The Impacts of Tax Policy on Alcoholic Beverage Sectors
and Alcohol Demands in Japan
Makiko Omura
Faculty of Economics
Meiji Gakuin University

No.13-03
November 2013

The Impacts of Tax Policy on Alcoholic Beverage Trends and Alcohol Demands in Japan
Makiko Omuraa

Abstract
This paper examines the evolution of alcohol sectors and the impact of tax policies on these sectors,
as well as the alcohol beverage demand systems in Japan, utilising the data from 1948 to 2011. Withtax policy analyses, liquor tax policies are found to have exerted different impacts on productions
and consumptions of different types of alcohols. Whilst sectoral growth and general economic
performance in terms of final consumption expenditure per capita are found significant with major
positive impacts, tax rates were found to have mixed impacts depending on the type of alcohol. The
analyses suggest the possibility of preferential tax rates being beneficial for boosting sectoral
performances for certain alcohols. The results from double-log and demand system equation
estimations of five alcohols suggest that all alcohols are normal goods with positive expenditureelasticities except for shōchu. Although shōchu is also suggested to possibly be the safest taxable
subject in Ramsey sense, the own-price elasticity estimates provide less coherent results, dependingon the applied model.
Key Words: liquor/alcohol tax, panel analysis, time-series analysis, AIDS, QUAIDS, dynamic
AIDs, JapanJEL Classification: H29, K34, N55_________________________
a. Associate Professor of Economics, Faculty of Economics, Meiji Gakuin University
e-mail: makiko@eco.meijigakuin.ac.jp
The author is grateful for Brain Poi for his advice in conducting the AIDS estimations.
1Introduction
In many countries, government policies have been playing major roles in alcoholic industry. The
importance of liquor tax has been examined by numerous authors worldwide, mainly to investigate
two issues: (1) its role in mitigating the adverse effects and social cost of alcoholic consumption,such as health problem and vehicle accidents (Cook and Moore, 2002; Chaloupka, Saffer and
Grossman, 1993; Cook and Tauchen, 1982); (2) its role in raising the tax revenue for the government.
These studies seem to give liquor tax sufficient justification for its existence and appropriate rateincrease, although some studies cast doubt on the claimed effectiveness of tax (Kenkel, 1996; Mast
et al. 1999). The liquor tax in Japan has always had its major footing on the tax revenue side. 1
Whatever the government intentions of taxing may be, whether liquor tax has any impact on the
production and consumption of alcohols is a matter of concern, as it can suggest the possibility of
liquor tax being an effective tool for different policy purposes. There are also views that excise tax,
and especially that on things such as alcohols and tobacco is less distortionary. According to Ramsey(1927)’s optimal consumption tax which minimises welfare losses due to price distortions, tax rateshould be inverse to the price elasticity of demand for the goods – thus, inelastically demanded
goods should be taxed more heavily. 2 There are studies which suggest that the alcohol consumption
is price inelastic, particularly for heavy drinkers, (Manning et al. 1995). On the other hand, there arestudies suggesting that alcohols consumption responds well to the price change, with negative
own-price elasticities varying in degrees depending on the alcohol type, as mentioned in Cook and1

To mitigate adverse alcoholic effects, Japan has taken a path to administer other regulations, such as increased
severity of punishment for drunk driving both in terms of criminal charges and social sanctions, rather than using
tax as a tool. For instance, public servant can even lose his job from drunk driving alone, without causing any fatal
accident, and restaurants and pub owners or personnel will be charged if they sell alcohol knowingly that thecustomer is driving back. There are few studies which estimated the social cost of alcohol-related problems inJapan, which show considerable costs to the society, although they used the base estimated figures from studies in
the US that can shift the estimation results drastically (Nakamura et al., 1993; also see Kaji, 2013, for more
information on various studies).
2
According to Corlett and Hargue (1953/54), the ideal tax should impose excise tax on all goods including leisure,and that tax revenue can be raised by imposing higher tax rates on goods that are complementary to leisure. If weconsider alcohols (and drinking) to be complementary to leisure and substitutes for labour, then higher liquor tax iswarranted.

