends t hat Professor  Klick's analysis is flawed on various technical grounds. As in 
the case of Professor  Klick's econometric analysis on smoking prevalence, Dr Chipty is of the view 
that New Zealand  is an invalid counterfactual for the purposes of studying the TPP measures ' 
effects, because of New Zealand 's January  2013 excise tax increase, a month after the 
introduction of the TPP measures .72 In particular, Dr Chipty submits  that there is no reliable way to 
correct for the failure to account for differential coun try-specific tax policies introduced at different 
times in Australia and New Zealand  because there is only a single month of data in New Zealand  
between implementation of the TPP measures  in Australia and the January  2013 New Zealand  
                                                
66 See Klick Report , (Exhibit UKR -5), pp. 3-6; and Klick Third Supplemental Rebuttal Report , (Exhibit 
HND-166), paras.  30-31. 
67 See Klick Report , (Exhibit UKR -5), pp. 35-36; Klick Rebuttal Report , (Exhibit HND -118), paras.  66-68; 
and Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  107-121. 
68 See Klick Rebuttal Report , (Exhibit HND -118), paras.  52-60. 
69 See Klick Third Supplemental Rebuttal Report , (Exhibit HND -166), para. 32. 
70 See Klick Supplemental Rebuttal Report , (Exh ibit HND -122), paras.  117-119; and Klick Third 
Supplemental Rebuttal Report , (Exhibit HND -166), paras.  44-45. 
71 See Klick Third Supplemental Rebuttal Report , (Exhibit HND -166), paras.  44-45. 
72 See Chipty Supplementary Report, (Exhibit AUS -511), paras.  16-19; and Chipty Rebuttal Report , 
(Exhibit AUS -535) (SCI), paras.  67-71. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- D-24 - 
 
  excise tax increase.73 Dr Chipty also questions the use of a highly flexible time trend that makes it 
difficult to estimate the effects of the very policies that likely created the trend.74 
3.1.1.3   Dr Chipty's reports  
60.  Australia's expert, Dr Chipty, considers the IMS/EOS data to be the on ly appropriate data to 
assess the TPP measures ' impact on cigarette sales volumes, because the IMS/EOS data capture 
virtually all sales in Australian market, given that the big three manufacturers account for all but 
1% of total sales. In addition, the IMS /EOS data are available for a longer period.75  
61.  Dr Chipty re -estimated the model of cigarette sales developed by IPE in its first report (time 
series regression analysis) by extending the period of analysis from January  2000 to 
September  2015 and controlling for a TPP measures  dummy variables, tax increases dummy 
variables (for May 2010, December  2013 and September  2014), a 2006 GHW dummy variable, a 
linear trend and month fixed effects.76  
62.  Overall, Dr Chipty concludes that the  TPP measures  had a negative and statistically significant 
effect on cigarette sales.77 Most of the results show statistically significant declines in cigarette 
sales even when using Professor  List's own standard error calculation.78 However, Dr Chipty notes 
that the res ults are sensitive to the decision whether to use a tobacco price variable or the tax 
levels variable instead of the tax indicators, and that specification testing suggests the use of tax 
levels are not appropriate.79  
63.  IPE counters that Dr Chipty "cherry -picked" a small subset of IPE's analyses for the purposes 
of undertaking adaptations or "corrections". According to IPE, Dr Chipty engaged in further 
"cherry -picking", reporting results from only a small subset of specifications, for example by using 
only on e specific measure of tobacco affordability (tax dummies) and simply ignoring the two 
superior alternatives (tax levels and tobacco prices, respectively). IPE submits  that Dr Chipty 
never even discussed any of the ARIMAX models, thus completely ignoring an  entire class of 
models.80 
3.1.2   Nielsen Retail Sales  
64.  Similar to the IMS/EOS data, the Nielsen retail sales data were used by the 
Dominican  Republic 's and Honduras' s experts to estimate econometrically the impact of the 
TPP measures  on cigarette retail volumes.  
3.1.2.1   IPE Report s 
65.  IPE argues that Dr Chipty 's decision to dismiss the Nielsen data due to its short sample period 
is unscientific. According to IPE, despite the relatively shorter period for which the Nielsen data are 
available, the dataset has two important adv antages as compared to the IMS/EOS  data and the 
Aztec data: (1)  compared to the IMS/EOS data, the Nielsen dataset provides actual sales to 
customers and is not affected by wholesalers ' strategic inventory management behaviour; and 
                                                
73 See Chipty Supplementary Report, (Exhibit AUS -511), paras.  3 and 12-19. Dr  Chipty also argued that 
Professor  Klick failed to account for the strategic inventory management associated with excise tax hikes but 
acknowledged that the failure to account for the buy up problem did not affect the estimates in 
Professor  Klick's analysis . Ibid. paras.  22-24.  
74 See Chipt y Supplementary Report, (Exhibit AUS -511), para. 25. 
75 See Chipty Third Rebuttal Report, (Exhibit 605), para. 70. 
76 See Chipty Second Rebuttal Report, (Exhibit AUS -591), paras.  28-31. 
77 See Chipty Surrebuttal Report, (Exhibit AUS -586), paras.  65-66; Chipty  Second Rebuttal Report, 
(Exhibit AUS -591), paras.  29-31, 53 -54, Appendix  D; and Chipty Third Rebuttal Report, (Exhibit AUS -605), 
paras.  74-75.  
78 See Chipty Second Rebuttal Report, (Exhibit AUS -591), paras.  28-31. 
79 See Chipty Third Rebuttal Report, (Exhibit 605), paras.  15-28 and 75. 
80 See IPE Summary Report , (Exhibit DOM -379), paras.  156-161. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  (2) compared to the Aztec  data, which are also at the retail level, the Nielsen data cover virtually 
the whole market.81  
66.  Similar to the analysis of the IMS/EOS and the Aztec data, IPE presents the results of the 
(1) modified trend analysis and (2)  ARIMAX model of tobacco retail sa les per capita controlling for 
at least a TPP measures  dummy variable, a cigarette price variable and a linear trend.82 The 
econometric analysis based on the Nielsen data covers the period February  2011 to 
December  2013.83 
67.  Overall, IPE concludes that the TPP measures  had no statistically significant effect on retail 
sales of cigarettes per capita.84 According to IPE, these results are robust across different 
specifications (e.g. different TPP starting date: October, November and December; controlling for 
the weighted average price of cigarettes, tax levels or tax policy change; and adjusting for 
seasonality in order to reduce the number of parameters to be estimated). In reality, some of IPE's 
results of the modified trend analysis (when the TPP measures  dummy variable starts in 
December  2012) suggest that the TPP measures  led to an increase in retail sales of cigarettes per 
capita.85 
68.  Dr Chipty agrees with IPE that the Nielsen data cover "virtually the whole market" and as 
such are superior to the Aztec data i n this respect. However, Dr Chipty contends that the sample 
size of the Nielsen data is a serious problem for IPE, which attempts to estimate at least 15 
different coefficients, including 12 -month indicators for seasonality, using 35 monthly 
observations. Dr Chipty argues that in IPE 's Nielsen analysis, the monthly effects are identified off 
of variation from three data points each, with only two for the January  effect. Dr Chipty submits  
that unlike the IMS/EOS data, which are affected by the issue of strat egic inventory management, 
but can be corrected for it, there is no workaround for the insufficient data issue.86 
3.1.2.2   Professor  Klick's reports  
69.  Professor  Klick also used the Nielsen retail sales data for Australia and New Zealand  to 
estimate a difference -in-difference model of the logarithm of cigarette retail sales per capita 
controlling for a TPP measures  dummy variable, the logarithm of tobacco price, country fixed 
effects, time -period fixed effects and country -specific trends. In Professor  Klick's first subm ission, 
the analysis focused on cigarette retail sales and not cigarette retail sales per capita. 
Professor  Klick's first difference -in-difference model also only controlled for a TPP measures  
dummy variable, time -period fixed effects and differential inte rcept term for New Zealand . In 
addition, a differential trends model was also estimated controlling for a TPP measures  dummy 
variable, an Australia monthly trend, and a New Zealand  monthly trend. The econometric analysis 
covers the period February  2011 to December  2013.87  
70.  Overall, Professor  Klick concludes that the TPP measures  are not associated with a statistically 
significant reduction in cigarette retail sales and cigarette retail sales per capita in Australia 
relative to New Zealand .88 However, two initial specifications, which do not control for price, find a 
                                                
81 See IPE Updated Report , (Exhibit DOM -303), para. 157; and IPE Third Updated Report , (Exhibit 
DOM-375), paras.  158-168. 
82 See IPE Report , (Exhibit DOM -100), p p. 67-73 and 201 -210; and IPE Updated Report , (Exhibit 
DOM-303), paras.  135-175 and 290 -326. 
83 See IPE Updated Report , (Exhibit DOM -303), para. 156. 
84 See IPE Updated Report , (Exhibit DOM -303), paras.  156-162; IPE Secon d Updated Report , (Exhibit 
DOM-361), paras.  32-35; IPE Third Updated Report , (Exhibit DOM -375), paras.  158-168; and IPE Summary 
Report , (Exhibit DOM -379), paras.  146-147. 
85 See IPE Third Updated Report , (Exhibit DOM -375), paras.  146-147 and 158 -168. 
86 See Chipty Surrebuttal Report, (Exhibit AUS -586), para. 77. 
87 See Klick Report , (Exhibit UKR -5), pp. 12-16; and Klick Rebuttal Report , (Exhibit HND -118), 
paras.  10, 39 -42, 44 -48 and 49 -51. 
88 See Klick Report , (Exhibit UKR -5), pp. 32-34; and Klick Rebuttal  Report , (Exhibit HND -118), 
paras.  54-64.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  positive and statistically significant TPP effect, suggesting that the TPP measures  led to an increase 
in cigarette sales in Australia relative to New Zealand .89  
71.  Professor  Klick also presents the results of a "crossfold validation" analysis to test various 
predictive models using the Nielsen data in terms of predictive accuracy. Professor  Klick concludes 
that the January  2013 tax increase in New Zealand  does not disqualify New Zealand  as a proper 
comparator because the best performing model is the one that includes New Zealand 's natural log 
per capita sales and monthly fixed effects and for which the TPP measures ' impact on per capita 
cigarette sales in Australia (relative to  New Zealand ) is statistically not significant.90 
72.  As described above, Dr Chipty is of the view that New Zealand  is an invalid counterfactual for 
the purposes of studying the TPP measures ' effects, because of New Zealand 's January  2013 
excise tax increase, a  month after the introduction of the TPP measures .91 Dr Chipty further 
submits  that the predictive ability measured by the "crossfold validation" is insufficient to validate 
a control group given New Zealand 's January  2013 tax increase.92  
3.1.3   Aztec Scanner Reta il Sales  
73.  Similar to the analysis of the IMS/EOS data, IPE used the Aztec data and applied different 
econometric approaches and model specification throughout their reports: (1)  time series 
regression analysis of cigarette retail sales; (2)  modified trend a nalysis of cigarette retail sales per 
capita; and (3)  ARIMAX model of cigarette retail sales per capita.93 The first approach was only 
presented in the first IPE Report  and is based on a model specification of the logarithm of retail 
sales of cigarettes tha t includes at least a TPP measures  dummy variable, dummies for the 2010 
and 2013 excise tax increase, month fixed effects and a trend. The second and subsequent IPE 
Report s only focused on the last two approaches, which to some extent were adopted to address 
some of the criticisms raised by Australia's expert, Dr Chipty. In those two approaches, the model 
specification was modified to focus on the logarithm of retail sales of cigarettes per capita  and to 
include at least a TPP measures  dummy variable, a cigarette price variable and a linear trend. IPE 
argues that Dr Chipty 's decision to dismiss the Aztec dataset due to its growing market coverage is 
unscientific because the use of linear time trends means it is possible to take into account changes 
in market coverage.94 The most recent econometric analysis reported in the IPE Report  covers the 
period from 27 July 2008 through 27  September  2015.95 
74.  Overall, IPE concludes that the  TPP measures  had no statistically significant effect on retail 
sales of cigarettes per capita.96 According to IPE, these results are robust across different 
specifications (e.g. different TPP starting date: October, November  and December; controlling for 
the weighted average price of cigarettes, tax levels or tax policy change; and adjusting for the 
increasing market share by benchmarking quarterly Aztec data to IMS/EOS data). In reality, when 
IPE's modified trend analysis specification controls for tax lev els (instead of cigarette price or tax 
dummies), the results suggests that the TPP measures  led to an increase in retail sales of 
cigarettes. Similarly, in a few ARIMAX specifications, the TPP measures ' impact on retail sales of 
cigarettes is positive and statistically significant.  
75.  As explained above, Dr Chipty argues that not all data are worth studying. She notes that the 
Aztec scanner data in particular has a growing coverage of retail sales over time, either through 
the growth of the sales outlets it co vers or through the inclusion of additional sales outlets, which 
                                                
