Discussion Papers In Economics
And BusinessResponse of Consumers to the Mandatory Disclosure ofInformation:Evidence from Natural Experiments
in Japanese Inter-brand Cigarette Demands

Junmin Wan
Discussion Paper 04-13-Rev.

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANResponse of Consumers to the Mandatory Disclosure ofInformation:Evidence from Natural Experiments
in Japanese Inter-brand Cigarette Demands

Junmin Wan
Discussion Paper 04-13-Rev.
February 2006
この研究は「大学院経済学研究科・経済学部記念事業」
基金より援助を受けた、記して感謝する。
Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANResponses of Consumers to the Mandatory Disclosure ofInformation: Evidence from Natural Experiments
in Japanese Inter-brand Cigarette Demands∗
Junmin Wan†
Osaka University, Japan∗ This was a revised version on January 9, 2006.

† I thank Kazuo Ogawa for advice and guidance while writing this paper; Charles Yuji
Horioka, Shinsuke Ikeda, and Fumio Ohtake of Osaka University and Ichirou Gombi of
Ritsumeikan University for valuable comments; Xiangyu Qu, Dariusz Stanko, Midori Wakabayashi, and seminar participants at Osaka University for helpful suggestions; Mikiyo Kii
Niizeki of Doshisha University for providing useful advice; and Takeo Hoshi of the Universityof California, San Diego, and Daiji Kawaguchi of Hitotsubashi University for many constructive suggestions. This paper is a revised version of chapter 5 of my doctoral dissertationin Osaka University. It was presented at the 2003 spring meeting of the Japanese Economic
Association at Oita University on 14 June 2003. Any remaining errors are my own responsibility. Correspondence: Junmin Wan, OSIPP, Machikaneyama 1-31, Toyonaka, Osaka 560-0043,
Japan. tel/fax: +81(6)68505839; E-mail: wan@osipp.osaka-u.ac.jp

Abstract
I estimated inter-brand cigarette demands with nicotine, tar content
and policy event information in Japan during 1950-84. The demand for all
brands increased but the demand for plain (non-filter) brands decreased
due to the dissemination of A Note about Health Damage from Smoking
in 1964. The demand for all brands increased but the demand forhigh-nicotine brands decreased due to the disclosure of nicotine and tar
content in 1967 and the labeling warnings in 1972, however consumers
had still preferred high-nicotine brands after 1972. Contrastively, thedemand for high-tar brands increased in 1967 but decreased in 1972, andconsumers had switched to prefer low-tar brands after 1972. Disclosure did
not reduce the intake of nicotine but reduced the intake of tar, accordingly
disclosure may benefit consumers by reducing the health risk as tar causes
cancers. In line with changes in inter-brand demands, the monopolistic
firm discontinued old products with poorer quality (plain, high-tar) but
provided new better ones (filter-tipped, low-tar).

JEL classif ication: I18, D12, D82
Keywords: disclosure, nicotine, tar, cigarette, inter-brand, panel estimation,
diﬀerence in diﬀerence

1

Introduction

Whether there a need exists for mandatory information disclosure continues tobe hotly debated. Many economists insist, by means of theoretical analyses,that mandatory disclosure is necessary, and much empirical evidence supports
this view. However, some economists do not accept this claim, and strong
evidence has recently undermined the idea that more information is better.1
Thus, a clariﬁcation of which side of the debate is correct is needed, which has
important implications for policy making and legislation.
In addition to clarifying the debate, this research sought to investigate theoutcome of recent legislation and legal changes regarding worldwide information disclosure about tobacco products. The World Health Organization (WHO)
Framework Convention on Tobacco Control (FCTC) was unanimously approvedby all WHO members (192 countries) on 27 May 2003. Over 57 countries, including Japan, had already ratiﬁed this treaty by September 2005. The FCTC
seeks to protect human health by reducing tobacco consumption, and has described in detail several methods for tobacco control. In particular, information
disclosure and labeling are believed to be important tools. For example, Article
11 states, ... each unit packet and package of tobacco products and any outside
packaging and labeling of such products shall, in addition to the warnings . .
., contain information on relevant constituents and emissions of tobacco products . . . .

Such labeling and information disclosure regulations have been

implemented in Japan since the 1960s and 1970s, respectively. By examining
the eﬀects of these policies in Japan, we can demonstrate directly the validityof Japanese policy, and also characterize the possible impacts of the FCTC on
cigarette consumption in the world.
Therefore, it is crucial to empirically test how consumers react to the new
1 See details in Dranove et al., (2003).

1

information releases mandated by Japanese policies. However, it is very diﬃcult
to measure the eﬀects of information disclosure, for two main reasons. First,
the abstract and general nature of information makes it diﬃcult to quantify anddeﬁne. Second, it is hard to separate the eﬀects of information disclosure fromthe eﬀects of other factors. For example, even if some information is presented
and has a particular eﬀect, the economy will always change for other reasons as
well; thus, any impact of information is in combination with other factors. As
a result of these problems, research on information disclosure is generally rare
and has been virtually nonexistent in Japan.
Furthermore, one could arrive at the eﬀect of information disclosure on nonaddictive goods by testing its eﬀect on addictive goods. It is commonly believedthat consumer responses in the case of addictive goods are less sensitive to exogenous information shocks than in the case of general goods, as the consumer
cannot easily give up addictive goods or ﬁnd substitutes for them. Therefore,
in the event of a statistically signiﬁcant eﬀect of information disclosure on the
consumption of the addictive good tobacco, it would be reasonable to infer the
existence of a similar, but stronger, eﬀect on the consumption of general goods.
With these ideas in mind, this paper proposes a new method for verifying
the eﬀects of information disclosure by incorporating information on productcontents into the demand equation. A diﬀerence-in-diﬀerence (DID) approachis provided for directly estimating those changes in inter-brand cigarette demands that result from policy changes and increased information awarenessabout nicotine and tar levels. Using cross-sectional time-series data, I examined
consumer responses to public information announcements. Because consumers
generally responded to the newly disclosed information, this implies that theypreviously had insuﬃcient information. Moreover, results of this study provide
new evidence that mandatory disclosure decreases tar intake and increases con-2

sumer welfare while making monopolistic ﬁrms improve product quality, supply
a greater number of new and better quality products, and discontinue theirproducts of poorer quality.
The composition of the paper is as follows: section 2 reviews related research,
section 3 describes policy events, section 4 presents the data, section 5 presents
the model and estimation techniques, section 6 reports the estimation results,
and section 7 provides the conclusion and discusses policy implications andissues relevant to future research.