2

Moore (2002). Price elasticities are estimated to be quite different depending on alcohol types,
among which beer typically has the lowest elasticities. For instance, a study by Clements et al.
(1997) estimating demand systems for beer, wine and spirits with 30 years data for seven countries in
Europe, Oceania and Northern America, found the average income and own-price elasticities thelowest for beer, 0.6 and -0.35, respectively. According to studies by Elder et al. (2010) who compiled
past studies on the impacts of alcohol tax, the price elasticity of demand for alcohol, althoughmeasured in different ways, found a median elasticity of -0.50 for beer, -0.79 for spirits, and -0.64 forwine. 3 However, there are also studies showing variations in elasticity estimates. Eakins andGallagher (2003), applying static and dynamic Almost Ideal Demand System (AIDS) models,estimate the own-price elasticity of beer to be -0.42~-0.77 depending on the applied model, whilethat of spirits and wine are -0.68~0.84 and -0.36~-1.59, respectively. They also compiled past studies
showing wider ranges of elasticities, such as beer’s own price elasticities varying from 0.09 to -0.95.
Andrikopoulos and Loizides (2010), applying a dynamic AIDS (DAIDS) for the analysis of beer,
wine and brandies in Cyprus, found in one of the estimation models beer to be price-elastic withstatistically significance while others were not. Obviously, the estimates can vary with data,
estimated demand functions and the formula for calculating elasticities. The estimation of elasticities
has been and still is an important topic as it can suggest policy directions.
In Japan, the alcoholic industry used to be one of the major contributors to the tax revenue.
Japanese government has executed several significant legal changes regarding alcohol production
and consumption, including the tax rates. There are yet few studies on the impact of liquor tax. One
study, which the author is aware of, estimate the price elasticity of saké as 0.58, shōchu as -0.15, beer
as -0.63, whisky as -0.35, and low-malt beer, referred here as fizzy drinks, as 0.61 (Takahashi et al.
2009), although the method taken is rather ad hoc, in the sense that they calculated elasticities basedon the differences in consumed quantities of goods at the currently prevailing prices and the3

No standard errors (SE) or statistical significance for the elasticity estimates are provided by these studies(Clements et al., 1997; Elder et al, 2010; Eakins and Gallagher, 2003).

3

hypothetical prices excluding the liquor tax. 4 Another paper which investigates income and priceelasticity of wine with double-log and Bayesian Age-Period-Cohort models, along with thedeterminants of wine consumption, gives the elasticities of -4.02 and -0.57, and of -0.001 and -0.798,
for income and price elasticities respectively, although none had statistical significance (Mori et al.
2012).
In this paper, we examine the evolution of alcohol sectors and the impact of tax policies on these
sectors, as well as the alcohol beverage demand systems in Japan, utilising the data from 1948 to2011. Firstly, we look at the production and consumption trends of alcohols, then we provide a brief
overview of the liquor tax system in Japan. An empirical model for analysing the impacts of tax ispresented, followed by the estimation results, where estimations are conducted for the panels ofdifferent alcohols and for each alcohol type. We then estimate income (expenditure) and priceelasticities of demand applying the double-logarithm (log-log) model, the AIDS model and its
several variants, which includes household characteristics, quadratic AIDS (QAIDS) and DAIDS.
Production and Consumption Trends of Alcoholic Beverages
Japan has seen different evolutionary paths for different types of alcoholic beverages since the endof the World War II (WWII). Government policies have had significant influences on the conduct of
alcoholic industry, as it was one of the major sources of tax revenue for the government for a longtime. In particular, saké industry has been greatly affected, because that was the major alcohol
consumed by the general public before the WWII, and because rice, from which saké is made, hasbeen and still is the main staple food of Japan. During the late 1950s to the 1970s, Japan experienced
a rapid economic growth as well as increasing westernisation of food and beverages. Westernalcoholic beverages such as beer, whisky and wine were on their increasing demand, particularly
since the 1970’s, and combined with the prevalence of low-quality saké originating from the4

Positive and negative signs are added by the author from their results table, since they did not specify them intheir results. No SE is provided.