89 However, D r Chipty notes that Professor  Klick made a transcription error and erroneously reported a 
statistically significant increase in sale in Professor  Klick's two specifications controlling for price . See Chipty 
Report, (Exhibit AUS -17), para. 53. 
90 See Klick Rebuttal Report , (Exhibit HND -118), paras.  44-51; and  Klick Third Supplemental Rebuttal 
Report , (Exhibit HND -166), para. 32. 
91 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  67-71. 
92 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  70-71. 
93 See IPE Report , (Exhibit DOM -100), p p. 67-73 and 201 -210; and IPE Updated Report , (Exhibit 
DOM-303), paras.  135-175 and 290 -326. 
94 See IPE Third Updated Report , (Exhibit DOM -375), paras.  146-147, 156 -157 and 169 -170. 
95 See IPE Third Updated Report , (Exhibit DOM -375), paras.  240-242.  
96 See IPE Updated Report , (Exhibit DOM -303), paras.  163-172; IPE Second Updated Report , (Exhibit 
DOM-361), paras.  26-31, 36 -38; IPE Third Updated Report , (Exhibit  DOM-375), paras.  169-175, 240 -242; and 
IPE Summary Report , (Exhibit DOM -379), paras.  148-150. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  could lead to the wrong conclusion that the TPP measures  increased cigarette sales even when it 
did not.97 Dr Chipty contends that, contrary to IPE's claim that the inclusion of a time trend 
mitigates the risk of bias, the inclusion of a time trend does not eliminate the risk of bias for at 
least two reasons: (1) the inclusion of a simple time trend in IPE 's model may mitigate some of 
the problem, but there is no reason to expect that it will e liminate it, because the trend is likely 
not flexible enough to adequately capture the variety of different business explanations that result 
in the Aztec data 's growing footprint; and (2)  more importantly, the simple time trend in IPE 's 
model cannot resol ve the fact that the Aztec data are missing information on total sales because 
they only contain information from 12 retail chains and do not contain information on certain retail 
channels of tobacco distribution.98  
3.1.4   Nielsen Retail Sales -Aztec Scanner  
76.  Professor  Klick considers that, contrary to Dr Chipty's claim, the Aztec scanner data are valid 
because there is no evidence that the market share covered by the Aztec data has been growing 
over time.99 In that context, Professor  Klick combines the Nielsen and Aztec data presented above 
by omitting the Convenience Independent sample from the Nielsen data, and for the months 
where the data sources overlap, using the Aztec data.100 Professor  Klick re -estimated the 
difference -in-difference model of retail sales of cigarettes in Australia relative to New Zealand . In 
addition to the difference -in-difference analysis of Australia and New Zealand , Professor  Klick also 
estimated a model without New Zealand  as a counterfactual control. The model specification 
controls for a TPP measures  dummy variable, the logarithm of tobacco price, the logarithm of the 
number of stores covered by the Aztec data and a linear trend. The tobacco price variable is 
instrumented to address any endogeneity bi as.101 In addition, to control for the Aztec data's 
alleged growing market coverage, a variable reporting the number of stores covered by the Aztec 
data is included in Professor  Klick's most recent model specification. The econometric analysis 
covers the per iod February  2011 to September  2015 or is restricted to the 
January  2012-September  2015 period because the data relating to the number of stores are only 
available beginning January  2012.  
77.   Overall, Professor  Klick concludes that the TPP measures  had no sta tistically significant effect 
on the retail sales of cigarettes.102 However, one of Professor  Klick's two difference -in-difference 
estimations finds a positive and statistically significant TPP effect suggesting that the 
TPP measures  led to an increase in re tail sales of cigarettes. Similarly, the results of the model 
specification without New Zealand  as a counterfactual and without a trend variable suggest that 
the TPP measures  led to an increase in the retail sales of cigarettes. Professor  Klick explains th at 
he does not view these results as suggesting that smoking has increased under the TPP measures , 
because of the "multiple comparison problem", which implies that when very many outcomes are 
examined, there is a relatively high likelihood that one will fi nd statistically significant results even 
by mere chance.103 
78.  Dr Chipty argues that Professor  Klick's analysis based on the Nielsen -Aztec data is flawed 
because the Nielsen -Aztec data appear to be covering a greater share of total market sales over 
time. Acco rding to Dr Chipty, one reason for the growing share of Professor  Klick's Nielsen -Aztec 
data over time in Australia is the exclusion of downward -trending sales from the Convenience 
Independent channel. Dr Chipty submits  that the IMS/EOS data are decreasing  much faster than 
Professor  Klick's constructed Nielsen -Aztec data, suggesting that the Nielsen -Aztec data are not an 
                                                
97 See Chipty Report, (Exhibit AUS -17), paras.  55-60; and Chipty Surrebuttal Report, (Exhibit 
AUS-586), para. 10. 
98 See Chipty Surrebuttal Report, (Exhibit AUS -586), paras.  75-76. 
99 See Klick Fourth Supplemental Rebuttal Report , (Exhibit HND -169), paras.  6-8. 
100 Professor  Klick explains that beginning in February  2014, the scanner data are no longer provided by 
the Nielsen Company. The Nielsen Company also did not  continue its Convenience Independent sample from 
January  2014 onward. However, scanner data, without the Convenience Independent sample, is available from 
Aztec beginning in March  2012 and continuing through June 2015. See Klick Supplemental Rebuttal Repo rt, 
(Exhibit HND -122), paras.  122-126. 
101 See Klick Fourth Supplemental Rebuttal Report , (Exhibit HND -169), paras.  9-11. 
102 See Klick Supplemental Rebuttal Report, (Exhibit HND -122), paras.  129-130; Klick Third 
Supplemental Rebuttal Report , (Exhibit HND -166), paras.  11-23; and Klick Fourth Supplemental Rebuttal 
Report , (Exhibit HND -169), paras.  12-14. 
103 See Klick Fourth Supplemental Rebuttal Report , (Exhibit HND -169), fn 10. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  adequate proxy for total cigarette sales in Australia. In addition, Dr Chipty contends that 
Professor  Klick's Nielsen -Aztec model does not allow for the possibility of estimating the net effect 
of the TPP measures  because the regression model controls for price, which itself embodies some 
of the policy effect.104 
3.1.5   Commissioned Roy Morgan Research Survey (Australia and New Zealand ) 
79.  As explained in the section discussing smoking prevalence and smoking incidence, the Roy 
Morgan Research dataset is a survey of individuals who were current or former (in the past 12 
months) smokers in both Australia and New Zealand  undertaken using  random digit dialling 
sampling techniques. The first wave of the survey was completed prior to the December  2012 
implementation of the TPP measures  between 2 November  2012 and 26 November  2012 in 
Australia and between 8 November  2012 and 1 December  2012 i n New Zealand . Subsequent 
waves have been carried out at three -month intervals.  
80.  Professor  Klick used the Roy Morgan Research data and estimated a difference -in-difference 
linear regression model and negative binomial models that explain the reported number  of 
cigarettes consumed controlling for a TPP measures  dummy variable, a dummy variable for an 
Australian baseline and a dummy variable for a post -TPP implementation time -period. The 
difference -in-difference analysis covers the period from November  2012 to  February  2014.105  
81.  Overall, Professor  Klick concludes that the TPP measures  had no statistically significant effect 
on the cigarette consumption in Australia relative to New Zealand .106 According to Professor  Klick, 
this finding is robust to specifying the number of cigarettes smoked in logarithm (to mitigate 
outliers), applying different estimators (linear regression, negative binomial regression, robust 
regression ), restricting the sample to only individuals who answered the survey in the 6 waves (to 
mitigate attrition), restricting the sample to only individuals who answered the survey at least in 
one post -TPP waves, restricting sample to Wave 1 and Wave 6, restricting sample to smokers 
planning to quit during Wave 1, and computing robust standard errors o r standard errors clustered 
by individuals.107 However, some of the results (when respondents who had noticed plain packs in 
Wave 1 or a pack change of any kind in Wave 1 are discarded) suggest that the TPP measures  led 
to an increase in cigarettes consumpti on. Professor  Klick explains that he does not view these 
results as suggesting that smoking has increased under the TPP measures , because of the 
"multiple comparison problem", which implies that when very many outcomes are examined, there 
is a relatively h igh likelihood that one will find statistically significant results even by mere 
chance.108 
82.  Dr Chipty submits  that Professor  Klick's difference -in-difference study does not provide a 
reliable estimate of the TPP measures ' effect in Australia, because one can not reliably implement a 
difference -in-difference estimation strategy without: (1)  a pre -period data, yet a majority of 
smokers were likely smoking plain packs during the survey's first wave; (2)  a control group that 
resembles the treatment group (i.e. Aus tralia) in important dimensions other than the treatment, 
yet New Zealand  had a unique and significant tax change between Waves 1 and 2.109 Dr Chipty 
further contends that Professor  Klick invalidated his own commissioned survey data analysis by 
arguing that (1) it makes little sense to talk about trends in very short time spans; (2)  examining 
differential trends with five or six data points is demanding more from the data than is reasonable; 
(3) wave-to-wave variability is quite large in the data; (4)  Dr Chip ty's analysis is inappropriate 
because it involves estimating a trend using data from a single calendar year; and (5)  no 
meaningful analysis can be conducted by seeking a time trend between Waves 2 and 6.110 
                                                
104 See Chipty Surrebuttal Report,  (Exhibit AUS -586), paras.  92-96. 
105 See Klick Report , (Exhibit UKR -5), pp. 20-21 and 30 -32. 
106 See Klick Report , (Exhibit UKR -5), pp. 30-32. 
107 See Klick Rebuttal Report , (Exhibit HND -118), paras . 25-28, 31 -33 and 37 -38. 
108 See Klick Rebuttal Report , (Exhibit HND -118), fn 24. 
109 See Chipty Report, (Exhibit AUS -17), para. 24; and Chipty Rebuttal Report, (Exhibit AUS -535) (SCI), 
paras.  54-71. Dr Chipty initially contended that Professor  Klick did not use clustered standard errors except in 
his fixed -effects models. Dr Chipty further argued that Professor  Klick did  not allow for heteroscedasticity in the 
error structure and account for the longitudinal nature of the data by clustering at the respondent level . Ibid. 
Appendix  C. 
110 See Chipty Rebuttal Report , (Exhibit AUS -535) (SCI), paras.  50-53. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  3.1.6   International Tobacco Control Policy Evaluation Pr oject  
83.  The International Tobacco Control (ITC) Policy Evaluation Project (ITC Project) is a 
longitudinal cohort survey to assess the impact, and identify the determinants of, effective tobacco 
control policies in more than 20 countries, including Australia.  The ITC Project covers a number of 
questions related to GHWs, including attention towards the health warnings, salience of the health 
warnings and the effect of health warnings on consumers ' thoughts, behaviours and intentions 
towards quitting.   
84.  Ajzen et al., in their expert report submitted by  the Dominican  Republic  and Indonesia, used 
the ITC dataset to estimate a generalized estimating equation model of the reported number of 
cigarettes smoked per day controlling for the survey mode (phone vs. web) and wave of 
recruitment, as well as respondents ' age, sex, income, education and past year quit attempts.111 
The econometric analysis covers the period from September  2011 to May 2013.112  
85.  Overall, Ajzen et al. conclude that TPP and enlarged GHWs had no impact on the average 
number of cigarettes smoked per day in the first fi ve months following the introduction of the 
TPP measures .113 The same result is found when the sample is restricted to the participants 
involved in the surveys pre - and post -implementation.114  
86.  Australia responds that Ajzen et al. have misunderstood certain fe atures of the ITC data and 
that their claim that there have been no changes in smoking behaviour post -TPP is without 
foundation.115 
3.1.7   National Tobacco Plain Packaging Tracking Survey  
87.  To track the effect of the TPP measures , Australia funded the National Tobacc o Plain 
Packaging Tracking Survey (NTPPTS), a nationwide  tracking survey that was conducted by CCV. 
The NTPPTS is a continuous cross -sectional baseline survey of about 100 interviews per week 
conducted from 9 April 2012 to 30 March  2014. A follow -up survey  of baseline participants then 
took place approximately four weeks after the initial survey, with the follow -up surveys conducted 
from 7 May 2012 to 4 May 2014.  
88.  The NTPPTS were used by scholars as well as several of the experts of the 
Dominican  Republic , Honduras and Indonesia to estimate econometrically the impact of the 
TPP measures  on reported cigarette consumption.  
3.1.7.1   Scollo et al. 2015a peer -reviewed study  
89.  Scollo et al. 2015a116 used the NTPPTS data to assess changes in reported price paid and 
changes in reported numbers of cigarettes consumed following the introduction of TPP and 
enlarged GHWs in the period up to and after the large increase in excise duty on 
1 December  2013. Th e authors estimated logistic and linear models to assess changes between 
the pre -TPP period ( April to September  2012) and three subsequent time periods: the transition 
phase during which plain packages were being introduced into the Australian market ( October and 
November  2012); TPP year 1 ( December  2012 to November  2013); and TPP post -tax 
(December  2013 to March  2014). All regression models control for sex, age, area socio -economic 
status, education, past three -month exposure to antismoking campaigns (for cigarette 
consumption analysis).  
                                                
111 We note that Ajzen et al. used the ITC dataset to replicate part of the analysis of Yong et al. 2015, 
who did not analyse cigarettes consumption. Ajzen et al. argue that Yong et al. 2015 failed to explain why they 
did not report the impact of the pack changes on cigarette co nsumption . Ajzen et al. Second Data Report, 
(Exhibit DOM/IDN -4), para. 34. 
112 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), paras.  21-29 and 48 -58. 
113 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), para. 28. 
114 See Ajzen et al. Data Reb uttal Report, (Exhibit DOM/IDN -6), para. 83. 
115 See Australia's response to Panel question No. 196, paras.  225 and 235.  
116 Scollo et al. 2015a, (Exhibits HND -133, DOM -237, DOM -311).  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  90.  Overall, Scollo et al. 2015a conclude, among others things, that the introduction of TPP and 
enlarged GHWs were not associated with a change in consumption among daily, regular or current 
smokers or among smokers of brands  in any market segment during the first year of 
implementation of the TPP measures . However, the authors find that reported consumption among 
regular smokers declined significantly following the December  2013 tax increase.117 
3.1.7.2   Ajzen et al.'s reports  
91.  Ajzen et al. re-analysed part of Scollo et al. 2015a118, applying the approach in Wakefield 
et al. 2015.119 Ajzen et al. estimated logistic, ordered logistic and linear regressions of the 
reported number of cigarettes smoked daily and the proportion of smokers consu ming a given 
number of cigarettes or more per day. The model specification includes a set of variables 
controlling for age group, gender, education group, socio -economic status group, potential 
exposure to televised antismoking advertising campaigns in the  past three months and cigarette 
costliness.120  
92.  Overall, Ajzen et al. conclude that the TPP measures  had no statistically significant impact on 
any measure of actual cigarette consumption.121 Ajzen et al. argue that, unlike 
Professor  Chaloupka's assertion , using a threshold of 20  or more cigarettes per day is not 
inappropriate because the results continue to find no change in cigarette consumption when 
thresholds of 5, 10, and 15 cigarettes per day are used.122 In addition, Ajzen et al. present the 
quarterly  results of the logit model, which suggests that t here was an immediate increase  in the 
probability of smoking 20 or more cigarettes per day in the first quarter following the 
implementation of the TPP measures  but no impact in the following quarters.123 More generally, 
Ajzen et al. disagree with Professor  Chaloupka's assertion  that the NTPPTS dataset has less power 
for detecting statistically significant changes in the more distal outcomes, such as actual tobacco 
use behaviour. According to Ajzen et al., a power analysis of the NTPPTS data concludes that the 
statistical power of the NTPPTS data to detect small changes in proximal and distal outcomes is 
very similar.124 
93.  Australia's expert, Professor  Chaloupka, argues that Ajzen et al.'s analyses of the NTPPTS 
data fail to recognize that the TPP measures ' impact should be smaller for the less proximal 
outcomes when one looks at the impact in the overall sample of smokers and recent quitters, 
given that smokers and recent quitters for whom the most proximal outcome s were unaffected 
would not be expected to show any change in the less proximal outcomes.125 Professor  Chaloupka 
further contends that using an insensitive measure of consumption, whether or not the smoker 
reports consuming 20 or more cigarettes per day, app ears to be an inappropriate threshold given 
that the average daily consumption of smokers in Australia is well below this level. According to 
                                                