2

Related Literature

2.1

Theoretical and empirical work

The most inﬂuential theoretical works on the topic of information disclosure
have been those of Grossman (1981) and Milgrom (1981). When information
disclosure is costless to the seller, when the buyer can costlessly conﬁrm whether
the disclosed information is true or false, and in the absence of moral hazards
on the part of the buyer, Grossman (1981) found that the optimal strategy ofthe seller is to fully disclose all information and to provide the buyer with complete quality assurance. In such a case, mandatory disclosure is not necessary,
because it is in the interests of the ﬁrm to disclose all information voluntarily.
However, Verrecchia (1983) introduced a nonzero information disclosure cost
into the standard model and then found that the seller instead chooses to disclose information only when the proﬁts from such a decision exceed the costs.
More recently, Fishman and Hagerty (2003) pointed out that in certain situations, mandatory disclosure may be worse than voluntary disclosure.2 In short,no consensus has yet been reached in the theoretical literature as to whether
2 Akita and Maeda (2005) also have made this argument3

mandatory or voluntary disclosure is the better policy choice.
In contrast, much empirical work exists on the eﬀects of information on consumption. Brown and Schrader (1990) demonstrated that the introduction ofhealth information empirically helped to explain the phenomenon that egg consumption in the United States decreased despite a decline in the price of eggs. In
their analysis, the accumulated yearly number of articles espousing either of two
opposing viewpoints (that cholesterol is either good or bad for the health) published in medical magazines between 1955 and 1987 was indexed as a measureof information. Yen and Chern (1992) found that the consumption of animal oil
was reduced, and that vegetable oil consumption signiﬁcantly increased, as a result of the disclosure that cholesterol is bad for the health, using the cholesterolindex of Brown and Schrader (1990) as a proxy for health information. Chern
et al. (1995) then obtained further evidence that health information aﬀectedconsumption by using the averages and variances of consumer beliefs as proxyvariables for information measures in accordance with the Bayesian information
model. Ippolito and Mathios (1995) also provided evidence that the dissemination of information on the negative eﬀects of cholesterol had an eﬀect on foodconsumption.
Mathios (2000) recently examined nutrition label information and supermarket scanner data from both before and after the introduction of the Nutrition
Labeling and Education Act. He found that mandatory labeling did have aneﬀect on consumer behavior and health. However, Dranove et al. (2003) provided evidence that the public disclosure of patient outcomes decreased patientand social welfare. Jin and Leslie (2003) used restaurant hygiene grade cards
as a measure of information disclosure and provided evidence that these grade
cards caused restaurants to make hygiene quality improvements, although they
could not directly estimate the demand for restaurant food, due to a lack of4

restaurant price information.
Using American survey data on cigarette consumption, Viscusi (1992) analyzed the eﬀect on smoking behavior attributable to the disclosure that smoking
is harmful to health. He found that the probability that an informed person
smoked was lower than that for an uninformed one. Furthermore, the introduction of such information signiﬁcantly decreased cigarette consumption. Yorozu
and Zhou (2002) used Japanese prefectural cigarette sales data and a prefectural
dummy based on whether there was a smoking and health advertising budget as
measures of information dissemination. They found that cigarette consumption
decreased signiﬁcantly in the prefectures with a budget for such advertising.
Along similar lines, Wan (2004) used monthly data and event dummies to analyze the eﬀect of information on total cigarette consumption and concluded that
information regarding the potential damage due to smoking reduced consumption signiﬁcantly in Japan.

2.2

Departure from previous work

In previous research, advertisements, regulations, and opinion polls were used
as measures of information. In contrast, this analysis uses not only policy information, such as regulation, but also the contents of goods, as measures of
information. The measures of information discussed in this paper are reliable,
and the measurement bias of this information is low. Furthermore, the estimation approach used here diﬀers markedly from those used in previous research,in that inter-brand demands are used directly, by means of a DID method.
Although much research related to cigarette consumption has been conductedusing both macro and micro data, there has been no analysis conducted to dateof the way in which nicotine and tar content information disclosure has aﬀectedinter-brand cigarette demand by causing consumers to switch products. This5inquiry is thus the ﬁrst of its kind.
This paper also diﬀers from that of Jin and Leslie (2003) in three main
respects. First, the estimation approach adopted directly estimates demandby means of disclosed information rather than by means of estimated revenue.
Second, this paper focuses on an addictive good (cigarettes), while Jin andLeslie (2003) did not. Third, this paper focuses on the response behavior ofa monopolistic ﬁrm faced with mandatory information disclosure, whereas Jin
and Leslie (2003) focused on relatively competitive ﬁrms (restaurants) underboth mandatory and voluntary disclosure.

3

Main Policy Events Concerning Smoking
Information in JapanThe Japan Tobacco and Salt Public Corporation (JT) is the only cigarette makerin Japan. It is a matter of established fact that JT is, and has generally been,
unwilling to voluntarily disclose complete information about the quality of its
products. This fact is consistent with the prediction of the standard theoryof information disclosure. Large costs associated with information disclosure
arise for both JT (in measuring cigarette contents and convincing the smokerthat the disclosed information is true) and the cigarette consumer (in verifyingthat the information disclosed by JT is true), if there is no government regulation. Therefore, because of these enormous costs of information disclosure andveriﬁcation, the government must legislate information disclosure and establish
organizations that verify information, such as various governmental inspection
agencies. In addition, a substantial tax should be charged to cover these costs.
The Japanese government has enacted such legislation, and has forced JT to
disclose cigarette content information in accordance with related laws.

6

For the purpose of conducting the analysis reported in this paper, threemain policy events pertinent to information about smoking in Japan were used
to measure information eﬀects quantitatively. The ﬁrst occurred on 6 February
1964, when the Ministry of Health and Welfare of Japan disseminated A Noticeabout Health Damage from Smoking to prefectural governors and to the mayors
of several designated cities following the release of the U.S. Smoking and HealthReport,which was published in 1964. One may consider this publication as

a completely exogenous shock to the consumer, as this was the ﬁrst time thatthe government oﬃcially informed consumers about the negative health eﬀects
of smoking.
The second information disclosure event in Japan concerned the nicotine andtar content of cigarettes. In 1967, the amounts of nicotine and tar per cigarette
were published in the newspapers, as mandated by the Ministry of Finance. One
may also consider this event as constituting a completely exogenous information
shock, for the following reason. Before this disclosure, neither consumers nor
JT possessed information about nicotine and tar levels; nicotine and tar levels
were ﬁrst measured in 1967. Before 1967, both demand and supply sides had
no data concerning nicotine and tar levels. As information regarding the levelsof nicotine and tar had not yet been disclosed, even as late as 1966, it can beassumed that consumer knowledge of nicotine and tar levels did not aﬀect theconsumption of cigarettes. After 1967, however, it can be inferred that consumer
behavior was inﬂuenced by the new information.
The third information disclosure event occurred on 20 April 1972, when theJapanese Ministry of Finance issued a directive put a warning label on cigarette
packs. Speciﬁcally, manufacturers were required to add the label, Smoking too
much may be bad for your health.