4

war-time shortage of rice, the upsurge of other alcoholic beverages were inevitable.
As we can see in Graph1, saké production and consumption are clearly decreasing after the oilshock in 1974, although it seems to be stabilising in recent years. In this graph, the production trendof saké is shown together with the taxed quantity of saké, since the produced quantity is measured in
its higher alcohol content of approximately 18~21º and while it is taxed in diluted quantity at around
15º, the degree in which it is normally sold and consumed. 5 The excess of taxed quantity of saké tothe produced quantity has largely been increasing since the oil shock up until the early 1990’s. This
may suggest that saké was increasingly diluted, perhaps due to a more efficient method of creating
raw saké with higher alcoholic content and/or due to an increasing demand for lower
alcoholic-content beverages, as highlighted by the sharp growth of beer, liquor and fizzy drinks. The
subsequent continuous decrease in the discrepancies between produced and taxed saké may suggest
the shift in the structure of saké types produced and demanded – the high quality saké, ginjoshu,
generally need not be diluted as it has alcohol content of around 15.5º in its raw form.
Shōchu, a Japanese spirit has much higher alcoholic contents compared to saké or wine, but are
generally taken in a diluted from. There are two types of shōchu: (1) kō-rui shōchu which contains
alcohol of less than 36º and is generally mass-produced by continuous- distillation method using
unrefined saké called moromi; (2) otsu-rui shōchu which contains alcohol of less than 45º and is
produced by single-distillation method using natural grains and potato. There are several kinds ofotsu-rui shōchu, made from either rice, wheat, buckwheat, foxtail millet, sweet potato, potato,chesnut, or brown sugar of Amami Islands, and they usually have distinct aroma. Many of theseotsu-rui shōchu are allowed to use a label of authentic (honkakuha) shōchu, if they meet thestandards set by the government in 2002. Shōchu has traditionally been regarded as a cheap ethanol
popular amongst the labour class, and authentic shōchu with strong aroma were mostly consumed
only within the region. Nonetheless, the improvement of distillation technology, together with the5

The information based on a personal communication with the National Tax Agency staff, although there is also
information that raw normal sake has alcohol content of around 22~23.º5

legal labelling of authenticity raised the branding value of these quality otsu-rui shōchu nationwide,
leading to the shōchu boom around 2003-2005 consumer seeking rare brands. 6

200
400
600 800
beer quantity(10,000KL)

3000

Graph1. Selected Alcoholic Beverage Production & Consumption: 1950-2011
quantity(1,000KL)
1000
2000

1994 H6 tax rev & third beer launch2006 H18 tax rev
1974 oil shock

1989 H1 tax rev

2003 H15 tax rev

1983 light bottle appears001968 sake-rice ration ends

1950

1955

1960

1965

1970

1975

1980 1985
year

1990

1995

2000

2005

2010

bubble economy

prd_sake

taxq_sakecons_sake

prd_shochu

cons_shochu

prd_whisky

cons_whisky

prd_wine

cons_wine

prd_spirits

cons_spirits

prd_liquor

cons_liquor

prd_fizzycons_fizzy

prd_beer in 1/10

cons_beer in 1/10

Note: 'taxq_sake reflect actual quantity as raw sake is diluted(prd_sake (except for some type) contains 18~21 degree of alcohol,
yet sold and consumed at about 15 degree of alcohol); Wine, liquor and fizzy drink categorised data available since 1963 and previous
year data are extrapolated using the aggregate data and corresponding categerical ratio data in 1963; liquor includes various beverages
made with alcohol, sugar and extract of 2 degree or more; liquor and fizzy include different types of the third beer.
Data Source: Japan National Tax Agency(2013)


Fizzy and liquor drinks both include different types of the second beer (low-malt beer) and thirdbeer (non-malt beer), which is made with ingredients other than malts such as maize and beans using
different methods. Japanese categorisation of “liquor” includes various sweet/sour cocktails andshōchu cocktail. 7 The rapid growth of liquor and fizzy drinks started in 1994 when Suntory, one of
the largest liquor companies in Japan, has launched the first successful second beer, which was also
called as tax-saving beer. The trend of second beer was followed by a rapid development of various

Other factors for this shōchu boom were heath and women – that shōchu was regarded as healthy alcohol withlow calorie, and was accepted by women who are a new consumer group (Nippon Keizai Shimbun (Kyushu
Regional Edition), 20 August 2004, p.14). The previous shōchu boom with a peak in 1985 was mainly led by thekōrui-shōchu (Development Bank of Japan, 2003).
7
Note also that categorisation of wine also includes wine-like beverages made from other fruits, whisky includes
both whisky and brandy, and spirits includes gin, vodka, rum, as well as distilled alcohol.
66kinds of ‘new genre beer.’ The time was right after the complete burst of the Bubble Economy whenbon-marché was gaining significance in daily life of people in Japan. 8 The prices of these beer-like
drinks have been typically around two-thirds to half of the price of beer, reflecting the lower tax
rate. 9 Looking at Graph1, it seems that H6 Tax Revision in 1994 which coincided the launch of the
new genre beer (categorised in either fizzy or liquor) has shifted the trend in beer downwards. It
looks as if beer was taken over by fizzy, then by liquor. The H15 Tax Revision of 2003 seems to haveshifted the fizzy trend downwards, while increasing the trend for liquor, which appears to be evenaccelerated by the H18 Tax Revision of 2006 that reduced the corresponding tax rate by 40% (seefootnote 6).
Saké, shōchu in diluted form, and wine, which are all typically taken with meals, can be
distinguished from beer, liquor and fizzy drinks due to its mid-range alcoholic content. As we cannot
see the trends for wine in Graph1 due to its relatively low quantity, we present saké, shōchu and wine
production and consumption separately in Graph2. Unlike saké, there is an increasing trend ofshōchu, as Japan experienced an authentic shōchu boom around 2003-2005 that boosted
consumption and shed lights on various kinds of shōchu. Nonetheless, its increasing trend seems tohave halted after the boom. Compared to saké and shōchu, we see much lower quantity of wine
production and consumption in the left panel of Graph2. If we look at the log
production/consumption in the right panel, however, wine shows even more rapid increase in its
trends compared to shōchu, although its growth has also somewhat stabilised after the 1998
polyphenol boom when red wine was particularly sought after.