117 Scollo et al. 2015a also find that the introduction of TPP and enlarged GH Ws was associated with an 
increase in use of value brands and smaller increases in prices for value relative to premium brands.  
118 Ajzen et  al. argue that Scollo et al.'s conclusion that TPP and enlarged GHWs had no significant effect 
on the average number  of cigarettes consumed per day underreports additional results that were not 
statistically significant. According to Ajzen et  al., Scollo et al. 2015a reported on only one of the seven 
measures on smoking behaviours and the impact of TPP and enlarged GHW s on each of the six unreported 
variables, dealing with the percentage of daily or weekly smokers, quitting, and relapse was not statistically 
significant . See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  225-227. We note, however, that Ajzen 
et al. do not reassess the analysis by Scollo et al. 2015a of the impact of TPP and enlarged GHWs and tax 
increase on type of tobacco products and price.  
119 Wakefield et al. 2015, (Exhibit s AUS-206, DOM -306). 
120 We note that Ajzen et  al. also re -estimate the ir models by replacing the TPP measures dummies with 
a monthly time trend.  
121 Ajzen et  al. reach the same conclusion with respect to measures related to quitting and relapse, 
which were unreported by Scollo et al. 2015a. In particular, on quitting, Ajzen et al. conclude that there was no 
statistical change in the proportion of adult smokers that quit for more than one month or had successfully quit 
between baseline and follow -up. On relapse, Ajzen et al. conclude that there was no statistical change in the 
proportion of adult ex -smokers that relapsed, still abstained from smoking at follow -up or had stayed quit for 
more than one week at follow -up. See Ajzen et al. Data Report, (Exhibit DOM/IDN -2), paras.  221-224, 
Appendix  A, pp. 95-97). 
122 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  63-65, Appendix  IV.  
123 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), para. 90. 
124 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), paras.  50-54, Appendix  II. 
125 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 4. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  Professor  Chaloupka, based on the 2013 Australian National Drug Strategy Household Survey, 
average daily consumpti on of Australian smokers was 13.7 cigarettes per day.126  
3.1.7.3   Professor  Klick's report  
94.  Professor  Klick also reconsiders the NTPPTS data and estimated a negative binomial model of 
the average cigarettes consumption per day for daily smokers, smokers in general, o r all 
participants, controlling for a TPP measures  dummy variable, gender, age, education, 
socio-economic status and linear trend. The econometric analysis covers the period from 9 
April 2012 to 4 May 2014.127  
95.  Overall, Professor  Klick concludes that the TPP measures  did not reduce consumption levels. 
In some of Professor  Klick's specifications, the TPP measures ' impact on average cigarettes per 
day for daily smokers and smokers in general is positive and statistically significant. According to 
Professor  Klick, these results are consistent with his findings based on the Roy Morgan longitudinal 
survey data as well as with Scollo et al. 2015a's findings, which note that the NTPPTS data show 
no decline in self -reported smoking consumption associated with the TPP measures .128 
96.  As explained above, although Australia's expert, Professor  Chaloupka , does not address 
specifically Professor  Klick's analysis of cigarette consumption based on the NTPPTS data,  
Professor  Chaloupka generally contends that because of its cross -sectional nature, the NTPPTS 
data limits the ability to follow the impact of the TPP measures  through the pathway from its 
impact on the most proximal outcomes, like perceived appeal and noticing of the labels, through 
less proximal outcomes, such as incre ased interest in quitting, to the most distal outcomes, such 
as actual tobacco use behaviour.129 Professor  Chaloupka  further argues that the impact of the 
TPP measures  on more distal outcomes should be smaller when the analysis is based on the 
overall sample  of smokers and recent quitters because  smokers and recent quitters for whom the 
most proximal outcomes were unaffected by the TPP measures  would not be expected to exhibit  
any change in more distal  outcomes . 
3.1.8   Cancer Institute New South Wales Tobacco Tracki ng Survey  
97.  The Cancer Institute New South Wales Tobacco Tracking Survey (CITTS) is a weekly tracking 
telephone survey of smokers and recent quitters (who quit in the past 12 months).  
98.  Professor  Klick used the CITTS data to estimate a negative binomial model  of the average 
number of reported tobacco units smoked per week controlling for the TPP measures , annual time 
trend, gender, individual age fixed effect, week of survey fixed effects and location fixed effects. 
The econometric analysis covers the period f rom January  2009 to December  2014.130  
99.  Overall, Professor  Klick concludes that the TPP measures  led to an increase in cigarette 
consumption, irrespective of whether the TPP period is taken to start in December  2012 or 
October  2012.131 Professor  Klick argues that these results are consistent with the finding from his 
study of the Roy Morgan Research Survey, Nielsen, Aztec, IMS/EOS and NTPPTS data.  
100.  Although Professor  Chaloupka does not address directly Professor  Klick's analysis of cigarette 
consumption based o n the CITTS data, Professor  Chaloupka contends that Professor  Klick failed to 
appropriately account for the changes in the CITTS methodology that led to a greater number of 
younger people and males in the survey sample, both of which have relatively higher  smoking 
rates, leading almost certainly to biased estimates towards showing an increase in smoking 
following the change in method.132 
                                                
126 See Chaloupka Rebuttal Report , (Exhibit AUS -582), para. 8. 
127 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  44-51. 
128 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), paras.  47-51. 
129 See Chaloupka Rebuttal Report , (Exhibit AUS -582), paras.  2-5. 
130 See Klick Second Supplemental Rebuttal Report , (Exhibit HND -165), paras.  25-26. 
131 See Klick Second Supplemental Rebuttal Report , (Exhibit HND -165), paras.  25-32. 
132 See Chaloupka Second Rebuttal Repor t, (Exhibit AUS -590), paras.  26-27. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  3.2  Analysis by the Panel  
101.  Having determined above that  the wholesale market data presented to us suggests an 
acceleration of th e reduction in cigarette sales following the entry into force of the TPP measures , 
the question before us at this stage of our analysis is whether this acceleration may, in part or in 
whole, be attributed to the TPP measures .133 
102.  As explained above, while we acknowledge that no data are perfect, we agree with Australia 
that the IMS/EOS data is  the most suitable available market data submitted by the parties to 
analyse the TPP measures ' impact on cigarette sales because the data are available monthly for a 
long period of time before and after the introduction of the TPP measures . In addition, the 
IMS/EOS data display a relatively high correlation coefficient with respect to the Nielsen retail 
cigarette sales data.  
103.  We consider  that the other market data sources c onsidered by the experts  of the 
Dominican  Republic , Honduras and Indonesia  suffer from a number of drawbacks in comparison 
with the IMS/EOS data. In particular, the Nielsen and Aztec data are both only available for a 
shorter sample period. In addition, th e Aztec data are characterized by an increasing market 
coverage making it difficult to distinguish the impact of other factors.  
104.  At the outset, we note that for a given market dataset , the different conclusions reached by 
the parties regarding the impact o f the TPP measures  on cigarette sales stem from the fact that 
their experts  use different model specification (i.e. different independent variables (e.g. cigarette 
sales or per capita cigarette sales) and different explanatory variables included in the mod el), 
estimation approaches and in some cases sample period. Even among the experts  of the 
Dominican  Republic  and Honduras , different model specifications are used.134  
105.  As explained in our review of the econometric study on smoking prevalence  in Appendix  C, 
we consider that our task is not to conduct our own econometric assessment of the contribution of 
the TPP measures  on cigarette sales or cigarette consumption , but rather to  review the robustness 
of the econometric evidence submitted by the parties.  
3.2.1   IPE's  econometric results  
106.  A careful review of the econometric results based on the IMS/EOS data reported by IPE leads 
us to question their robustness on various grounds, many of which are similar to th ose considered 
in our review of IPE's analysis of smoking pr evalence in Appendix  C. In particular, we note that 
IPE's preferred specification of the modified trend analysis and the ARIMAX model include s both a 
price variable and a time trend variable, which happen to be highly collinear with each other. 
Multicollin earity appears to be even more marked when the model specification of the ARIMAX 
model includes five lags of the logarithm of per capita sales variables and of the price variable.135 
Furthermore, we note that IPE fails to take into account the potential impa ct of the TPP measures  
on tobacco prices. Similarly, IPE ignores the fact that the proportionality assumption underlying 
the use of the tax level in the analysis of the IMS/EOS data is rejected. Moreover, IPE does not 
address the fact that the price variab le and the tax level variable appear to be non -stationary. We 
note, however, that when the model includes the excise tax dummy variables, which were initially 
proposed by IPE itself in its first report but later rejected as inferior control variables, most  results 
                                                
133 We note that the parties did not present any graphical analysis of reported cigarette consumption 
based on survey data. That is why the conclusions we reached so far only apply to cigarette sales used as a 
proxy of cig arette consumption.  
134 For instance, IPE initially analysed the impact of the TPP measures on (the logarithm of) cigarette 
sales (see IPE Report , (Exhibit DOM -100)) but subsequently analysed the impact on (the logarithm of) per 
capita cigarette sales . See, e.g. IPE Updated Report , (Exhibit DOM -303). Similarly, IPE initially (see IPE Report , 
(Exhibit DOM -100)) control for excise tax increases by specifying dummy variables for each excise tax hike 
implemented during the sample period, while IPE later in the p roceedings (see , e.g.  IPE Second Updated 
Report , (Exhibit DOM -361)) consider the variable of tobacco price to be a better proxy for excise tax increases. 
Professor  Klick applies an IV estimation procedure to take into account the potential endogeneity of t he price 
variable with respect to cigarette sales while IPE and Professor  List do not address the potential endogeneity of 
the price variable . See Klick Rebuttal Report , (Exhibit HND -118), paras.  52-60.  
135 See IPE Second Updated Report, (Exhibit DOM -361), pp. 38-40; and IPE Third Updated Report , 
(Exhibit DOM -375), p p. 120-122. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  suggest the TPP measures  had a negative and statistically significant impact on wholesales 
cigarette sales.  
107.  We also question the validity of IPE's results based on the Nielsen data for the same reasons 
mentioned above, namely the use of the price  variable. In particular, we note that in some 
specifications of the modified trend analysis, which include a trend variable and the price variable 
in the past month, only a couple of month dummies are statistically significant.136 The same issue 
arises in s everal specifications of the ARIMAX model, where the time trend variable and the 
logarithm of cigarette sales per capita in the previous month are both not statistically significant, 
which would suggest that cigarette sales do not follow a dynamic pattern,  despite graphical 
evidence attesting to the contrary.137 We also note that some of the results of the modified 
analysis based on the procedure to compute the standard errors applied initially, but that were 
later rejected by the IPE, find a positive and sta tistically significant impact of the TPP measures  on 
cigarette sales.138 As explained in the review of the econometric studies on smoking prevalence, 
the choice of the maximum lag required to compute robust standard error is not well established in 
the statistics and econometric literature and it is therefore unclear to what extent these results 
would have change d for a range of different parameter values.139 We note also that in some 
specifications of the ARIMAX model based on the deseasonalized Nielsen data the estimated 
coefficient of the lagged dependent variable is negative and statistically significant, which is in 
contradiction with the results of the same model based on the Aztec data .140 In addition, as 
explained earlier, the sample period of the Nielsen  data is limited with only 35  observations 
available. Yet, a smaller sample size (i.e. number of observations) makes it, all else being equal, 
more difficult to estimate more accurately any impacts on cigarette sales.  
108.  We also question the IPE's results ba sed on the Aztec data.141 As explained above, the Aztec 
data are characterized by a growing market coverage, which, in our view, makes it more difficult 
to distinguish the impact of the explanatory variables, including the TPP measures  dummy 
variable, from t he growing market coverage. We note that the IPE proposed as a robustness check 
to adjust the Aztec data for the increasing market coverage. Yet, we note that the IPE did not 
provide any evidence that would justify why the transformed Aztec data would refl ect more 
accurately the actual fluctuation of the cigarette retail sales. In fact, we note that the correlation 
coefficient between the adjusted Aztec data and the Nielsen data or the IMS/EOS data is lower 
than with respect to the original Aztec data.142  
3.2.2   Professor  Klick's econometric results  
109.  Similarly, a review of the econometric results reported by Professor  Klick leads us to 
question their robustness. In particular, we note that in the first stage of the IV estimation of 
                                                
136 We also note that the estimated coefficients of the modified trend analysis based on the Nielsen data 
are different between IPE Second Updated Report  (Exhibit DOM -361), p p. 41-42 an d IPE Summary Report  
(Exhibit DOM -379), p. 54 and backup material, although this is the same model specification and sample 
period. We also note that the model specification with tax dummies based on the Nielsen data reported in 
Table 4.2 -2 in IPE Summary Report  (Exhibit DOM -379) actually do not include the December  2013 tax dummy 
variable . See IPE Summary Report , (Exhibit DOM -379), backup material.  
137 See IPE Second Updated Report , (Exhibit DOM -361), p p. 45-46. 
138 See IPE Second Updated Report , (Exhibit DOM -361), backup material.  
139 See the email exchange between the parties and STATA developers in the IPE Summary Report , 
(Exhibit DOM -379), p. 70; and Chipty Second Rebuttal Report, (Exhibit AUS -591), p p. B1-B2. 
140 See IPE Third Updated Report , (Exhibit DOM -375), pp. 76-77. In addition, we note that in some 
specifications of the modified trend analysis based on the deseasonalized Nielsen data  the estimated coefficient 
of the TPP measures is positive and statistically significant.  
141 We note that in a couple of spe cifications, which include , for instance , the tax level variable, the 
results find a positive and statistically significant TPP measures' effect. See IPE Summary Report , (Exhibit 
DOM-379), p. 54; and IPE Third Updated Report , (Exhibit DOM -375), p p. 124 and  127. Similar findings are 
sometimes found when the standard errors are computed applying the initial procedure proposed by IPE, 
namely the IVREG2 command, for the July 2008-May 2015 sample period . See IPE Second Updated Report , 
(Exhibit DOM -361), backup material.  
142 The weekly adjusted Aztec data were aggregated to monthly data by assuming that each weekly 
cigarette quantity can be evenly split for each day of the week. The correlation coefficient between the Nielsen 
data and the original Azt ec data is equal to 0.84, while the correlation between the Nielsen data and the 
adjusted Aztec data is equal to 0.71. The correlation between the original Aztec data and the IMS/EOS data is 
0.38, while the correlation between the adjusted Aztec data and t he IMS/EOS data is 0.32.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  Professor  Klick's difference -in-difference analysis based on the IMS/EOS data, surprisingly none of 
the 54  time-fixed effects are statistically significant. We further note that the second stage of the 
IV estimation is affected by the multicollinearity between the instrumented price variabl e and the 
linear trend variable.143 In addition, it is unclear how the standard error and confidence interval of 
the total effect of the TPP measures , composed of the direct estimated TPP measures ' impact on 
cigarette sales obtained in the second stage of th e procedure and the indirect estimated 
TPP measures ' impact on cigarette price obtained in the first stage of the procedure through the 
impact of cigarette price on cigarette sales, were calculated.  We also question the results of the 
difference -in-differe nce analysis based on the Nielsen -Aztec data because of the use of the price 
variable as well as the growing market coverage of the data.144 In particular, we note that in the 
first stage of the IV estimation procedure, multicollinearity appears to be high b etween the change 
in excise tax variable, the country -specific trend variable and the TPP measures  dummy variable. 
Similarly, the multicollinearity between the instrumented price variable, the country -specific trends 
and several time -fixed effects is parti cularly high in the second stage of the IV estimation 
procedure.145 In addition, we note that surprisingly most of the time -fixed effects in both first and 
second stages of the IV estimation procedure are not statistically significant. We also question the 
results of the model specification without New Zealand  counterfactual control, because the 
specification without a time trend finds a positive and statistically significant TPP measures ' effect 
and the specifications with (linear or quadratic) trend find that none of the explanatory variables, 
except the constant, are statistically significant.146  
110.  Similar to our conclusion regarding Professor  Klick's difference -in-difference analysis of 
smokin g incidence based on the Roy Morgan Research Survey data, we question the validity of the 
results on the reported number of cigarettes consumed on the same grounds, namely the 
pre-period of the analysis is not valid because Professor  Klick is unable to acc urately identify the 
respondents, who had noticed plain packs in the pre -period. Furthermore, we note that the 
instrumented tax used in the second stage of the IV  estimation procedure displays signs of 
multicollinearity with respect to the TPP measures  dummy and several time fixed effects.147  
111.  We also question Professor  Klick's results on the average reported number of cigarettes 
smoked per day based on the NTPPTS data because the majority of the results suggest that the 
TPP measures ' effect is positive and statistically significant.148 It is unclear to what extent this 
finding is the result of the model not being specified correctly given that Scollo et al. 2015a using 
the same NTPPTS data but applying a different model specification find that cigarette consum ption 
did not change during the first year of the implementation of the TPP measures .149 For instance, 
we note that unlike Scollo et al. 2015a, Professor  Klick does not control for the past three -month 
exposure to anti -smoking campaigns that aired on televis ion during the survey period.  
112.  Similarly, we question the validity of Professor  Klick's results on the reported number of 
tobacco units consumed per week based on the CITTS data . We note that most of the 49  fixed 
effects associated with the week of survey a re surprisingly not statistically significant in most 
specifications.150 In addition, as noted in Appendix  B, the survey data, such as the CITTS data, 
may, as suggested by Australia, be more suited to analysing the impact of the TPP measures  on 
                                                