This warning had to be displayed on thepacks of all brands produced after April 1972, and this mandatory disclosure

7continues today.
Tax revenues were necessary to enforce these policies and to cover the related
costs. Therefore, one may think of part of the cigarette tax revenues as thecosts associated with information disclosure, e.g., veriﬁcation costs. According
to Wan (in press), the price of cigarettes today is completely controlled by theJapanese government, and special laws are frequently passed to enact cigarette
tax changes. In fact, seven cigarette tax increases have been passed, not becauseof ﬂuctuations in the demand for cigarettes, but because of a large public deﬁcit.
Thus, the price of cigarettes is an exogenous variable for the Japanese cigarette
consumer. Therefore, the prices of all brands were included in the estimation
equation, not only to control for eﬀects other than those of information about
nicotine and tar, but also to obtain the variations in price across all brands.

4

Data

The time-series sales data used for each brand came from the National Budget
and theHistory of the Japanese Cigarette Monopoly.

3

In particular, thedata included information for the period 1950-1984 on the consumption of 55
brands that had more than 95 percent of the total market share after 1960. In
addition, the data included each brand’s price and respective levels of nicotine
and tar. The nicotine and tar-level data were announced oﬃcially in the Asahi
Shimbunand theMainichi Shimbun.

4

Policy dummies were used to indicate whether disclosure of information occurred, i.e., they were assigned a value ofdesignated as

1

0

before an event occurred andafter the event. A time trend and its square were also

used. Furthermore, macroeconomic factors, such as income and population,
3 In Japanese, theNational Budget is Kuni No Yosan, and the History of theJapanese Cigarette Monopoly is Nihon Tabako Senbaishi.
4 The Asahi Shimbun and the Mainichi Shimbun are the main newspapers in Japan.
The information on nicotine and tar content was obtained from these two newspapers.

8were taken into consideration. The time transitions of nicotine and tar levels
per cigarette are presented in Figure 1. This graph shows that cigarette nicotine
and tar content decreased after 1967, and that the decrease in nicotine levels was
slightly more sudden than that of tar. Figure 2 presents the time transition ofannual per capita cigarette consumption versus annual consumption per smoker.
Cigarette consumption per capita increased until the mid-1970s and then leveled oﬀ. However, cigarette consumption per smoker has been increasing until
the present time.5 The total intake of nicotine and tar per capita is presented
in Figure 3. Nicotine consumption exhibited an upward trend until 1967 but
declined thereafter. This trend then turned upward again until 1972, shifting
to another downward trend thereafter. Tar consumption, however, increased
slowly after 1967 and declined from 1972. The total intakes of nicotine andtar per smoker are presented in Figure 4. The pattern of nicotine consumption
exhibited similar tendencies to that of tar; this trend increased until 1963 butthen shifted to a downward trend from 1964. However, it is noteworthy thatin 1972, nicotine consumption moved in the opposite direction to that of tar
consumption.
To help assess the subjective changes in consumer consciousness that occurred with the dissemination of new information, I investigated the number ofnewspaper articles with headlines containing relevant keywords.6 The numberof articles with titles related to the harmful eﬀects of smoking, or to not smoking, suddenly increased after 1964. There were a few more articles with titles
including the keyword nicotine than there were titles including tar around
1967, although the number of articles with titles containingtar

increasedfrom 1972. It appears that these changes in consumer consciousness correspondto the changes in the consumption patterns presented in Figure 1, and to the
5 Calculation details were presented by Wan (in press).

6 I searched keywords in the Asahi Shimbun Database. The data obtained and a graph areavailable upon request.

9

changes in the total intake of nicotine and tar shown in Figure 4.

5

Speciﬁcation and Estimation Methods

5.1

Modeling the eﬀects of the policy events in 1964, 1967,
and 1972

The response of consumers to the 1964 policy event was likely represented by
the adjustment in total cigarette consumption and inter-brand switching that
occurred. Ideally, consumers should have restricted their consumption of plain
cigarettes, if they only had information regarding plain and ﬁltered cigarettes.
Therefore, plain-cigarette consumers may be taken as a treatment group, withﬁltered-cigarette consumers used as a control group.
Similarly, the response of consumers in 1967 to the disclosure of information
about nicotine and tar content levels can be represented by switches among
brands or an adjustment of total consumption following the disclosure of thisinformation. Once consumers became aware that nicotine and tar were bad fortheir health, the demand for brands with a high-nicotine or tar content shouldhave decreased, while the demand for low-nicotine brands characterizing thecontrol group should have increased.
Finally, the consumer response to the 1972 warning label on cigarette packs
that

Smoking too much may be bad for your healthcan similarly be used

to characterize the market response to the disclosure of nicotine and tar information in 1967.

5.2

Econometric model

As noted by Wan (2004), consumer consumption of cigarettes is based not only
on cigarette prices, but also on the available information concerning the dam-

10

aging eﬀects of smoking. If one ignores the aspect of addiction, a simple model
for cigarette brand demand can be described as follows: demand for brandit =f (the attributes of the brandit , policy information, etc.). The attributes of thebrand and relevant policy information can be used as proxies for the extent ofconsumer knowledge about the harmful eﬀects of smoking.
Dit = β0 + β1 ∗ time + β2 ∗ time2 + β3 ∗ priceit + β4 ∗ incomet + β5 ∗ af ter64+β6 ∗ plaini + β7 ∗ af ter64 ∗ plaini + β8 ∗ af ter67 + β9 ∗ nicotineit+β10 ∗ af ter67 ∗ nicotineit + β11 ∗ af ter72+β12 ∗ af ter72 ∗ nicotineit + ai + uit . (1)Two assumptions may also be made:Assumption 1 : E(uit |xitj , ai )= 0,Assumption 2 : Cov(xitj , ai )= 0,where the x are explanatory variables and j = 1, 2, ..., 12, is the number of
explanatory variables; i = 1, 2, ..., 55; t = 1, 2, ..., 35. The two assumptions
presented above are consistent with the characteristics of the sample. It caneasily be veriﬁed that Assumptions 1 and 2 are satisﬁed by the sample used, as
the explanatory variables are the attributes of brands and policy information.
The variables used in the estimation were constructed as follows.