8Japan experienced a period of economic bubble, mainly from the end of 1986 to 1991, due to real estate andstock exchange speculations.
9
For a typical size of beer (350ml), the tax were (1) ¥77.7 for beer and fizzy drink with malts content of 50% or
more, (2) ¥53.4 for fizzy drink with 25-50% of malts, and (3) ¥36.8 for fizzy drink with 0-25% malts. The 2003
revision has extended (1) to include fizzy drink with 50% or more of malts and wheat, increased the tax of (2) and(3) by ¥8.9 and ¥10.2, and also newly imposed tax of ¥47 onto (4) other fizzy drinks. The 2006 tax has decreased
the tax of (4) by ¥19 (National Tax Agency 2003, 2006).

7

8

2000

Graph2. Selected Alcoholic Beverage Production & Consumption(in 1,000KL & log): 1948-2011
sake-rice ration ends

log quantity(1,000KL)
4
6

500

sake-rice ration ends

oil shocklight bottle appears
oil shockpolyphenol boom0

polyphenol boom

2

quantity(1,000KL)
1000
1500

light bottle appears

1940

1960

1980
year

2000

1940

2020

1960

1980
year

2000

bubble economy

prd_sake

taxq_sakecons_sake

prd_shochu

cons_shochu

prd_wine

cons_wine

2020

Note: 'taxq_sake reflect actual quantity as raw sake is diluted(prd_sake (except for some type) contains
18~21 degree of alcohol, yet sold and consumed at about 15 degree of alcohol).
Data Source: Japan National Tax Agency (2013)


A Brief Overview of the Liquor Tax 10
In this section, we briefly review the evolution of the liquor tax which saw several major changes inrecent decades, a summary of which is provided in Table1. Currently, there are mainly ten types ofalcohols being classified by the liquor tax law, (1) saké, (2) synthetic saké, (3) shōchu (Japanesespirits), (4) beer, (5) whisky and brandy, (6) wine, (7) spirits, (8) liquor, (9) fizzy drinks, (10) otheralcohols. The evolution of liquor specific (volume-based) tax is shown in Graph3. The provided
liquor specific tax rate is the base rate for each category, and the actual tax rate is increased
according to the ethanol content above the base degree. 11
The liquor tax has a long history and numerous changes since 1872. The existing tax law was

10

The information here is based on the liquor tax evolution table (1950-2006) available at the National Tax
Agency.
11
Currently, a one degree increase in alcohol content above the standard is levied an additional JPY10,000 or
JPY11,000 for shōchu, whisky, spirits. Note that there are still sub-categories of tax rate for (9) fizzy and (10) otheralcohols.

8created in 1953 (S28), with significant revision in 1962 (S37) establishing the base for the current tax
structure (Japan Cabinet Office, 2000). 12 In this revision of 1962, the new system of ad valorem tax
was adopted for expensive alcohols, along with the volume-based specific tax for other types ofalcohols. Also, the recategorisation of types took place and the self-assessment tax systemcommenced. The general tendency of liquor tax was such that higher tax rate was applied to
expensive alcohols. For saké, the government set up a revised class system in 1964 (S39), consistingwith special-class, first-class and second-class, and started to levy tax on the special-class saké twoyears later. The system of levying different tax rates to different classes of saké had actually started
earlier in 1943 (S18) and existed until 1992 (H4), when the unified tax rate system for sakécommenced. 13 Similarly, there were complicated ad valorem tax systems for expensive wines andsimple specific tax for other wines. The ad valorem tax for wine was abandoned and tax rate wasunified in 1989 (H1). The specific tax rate in nominal terms was largely reduced during the 1950s,
until the trend is reversed to increasing rate in 1968 for most alcohol types. The specific tax was thenincreased in several stages, until the legal revision of April 1989 (H1) which saw a significant
decrease in tax rate for wine, whisky, beer, and the first-class saké, with the abolishment ofspecial-saké classification as well as the class-system for wine and whisky. 14 On the other hand, tax
rates for shōchu, which was considerably lower than other spirits, such as whisky and brandy, never
reversed its increasing tax trend up to present. 15 The tax rate for wine which has also been
comparatively lower compared to saké or synthetic saké, also reverted to increasing rate in 2003. The
definition of fizzy drinks was significantly modified in 1994, and the rates were increased twice