143 Evidence of multicollinearity is confirmed by the variance inflation factors statistic.  
144 We note that the Aztec data used by Professor  Klick is available monthly, while IPE and Professor  List 
used the Aztec data reported at the weekly level.  
145 We also note that without the country -specific trend variable, the change in excise tax variable 
continues to display a high variance inflation factor statistics, when the country -specific trend variable is 
removed ( see Klick Fourth Supplem ental Rebuttal Report , (Exhibit HND -169), backup material).  
146 See Klick Third Supplemental Rebuttal Report , (Exhibit HND -166), backup material; and Klick Fourth 
Supplemental Rebuttal Report , (Exhibit HND -169), backup material. We also note that according t o standard 
unit root tests, the variable reporting the number of stores covered by the Aztec data is not stationary.  
147 We also note that in the first stage of the IV estimation procedure, surprisingly the majority of the 
time fixed effects are not statisti cally significant. The same issues arise in a couple of specifications considered 
in Professor  Klick's "crossfold validation". In one specification, the only variable statistically significant is the 
constant term or the level of cigarette sales in New Zealand (see Klick Rebuttal Report , (Exhibit HND -118), 
backup material).  
148 See Klick Supplemental Rebuttal Report , (Exhibit HND -122), p p. 19-21. 
149 See Scollo et al. 2015a, (Exhibits HND -133 DOM -237, DOM -311), p. ii73. 
150 See Klick Second Supplemental Rebuttal  Report , (Exhibit HND -165), p p. 11-12. We also note that 
most of the results suggest that the TPP measures' effect on reported tobacco units consumed per week is 
positive and statistically significant.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  proximal outc omes, such as appeal, GHWs and ability of the pack to mislead than more distal 
outcomes, such as smoking behaviours.  
3.2.3   Ajzen et al.'s econometric results  
113.  A careful review of Ajzen et al.'s analysis of the reported number of cigarettes smoked daily 
and the p roportion of smokers consuming at least a given number of cigarettes per day reported in 
the NTPPTS  data leads us to conclude that Ajzen et al. corroborate Scollo  et al.'s (2015a) findings 
that there were no changes in daily cigarette consumption during the first year of implementation 
of the TPP measures .151 We note, however, that in several specifications, Ajzen et al. do not 
analyse directly the quantity of cigarettes smoked reported by the respondent, but, instead, focus 
on the probab ility the respondent consumes a given number of cigarettes or more per day. We 
further note that Ajzen et al.'s quarterly results find that the probability of reporting smoking 20 
cigarettes or more per day increased in the first quarter following the intr oduction of the 
TPP measures .152 Yet, Ajzen et al. do not provide any explanation that would explain such a result.  
114.  The review of Ajzen et al.'s analysis of the number of cigarettes smoked per day reported in 
the ITC dataset also raises a number of questions . At the outset, we note that Ajzen et al. do not 
analyse directly the number of cigarettes smoked per day, but a categorical variable distinguishing 
between 0 -10, 11 -20, 21 -30 and more than 30 cigarettes per day. We further note that the model 
specificati on does not control for anti -smoking advertising in mass media, as acknowledged by 
Ajzen et al.153, and for cigarette costliness. It is therefore unclear if the results would be similar if 
these explanatory variables had been taken into account. In addition,  we note that the results of 
the weighted prevalence estimates are based in a specification in which only a few variables, 
namely the variables for high education level, quit attempt and survey mode , are statistically 
significant, besides the constant.154 It is therefore unclear why most explanatory variables in the 
model considered by Ajzen et al. are not statistically significant.  
3.2.4   Dr Chipty's econometric results  
115.  Turning to the econometric results analysing wholesale cigarette sales based on the IMS/EOS 
data submitted by Australia's expert, Dr Chipty, we note that some concerns that we raised 
regarding the experts of the Dominican  Republic 's, Honduras' s and Indonesia 's approaches and 
results of the market data have been to some extent addressed by Dr Chipty. In particular, Dr 
Chipty specifies excise tax increases dummy variables and thus avoids the problems of 
endogeneity associated with the inclusion of the price variable as well as the unit root problem of 
the price or tax level variables. We further note th at part of Dr Chipty's model specification is 
based on the first specification proposed by the IPE but modified to account for strategic inventory 
management and the 2006 GHWs regulation.  
116.  A careful review of Dr Chipty's econometric results further shows th at the negative and 
statistically significant impact of the TPP measures  on wholesale cigarette sales is robust to 
alternative specifications, including different TPP starting date (October, November  and 
December  2012), and to Professor  List's procedure to  compute standard errors.155 We note 
however that the TPP measures ' effects are no longer statistically significant when the set of tax 
hikes dummies are replaced by a tax levels variable. Yet, we note as explained earlier that 
                                                
151 We note that the model specification considered by Ajzen et  al. is different from the one developed 
by Professor  Klick. For instance, Ajzen et  al. include dumm y variables for two age groups, while Professor  Klick 
includes a single age variable. Ajzen et  al. also includes dumm y variables for different groups of education and 
socio-economic status, respectively, while Professor  Klick includes a single variable for education and another 
variable for socio -economic status.  
152 See Ajzen et al. Data Rebuttal Report, (Exhibit DOM/IDN -6), p. 22. 
153 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), para. 18. 
154 See Ajzen et al. Second Data Report, (Exhibit DOM/IDN -4), backup material. When the sample is 
restricted to participants involved in the pre - and post -implementation surveys,  the only statistically significant 
variables are two age categories, quitting attempt and the constant. In the weighted prevalence estimates 
results, the only statistically significant variables are two age group categories . Ajzen et al. Data Rebuttal 
Report, (Exhibit DOM/IDN -6), backup material.  
155 See Chipty Surrebuttal Report, (Exhibit AUS -586), p. 40; and Chipty Second Rebuttal Report, 
(Exhibit AUS -591), p p. 19-20, 33, and D1. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  specification testing suggests  tax levels are not appropriate in the model specification.156 
Furthermore, the tax levels variable is likely to be non -stationary.  
117.  Overall, based on the most recent econometric evidence submitted by Australia, there is 
some econometric evidence suggesting that TPP and enlarged GHWs contributed to the reduction 
in wholesale cigarette sales in Australia.157  
4  EVIDENCE RELATING TO  THE EVOLUTION OF IMPORTS  OF CIGARS  
118.  The parties did not present an econometric analysis of the post -implementation impact of 
the TPP measures  on cigar consumption. Rather, the parties addressed a graphical and descriptive 
analysis of trade data.  
119.  According to data analysed by Australia158, the value and volume of Australian cigar and 
cigarillo imports shows fluctuations within a set range th roughout the period between March  2005 
and March  2015.159 Australia notes, in any event, that the values represented in this dataset are 
"customs values", and may not represent the actual value of the products.160 
120.  Australia also submits the HoustonKemp Report161, which notes that all cigars and cigarillos 
sold in Australia are currently imported.162 The HoustonKemp Report  concludes that imports of 
cigars and cigarillos have fluctuated over time and have fallen significantly since 20 [[***]]: annual 
imports of cigars and cigarillos fell by [[***]]% from 20 [[***]] to 20 [[***]], following the 
introduction of the TPP measures  in December  2012, whereas annual import volumes fell at a 
faster rate prior to the TPP measure s being introduced, by [[***]]% from 20 [[***]] to 
20[[***]].163 As regards monthly cigar and cigarillo imports to Australia, the HoustonKemp Report  
finds that the level of monthly imports varies substantially, although, on average, these have been 
falling since the TPP measures  came f ully into force. The HoustonKemp Report  adds that some of 
the increases in imports for a particular month coincide with the introduction of the TPP measures  
and increases in excise tax rates.164  
121.  Based on data from the International Trade Centre's trade stat istics database, 
the complainants argue that cigar imports to Australia have remained relatively stable over the 
period 2010 -2014, and point out that the difference between the evolution of cigarette and cigar 
imports to Australia can be explained by the f act that the reduced -fire risk requirements did not 
apply to cigars.165 
122.  As regards large cigars (i.e. excluding cigarillos and little cigars), the HoustonKemp Report  
adds that total imports into Australia from all countries have varied within the range of 
[[***]],000 kg to [[***]],000 kg from 20 [[***]] to 20 [[***]], and the level of imports fell from 
20[[***]] to 20 [[***]], immediately before the TPP measures  came into force, but have risen in 
20[[***]].166 The HoustonKemp Report  concludes that "[i]t follows that there is no evidence of the 
TPP measure[s] causing a fall in the imports of large cigars".167  
                                                
156 See Chipty Third Rebuttal Report, (Exhibit AUS -605), paras.  27-29. 
157 See Ch ipty Third Rebuttal Report, (Exhibit AUS -605), p p. 22 and 51; and Chipty Second Rebuttal 
Report, (Exhibit AUS -591), p p. 33, D1, and D2. 
158 Supplementary Graphs, Import Volumes, Value and Share of the Market, ( Exhibit AUS -512).  
159 Supplementary Graphs, Import Volumes, Value and Share of the Market, ( Exhibit AUS-512), Fig ures 
7, 8, 13 , and 14.  
160 Supplementary Graphs, Import Volumes, Value and Share of the Market, ( Exhibit AUS-512), Fig ures 
7, 8, 13 , and 14.  
161 HoustonKemp Report , (Exhibit AUS -19) (SCI) . 
162 HoustonKemp Report , (Exhibit AUS -19) (SCI) , p. 45. 
163 HoustonKemp Report , (Exhibit AUS -19) (SCI), p. 45. 
164 HoustonKemp Report , (Exhibit AUS -19) (SCI), p. 45. 
165 Dominican  Republic 's response to Panel question No. 5. See also Hondura s's response to Panel 
question No. 5; Cuba's response to Panel question No. 5 (annexed to its response to Panel question No. 138); 
and Indonesia's  response to Panel question No. 5. 
166 HoustonKemp Report , (Exhibit AUS -19) (SCI), p. 47. 
167 HoustonKemp Report , (Exhibit AUS -19) (SCI), p. 47. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  123.  We have difficulty drawing conclusions from the above evidence on the evolution of 
Australian cigar, large handmade ( LHM) cigar, or cigarillo consumption and imports.  Based on the 
above evidence, we conclude that, despite fluctuations, overall imports of cigars and cigarillos 
have experienced a downward trend in recent years. However, it is unclear whether and to what 
extent this i s attributable to the TPP measures . 
124.  Some of the evidence submitted by the parties relates to cigar imports per complainant. In 
particular, the HoustonKemp Report  submitted by Australia explains that the complainants have 
accounted for a small proportion of  Australia's annual imports of cigars and cigarillos in general. 
From 19 [[***]] to 20[[***]], Cuba accounted for between [[***]]% and [[***]]% of total annual 
imports, the  Dominican  Republic  accounted for between [[***]]% and [[***]]% of imports, and 
the other complainants collectively accounted for less than [[***]]% of imports.168 
125.  Furthermore, the Panel explored with Cuba, Honduras, and the Dominican  Republic  whether 
they had data on cigar sales to Australia and how these were affected by the TPP measures . Cuba 
does not provide a direct answer to the Panel's question concerning how volumes and values of 
sales of Cuban cigars in Australia, including Cuban LHM cigars, and Cuban LHM cigars carrying the 
Habanos GI and/or the Cuban Government Warranty Seal might have changed as a result of the 
TPP measures , and whether the price of cigars in the above product categories has changed as a 
result of the TPP measures.169 Cuba states that a reply to this question would require access to the 
data on retail sales of Cuban LHM cigars in Australia as well as other markets for purposes of 
comparison, and these data would have to be analysed and compared so as to take account of the 
specific features of eac h market (such as the level of taxes) in order to draw reasonable 
conclusions; however, "[a]t present, Cuba does not have access to such data".170 Australia points 
out that Cuba's response does not provide the Panel with any information or evidence about the  
volume and value of sales of Cuban cigars in Australia following the introduction of tobacco plain 
packaging.171  
126.  Nonetheless, Cuba provides data as regards sales volumes of Cuban LHM cigars in Australia, 
namely data relating to wholesale sales of LHM cigars in Australia between January  2009 and 
July 2014 by Pacific Cigar Company (PCC).172 Cuba considers such data as a relevant measure of 
consumption of LHM cigars as it is estimated that PCC have held a market share of 
approximately  70% of total LHM cigar sales in Australia over the relevant period.173 According to 
Cuba, these data show that monthly sales of LHM cigars in Australia largely fluctuated within a set 
range of sticks per month for the majority of the relevant period, rising to the upper end of this 
range from 2013 onwards.174 Cuba adds that there does not appear to have been any decrease in 
monthly sales of LHM cigars after December  2012 when the TPP measures  were introduced, 
not least when the post -implementation sales volumes are compared to monthly sa les in the two 
years immediately prior to the introduction of the TPP measures .175 According to Cuba, indeed, 
it appears that sales of LHM cigars in Australia have marginally increased since December  2012.176 
Cuba draws similar conclusions from the same sales information in half -yearly, rather than 
monthly, format. According to Cuba, the same sales data in half -yearly format illustrate the 
consistency of sales volumes over time and the apparent increase in sales of LHM cigars in the 
post-implementation period.177 
127.  Australia points out that the HoustonKemp Report  demonstrates that although overall 
volumes of cigar and cigarillo imports into Australia have been declining since the introduction of 
tobacco plain packaging, in 20 [[***]] imports of Cuban cigars into Aust ralia "rose to their highest 
level since 19 [[***]], after the TPP measure was introduced".178 Indeed, the HoustonKemp Report  
                                                