Ddenotes the annual demand for each brand, divided by the Japanese population;
timeofis a time trend for the years 1950, 1951, ..., 1984;

time

divided by 100;

price

time2

is the squareis the nominal price of each brand divided

by the consumer price index (CPI); income is Japanese per capita disposable
income divided by the CPI;

after64

period after 1964 and 0 otherwise;

is a time dummy, which equals 1 for the

plain
11

is a dummy for plain brands, whichequals 1 if the brand was plain and 0 otherwise;

after64*plain

after67

for the intersection of after64 and plain;is a time dummy, whichtar

is the tar content

after67*tar

is a term for theequals 1 for the period after 1967 and 0 otherwise;of each brand as disclosed in the newspapers;

is a termintersection of after67 and tar;nicotine

as disclosed in the newspapers;

after67*nicotine is a term for the intersectionof after67 and nicotine;

after72

period after 1972 and 0 otherwise;of after72 and tar; andis the nicotine content of each brandis a time dummy, which equals 1 for theafter72*tar

after72*nicotine

is a term for the intersection

is a term for the intersection ofafter72 and nicotine. The number of observations, maximum value, minimum
value, average, standard error, and so on, for each variable, are summarized inTable 1.

5.3

Information on nicotine and tar content before 1967

In 1967, the nicotine and tar content of only existing brands was tested. Thus,
information on nicotine and tar content before 1967 is lacking. Therefore, theassumption was made that the nicotine and tar content prior to 1967 was equal
to the value disclosed in 1967. Given that nicotine and tar levels are the primarycharacteristics of a cigarette brand, JT may have chosen to produce new brands,
rather than change the content of its old brands; JT would have incurred large
costs in changing the components of an existing brand.7
Accordingly, consumers could not “see” information about nicotine and tar
content before 1967, but it would be reasonable that they might estimate thecontent of their favorite brands to some degree by their taste sensations. To
capture this eﬀect, I use information about nicotine and tar content in 1967 asa proxy for the one prior to 1967.
7 See thefor details.

History of the Japanese Cigarette Monopoly

12(Tabako Senbaishi in Japanese)

5.4High correlation between nicotine and tar

It is reasonable that cigarette consumers should generally choose brands basedon their information about nicotine and tar content. As high-nicotine brands
always have a higher tar content, tar content is strongly and positively correlatedwith nicotine content. In fact, the coeﬃcient of correlation in this case is 0.9261.
Therefore, the possibility of multicollinearity arises when nicotine and tar areboth included in a regression equation. In consequence, either nicotine or tar
was dropped from the model to control for this potential problem.
However, the coeﬃcient of correlaton is not equal to 1, it also makes sensethat the estimation is performed including both nicotine and tar. If eithor
nicotine or tar is dropped from the model, the issue of an omitted variable mayarise. Thus, I make three estimations and then compare their results to control
for these issues.

5.5

Data unavailable after 1984

Data from 1985 are not available, because JT has not disclosed its inter-brandcigarette sales information since its privatization in 1985. If the information disclosure events considered in this paper were unrelated to JT’s privatization, thenthe obtained estimators should be consistent.8 It is reasonable that these eventsshould have been independent, because JT’s privatization was mainly caused bytrade conﬂicts and the trade-liberalization talks that took place between Japanand the United States in the 1980s.9 Partially relevant information is also available from the following Web address. http://www.kantei.go.jp/jp/gyokaku/1006kiki2besi.html

8 See Chapter 17 of Wooldridge (2002) for details.

9 See thefor details.

History of the Japanese Cigarette Monopoly

13(Tabako Senbaishi in Japanese)5.6

Unobserved (potentially existing) samples

The observed sample is unbalanced because new brands were introduced andsome old brands were withdrawn from the market at diﬀerent times. The demand for discontinued brands or those that had not yet been introduced could
not be observed. This observation indicates a typical selection bias problem, assuming that the introduction and discontinuation of brands was a choice madeby JT. Under the assumption that JT s strategy for the introduction and discontinuation of brands was based on the observed information x in equation (1)and the unobserved time-invariant ai , a relevant ﬁxed-eﬀects estimator should
be unbiased.10
If JT’s strategy for the selection of brands were based not only on the information in equation (1), but also on the unobserved time-variant growth rate of
demand, the following random growth model would be more suitable.
ln(Dit ) = γ0 + γ1 ∗ time + γ2 ∗ time2 + γ3 ∗ ln(priceit ) + γ4 ∗ ln(incomet )+γ5 ∗ af ter64 + γ6 ∗ plaini + γ7 ∗ af ter64 ∗ plaini + γ8 ∗ af ter67+γ9 ∗ ln(nicotineit) + γ10 ∗ af ter67 ∗ ln(nicotineit)+γ11 ∗ af ter72 + γ12 ∗ af ter72 ∗ ln(nicotineit)+gi ∗ time + ai + uit . (2)

Here,

ln

denotes the natural logarithm, and gi is the potential growth rateof brand i. An estimation of this speciﬁcation was also performed.

5.7

Estimation methods

For the purpose of estimating equation (1), ﬁxed-eﬀects (FE, where Assumption 2 is not required) and random-eﬀects (RE) panel estimation techniques
10 See Chapter 17 of Wooldridge (2002) for details.

14were used. A Hausman-Wu test was used to identify which speciﬁcation was
superior.11
In the estimation of equation (2), the ai were removed via ﬁrst-diﬀerencing;
this diﬀerenced equation was then estimated using FE (with the gi removed)
and RE methods. In this process, the variables time and time2 in equation (2)became constant, as did time in the diﬀerenced equation.

5.8

The monopolistic ﬁrm’s strategy for the selection ofbrandsPooled ordinary least squares (POLS) estimation was used to determine how JT
selected new and discontinued brands in response to the mandatory disclosure of
nicotine and tar content information. A new brand dummy (new brand), whichequals 1 at the time of the ﬁrst observation of a new brand and 0 otherwise, wasconstructed, in addition to a discontinued brand dummy (discontinued brand),
which equals 1 when a brand was observed for the last time and 0 otherwise. The
dependent variable was taken to be either nicotine or tar, while the independent
variables included time, the square of time, after67, after72, the new branddummy, and the discontinued brand dummy, which characterized JT’s strategy
of brand selection. These estimations were essentially diﬀerence tests for the
nicotine and tar content of discontinued brands, as well as those of new andexisting brands, both before and after 1967 and 1972, that were performed toverify whether there were signiﬁcant diﬀerences.

11 Even though FE estimators are sometimes accepted by the Hausman-Wu test, RE estimation results may also be robust in this context because nicotine and tar levels are nearlytime invariant.