12

The expression of S# and H# in parentheses signifies the year according to the Japanese era name. We note thissince all legal and official systems in Japan utilise this year-era expression.
13
At one point in time (1958-1962), there were four classes of saké, including quasi-first class. The special-class
was abolished in 1989, three years earlier than the abolition of all saké classes.
14
Along with the liquor tax, we should note that April 1989 marked a significant environmental change that thevery first consumption tax was introduced in Japan at 3%. The consumption tax was increased to 5% in 1997.
15
The increased tax rate for shōchu was induced by international pressure, as the alcohol exporting countries filed
a complaint to GATT/ WTO as Japanese Liquor Tax system was essentially a tariff barrier against the iported spirits(WANDS, 1996; National Tax Agency, 2013).

9since then.
[Table1]tax rates in JPY (per L)
200
400

1989 H1 tax rev

500
1000
1500
2000
whisky tax rates in JPY (per L)

600

Graph3. Liquor Tax Rate Evolution: 1950-2011

2006 H18 tax rev

1994 H6 tax rev

002003 H15 tax rev

1950

1960

1970

1980
year

1990

2000

2010

speclss_sake

1stclss_sake

2ndclss_sake

1stclss_synsake

2ndclss_synsake

1stclss_shochu

2ndclss_shochu

beer

1stclss_wine

2ndclss_wine

1stclss_fizzy2ndclss_fizzy

speclss_whisky

1stclss_whisky

2ndclss_whisky

Data Source: Japan National Tax Agency(2013)
Thus, the differential tax rates for the same alcohol type continued for saké, synthetic saké, wine
and whisky, until all class system was abrogated by the tax revision of May 2006, as shown in
Graph3. The sole exception was shōchu, where the distinction was not ordered by class or rank but
by its production method and ingredients; single-distilled otsu-rui shōchu had a lower tax rate, while
continuous-distilled kō-rui shōchu had higher tax rate, until tax rates were unified in 2000 (H12).16
The actual amount of tax levied for each alcohol type-class is fairly complicated, since it depends on
the actual ethanol contents, and there have been different rules and exemptions on the applicable tax
rates. Given also that we do not have data on class-wise production and consumption for each

Note that in Graph3 & 5, we denoted higher tax rate of shōchu, kō-rui, as the first-class and otsu-rui as thesecond-class merely based on their tax rates. Shōchu’s tax rate is for the base rate of 25º alcohol level.
1610alcoholic beverage, we use average tax rate per alcohol type which is derived by dividing theaggregated taxed value per type by taxed quantity per type, in order to analyse the impact of tax
policy. The aggregated tax value includes ad valorem tax and specific tax. In Graph4a and Graph4b,
we see average tax rates of all major beverage types in nominal terms and real terms, respectively.
The average tax rates in real terms have largely decreasing trends, except for whisky which had alarge bump in the middle, around 1970~1990. Although the tax rate is highest for whisky per kilolitre,
it is the highest for beer in terms of 1º of alcohol, and in terms of tax proportion to averagecommodity price (Table2). By far the lowest tax rate in all aspects is that for wine. Recent tax
revisions have especially attempted to make the tax burden more equitable across different alcohol

1989 H1 tax rev

2006 H18 tax rev

avtax in JPY (per L)
200
300
400

1994 H6 tax rev

2003 H15 tax rev

0

0

100

1997 H9 tax rev

500
1000
whisky avtax in JPY (per L)

500

Graph4a. Average Tax Rates (selected, nominal): 1948-2011

1500

types.