168 HoustonKemp Report , (Exhibit AUS -19) (SCI), p p. 46-47. 
169 Cuba's response to Panel question No. 193. 
170 Cuba's response to Panel question No. 193. 
171 Australia's comments on Cuba's response to Panel question No. 193. 
172 Cuba's first written submission, paras.  159-161. 
173 Cuba's first written submission, para. 159. 
174 Cuba's first written submission, para. 160. 
175 Cuba's first written submission, para. 160. 
176 Cuba's first written submission, para. 160. 
177 Cuba's first written submission, para. 161. 
178 Australia's comments on Cuba's responses to Panel question Nos. 192, 194, and 195 (citing 
HoustonKemp Report , (Exhibit AUS -19) (SCI), p. 47). WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  finds that approximately [[***]],000 kg of cigars and cigarillos were imported from Cuba each 
year from 20 [[***]] to 20[[***]]; however, in 20 [[***]], Cuba's imports into Australia rose to the 
highest level since 19 [[***]], after the TPP measures  were implemented.179 As regards large cigar 
imports into Australia (i.e. excluding cigarillos and other cigars), the  HoustonKemp Report  finds 
that Cuba's share has increased from 19 [[***]] to 20[[***]].180 
128.  Based on the data concerning PCC and the data available in the HoustonKemp Report , we 
conclude that there has been an increase in the volume of Cuban LHM cigar and cigar/cigarillo 
sales in Au stralia. Of note, the underlying data is limited and indirect in that it does not provide 
any information on the factors d riving the evolution of sales of Cuban cigars in Australia or address 
the role of the TPP measures  in that regard.  
129.  As regards sales of  Dominican  Republic  cigars in Australia, the Dominican  Republic  notes, as 
a preliminary matter, that general international trade statistics that capture trade reported by 
domestic customs authorities, such as the UN Comtrade Database, do not provide a reli able source 
of information. In particular, for the purposes of tracking Dominican  Republic  cigar sales in 
Australia, this data is not helpful for a number of reasons, not least because it can mis -specify the 
true country of origin if a company is domiciled  in a third country and because Dominican  Republic  
cigars may be mis -classified if the product is imported into, and then re -exported by, a third 
country (e.g. Belgium, the Netherlands, Singapore or Hong Kong).181  
130.  Rather, the Dominican  Republic  submits data  from the Dominican  Republic 's cigar industry 
for sales of Dominican  Republic  cigars in Australia.182 According to the Dominican  Republic , this 
data shows that following the implementation of the TPP measures , there has been a decline in 
sales of Dominican  Republic  cigars, which are predominantly premium hand -rolled products.183 The 
Dominican  Republic  notes that it has not been able to obtain data regarding the price and value of 
Dominican  Republic  cigar sales in Australia following the imposition of the TPP measures .184 
131.  Australia responds that the Dominican  Republic 's data show that the volume of sales of 
Dominican  Republic  cigars in Australia has declined in the period following the introduction of 
tobacco plain packaging; however, the Dominican  Republic  provides no evidence of the impact of 
the TPP measures  on the value and prices of sales of Dominican  Republic  cigars in Australia.185 
Further, Australia notes, although requested by the Panel, the Dominican  Republic  has not 
provided any information on the imp act of the measure on the subset of cigars that were 
permitted to use the GI "Cigarro  Dominicano" prior to the implementation of tobacco plain 
packaging."186 
132.  We agree with the Dominican  Republic  that the UN Comtrade Database has limitations, for 
establishing  export patterns from an individual exporter. We also concur with the limitations of the 
Dominican  Republic 's sales data highlighted by Australia. Importantly, none of the data explains 
the role of the TPP measures  in any changes to sales of Dominican  Republic cigars in Australia.  
133.  Based on data from the UN Comtrade Database, Honduras argues that the volumes and 
values of Honduran cigars imported into Australia have "drastically decreased".187 According to 
Honduras, "at face value", the value and volume of tra de in Honduran cigars to Australia has 
"drastically decreased" as there has been "a drop by 98%" between 2010 and 2014.188 
Honduras  adds that, in terms of the combined value and quantity of imports of Honduran cigars 
into Australia, if one compares 2010 and 2011 to 2013 and 2014 (i.e. discounting the year of 2012 
as the year when plain packaging was introduced), import values have decreased by 91% and 
import volume by 97%.189 Honduras points out that in the same period, its exports of cigars to the 
                                                
179 HoustonKemp Report , (Exhibit AUS -19) (SCI), p. 47. 
180 HoustonKemp Report , (Exhibit AUS -19) (SCI), p. 47. 
181 Dominican  Republic 's response to Panel question No. 194. 
182 Dominican  Republic 's response to Panel question No. 194. 
183 Dominican  Republic 's response to Panel question No. 194. 
184 Dominican  Republic 's response to Panel question No. 194. 
185 Australia's comments on Cuba's response to Panel question No. 194. 
186 Australia's comments on Cuba's response to Panel question No. 194. 
187 Honduras's response to Panel question No. 195. 
188 Honduras's response to Panel  question No. 195. 
189 Honduras's response to Panel question No. 195. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  world substa ntially increased, which confirms that there was not a general downward trend of 
Honduran cigar exports in the period 2010 to 2014 but that the drastic decline is specific to the 
Australian market with tobacco plain packaging.190 
134.  Australia notes that Hondura s relies on the UN Comtrade Database, which the 
Dominican  Republic  has qualified as "unreliable" and "not helpful"191, and does not provide any 
data on the prices of its cigars in the Australian market.192 Australia adds that notwithstanding the 
disagreement a mong Honduras and the Dominican  Republic  as to the reliability of the 
UN Comtrade Database, the data presented by Honduras appears to show a rapid decline in sales 
of Honduras cigars in Australia beginning in 2012 (the year that the TPP measures  were 
introduced), and such decline in imports is consistent with Australia's argument that the packaging 
changes introduced in late 2012 led to a decline in cigar smoking prevalence.193 
135.  As noted, we agree with Australia and the Dominican  Republic  concerning the serious 
limitations of the UN Comtrade Database highlighted by the Dominican  Republic  for establishing 
total imports (direct and indirect) from an individual exporting country. Accordingly, we have 
difficulty drawing conclusions from such d ata specifically for all imports (direct and indirect) of 
Honduran cigars to Australia.  
136.  In the light of the above, we conclude that the evidence before us on cigars, cigarillos and 
LHM cigars allows us to draw limited conclusions on the evolution of certa in consumption trends.  
We note that despite fluctuations, overall imports of cigars and cigarillos to Australia have followed 
a downward trend in recent years.  However, we have no evidence to link these conclusions to the 
TPP measures  that would allow us t o draw conclusions on the basis of this evidence on the  effect 
of the TPP measures  on cigar consumption in Australia.  
5  OVERALL CONCLUSION O N POST -IMPLEMENTATION EVIDE NCE ON TOBACCO 
PRODUCT SALES VOLUMES  
137.  Overall, based on the most recent data available and evidence submitted by the parties, we 
find that:  
a. There is some evidence that cigarette sales in Australia continued to decrease following 
the introduction of the TPP measures . 
b. The downward trend in cigarette sales in Australia appears to have accelerated in the 
post-TPP period.  
c. Although it is impossible to distinguish between the impact of TPP and enlarged GHWs, 
there is some econometric evidence suggesting that the TPP measures , in combination  
with the enlarged GHWs implemented at the same time,  contributed to the reduction in 
wholesale cigarette sales, and therefore cigarette consumption, after their entry into 
force.  
d. The evidence before us on the evolution of consumption of cigars in the post -TPP period 
is more limited and does  not allow us to draw clear conclusions on the effect of the 
TPP measures  on cigar consumption in Australia.  
138.  We note, however, that no post -implementation empirical evidence has been presented to us 
on the impact of the TPP meas ures on cigars and cigarillos consumption.  
 
                                                
190 Honduras's response to Panel question No. 195. 
191 Australia's comments on Cuba's response to Panel question No. 195 (referencing 
Dominican  Republic 's response to Panel question No. 194).  
192 Australia's comments on Cuba's response to Panel question No. 195. 
193 Australia's comments on Cuba's response to Panel question No. 195. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  APPENDIX  E: 
 
POST -IMPLEMENTATION EVIDE NCE ON DOWNWARD SUBS TITUTION  
IN THE CIGARETTE  MARKET  
1.  The Dominican  Republic  and Indonesia submitted empirical statistical and econometric studies 
analysing the impact of the TPP measures  (and enlarged GHWs) on the change in consumption 
patterns from premium to lower -priced brands.1 Different terms have been used to refer to this 
phenomenon: downward substitution2 or downtrading.3  
2.  One of the only points of agreement among the parties is t hat it is not possible, on the basis of 
the available data, to distinguish between the impact of plain packaging and the impact of the 
enlarged GHW s on cigarette sales or consumption, because both measures were implemented at 
exactly the same time.4 Unless  specified otherwise, the impact of plain packaging in this section 
therefore refers to the impact of plain packaging and enlarged GHWs . 
3.  The Dominican  Republic  and Indonesia  argue that all the empirical statistical and econometric 
studies undertaken by the ir experts, the IPE (for the Dominican  Republic ), and Professor  List (for 
the Dominican  Republic  and Indonesia), point to the fact that the TPP measures  led consumers to 
replace higher -priced cigarettes with low -priced cigarettes and to shift their preferences from 
higher -priced to low -priced cigarettes.5 
4.  Similar to the discussion on smoking prevalence and cigarette consumption, we note that the 
evidence presented to us to analyse substitution can be grouped in three main approaches, that 
are reviewe d separately next:  
 First, the Dominican  Republic  and Indonesia have submitted descriptive statistics 
analysis aimed at determining whether the shares of higher - to low -priced cigarettes 
sales and smokers have increased following the implementation of the TPP measures ; 
 Second, the Dominican  Republic  and Indonesia have submitted statistical analysis to 
determine whether there was a break in the trend in downward substitution following the 
implementation of the TPP measures , and in particular, whether the redu ction in the 
shares of higher - to low -priced cigarette sales and smokers have accelerated following 
the implementation of the TPP measures ; 
 Finally, some of the parties ha ve submitted econometric analyse s to determine whether 
the TPP measures  have contribu ted to the downward trend of the relative quantities and 
preferences by isolating and quantifying the different factors that can explain the 
evolution of the share of sales volume of higher - to low -priced cigarettes as well as the 
evolution of the share of  higher -priced cigarette smokers relative to smokers of 
low-priced cigarettes.  
5.  Unlike the discussion on smoking prevalence and cigarette consumption, however, Australia did 
not engage in estimating the impact of plain packaging on downward substitution in cigarettes . 
Australia argues that the Dominican  Republic  and Indonesia have failed to demonstrate that any 
                                                
1 See IPE Report , (Exhibit DOM -100); IPE Updated Report , (Exhibit DOM -303); IPE Second U pdated 
Report, (Exhibit DOM -361); IPE Third Updated Report , (Exhibit DOM -375); IPE Summary Report , (Exhibit 
DOM-379); and List Rebuttal Report, (Exhibit DOM/IDN -3). 
2 See IPE Report , (Exhibit DOM -100), p p. 16-17. 
3 See IPE Updated Report , (Exhibit DOM -303), paras.  212 and 228-235; and List Rebuttal Report, 
(Exhibit DOM/IDN -3), paras.  104 and 111.  
4 See Australia's first written submission, para. 518; Dominican  Republic 's response to Panel question 
No. 8, para. 61; Honduras's response to Panel question No. 8; and Indonesia's response  to Panel question 
No. 8, para. 8. 
5 See IPE Report , (Exhibit DOM -100), paras.  4 and 61 -67; IPE Updated Report , (Exhibit DOM -303), 
paras.  176-180; IPE Second Updated Report , (Exhibit DOM -361), paras.  43-59; IPE Third U pdated Report, 
(Exhibit DOM -375), paras. 23 and 245 -258; IPE Summary Report , (Exhibit DOM -379), paras.  43-45; and  List 
Rebuttal Report, (Exhibit DOM/IDN -3), paras.  104-111. WT/DS435 /R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  downward substitution effects that have occurred in the Australian market are attributable to the 
TPP measures  and not to other factors.6 
1  WHETHER DOW NWARD SUBSTITUTION I N CIGARETTES  INCREASED FOLLOWING THE 
IMPLEMENTATION OF TH E TPP MEASURES  
6.  Two market data sources tracking cigarette sales volumes in Australia were used by the 
experts of the Dominican  Republic , Honduras and Indonesia to compute the shar e of sales volume 
of higher - to low -priced cigarettes: (1)  In-Market -Sales/Exchange of Sales (IMS/EOS) data and 
(2) Aztec data. In addition, the experts of the Dominican  Republic  and Indonesia used the Roy 
Morgan Single Source (RMSS) survey data to compute  the difference between the share of 
higher -priced cigarette smokers and the share of low -priced cigarette smokers.  
1.1  Datasets and related studies  
1.1.1   In-Market -Sales/Exchange of Sales  
7.  The IPE classifies monthly tobacco product sales from manufacturers to whole salers and 
retailers reported in the IMS/EOS data by classifying the cigarette market into two distinct price 
segments, derived from information provided from the Aztec data: (1)  higher -priced cigarettes 
comprising "premium" and "mid -price" factory -made ci garettes, and (2)  low-priced cigarettes 
comprising "low -price" and "deep discount" factory -made cigarettes and cigarette stick equivalents 
(CSE) from fine -cut tobacco.7 
Figure E. 1: Monthly Sales Volumes of Higher - and Low -Priced  Sticks Based  on IMS/EOS  
Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of plain packaging and enlarged GHWs.  
Source :  IPE Updated Report, (Exhibit DOM -303), p. 73. 
                                                