15

6

Results and Their Explanation

6.1

Panel estimation with level data

Table 2 presents the results of the panel regressions using level data. The
ﬁrst and second columns contain results regarding nicotine, while the third andfourth columns contain results concerning tar. The Hausman-Wu test for theestimation with nicotine accepted the RE formulation. Note that the coeﬃcients
after64,

forafter67,

andafter72

for this case are signiﬁcantly positive,

as indicated in the ﬁrst column.12 Similarly, the Hausman-Wu test for theestimation with tar ﬁt the FE formulation, and the coeﬃcients forandafter72

after64

presented in the fourth column are signiﬁcantly positive. These

results imply that the policy events of 1964 and 1972 both increased cigarettesales. However, the coeﬃcient for after67 in the fourth column is signiﬁcantly
negative and is opposite in sign to the coeﬃcient in the case of nicotine, implyingthat the coeﬃcient forafter67

considered, and that the variable

is sensitive to whether nicotine or tar wasafter67

may have been highly correlatedwith nicotine and tar content itself. Thus, it is not clear whether the sale ofcigarettes truly increased after the policy event of 1967.
In the ﬁrst column of the same table, the coeﬃcients forcome

are not signiﬁcant. The coeﬃcient forbut the coeﬃcient forafter64*plain

the estimated coeﬃcients for

plain

plain

price

and

in-

is signiﬁcantly positive,

is signiﬁcantly negative. The sum of
andafter64*plain

is signiﬁcantly neg-

12 Due to the event in 1964, consumers signiﬁcantly switched to ﬁlter-tipped cigarettes. The
ﬁlter-tipped cigarette would be felt light compared with the plain brands when the otherfactors were the same, thus smokers would smoke more to keep the smoking or nicotine
stock in their bodies. The other reason might be the consumers illusion, that is, the ﬁltertipped were considered safer , thus the smoker could smoke more safer (ﬁlter-tipped)cigarettes under the same health risk. Even though consumers still preferred high-nicotine
brands after 1972, but coeﬃcients on after67*nicotine and after72*nicotine are signiﬁcantly
negative, respectively. These results implied that consumers switched to lower-nicotine brands
after these policy changes. Those consumers had to consume more lower-nicotine cigarettes
to keep or smooth the intake of nicotine as shown in Figure 4.

16

ative ( plain+

after64*plain= 123.194, standard error = 63.004, p =0.051), which suggests that the sales of plain cigarettes decreased signiﬁcantly
and implies that smokers started to buy ﬁltered cigarettes after the policy eventof 1964. The coeﬃcient for

nicotine

cients for after67*nicotine andis signiﬁcantly positive, but the coeﬃ-

after72*nicotine are signiﬁcantly negative.

The sum of the coeﬃcients for

nicotine

cantly positive ( nicotine

after67*nicotine+

andafter67*nicotine

is signiﬁ-= 143.294, standard error =26.569, p = 0.000), which suggests that the demand for high-nicotine cigarettes
increased signiﬁcantly after the policy event of 1967. The sum of the three coeﬃcients for

nicotine,

after67*nicotine,

signiﬁcantly positive ( nicotine+

andafter72*nicotine

after67*nicotine+

is alsoafter72*nicotine= 57.521, standard error = 25.952, p = 0.027), which suggests that the demandfor high-nicotine cigarettes increased signiﬁcantly, even after the policy eventof 1972. These results indicate that the sales of high-nicotine brands decreased
signiﬁcantly compared to those of low-nicotine brands, after the introduction of
the information disclosure regulations in 1967 and in 1972; however, consumers
generally still preferred high-nicotine brands.
In the fourth column, the coeﬃcient for price is negatively signiﬁcant. The
coeﬃcient forincomeis not signiﬁcant. The coeﬃcient forafter64*plain

is signiﬁcantly negative and implies that the sales of plain cigarettes decreased
signiﬁcantly after the policy event of 1964. The coeﬃcient forafter67*tar

but not signiﬁcant. The coeﬃcient forbut the coeﬃcient forcoeﬃcients forafter67*tar

tarafter72*tar
and

tar

is positiveis signiﬁcantly positive,

is signiﬁcantly negative. The sum of theafter67*tar

is signiﬁcantly positive ( tar+= 13.631, standard error = 3.510, p = 0.000), which suggeststhat the demand for high-tar cigarettes increased signiﬁcantly after the policy
event of 1967. The sum of the three coeﬃcients for

17

tar,

after67*tar,

andafter72*tar

after72*tar

is positive but not signiﬁcant ( tar+after67*tar+= 4.333, standard error = 3.651, p = 0.236), which suggests thatthe demand for high-tar cigarettes did not increase signiﬁcantly after the policy
event of 1972. These results indicate that the sales of high-tar brands increased
signiﬁcantly after the introduction of the information disclosure regulations in
1967 but decreased signiﬁcantly after 1972 compared to those of low-nicotine
brands. The increased availability of tar information decreased sales of high-tar
brands following the warning-label legislation of 1972; in fact, consumers havenot signiﬁcantly preferred high-tar brands since 1972.
The ﬁfth and the sixth column present the result when both nicotine andtar are simultaneously included in the estimation. RE and FE estimation are
performed, but the FE result is accepted by the Hausman-Wu test. The obtained
related coeﬃcient sums are
0.019);

nicotine +nicotine+

after67*nicotine= 108.747 (p =after67*nicotine + after72*nicotine = 122.305 (p =0.002); tar + after67*tar = 2.793 (p = 0.609) and tar + after67*tar +after72*tar = - 10.80214 (p = 0.024). These results imply that the consumers
prefer high nicotine and low tar brands after 1972. It is nearly consistent withthe results in the ﬁrst and the fourth column.
I sum up above ﬁndings here. Due to information disclosure, smokers switched
to prefer brands with lower nicotine and lower tar, and they increased cigarette
cosumption; as a result, smokers smoothed or kept their intakes of nicotine,
just as shown in Figure 4. As smoking rate decreased, total intake of nicotine
and tar per capita decreased after information disclosure as shown in Figure 3.
By contrast, total intake of nicotine per smoker almost did not decreased, andtotal intake of tar per smoker only decreased slightly. The consumers’ intake ofnicotine is consistent with the addictive nature of nicotine.13
13 Rational addiction hypothesis is empirically supported by cigarette consumption in Japan.
See Wan (2005) for details.

18

6.2

Panel estimation with growth rate data

Table 3 presents the results for the panel regressions of equation (2) using growthdata. The ﬁrst and second columns present the results of the estimations including nicotine, while the third and fourth columns contain the results fromthe estimations including tar. The Hausman-Wu test accepted the RE estimations (second and fourth columns). The estimated coeﬃcients forand∆ln(income)∆ln(price)

are signiﬁcantly negative and positive, respectively, whichmeans that the inter-brand price elasticity for cigarettes was -0.474 and thecorresponding income elasticity fell between 2.343 and 2.409. The

constant

has a signiﬁcantly positive sign and corresponds to the time trend of equation(2), thus implying that cigarette sales exhibited a signiﬁcant growth trend. The
estimated coeﬃcient for time

is signiﬁcantly negative and corresponds to thesquare of the time trend in equation (2), implying that the trend of the sales
growth was nonlinear. The coeﬃcient for∆after64

is signiﬁcantly negative,

and this implies that the growth rate of cigarette sales signiﬁcantly decreased
after 1964. The coeﬃcients for ∆after67,∆after72, and ∆after64*plain

are not signiﬁcant.
In the second column (FE estimation with nicotine), the coeﬃcients for∆ln(nicotine),∆after67, and ∆after67*ln(nicotine) are not signiﬁcant.