1950

1960

1980
year

1970

1990

2000

2010

sake

synsakeshochubeer

wine

spirits

liquorfizzy

whiskyNote: avtax created by tax-value/taxed-quantity; taxv_wine up to 1962 extrapolated with the corresponding ratio data in 1963.
Data Source: Japan National Tax Agency(2013)
11

400 600 800 1000 1200 1400 1600 1800
whisky avtax in JPY (per L)

avtax in JPY (per L)
200 400 600 800 1000 1200

Graph4b. Average Tax Rates (real): 1955-2011

2006 H18 tax rev

2003 H15 tax rev
1997 H9 tax rev
1994 H6 tax rev

01989 H1 tax rev

1950

1960

1970

1980
year

1990

2000

2010

sake

synsakeshochubeer

wine

spirits

liquorfizzy

whiskyNote: avtax created by tax-value/taxed-quantity; taxv_wine up to 1962 extrapolated with the corresponding ratio data in 1963.
Real term uses deflator for Final Consumption Expenditure (1.1955~1979(1990/H2-constant:64SNA,adjusted to match 2000-const);
2.FY1980~2009(2000/H12-constant:93SNA); 3.2010~2011(2005/H17-constant:93SNA, adjusted to match 2000-const)).
Data Source: Japan National Tax Agency(2013)
[Table2]
Reviewing the price and tax-price ratio for saké, shōchu, beer, whisky and wine, for which we havethe data, generally speaking, nominal prices are increasing with the economic development, while
real prices are decreasing for most alcohols. In the left panel of Graph5, Graph5a, we findmoderately concave trends for saké, shōchu and beer, and more acute concave curves for whisky andwine, hitting the highest prices around the time of Bubble Economy (around 1986-1991). In the rightpanel, Graph5b showing prices in real terms, we have slight convex function for saké, shōchu andbeer, yet more acute movement for wine and whisky. During the Bubble Economy, expensive
commodities were sought after, and the observed trends for whisky and wine are considered toreflect the increased import of high priced items. While the price of whisky was fairly constantly
decreasing after the Bubble’s burst, until 2005, the price of wine did not decrease as much, butreverted to its increasing trends (in real terms) around the mid-1990s, hitting the polyphenol boom of
121997-98.

1970

1980 1990
year

2000

bubble economy
whisky

2010

2000

1960

sake
wine

3000
2500

1500
1000

real price JPY

0

1500

1000
500

0

1960

500

1500

2000

1000
500

nominal price whisky JPY

2500

3000

Graph5b. Average Price per L (real)

real price whisky JPY

Graph5a. Average Price per L (nominal)

nominal price JPY

1500

Graph5. Selected Alcoholic Beverage Average Price per L:
1963-2011 (nominal and real)

1970

1980 1990year

shochu
fizzy

2000

2010

beer

Note: Price calcuated from Average Expenditure data:(1) 1963-2007: 20-3-a Annual Household Expenditures and Quantity Purchased by Commodity(Non-agricultural,forestry and fishery Households with 2 or more, All Japan (1963-2007));(2) 2008-2010: 20-3-b Annual Household Expenditures
and QuantityPurchased by Commodity, (Households with 2 or more, including agricultural, forestry and fisheries households, All Japan(1963-2007));(3) 2011: Annual Household Expenditures and Quantity Purchased by Commodity (Households with 2 or more, All Japan(1990-2012))
Data Source: Japan National Statistical Bureau(2013)
As for the liquor tax-price ratio shown in Graph6, there are several features to be noticed. Most
tax-price ratios are relatively stable or slightly decreasing except for shōchu and whisky. For shōchu,its tax rate was raised considerably in 1997 and 1998 (H9 and H10) due to criticisms by othercountries that its tax rate remained too low in comparison to other spirits such as whisky or brandy(see footnote14). For whisky, we see a steep increase in the ratio during the mid-1960s, then a steep
decrease in the mid-1990s, both due to tax revisions. We see two particularly high tax-price ratios,
whisky and beer. Whilst higher tax ratio for whisky is not unusual since it is generally viewed as aluxurious item, beer is often considered to be a less expensive alcohol consumed by wider population,
thus with relatively low rate of tax vis-à-vis its value. Japan’s having a high tax ratio for beer
originates from an outdated view from the pre-war period, recognising beer as a luxurious imported
commodity. In addition, the fact that beer is produced by large companies makes the collection of
liquor tax easier for the government, and as such, voluntary tax rate reduction may not be easily
13foreseeable. Indeed, beer has been having the highest tax-price ratio for most of periods.