6 Australia's first written submission, paras.  542-546. 
7 See IPE Report , (Exhibit DOM -100), p. 76. 
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  8.  The IPE notes, as depicted in Figure E.1 , that sales volumes of both higher - and low -priced 
cigarettes are m arked by strong seasonal patterns. According to the IPE the overall relationship 
between sales of higher -priced and low -priced cigarettes changes over time and is not linear.8 In 
particular, between 2002 and up to 2008, sales volumes for higher -priced cigarettes and 
low-priced cigarettes remained relatively stable, with volumes of higher -priced products being 
more than twice as large as those for low -priced products. From mid -2007 on, sales volumes of 
higher -priced cigarettes started to decline, but vol umes of low -priced goods remained largely 
stable. From late 2012 onwards and following the entry into force of the TPP measures , volumes of 
low-prices sticks began to increase, and from late 2013 on, more low -priced cigarettes were sold 
than higher -priced cigarettes.  
9.  The IPE further compares the evolution of the ratio of higher - to low -priced cigarettes with 
respect to the ratio of cigarettes' average high prices to low prices, as shown in Figure E.2 .9 The 
IPE notes that the relative sales volumes were quite stable up to mid -2007, with a weak linear 
downward trend. During the same period, relative prices increased only slightly. From mid -2007 
onwards, relative prices started to increase much faster than before, meaning that higher -priced 
cigarettes became more and more expensive relative to low -priced alternatives. Coinciding with 
the relative price increase (from mid -2007 onwards), relative quantities (quantities of 
higher -priced sticks relative to low -priced sticks sold) started to decrease from mid -2007. Since 
the introduction of the TPP measures , the sales ratio of higher - to low -priced cigarettes continued  
to decrease, while the relative prices continue d to increase.10 
Figure E. 2: Monthly Sales Volumes Ratio of Higher -to Low -Priced Sticks and Ratio of 
Average Higher  to Low Prices Based on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tob acco per stick. The vertical dashed line indicates the 
introduction of plain packaging and enlarged GHWs.  
Source :  IPE Updated Report, (Exhibit DOM -303), p. 75. 
                                                
8 See IPE Report , (Exhibit DOM -100), p. 80. 
9 We note that Professor  List reports also the evolution of the ratio of higher - to low -priced cigarettes 
based on the IMS/EOS data . List Rebuttal Report, (Exhibit DOM/IDN -3), pp. 27-28. We note, however, that 
unlike IPE, Professo r List does not include the sales of RYO tobacco in his analysis of the Aztec data.  
10 See IPE Updated Report , (Exhibit DOM -303), p p. 192-194. 
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  1.1.2   Aztec Scanner  
10.  The experts of the Dominican  Republic  and Indonesia do not present a graphical analysis of 
downward substitution using the Aztec data. Instead, the IPE and Professor  List use the Aztec 
scanner data in the context of econometric studies, which will be reviewed in detail next. But in 
that context, Professor  List pre sents the evolution of the ratio of higher - to low -priced cigarettes 
based on the Aztec data, which, as shown in Figure E.3 , displays a downward trend and continues 
to decrease in the post -TPP period.11 
Figure E. 3: Weekly Sales Volumes Ratio of Higher -to Low -Priced Sticks 
Based  on Aztec  Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dashed line indicates the 
introduction of plain packaging and enlarged GHWs.  
Source :  List Rebuttal Report , (Exhibit DOM/IDN -3), p. 29. 
 
1.1.3   Roy Morgan Single Source  
11.  In addition to market data, the IPE considers the RMSS survey data and presents, as shown in 
Figure E.4 , the evolution of the difference between the share of smokers preferring brands from 
the higher -priced segment and the share of smokers preferring brands from the low -priced 
segment.12 According to the IPE, the share of higher -priced cigarette smokers relative to smokers 
of low -priced cigarettes has been declining, with very little development in relative brand 
preferences and relative pric es between 2002 up to mid -2007. Thereafter, relative prices rose and 
relative brand preference declined, implying an inverse relationship between relative brand 
preferences and relative prices between mid -2007 and late 2012. In the post -TPP period, relativ e 
brand preference has continued to decline.13 
                                                
11 See List Rebuttal Report, (Exhibit DOM/IDN -3), pp. 28-29. We note, however, that unlike IPE, 
Professor  List does  not include the sales of RYO tobacco in his analysis of the Aztec data.  
12 See IPE Report , (Exhibit DOM -100), p. 90; and IPE Updated Report , (Exhibit DOM -303), para. 89. 
13 See IPE Report , (Exhibit DOM -100), p p. 87-90; and IPE Updated Report , (Exhibit DOM -303), 
paras.  217-221. 
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  Figure E. 4: Monthly Brand Preference for Higher -Priced versus Low -Priced Brands and 
Ratio of Average Higher  to Low Prices Based on RMSS Data  
 
Note:  The vertical dashed line indicat es the introduction of plain packaging and enlarged GHWs.  
Source :  IPE Updated Report, (Exhibit DOM -303), p. 89. 
 
1.2  Analysis by the Panel  
12.  As in the case of analysing smoking prevalence and cigarette consumption, we acknowledge 
the importance of analysing the  trends of the ratio of higher - to low -priced cigarettes and the 
difference in share of higher -priced cigarette smokers relative to smokers of low -priced cigarettes 
with the most recent available data. As explained in the analysis of cigarette consumption,  we 
recognize that there is no perfect market sales data in terms of market coverage, frequency 
(weekly, monthly or annually) and period covered.14 We also note, at the outset, that neither the 
IPE nor Professor  List subsequently updated their graphical ana lysis of the ratio of higher - to 
low-priced cigarettes with more recent data.  
13.  After a careful review of the most recent available IMS/EOS and Aztec datasets, we notice 
that despite fluctuations, the ratio of higher - to low -priced cigarettes sales has expe rienced a 
downward trend in the period following the introduction of plain packaging, as depicted in  
Figure  E.5.15 Conversely, we note that the ratio of the average higher -segment prices to 
low-segment prices has on average increased over the same period. Furthermore, we note that 
the co -relation between the ratio of higher - to low -priced cigarettes sales and the rati o of the 
average higher -segment prices to low -segment prices is strong and negative.  
                                                
14 See IPE Updated Report , (Exhibit DOM -303), para. 137; and IPE Summary Report , (Exhibit 
DOM-379), paras.  131-133. In particular, the IMS/EOS data cover sales from manufacturers to wholesalers 
and retailers, while the Aztec data cover  sales from retailers to consumers. Similarly, the Aztec dataset is only 
available from 27 July 2008 to 27 September  2015, while the IMS/EOS data cover a larger sample period, from 
January  2000 to September  2015. Likewise, the IMS/EOS data cover almost 99%  of the Australian market, 
while the Aztec data cover 67% of the Australian market.  
15 The weekly Aztec data were aggregated to monthly data by assuming that each weekly cigarette 
quantity can be evenly split for each day of the week.  
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  Figure E. 5: Graphical Assessment of Monthly Sales Volumes Ratio of Higher - to 
Low-Priced Sticks Based on IMS/EOS and Aztec Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of plain packaging and enlarged GHWs.  
Source :  IPE Third U pdated Report , (Exhibit DOM -375),  backup material.  
 
14.  The evolution of the shares of smokers preferring higher -priced brands and those preferring 
low-priced brands, as depicted in Figure E.6 , leads us to qualify our previous conclusion. In 
particular, we note that the share of smokers preferring higher -priced brands has decreased, while 
the share of smokers preferring low -priced brands has experienced a small but positive increase. 
In add ition, the share of smokers preferring higher -priced brands has, on average, decreased at a 
much faster rate than the share of smokers preferring low -priced brands has increased, confirming 
the decrease in smoking prevalence.16 This explains why, as shown i n Figure E.7 , the difference 
between the shares of smokers preferring higher -priced brands and low -priced brands has, on 
average, continued to decrease after the introduction of the TPP measures , such tha t in May, 
June and September  2015, the share of smokers preferring low -priced brands is higher than the 
share of smokers preferring higher -priced brands.  
15.  We further note that the downward trend of relative preferences based on the RMSS data is 
slightly mo re pronounced that the downward trend of relative quantities based on the IMS/EOS 
and Aztec data. We next review whether the downward trend of the ratio of higher - to low -priced 
cigarettes sales and the difference between the shares of smokers preferring h igher-priced brands 
and those preferring low -priced brands have accelerated in the post -TPP period.  
 
 
                                                
16 The growth rate diff erential between the shares of smokers preferring higher -priced brands and those 
preferring low -priced brands is equal to 2.7 for the period from June 2001 to September  2015. The growth rate 
differential is equal to 2.3 for the period from June 2007 to September  2015. See IPE Third Updated Report , 
(Exhibit DOM -375), back -up material.  
11.051.11.151.21.251.3
0.40.91.41.92.42.93.4
Jan-00
May-00
Sep-00
Jan-01
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Relative pricesRelative quantities
Year
Ratio of high-priced segment (FMC) to low-priced segment (FMC and CSE) in billions sticks based on IMS/EOS data
Ratio of high-priced segment (FMC) to low-priced segment (FMC) in billions sticks based on Aztec data
Ratio of average high-segment prices to low-segment pricesWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-7 - 
 
  Figure E. 6: Graphical Assessment of Brand Preference Based on RMSS Data  
 
Note:  The vertical dashed line indicates the introduction of plain packaging and enlarged GHWs.  
Source :  IPE Third Updated Report , (Exhibit DOM -375), back -up material.  
Figure E. 7: Graphical Assessment of Difference in Brand Preference Based on RMSS Data  
 
Note:  The vertic al dashed line indicates the introduction of plain packaging and enlarged GHWs.  
Source :  IPE Third Updated Report , (Exhibit DOM -375), back -up material.  
3.05.07.09.011.013.015.017.0
Jun 2001
Mar 2002
Dec 2002
Sep 2003
Jun 2004
Mar 2005
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Sep 2006
Jun 2007
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Dec 2008
Sep 2009
Jun 2010
Mar 2011
Dec 2011
Sep 2012
Jun 2013
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Sep 2015Share of smokers in population (%)
Year
Preference for low-priced brands Preference for high-priced brands
1.081.151.221.29
-0.0500.050.10.15
Jun 2001
Mar 2002
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Relative pricesRelative brand preferences
Year
Difference between preference for higher-priced FMC and low-priced FMC
Ratio of average high-segment prices to low-segment pricesWT/DS435 /R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-8 - 
 
  2  WHETHER DOWNWARD SUB STITUTION IN CIGARETTE S ACCELERATED AFTER THE 
ENTRY INTO FORCE OF THE TPP MEASURES  
16.  We determined that, in the period following the introduction of the TPP measures , the most 
recent market and survey data show two trends. First, there is a continuing decrease of the ratio 
of higher - to low -priced cigarettes sales. Second, there is a decrea se in the share of smokers 
preferring higher -priced brands to those preferring low -priced brands. We now turn to consider 
whether there was a shift in these trends in the post -TPP implementation period. The 
Dominican  Republic 's and Indonesia's experts exam ine this issue by applying different 
methodologies, which are described next. We then present our analysis.  
2.1  Datasets and related studies  
2.1.1   In-Market -Sales/Exchange of Sales  
2.1.1.1   IPE Report s 
17.  Based on the graphical assessment discussed above17, the IPE submits that since the 
implementation of the TPP measures  in December  2012, relative quantities of higher - to low -priced 
cigarettes sales have been significantly lower than the interpolated pre -plain packaging trend, as 
depicted in Figure E.8.18 
Figure E. 8: Trend Assessment of Monthly Sales Volumes Ratio of Higher - to Low -Priced 
Sticks and Ratio of Average Higher  to Low Prices Based on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dashed line indicates the 
introduction of plain packaging and enlarged GHWs.  
Source :  IPE Updated Report, (Exhibit DOM -303), p. 75. 
 
                                                
17 See paras.  8 and 9 above.  
18 See IPE Updated Report , (Exhibit DOM -303), para. 194. 
1.081.131.181.23
0.511.522.53
Feb 2002
Jul 2002
Dec 2002
May 2003
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Relative pricesRelative quantitites
Year
Ratio of high-priced segment (FMC) to low-priced (FMC and CSE) in billions sticks
Ratio of average high -segment prices to low -segment pricesWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-9 - 
 
  2.1.1.2   Professor  List's report  
18.  Professor  List presents the results of an event study analysing whether there has been a shift 
in the evolution of the ratio of higher - to low -priced cigarettes sales following the introduction of 
plain packaging and enlarged GHWs.19 Specifically, a seasona lly adjusted Autoregressive 
Integrated Moving Average (ARIMA) model is estimated controlling for the change in the ratio of 
higher - to low -priced cigarettes sales during the previous month and the change in the 2006 
GHWs. A dynamic model of the ratio of hi gher- to low -priced cigarettes sales is also estimated 
controlling for the quantity ratio of higher - to low -priced cigarettes sales during the previous 
month, the price ratio of higher -to low priced cigarettes  in the previous month, a linear time trend , 
and the 2006 GHWs.20 The most recent analysis covers the period from February  2002 to 
June 2015.  
Figure E. 9: Event Study on Sales Volumes Ratio of Higher - to Low -Priced Sticks 
Based  on IMS/EOS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacco per stick. The vertical dashed line indicates the 
introduction of plain packaging and enlarged GHWs.  
Source :  List Rebuttal Report , (Exhibit DOM/IDN -3), p. 28. 
 
                                                
19 We note that Professor  List's event study is a trend -projection analysis that does not estimate directly 
the impact of the TPP measures, but rather assess es whether there is a difference between the counterfactual 
ratio of higher - to low -priced cigarettes sales in the absence of the TPP measures and the actual ratio of 
higher - to low -priced cigarettes sales. That is why we have decided to discuss Professor  List's event study 
under the subsection addressing whether there was a change in downward substitution in cigarettes in the 
post-implementation period.  
20 An event analysis consists of (1) estimating the model of the ratio of higher - to low -priced cigarettes 
sales during the pre -plain packaging period; (2)  forecasting the ratio of higher - to low -priced cigarettes sales 
that would have been prevailed in the absence of the TPP measures using the estimated model's parameters in 
the post -implementation period; and  (3) determining whether the difference between the observed ratio of 
higher - to low -priced cigarettes sales volumes and the estimated counterfactual ratio of higher - to low -priced 
cigarettes volumes is statistically different from zero . See List Rebuttal Report, (Exhibit DOM/IDN -3), 
para. 109. 
00.511.522.533.54
Jan 2010
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May 2015Ratio of high -to low -priced segment 
(FMC billions sticks per month)
Year
Ratio of higher-priced segment (FMC) to low-priced (FMC) in billions sticks
ARIMA dynamic forecasted ratio of higher-priced segment (FMC) to low-priced (FMC) in billions sticks
OLS forecasted ratio of higher-priced segment (FMC) to low-priced (FMC) in billions sticksWT/DS435 /R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-10 - 
 
  19.  Professor  List concludes that according to both models, there is a negative and statistically 
significant difference between the observed ratio of higher - to low -priced cigarettes sales and the 
estimated counterfactual ratio of higher - to low -priced cigarettes sales, as depicted in Figure E.9 . 
According to Professor  List, the fact that the ratio of higher - to low -priced cigarettes sales did 
decrease faster in the post -implementation period provides evidence that the TPP measures  have 
led to important changes to the composition of sales in the Australian market, which is consistent 
with Australian consumers "downtrading" when making their cigarette choices.21 
2.1.2   Aztec Scanner  
20.  Professor  List carried out the same event study using the Aztec scanner data. A seasonally 
adjusted ARIMA model and a dynamic model of the ratio of higher - to low -priced cigarettes sales  
volumes are estimated controlling for change in the quantity ratio of higher - to low -priced 
cigarettes sales during t he previous month as well as the price ratio of the higher - to low -priced 
cigarettes during the previous month and the linear time trend variable for the dynamic model. 
The analysis covers the period from July 2008 to May 2015.  
21.  Professor  List reaches the s ame conclusion that there is a statistically significant decrease in 
the ratio of higher -priced to low -priced cigarettes sales in the post -implementation period relative 
to the predicted ratio, as shown in Figure E.10 , which is consistent with downward substitution 
from higher -priced to low -priced cigarettes.22 
Figure E. 10: Event Study on Sales Volumes Ratio of Higher -to Low -Priced Sticks 
Based  on Aztec Data  
 
Note:  The vertical dashed line indicates the introduction of plain packaging and enlarged GHWs.  
Source :  List Rebuttal Report , (Exhibit DOM/IDN -3), p. 29. 
 