However, the coeﬃcient for∆after72*ln(nicotine)

is negatively signiﬁcant,and this implies that the growth rate of the cigarette sales of high-nicotine
brands did not signiﬁcantly change in 1967 but signiﬁcantly decreased after
1972.
In the fourth column (FE estimation with tar), the coeﬃcients for ∆ln(tar),∆after67,
eﬃcient forand∆after67*ln(tar)∆after72*ln(tar)are not signiﬁcant. However, the co-is negatively signiﬁcant, which implies thatthe growth rate of the cigarette sales of high-tar brands did not change sig-

19

niﬁcantly in 1967 but signiﬁcantly decreased after 1972. In the sixth column(FE estimation with nicotine and tar), the coeﬃcients on time,∆ln(income)andconstant∆ln(price),are signiﬁcant and close to the ones in thesecond and the fourth columns. The other coeﬃcients are not signiﬁcant. It
may be caused by the multicollinearity or by too many parametors.
From the information in Table 3, one may conclude that the policy eventsof 1964 and 1967 did not have signiﬁcant eﬀects on the growth of inter-brandcigarette demand, while the growth rate of the demand for high-nicotine andhigh-tar brands decreased due to the policy event of 1972. Since a consumer’s
choice of brand requires information regarding nicotine and tar levels, one may
infer that the eﬀect in 1972 was ancillary to that of the 1967 information disclosure. The consumer could not have chosen a brand based on nicotine and tar
contents if such content information had not been released in 1967.

6.3

Impacts on the monopolistic ﬁrm

During the period of voluntary disclosure (before 1967), JT did not disclose
content information. In contrast, JT disclosed all information regarding nicotine
and tar content during the period of mandatory disclosure (after 1967). It isnoteworthy that the number of brands on sale increased continuously throughout
both periods, and that the rate of increase became greater after the mid-1960s.
Furthermore, the annual average sales of each brand decreased continuously.
In other words, JT supplied more brands after the introduction of mandatory
disclosure. Moreover, changes also occurred in the composition of consumer
demand for plain versus ﬁltered cigarettes. Before 1964, 3 plain brands wereintroduced, but after 1964, there were no new plain brands. Only 2 ﬁlteredbrands were introduced before 1964, but after 1964, 47 ﬁltered brands wereintroduced. Thus, JT supplied more ﬁltered brands and fewer plain brands

20

after the policy event of 1964. In addition, graphs of the time transitions for thenumber of discontinued and new brands indicate that remarkably large numbersof new brands were introduced in 1964, 1967, and 1972.14 No brands werediscontinued before 1972, but many were discontinued thereafter. These facts
imply that JT introduced many new brands in response to the events of 1964,
1967, and 1972 and discontinued many brands in response to the policy eventof 1972. Finally, the average nicotine and tar content of both discontinued andnew brands indicates that a transition occurred in favor of low tar and nicotine.
In particular, the average nicotine content of the discontinued brands was higher
than that of the new brands, implying that JT discontinued many high-nicotine
brands and introduced many low-nicotine brands. Similarly, the amount of tar
in the discontinued brands was on average higher than that of the new brands,
implying that JT discontinued many high-tar brands and introduced many lowtar brands.
After 1967, 20 brands were discontinued, while 39 new ones were introduced;
only 13 brands had been introduced before 1967. Using a diﬀerence test, it
was possible to determine that the nicotine and tar content of the cigarettes
that were discontinued after 1967 was higher than that of the newer brands.
Moreover, it was likewise determined that the nicotine and tar content of brands
introduced before 1967 was much higher.
To formally test the above implications, four estimations were performed
using POLS. The results of these estimations are summarized in Table 4. The
ﬁrst and second columns contain the results for the nicotine content of new
and discontinued brands, while the third and fourth columns present the results
for tar content. In the third column, the coeﬃcients for
ter72,

andnew brand

discontinued brandafter67,af-

are signiﬁcantly negative, but the coeﬃcient foris signiﬁcantly positive. These results imply that JT

14 The graphs are available upon request.

21

supplied more lower-nicotine brands and discontinued higher-nicotine brands.
In the fourth column, the results are very similar to those in the second column
and imply that JT supplied more lower-tar brands and discontinued higher-tar
brands.
It seems contradictory that consumers still preferred high-nicotine brands,
and that JT nonetheless discontinued brands of this type and instead supplied
low-nicotine brands.15 However, this may actually be a rational response by
JT: ﬁrstly, high-nicotine brands also tend to be high in tar, and consumers
dislike high-tar brands. In fact, the growth rate of high-nicotine brands was
signiﬁcantly lower than that of other cigarettes. Secondly, if consumers switch
to consume low nicotine brands, they have to consume more cigarettes to smooth
the intake of nicotine because of nicotine’s addictive nature; Thus, JT may sellmore cigarettes and get much larger proﬁt. This strategy of brand selection
would be consistent with JT’s proﬁt maximiziton.

7

Conclusion and Policy Implications

By incorporating information on product contents into the demand equation,
this paper has presented a new way to test the eﬀects of information disclosure
on consumption. Moreover, this new methodology was used to test the eﬀects ofmandatory information disclosure regulations on Japanese inter-brand cigarettedemand. The main ﬁndings are as follows.
In 1964, the demand for all cigarette brands increased, and the demand forplain cigarettes decreased, due to the dissemination of

A Notice about Health

Damage from Smoking. The growth rate of the demand for all brands decreased
from 1964. Compared with that for low-nicotine brands before the information
disclosure, the demand for high-nicotine brands decreased due to the mandatory
15 This point was ﬁrst argued by Takeo Hoshi.

22disclosure of 1967, and also decreased due to labeling warnings that were implemented in 1972. However, consumers greatly preferred high-nicotine brands
before the information disclosure; in fact, consumers still preferred high-nicotine
brands even after the events of 1967 and 1972. The growth rate of high-nicotine
brands did not change signiﬁcantly in 1967 but did decrease signiﬁcantly after
1972. Compared to that for low-tar brands before the information disclosure,the demand for high-tar brands increased due to the mandatory disclosure in1967 but decreased due to the labeling warnings in 1972. The total eﬀect wasthat consumers generally did not prefer high-tar brand cigarettes after 1972.
The growth rate of high-tar brands did not signiﬁcantly change in 1967 but
signiﬁcantly decreased after 1972.
In harmony with the change in consumer preferences caused by the disclosure of information about the health eﬀects of smoking, JT also supplied more
and better-quality products and discontinued products of poorer quality by supplying more ﬁlter-tipped, low-tar (nicotine) brands and discontinuing plain andhigh-tar (nicotine) brands.16 This JT’s strategy is consistent with its proﬁt
maximiziton because if consumers switch to consume low nicotine brands, they
have to smoke more cigarettes to keep the intake of nicotine and then JT may
sell more cigarettes.
These results are consistent with the time transitions that occurred in the
average nicotine and tar per cigarette, total nicotine intake, and the tar per
capita and per smoker. This suggests that the cigarette consumer had an insuﬃcient amount of information before the disclosure events took place, as the
mandatory disclosure of information resulted in a decreased intake of tar per
capita and per smoker.
The policy implications of this paper are as follows. The mandatory disclo16 Medical research has corroborated that low-tar cigarettes are ofbetter quality thanhigh-tar brands, as tar is a cause of cancer; thus, ﬁltered cigarettes are better than those
without ﬁlters because ﬁlters remove some of the tar and other harmful ingredients.