.6

Graph6. Selected Alcoholic Beverage Tax-Price Ratio: 1963-2011
2006 H18 tax rev
2003 H15 tax rev.41989 H1 tax rev.2

tax-price ratio

1997&98 H9&10 tax rev (WTO)

1994 H6 tax rev & third beer launch
1974 oil shock0

1967 S39 registration & license tax begins

1960

1970

1980
sake
whisky1990
shochu
wine

2000

2010

beer
fizzy

Note: price data calculated from consumption expenditure data:(1) 1963 to 2007: 20-3-a Annual Household Expenditures and Quantity Purchased
by Commodity(Non-agricultural,forestry and fishery Households with 2 or more, All Japan(1963-2007));(2) 2008 to 2010: 20-3-b Annual Household
Expenditures and QuantityPurchased by Commodity (Households with 2 or more, including agricultural, forestry and fisheries households,All Japan(2000-2010));(3) 2011: Annual Household Expenditures and Quantity Purchased by Commodity (Households with 2 or more, All Japan(1990-2012))
Data Source: Japan National Statistical Bureau(2013)


Empirical Model: the Impacts of Tax Policy
As we have seen, government policy appears to have significant influence on the supply anddemand of alcoholic beverages. We therefore attempt to estimate likely impacts of tax policy on
production and consumption of different types of alcohols. We set three dependent variables, taxed
quantity (taxq), consumption (cons), and domestic taxed quantity (taxqdome). 17 Taxed quantity (taxq)
of each type of alcohol is used instead of produced quantity. The taxq figures are highly similar to the
produced quantity for most alcohols, yet due to complicated system of measuring production andevolving regulations, taxed quantity more accurately reflects the quantity traded in the market. 18 In

17. The correlation coefficients between these three variables are high, taxq and cons is 0.9995, taxq and taxqdome is0.9678, and taxqdome and cons is 0.9686.
18
While produced and taxed quantities are highly similar for most type of alcohols, with correlation coefficients ofabove 0.99, or above 0.98 (even for saké, synthetic saké and spirits), there is certain divergence for wine withcorrelation coefficient of 0.9523. In addition to the divergence between produced and taxed quantity for saké

14

order to understand the impacts of tax policy on domestic producers, we have taxqdome as one of thedependent variable, yet we currently have data available for shorter period, only since 1980. 19
Therefore, the estimated results will be reflecting more recent trends.
With ten types of alcohols, (1) saké, (2) synthetic saké, (3) shōchu, (4) beer, (5) whisky and brandy,(6) wine, (7) spirits, (8) liquor, (9) fizzy drinks, (10) other alcohols, we conduct panel estimation for
all types as well as for several types together, as categorising them into similar types may elucidate
certain policy impacts. Time-series estimations are also conducted for each type of alcohol separately.
A summary table of variables is provided in Table 2.
Although ideally, we should include tax rates corresponding to classes or categorisation within thetype as an independent variable, we do not have quantity data for each class to enable the class-wise
analysis. Also, the fact that tax rates vary with its produced alcoholic contents within each class forsome alcohol types means that products within the same class can be levied different amounts of tax.
Moreover, the taxing method using the base degree plus the excess degree of alcoholic content alsomeans that tax rate per 1º of ethanol may not necessarily be the same even for the same type ofalcohol. Hence, we utilise an averaged tax rate (avtax) across classes within each type as a proxyvariable for tax policy, derived by dividing the taxed-value by taxed quantity of each type. We see in
Graph5 that average tax rates lie mostly between the first- and second-class specific tax rates for saké
and shōchu for the period during which multiple classes were present, although it is above thestandard specific tax rate for wine. This is due to the presence of ad valorem tax, which was present
until 1989. 20 The ad valorem tax was applied mainly to high valued, imported wine, whisky anddescribe earlier, there are also such divergence for wine. According to a personal communication with the National
Tax Agency officials in 2013, such divergence is considered to be mainly due to the utilisation of imported grape
juice concentrate, which is not necessarily counted in production figure. It can also be due to the time lag between
production and taxation time.
19
For most alcohol types, the proportion of imported alcohols is not very large, except for wine and whisky. Wine
has the highest share of imports, and it has been constantly increasing, accounting for more than 50% of wine
consumption since 1994. For whisky, the proportion has been around 20%, yet on its continuously decreasing trend.
20
The abolition of ad valorem tax in effect can be viewed to have been replaced by the sales tax introduced in thesame year. The sales tax is applicable to all commodities in principle, started at 3% in 1989 (H1) and subsequently