22.  Although Professor  List acknowledges that it is impossible to se parate the GHW effect from 
the plain packaging effect without making an assumption on the size of one of the effects, he 
                                                
21 See List Rebuttal Report, (Exhibit DOM/IDN -3), paras.  110-111. 
22 See List Third Supplemental Report, (Exhibit DOM/IDN -7), paras.  56-61 and 80.  
0.71.21.72.22.7
Jan 2010
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May 2015Ratio of high -to low -priced segment 
(FMC billions sticks per week)
Year
Ratio of higher-priced segment (FMC) to low-priced (FMC) in billions sticks
ARIMA dynamic forecasted ratio of higher-priced segment (FMC) to low-priced (FMC) in billions sticks
OLS forecasted ratio of higher-priced segment (FMC) to low-priced (FMC) in billions sticksWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-11 - 
 
  proposes to examine the effect of Canada's GHW policy on  the composition of higher - and 
low-priced cigarette sales. In September  2011, Canada mandated an increase in the GHW to 75% 
of the front and back of the pack, which is, according to Professor  List, similar to the GHW increase 
that coincided with Australia 's implementation of its TPP measures  in December  2012. 
Professor  List presents  the econometric results of an event study of the ratio of higher - to low -tier 
cigarettes in Canada controlling for the sales composition in the previous month, the price ratio in 
the previous month, a linear time trend and a dummy variable for the 2011 GH W change. 
Professor  List concludes that the 2011 GHW change in Canada had no impact in the decrease in 
the ratio of higher - to low -priced cigarette sales. Professor  List argues that the evidence of no 
impact of the GHW on cigarettes sales composition in Ca nada is consistent with the plain 
packaging element and not the enlarged GHW s having an important role on the change in the 
composition of higher - and low -priced cigarette sales observed after the introduction of the 
TPP measures  in Australia.23  
2.1.3   Roy Morgan  Single Source  
23.  Based on the graphical assessment of the RMSS data presented above24, the IPE submits that 
shortly after the introduction of the TPP measures , relative brand preferences started to shift 
downwards to a much greater extent, and at a much great er rate, compared to the pre -plain 
packaging trend, as depicted in Figure E.11.25  
Figure E. 11: Monthly Preference for Higher -Priced versus Low -Priced Brands and 
Ratio  of Average Higher  to Low Prices Based on RMSS Data  
 
Note:  The vertical da shed line indicates the introduction of plain packaging and enlarged GHWs.  
Source :  IPE Updated Report , (Exhibit DOM -303), p. 89. 
 
                                                
23 See List Rebuttal Report, (Exhibit DOM/IDN -3), paras.  112-118. 
24 See para. 11 above.  
25 See IPE Updated Report , (Exhibit DOM -303), para. 194. 
0.971.031.091.151.211.27
-0.020.030.080.13
Feb 2002
Jul 2002
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Dec 2012
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Jun 2015
Relative pricesRelative brand preferences
Year
Difference between preference for higher-priced FMC and low-priced FMC
Ratio of average high -segment prices to low -segment pricesWT/DS435 /R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-12 - 
 
  2.2  Analysis by the Panel  
24.  As explained in our analysis of the TPP measures ' impact on smoking prevalence and cigarette 
consumption26, we are not required to present a unified econometric analysis but to assess the 
robustness of the results submitted by the parties. In addition, our conclusions apply exclusively to 
the data (including the sample period), and econometric resu lts submitted by the parties, and 
cannot in any way be generalized to other datasets and econometric studies.  
2.2.1   IPE Report s 
25.  A careful review of the IPE's graphical analysis of the ratio of higher - to low -priced cigarettes 
sales leads us to the same conclusio n reached by the IPE. In particular, extending the analysis to 
the most recent available data provided by the parties, we find that, according to a standard 
mean -comparison test, the ratio of higher - to low -priced cigarettes sales based on the IMS/EOS 
data in the post -implementation period is statistically significantly lower than in the 
pre-implementation period. This is confirmed by Figure E.12 , which shows that the trend of 
relative quantities in the post -implementation has become steeper compared to the 
pre-implementation trend, implying that the fall in the ratio of higher - to low -priced cigarettes 
sales has accelerated in the post -implementation per iod. The same conclusion can be drawn with 
the Aztec data.  
Figure E. 12: Preference for Higher -Priced versus Low -Priced Brands Pre - and  
Post-TPP Trends  Based on RMSS Data  
 
Note:  Conversion rate of 0.8 grams of fine -cut tobacc o per stick. The vertical dotted lines indicate excise 
tax hikes. The vertical dashed line indicates the introduction of plain packaging and enlarged GHWs.  
Source :  IPE Third Updated Report , (Exhibit DOM -375), backup material.  
 
26.  We reach a similar conclusio n with respect to the difference between the share of smokers 
preferring higher -priced brands and those preferring low -priced brands. We note that the 
downward trend of the difference between smokers preferring higher -priced brands and those 
                                                
26 See Appendices C and D.  
0.40.91.41.92.42.9
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to low -segment pricesquantitites
YearWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-13 - 
 
  preferring low -priced brands has accelerated in the post -implementation period, as shown 
in Figure E.13. 
Figure E. 13: Sales Volumes Ratio  of Higher -to Low -Priced Sticks Pre - and Post -TPP 
Trends Based on IMS/EOS Data  
 
Note:  Vertical dashed line indicates the introduction of plain packaging (and enlarged graphic warnings).  
Source :  IPE Updated Report , (Exhibit DOM -303), p. 89. 
 
2.2.2   Professor  List's report  
27.  After a careful review of the results of Professor  List's event study of the impact of the 
TPP measures  on the ratio of higher -priced to low -priced cigarettes sales, we question the validity 
of Professor  List's results for a number of reasons , some of which are specific to one model 
considered by Professor  List.  
28.  We note that in most estimations of the ARIMA model for the pre -plain packaging period 
based on the IMS/EOS and Aztec data that are used to forecast the value of the ratio of 
higher -priced to low -priced cigarettes sales in the post -implementation period, none of the 
explanatory variables is statistically significant, besides the moving averages parameters. The lack 
of statistically significant variables is surprising to us given that t he ARIMA model only includes 
one or two explanatory variables. We further note, as in the ARIMA model analysing smoking 
prevalence, that the estimated lagged moving average parameter of the ARIMA model based on 
the IMS/EOS data is not statistically differe nt from -1, which would likely lead to large forecasting 
errors. This is, in our view, problematic because Professor  List's approach relies on the 
post-implementation forecasting errors to determine whether there was a statistically significant 
change in t he downward trend in the ratio of higher -priced to low -priced cigarettes sales.  
 
-0.04-0.0200.020.040.060.080.10.120.14
Jun 2001
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Jun 2011
Nov 2011
Apr 2012
Sep 2012
Feb 2013
Jul 2013
Dec 2013
May 2014
Oct 2014
Mar 2015
Aug 2015Difference between preference for 
higher -priced FMC and low -priced FMC
YearWT/DS435 /R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-14 - 
 
  Figure E. 14: Ratio of Average Higher  to Low Prices and Linear Time Variable 
Based  on RMSS Data  
 
Source :  List Rebuttal Report , (Exhibit DOM/IDN -3), backup material.  
 
29.  We also note that the dynamic model faces multicollinearity problems between the time trend 
variable and the price ratio variable when using the IMS/EOS data and between the time trend 
variable and the ratio of higher -priced to low -priced cigarettes sales during the previous month 
when using the Aztec data.27 In other words, the price ratio variable and the time trend variable 
seem to convey the same information, as shown in Figure E.14 , and as a result one of them 
becomes redundant in the model specification with the IMS/EOS data. A similar conclusion applies 
to the time trend variable and the ratio of higher -priced to low -priced cigarettes sales during the 
previous month with the Aztec data. In both cases, this multicollinearity problem could explain 
why the dynamic model finds that the lagged price ratio variable is not statistically significant. This 
is particularly surpr ising given that one of the Dominican  Republic 's experts, the IPE, considers 
relative prices to be one of the factors leading to downward substitution from higher -priced to 
low-priced cigarettes.28 We also question why Professor  List implicitly assumes in t he models 
based on the IMS /EOS data that the effect of the 2006 GHW disappears following the introduction 
of the TPP measures . More generally, Professor  List did not take into account the impact of the 
excise tax hikes in the pre - and post -plain packaging periods. Yet, according to Australia, tobacco 
manufacturers operating in Australia have attributed downtrading effects to increases in excise 
taxes.29 
30.  We also question the relevance of using Canada's GHW policy change to infer that plain 
packaging and not t he enlarged GHW s had an impact on the ratio of higher - to low -tier cigarettes 
in Australia. Professor  List did not provide evidence that would justify making such an inference, 
although he acknowledges that the empirical estimates for Canada rest on strong  assumptions.30 
                                                
27 Evidence of multicollinearity is confirmed by the variance inflation factors statistic.  
28 See IPE Updated Report , (Exhibit DOM -303), para. 194. 
29 See Australia's first written submission, paras.  544-545; Australia's second written submission, 
paras.  418-419; B ATA Media Release , (Exhibit AUS -255); and B AT, Half-Year Results 2015 , (Exhibit AUS -556).  
30 List Rebuttal Report, (Exhibit DOM/IDN -3), para. 118. 
1.051.071.091.111.131.151.171.191.211.231.25
Feb 2002
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Jul 2007
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Dec 2012Relative price
Year
Ratio of average higher- to low-segment prices Positive linear time trendWT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-15 - 
 
  31.  Overall, and in this context, we consider the results of Professor  List's event study to be of 
limited use in helping to answer the question whether the TPP measures  led to a change in the 
downward trend of the ratio of higher -priced to low -priced cigarettes sales. That being said, and as 
explained above, we find that, according to a standard mean -comparison test, the average 
cigarette sales volumes based on the IMS/EOS data and the Aztec data in the post -implementation 
period are statistical ly significantly lower than in the pre -implementation period. Similarly, the 
downward trend of the difference between the shares of smokers preferring higher -priced brands 
and those preferring low -priced brands based on the RMSS data has accelerated in the  post-plain 
packaging period.  
32.  In any event, as in respect of smoking prevalence and smoking consumption, the fact that the 
downward trends of the ratio of higher - to low -priced cigarettes sales and the difference between 
the share of smokers preferring hi gher-priced brands and those preferring low -priced brands have 
accelerated in the post -implementation period does not necessarily imply that the TPP measures  
are having a statistically significant impact, given that other factors, unrelated to the 
TPP measures , could explain the respective trend shift. The extent to which the TPP measures  
have an impact on the ratio of higher -priced to low -priced cigarettes sales and on the difference 
between the shares of smokers preferring higher -priced brands and  low-priced brands is reviewed 
next. 
3  WHETHER THE TPP MEASURES  CONTRIBUTED TO DOWNW ARD SUBSTITUTION IN 
CIGARETTES  
33.  As explained above, we have determined that the ratio of higher -priced to low -priced 
cigarettes sales and the difference between the shares of smokers preferring higher -priced brands 
and those preferring low -priced brands in Australia have continued to experience a decline, which 
has accelerated in the post -plain packaging period. To the extent that there has been a greater 
reduction in these met rics after the entry into force of the TPP measures , the question arises 
whether, and if so, to what extent, plain packaging contributed to reducing these metrics.  
34.  As for the analyses of smoking prevalence and cigarette sales and consumption, the 
Dominica n Republic 's and Indonesia's experts proposed different econometric methods to estimate 
the impact of the TPP measures  on relative quantities and preferences of higher -priced cigarettes 
with respect to low -priced cigarettes. As mentioned above, the Dominic an Republic 's and 
Indonesia's experts recognize, however, that it is impossible to technically distinguish between the 
impact of plain packaging and the impact of the enlarged GHWs on relative quantities and 
preferences of higher -priced cigarettes with res pect to low -priced cigarettes, because both 
measures were implemented at the exact same time.31 
3.1  Datasets and related studies  
3.1.1   In-Market -Sales/Exchange of Sales  
35.  Several reports by the IPE have been submitted, estimating econometrically the impact of the 
TPP measures  on the logarithm of the ratio of higher - to low -priced cigarette wholesale sales using 
the IMS/EOS  data. Throughout these reports, different econometric approaches and model 
specification s have been proposed: (1)  time series regression analysis; (2)  modified trend 
analysis; and (3)  Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) 
model.32  
36.  The first approach was only presented in the first IPE Report  and is based o n a model 
specification of the logarithm of the ratio of higher - to low -priced cigarette sales that includes a 
TPP measures  dummy variable, dummy variables for the 2010 and 2013 excise tax increases, a 
2006 GHW dummy, the logarithm of the higher - to low -priced cigarettes price ratio, month fixed 
effects and a time trend variable.  The second and subsequent IPE  reports only focused on the last 
                                                