23sure of information about smoking is likely to decrease the incidence of cancer
caused by tar intake and increase consumer welfare, if consumers always choose
their favorite cigarettes. Thus, mandatory information disclosure is both important and indispensable. These regulations are of great importance to theconsumer in light of the current lack of information provided to consumers,
and they should also force monopolistic ﬁrms to improve the quality of theirproducts by shifting consumer demand.
In closing, there are two major issues that were not been addressed in thisstudy. The ﬁrst is that the addictive nature of smoking was not considered in theestimated model. It would be interesting to introduce the eﬀect of information
disclosure into the framework of Becker et al. (1994) or Wan (in press). The
second issue is that the approach of Yen and Chern (1992) should have beenused to estimate information eﬀects. However, when this approach was used,data limitations became a major problem, because the data set has too many
brands, too many missing values,17 and a very short time-series.

17 This is also a typical attrition issue. See Kawaguchi and Neumark (2004) for details.

24References
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Dranove, D., D. Kessler, M. McClellan, and M. Satterthwaite (2003) Is More Information Better? The Eﬀects of Report Cards on Health Care Providers,
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Fishman, M. J., and K. M. Hagerty (2003) Mandatory versus Voluntary Disclosure in Markets with Informed and Uninformed Customers, Journal ofLaw, Economics, & Organization, 19(1), 45-63.
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Ippolito, P. M., and A. D. Mathios (1995) Information and Advertising: The

25

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Jin, G. Z., and P. Leslie (2003) The Eﬀect of Information on Product Quality: Evidence from Restaurant Hygiene Grade Cards, Quarterly Journal of
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Ministry of Health and Welfare of Japan, Report on Smoking and Health, 1stedition, 1987; 2nd edition, 1993.
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Tobaccoand

Health,http://www.health-net.or.jp/tobacco/front.html.
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Verrecchia, R. (1983) Discretionary Disclosure, Journal of Accounting and Economics, 5, 179-194.

26

Viscusi, K. W. (1992) Smoking: Making the Risky Decision, New York, NY,
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the Graduate School of Economics and Osaka School of International Public
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641.
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Yen, S. T., and W. S. Chern (1992) Flexible Demand Systems with Serially Correlated Errors: Fat and Oil Consumption in the United States, American
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27

Figure 1. Average nicotine and tar content per cigarette

30

2.5

1.5
15
1
10

0.5

5

0

Source: author's calculation

28

1984

1982

1980

1978

1976

1974

1972

1970

1968

1966

1964

1962

1960

1958

0
1956

Average nicotine (mg) per cigarette

20

Average tar (mg) per cigarette

25

2

Average nicotine(mg) percigarette

Average tar (mg)
per cigaretteFigure 2. Cigarette consumption per capita and per smoker
600

500
Cigaretteconsumption(packs per year)
per capita

400

300
Cigaretteconsumption(packs per year)
per smoker

200

100

Source: author's calculation

29

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1974

1972

1970

1968

1966

1964

1962

1960

1958

1956

1954

0

Figure 3. Total intake of nicotine and tar per capita

200

2500

160
140
120

1500

100
80

1000

60
500

40
20

0

Source: author's calculation

30

1984

1982

1980

1978

1976

1974

1972

1970

1968

1966

1964

1962

1960

1958

1956

0

Total intake of tar (mg) per capita

2000

1954

Total intake of nicotine (mg) per capita

180

Total intake ofnicotine (mg) per
capitaTotal intake of tar(mg) per capita

Figure 4. Total intake of nicotine and tar per smoker

600

8000
7000

400
5000
300

4000
3000

200
2000
100
1000
0

0

Source: author's calculation

31

Total intake of tar (mg) per smoker

6000

1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984

Total intake of nicotine (mg) per smoker

500
Total intake ofnicotine (mg) per
smokerTotal intake of tar(mg) per smoker

Table 1
Descriptive statistics
Variable

Obs

Mean

Std. Dev.

Min

Max

id
year

688
688

21.84
1973.59

14.08
7.84

1
1950

55
1984

price

688

0.09

0.04

0.02

0.28

demand̲perincomedemand

688
688
688

90.56
11.79
9610.63

177.003.63
19203.04

0.00062.10
0.06

1114.0915.37
132234.20

nicotine
tar

688
688

1.41
19.68

0.48
4.98

0.30
6

2.76
32

nominal̲price

688

6.14

3.06

1.5

13.32

disposable̲income

688

104854.70

67176.35

2820.41207215

population
cpi
after64
after67
after72
plain
after64*plain
after67*nicotine
after67*tar
after72*nicotine

688
688
688
688
688
688
688
688
688
688

109251
69.10
0.88
0.82
0.67
0.26
0.16
1.05
15.04
0.79

9153.82
30.87
0.32
0.38
0.47
0.44
0.36
0.62
8
0.63

83200
16.14
0
0
0
0
0
0
0
0

120235112.10
1
1
1
1
1
2.76
32
2.2

after72*tar
time

688
688

11.57
24.59

8.70
7.84

0
1

27
35

time̲square/100Δln(demand)Δln(income)Δafter64

688
633
633
633

6.66
-0.05
0.04
0.01

3.42
0.74
0.04
0.12

0.01
-7.82
-0.01
0

12.25
4.16
0.11
1

Δafter64*plain
Δafter67

633
633

0.01
0.03

0.10
0.16

0
0

1
1

Δln(nicotine)

633

-0.01

0.05

-0.42

0.36

Δafter67*ln(nicotine)
Δafter72
Δafter72*ln(nicotine)Δln(price)Δln(tar)

633
633
633
633
633

0.01
0.04
0.01
-0.02
-0.01

0.11
0.19
0.10
0.10
0.04

-0.42
0
-0.51
-0.22
-0.47

1.02
1
0.79
0.32
0.23

Δafter67*ln(tar)Δafter72*ln(tar)

633
633

0.07
0.11

0.51
0.57

-0.47
-0.47

3.45
3.30

32

Table 2
Effect of disclosure of nicotine and tar content on inter-brand cigarette demand(panel estimation with level data)
Dependent variable = demand̲pertarnicotine
nicotine and tar
RE
FE
RE
FE
RE
FE
time
1.627
2.575
-3.898-3.931
4.784
5.378(5.663)(5.700)(5.819)(5.847)(5.679)(5.725)time̲square/100-8.798(7.761)-10.479(7.838)-1.850(7.946)price-2.111(8.010)-15.473(7.808)**-107.354(332.645)-1.906(10.425)
271.527(35.504)***283.470(75.287)***-350.657(38.892)***-61.273(113.008)
358.687(51.002)***-253.497(63.391)***
268.199(64.286)***10.002(52.863)-16.731(7.904)**41.101(366.156)-0.633(10.477)276.460(35.588)***-515.349 -352.848 -1,236.581 -1,216.566(321.121) (354.587) (311.190)*** (343.490)***income-3.315-2.676-1.429-0.397(10.326)(10.324)(10.839)(10.888)
after64238.845247.177279.594
282.023*********(34.996)(36.892)(36.939)***(34.954)plain
181.562263.517**(71.076)(76.180)***after64*plain-304.756 -312.580-389.269-391.782-355.045
***
***
***
***
(37.287)(37.315)(40.062)(40.098)(38.951)***after67205.345178.972-204.053-207.325-76.812******(113.718)(89.929)(90.970)(113.254)(113.903)
nicotine
254.232
260.170360.230******(42.590)(51.937)***(42.211)after67*nicotine -110.939 -97.694-251.483****(46.516)(47.024)(64.168)***after72
144.234
145.358
201.381194.781275.151(44.379)*** (44.724)*** (62.340)*** (63.530)***(65.645)***after72*nicotine-85.772-84.318
13.558(53.217)(26.117)*** (26.456)***
tar
2.983
4.961
-20.079-18.822***(4.586)(4.720)(5.407)(5.580)***after67*tar
8.516
8.670
21.17821.614(4.405)*(4.425)*(6.004)***(6.042)***after72*tar-9.705-9.298-13.104-13.595********(2.913)(2.983)(5.740)(5.809)**constant-469.642 -446.987
18.11153.059-316.083-284.756(133.414) (129.911)** (137.061)**(121.296)*** (124.167)*** (124.871)
Observations
688
688
688
688
688
688
Number of groups
55
55
55
55
55
55
R-sq: within
0.32
0.33
0.28
0.28
0.34
0.35
between
0.00
0.01
0.00
0.00
0.00
0.00
0.08
0.02
0.06
0.01
0.09
0.01
overallsigma̲u149.47168.67149.64175.89150.49179.62sigma̲e
84.55
84.55
87.31
87.31
80.51
83.51
rho(fraction ofvariance due to
0.76
0.80
0.75
0.80
0.77
0.82
u̲i)
Hausman-Wu
6.23
82.09
20.52
test statistics
Standard errors in parentheses*
significant at 10%; ** significant at 5%; *** significant at 1%

33

Table 3
Effect of disclosure of nicotine and tar content on growth of inter-brand cigarette demand(panel estimation with data on growth rates)
Dependent variable = Δln(demand)
nicotinetar
nicotine and tar
RE
FE
RE
FE
RE
FE
time
-0.016-0.026-0.016-0.026-0.016-0.026(0.006)*** (0.006)***(0.006)*** (0.006)***(0.006)*** (0.006)***Δln(price)-0.441(0.285)-0.078(0.496)-0.474(0.280)*2.409(1.256)*-0.207(0.486)Δln(income)

1.498(1.268)

Δafter64
Δafter64*plain

0.106(0.561)0.277(0.550)Δln(nicotine)

0.927(1.130)-0.065(1.136)

Δafter67

0.540(0.596)0.162(0.595)

Δafter67*ln(nicotine)-0.569(0.928)0.148(0.929)Δafter72

0.087(0.209)0.086(0.208)

Δafter72*ln(nicotine)-0.944(0.411)**-0.908(0.410)**-0.443(0.286)-0.075(0.497)-0.474(0.280)*2.343(1.254)*-0.208(0.487)-0.070(0.499)-0.474(0.281)*
2.362(1.262)*-0.207(0.487)0.098(0.562)0.277(0.551)

0.096(0.563)0.283(0.552)

10.94(1.814)0.635(1.799)0.526(6.109)-0.1.831(5.991)-0.609(1.603)-0.287(1.583)

1.302(3.782)-0.266(3.723)-0.768(0.719)-0.970(0.708)1.479(1.267)2.230(3.988)4.518(2.273)**-0.923(3.964)3.711(2.264)-0.440(0.287)1.433(1.276)Δln(tar)

1.082(1.520)-0.230(1.514)0.334(2.481)-1.356(2.441)

Δafter67*ln(tar)-0.635(1.242)0.368(1.235)0.012(2.144)0.706(2.102)

Δafter72*ln(tar)-1.315(0.752)*0.494(0.192)**-0.428(1.327)0.122(1.306)0.278(0.200)0.491(0.192)**constant

0.288(0.200)0.487(0.191)**-1.589(0.756)**0.285(0.199)Observations
Number of groups

633
55

633
55

633
55

633
55

633
55

633
55

0.10
0.22
0.02
0.30
0.67

0.11
0.23
0.02
0.58
0.67

0.10
0.21
0.02
0.29
0.67

0.11
0.22
0.02
0.57
0.67

0.10
0.21
0.03
0.28
0.67

0.11
0.22
0.02
0.58
0.67

0.16

0.42

0.16

0.42

0.15

0.42

R-sq:

withinbetweenoverallsigma̲usigma̲erho(fraction ofvariance due to u̲i)
Hausman-Wu test
statistics

78.44

33.21

Standard errors in parentheses*

significant at 10%; ** significant at 5%; *** significant at 1%

34

22.66

Table 4
Nicotine and tar contents among new, existing and exiting brands(pooled OLS estimation)
Dependent variable=nicotine
time-0.029-0.334***(0.015)(0.089)-0.035(0.021)*-0.028(0.029)-0.327(0.206)(0.009)time̲square/100-0.019Dependent variable=tar

after64
after67

after72***-0.103(0.151)-0.442(0.287)

0.062

0.311

(0.090)(0.885)-0.119-1.880(0.068)*(0.669)***-0.199-2.216(0.053)***(0.523)***new̲brand-0.294(0.051)***-0.289(0.051)***-2.694(0.506)***-2.621(0.498)***exiting̲brand

0.119

0.141

1.182

1.434

(0.792)(0.778)*30.18228.014

constant(0.080)(0.079)

2.367

2.240

(0.091)***(0.122)****(0.902)***(1.200)***Observations

652

652

652

652

R-squared

0.47

0.49

0.51

0.54

Standard errors in parentheses*

significant at 10%; ** significant at 5%; *** significant at 1%35