31 See Dominican  Republic 's response to Panel question No. 8, para. 61; List Report, (Exhibit 
DOM/IDN -1), para. 113; Honduras's response to Panel question No. 8; and Indonesia's response to Panel 
question No. 8, para. 8.  
32 See IPE Report , (Exhibit DOM -100), p p. 67-73 and 201 -210; and IPE Updated Report , (Exhibit 
DOM-303), paras.  135-175 and 290 -326. WT/DS435 /R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
- E-16 - 
 
  two approaches. The modified trend analysis estimates a standard time series regression model of 
the logarithm of the  ratio of higher -to lower -priced cigarette sales using (heteros cedastic) 
autocorrelation -robust standards errors and controlling for a TPP measures  dummy variable, 
dummy variables for the 2010, 2013 and 2014 excise tax increases, a 2006 GHW dummy, the 
(current or lagged) logarithm of the higher - to low -priced cigarettes price ratio, month fixed effects 
and a time trend variable. The ARIMA model includes the same set of explanatory variables as well 
as the (one up to four) lagged logarithm of the ratio of hi gher-to lower -priced cigarette sales and 
the (one up to four) lagged logarithm of the price ratio. The most recent econometric analysis 
covers the period February  2002 through August  2015.  
37.  Overall, the IPE concludes that the TPP measures  had a negative and  statistically significant 
effect on the logarithm of the ratio of higher - to low -priced cigarette sales. According to the IPE, 
these results are robust across different specifications (e.g. different plain packaging starting date: 
October, November  and De cember; alter native time trend specification:  linear, quadratic and 
cubic; and alternative methods of calculating standard errors of the modified trend analysis).33 
38.  Although the IPE acknowledges that there is no perfect way to separate the plain packaging 
and enlarged GHW effects, it argues that there are indirect ways to study any effect of the 
enlarged GHW requirement on downtrading  in Australia, such as estimating the downtrading  effect 
of another tobacco control policy introduced in isolation in Australi a, without the simultaneous 
introduction of a confound. The IPE proposes using the introduction of GHWs in Australia in 2006 
as a proxy for the implementation of the enlarged GHW requirement in December  2012. Given that 
the econometric results of the analy sis of the logarithm of the ratio of higher - to low -priced 
cigarette wholesale sales find that the impact of the 2006 GHW is negative but not statistically 
significant, the IPE argues that the plain packaging component is likely responsible for the vast 
majority of the downtrading  effect found from the December  2012 policy change.34 
3.1.2   Aztec Scanner  
39.  The IPE performed the same (1)  time series regression analysis; (2)  modified trend analysis; 
and (3)  ARIMAX model analysis using the Aztec scanner data.35 The exact same set of explanatory 
variables is included, except the 2006 GHW dummy. The analysis covers the period from July 2008 
to May 2015.  
40.  Overall, the IPE finds the same conclusion as the analysis based on the IMS/EOS data, namely 
the impact of the TPP measures  on the logarithm of the ratio of higher - to low -priced cigarette 
retail sales is negative and statistically significant. According to the IPE, these results are robust 
across different specifications (e.g. different plain packaging starting dat e: October, November  and 
December; alter native time trend specification:  linear, quadratic and cubic; and alternative 
methods of calculating standard errors of the modified trend analysis).36 In reality, the estimated 
coefficient of the TPP measures  dummy v ariable is not statistically significant in a couple of 
specifications.37 
3.1.3   Roy Morgan Single Source  
41.  The RMSS data were used by the Dominican  Republic 's and Indonesia's experts to estimate 
econometrically the impact of the TPP measures  on the relative preferences of higher -priced 
cigarettes with respect to low -priced cigarettes.  
                                                
33 See IPE Report , (Exhibit DOM -100), p p. 83-86 and 223 -233; IPE Updated Report , (Exhibit DOM -303), 
paras.  195-201; IPE Second Updated Report , (Exhibit DOM -361), paras.  45-48; and IPE Third Updated Report , 
(Exhibit DOM -375), paras.  249-251. 
34 See IPE Updated Report , (Exhibit DOM -303), paras.  228-234. IPE also presented a graphic analysis of 
the relative quantities with respect to the introduction of GHWs in 2006 and plain packaging in 2012.  
35 See IPE Report , (Exhibit DOM -100), p p. 80-83; and IPE Updated Report , (Exhi bit DOM -303), 
paras.  205-206. 
36 See IPE Report , (Exhibit DOM -100), p p. 234-244; IPE Updated Report , (Exhibit DOM -303), 
paras.  202-208; IPE Second Updated Report , (Exhibit DOM -361), paras.  49-52; and IPE Third Updated Report , 
(Exhibit DOM -375), paras.  252-254. 
37 This is the case when the starting date of the TPP measures dummy variable is set to October  2012. 
See IPE Third Updated Report , (Exhibit DOM -375), p. 140. WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  3.1.3.1   IPE Report s 
42.  The IPE presented in various reports the results of a standard probit model of the probability 
of an individual cigarette smoker consuming higher -priced cigarettes . The model controls  for a 
TPP measures  dummy variable, (current or lagged) relative price of higher -priced versus 
low-priced cigarettes, gender dummy, polynomial of degree 4 of the age variable, polynomial of 
degree 4 of the education varia ble, polynomial of degree 4 of the income group variable, dummy 
variables for the 2010, 2013, 2014 and 2015 excise tax increases , and a trend variable.38 In its 
first report, the IPE also estimated a linear probability model, whose model specification inclu ded 
the same demographic variables as well as a social class variable but without any of the tax hike 
dummy variables and the trend variable.39 The analysis covers the period from July 2006 through 
September  2015.  
43.  Overall, the IPE concludes that the impact of the TPP measures  on the probability that an 
individual smoker prefers higher -priced brands is negative and statistically significant.40 According 
to the IPE, this finding is robust to different model specifications (e.g.  different plain packaging 
startin g date: October, November  and December, inclusion of the first lagged of the price ratio, 
and excise tax increases dummies).  
44.  The IPE further submits that plain packaging and not the enlarged GHW s is likely responsible 
for the vast majority of the downtrading  effect from the introduction of the TPP measures  because 
a modification of the model specification enabling to extend the sample period from February  2002 
to September  2015 and controlling for the 2006 GHW finds a negative but not statistically  
significant impact of the 2006 GHWs on the probability of smoking cigarettes from the 
higher -priced segment.41 
3.1.3.2   Professor  List's Report  
45.  Professor  List presented econometric results of a two -stage micro -econometric model based 
on the RMSS data. The first sta ge estimates the likelihood of a representative person smoking a 
high or medium -priced segment brand of cigarettes, conditional on being a smoker, in a given 
month and controlling for demographic characteristics (e.g.  age, fourth order polynomials of 
gende r, education, and income position). The second stage conducts a before and after analysis on 
the likelihood for each month computed in the first stage by estimating a linear probability model 
controlling for the TPP measures , higher - to low -priced cigarett es price ratio and/or linear trend, 
and weighting changes by Roy Morgan Research. Professor  List re -estimated the same model for a 
representative person smoking a low -priced segment brand of cigarettes. The econometric analysis 
covers the period from July 2006 to June 2015.  
46.  Overall, Professor  List concludes that the TPP measures  had a statistically significant negative 
effect on the likelihood of consuming higher -priced cigarettes but a positive and statistically 
significant effect on the likelihood of con suming lower -priced cigarettes.42 
3.2  Analysis by the Panel  
47.  Having determined above that the decrease in the ratio of higher - to low -priced cigarette 
sales and in the difference between the share of smokers preferring higher -priced brands and the 
share of those  preferring low -priced brands has accelerated following the entry into force of the 
TPP measures , the question before us at this stage of our analysis is whether this acceleration 
may, in part or in whole, be attributed to the TPP measures . 
                                                
38 See IPE Updated Report , (Exhibit DOM -303), paras.  245-250. 
39 See IPE Report , (Exhibit DOM -100), p p. 245-250.  
40 See IPE Report , (Exhibit DOM -100), p p. 90-94; IPE Updated Report , (Exhibit DOM -303), 
paras.  223-227, p. 134; IPE Second Updated Report , (Exhibit DOM -361), paras.  53-55; and IPE Third Updated 
Report , (Exhibit DOM -375), paras.  255-256. 
41 See IPE Updated Report , (Exhibit DOM -303), paras.  231-235, p. 134. 
42 See List Rebuttal Report, (Exhibit DOM/IDN -3), paras.  106-107.  WT/DS435 /R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  48.  At the outset, we note, as explained above, that Australia did not provide any econometric 
evidence on downward substitution. We also note that Dominican  Republic 's and Indonesia's 
experts use the same data sources but consider different model specifications and approach es.43  
49.  As explained in our review of the econometric study on smoking prevalence and cigarette 
sales and consumption, it is not our task to conduct our own econometric assessment but rather 
review the robustness of the econometric evidence submitted by each  party.  
3.2.1   IPE's econometric results  
50.  A careful review of the econometric results based on the IMS/EOS data provided in the IPE 
reports leads us to conclude that there is some evidence, albeit limited, that the TPP measures , 
together with the englarged GHWs introduced on the same date,  appear to have had a negative 
impact on the ratio of higher - to low -priced cigarette wholesale sales. We note, however, that the 
price ratio has a much larger impact on the ratio of higher - to low -priced cigarette wholesale sal es. 
This finding is in line with the strong negative correlation between price ratio and quantity ratio, as 
well as the evidence submitted by Australia regarding the impact of the tobacco industry's own 
marketing and pricing strategies on downtrading in th e Australian market.44 Similarly, the 
econometric results show that the overall impact of the excise tax hikes on the ratio of higher - to 
low-priced cigarette wholesale sales is larger the TPP measures . 
51.  That being said, we note that some specifications of t he modified trend analysis are 
characterized by multicollinearity between the quadratic or cubic trend variables and the current 
and/or lagged price ratio. We note that the issue of multicollinearity is even more severe in all of 
the specifications of the ARIMAX model based on the IMS/EOS data. The multicollinearity is 
particularly high between the quadratic or cubic time trend variables, the lagged price ratio and 
lagged quantity ratio.45 We also question the results of most ARIMAX models, because the resul ts 
find that the higher - to low -priced cigarettes price ratio has either no impact or a statistically 
positive impact. It is unclear what drives such results, although we note that the price ratio is 
negative and statistically significant in the specificat ions, which are less affected by 
multicollinearity by including only a linear time variable. The results of some specifications also 
suggest that the trend variable has a positive and statistically significant impact, which is in 
contradiction with other e conometric results and the graphical analysis discussed above. We 
therefore reject the results of the ARIMAX model based on the IMS/EOS data.  
52.  We also question the validity of the econometric results based on the Aztec retail data on the 
same grounds. We no te that the results of the modified trend analysis are affected by high 
collinearity between the linear trend variable and the current price ratio as well as the price ratio in 
the previous month. The c ollinearity problem also arises in the ARIMAX model be tween the 
logarithm of the ratio of higher - to low -priced cigarette retail sales in the previous month, the 
trend variable(s) and the price ratio in the previous (second to fourth) months. The collinearity is 
even more severe when the current price ratio i s included in the model specification. We also note 
that all the results of the ARIMAX model find that the impact of the logarithm of the ratio of 
higher - to low -priced cigarette wholesale sales in the previous month is positive and statistically 
significa nt, which is in contradiction with the negative and statistically significant impact found in 
the econometric analysis based on the IMS/EOS data.  
53.  Our review of the IPE's micro analysis of the effect of the TPP measures  on smokers' relative 
preference for h igher-priced versus low -priced cigarettes based on the RMSS data leads to 
question the validity of some of its results. Besides the issue of collinearity between the price ratio 
and the time trend variable, we note that the impact of the relative price of higher -priced 
cigarettes with respect to low -priced cigarettes in the current or previous month on the probability 
of choosing higher -priced cigarettes is never statistically significant. This finding is, in our view, 
rather surprising given that as acknow ledged by the IPE itself, the individual choice of 
higher -priced versus low -priced cigarettes is likely to be influenced by the relative price of the two 
                                                
43 For instance, Professor  List does not include dummy variables for the excise tax increases unlike IPE. 
Similarly, Professor  List presents the results of a two -stage econometric model applied to the RMSS data, while 
IPE presents the results of one -stage micro -econometric analysis.  
44 See Australia's second written submission, paras.  418-419. 
45 Evidence of multicollinear ity is confirmed by the variance inflation factors statistic.  WT/DS435/R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  product groups.46 Yet, the IPE did not provide any explanations that would justify such surprising 
results.  
3.2.2   Professor  List's econometric results  
54.  We also question the validity of Professor  List's two -stage econometric model of the 
probability of a representative person smoking a high or medium price segment brand of 
cigarettes based on the RMSS data on vari ous grounds. First, we note that, in the first stage of the 
model of the representative smoker, more than 60% of the individual monthly estimations report 
that either none or only one or two of the explanatory variables are statistically significant.47 
Similarly, there is only up to two explanatory variables that are statistically significant in more 
than 43% of the individual monthly estimations in the first stage of the model of the 
representative smoker of low -tier cigarettes . It is therefore unclear to w hat extent the results of 
the second stage of the analysis are reliable given the lack of statistical significance in the first 
stage. Second, as explained above, issues of multicollinearity arise between the ratio of higher - to 
low-priced cigarettes price s and the time trend. Third, several estimation results find surprisingly 
that the price ratio is statistically not significant. Finally, we note that Professor  List does not, 
unlike the IPE, take into account the impact of the excise tax hikes on the prob ability of smoking, 
which is considered by the parties to be one of the most efficient tobacco control polic ies.  
55.  Although we question the validity of Professor  List two -stage econometric model analysis, we 
cannot rule out that plain packaging and enlarged GHWs contributed to the reduction in the ratio 
of higher - to low -priced cigarette wholesale sales in Australia based on the most recent 
econometric evidence on wholesale data submitted by the IPE. That being said, the extent t o 
which this reduction in the ratio of higher - to low -priced cigarette wholesale sales in Australia that 
could be attributed to the TPP measures , represents only downtrading  is unclear to our eyes. As 
highlighted in the graphical analysis presented above, the reduction in higher -priced segment 
wholesale sales has decreased at a much faster rate than the sales of low -priced cigarettes, which 
implies that at least part of the reduction in the ratio of higher - to low -priced cigarette wholesale 
sales is due to the overall reduction in the total wholesale sales volume following and due to the 
introduction of the TPP measures , as we concluded earlier.  
4  OVERALL CONCLUSION O N POST -IMPLEMENTATION EVIDE NCE ON DOWNWARD 
SUBSTITUTION  IN CIGARETTES  
56.  Overall, based on the mo st recent data available and econometric evidence submitted by the 
parties, we find that:  
a. There is evidence that the ratio of higher - to low -priced cigarette wholesale and retail 
sales and the difference between the share of smokers preferring higher -priced 
cigarettes and the share of those preferring low -priced cigarettes in Australia continued 
to decrease following the introduction of the TPP measures . 
b. The downward trend in the ratio of higher - to low -priced cigarette wholesale and retail 
sales and the d ifference between the share of smokers preferring higher -priced 
cigarettes and the share of those preferring low -priced cigarettes in Australia appears to 
have accelerated in the post -plain packaging period.  
c. Although it is impossible to distinguish between the impact of plain packaging and 
GHWs, there is some econometric evidence suggesting that the TPP measures  
contributed to the reduction in the ratio of higher - to low -priced cigarette wholesale 
sales. That said, it is unclear to what extent this reduction in the quantity ratio 
attributable to the TPP measures  represents only downward substitution. In fact, given 
that the reduction in higher -priced segment wholesale sales has decreased at a much 
faster rate than the increase in sales of low -priced cigarettes, at least part of the 
reduction in the quantity ratio is due to the overall reduction in the total wholesale sales 
volume following and due to the introduction of the TPP measures  and enlarged GHWs , 
                                                
46 See IPE Updated Report , (Exhibit DOM -303), paras.  231-235 and 218.  
47 12 demographic characteristics and the constant term are included in the first -stage model 
specification.  WT/DS435 /R/Suppl.1 • WT/DS441/R/Suppl.1 • WT/DS458/R/Suppl.1 • WT/DS467/R/Suppl.1  
 
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  as we  have concluded in our previous analysis on cigarette consumption. In addition, the 
econometric results show that the increase in relative cigarette price and excise tax 
hikes have had a negative and greater impact on the the ratio of higher - to low -priced  
cigarette wholesale sales than the TPP measures . 
57.  We note, however, that no post -implementation empirical evidence has been presented to us 
on the impact of the TPP measures  on the ratio of higher - to low -priced cigars and cigarillos.  
 
__________