15brandy, although we have no available detailed information on this tax system. In this regard, eventhe average tax figure may not serve as a good proxy for tax policy for the period before 1989 forthese items. We also utilise the tax-price ratio (taxratio) for each alcohol type, which is calculated asa ratio of average real tax value per litre to price per litre, with data from household consumption
expenditure records available since 1963. 21
The tax revisions especially since 1989 is said to have been aiming to achieve “neutrality, simplicity
and fairness” of tax across different alcohol types (Japan Cabinet Office, 2000). As such, if liquor tax
policy has historically been used as a revenue generating tool by the government, we might suspectthat tax policy has been influenced by the market performance such as sectoral growth, rendering thelatter endogenous to the tax system, although not contemporaneously. To avoid the possible
endogeneity problem arising from an omitted variable problem, such as the prospect of sectoral
growth viewed by the National Tax Agency, we include a variable, growth rate of tax value in a
3-year moving average form (ΔlnMA(3)_taxvi). Additionally, we consider final consumption
expenditure per capita (fcepc) to capture the general economic growth, and several dummies tocapture the booms and other significant situational change.
With a panel data set, we would estimate the error-component models with fixed-effects or
random-effects, decomposing the error term uit into vi, type-specific error, and eit that affects
observation it. Nonetheless, the error terms are found to be either or both serially correlated and/or
heteroskedastistic for all the estimation models. 22 Therefore, we conduct estimations with feasible
generalised least squares (FGLS) estimator allowing for panel-specific autocorrelation andheteroskedasticity across panels. We estimate the following basic model with/without someincreased to 5% in 1997. In line with the argument of Chetty et al. (2009), the impact of sales tax may have beensmaller than that of price increase because sales tax was not included in the price tag in the beginning. The
inclusive sales tax, ‘salient tax’ rule was introduced in 2004 (H16), after 15 years.
21
We utilise two data sets for household consumption expenditure record for the period of 1963-2011 for saké,shōchu, beer, whisky and wine. Expenditures are used to derive the average price per litre for each of these alcohols.
The data on commodity price is not used because of partially mismatched categorisation with our data sets.
22
We applied serial correlation test suggested by Drukker (2003) and Wooldridge (2002), and a likelihood-ratio
test for heteroskedasticity.

16independent variables.
(1) INDit = α + β1 lnavtaxit + β2 ΔlnMA(3)_taxvit + β3taxratioit+ β4lnfcepct +γ Dtaxchng+ θ Dboom + uit,
where uit = ρ uit-1 + εt , εt ~ IID(0,σε2),| ρ |<1,

where INDit is either of: lntaxqit, lnconsit, and lntaxq_domeit
The three dependent variables for which we conduct estimations, lntaxqi is log of taxed quantity(taxq), lnconsi is log of consumption (cons), and lntaxq_domei is log of taxed quantity of domestic
produces (taxqdome), for alcohol type i. For independent variables, lnavtaxi (avtax) is the average real
tax rate for i, ΔlnMA(3)_taxvi (grw_taxv), is a growth rate of three-year moving average of taxed
value, taxratioi is the proportion of tax to the price of alcohol, lnfcepct (fcepc) is log of real financial
consumption expenditure per capita, Dtaxchng is a vector of dummy variables denoting the period ofimportant tax changes, S37 (1962-1988), H1 (1989-1993), H6 (1994-211), H5 (2003-2011) and H18(2006), and Dboom is a vector of dummy variables for important events, namely, the red-wine
polyphenol boom (1997-1998) and the shōchu boom (2003-2005).
Given the fact that different types of alcohol may have different reaction to policy changes, we also
conduct estimations using groups of similar alcohols. Thus, estimations are conducted for thefollowing groups: (G0) all alcoholic types; (G1) dinner alcohol (saké, synthetic saké, shōchu, winewith about 12~15º of alcohol), where shōchu is normally taken in diluted form; (G2) hard liquor(shōchu, spirits, whisky, with about 25~50º of alcohol); (G3) light alcohol (beer, fizzy, liquor with
about 5º of alcohol). Additionally, we conduct time-series estimation for each alcohol type, with anautoregressive moving-average (ARMA) model with maximum likelihood estimator, which allows
for autocorrelated dependent variable (the AR component) as well as autocorrelated random
disturbances (the MA component), both of which is set as order of one. 23 Thus the disturbancestructure is: ut = ρut-1 + εt + θεt-1.
23

Since we do not have much theoretical suggestion in determining the appropriate number of lags for wine
consumption, we made use of the correlogram, ran model with higher lags and check their significance, and madeuse of several information criteria, such as the Schwarz’s Bayesian information criterion (SBIC), the Akaike’s
information criterion (AIC) and the Hannan and Quinn information criterion (HQIC).

17

Estimation Results: Impact of Tax Policy
The estimation results are presented in Table3~6 for each groups, G0 to G3. Note that theestimation results in the first column of each table, model (1), exhibited a sign of multicollinearity
with relatively high variance inflation factors of above 10, but are presented here as they are
generally comparable with other model results.
For G0, all alcohol types, we have significant positive impact of sectoral growth (grw_taxv), tax –price ratio (taxratio) and final consumption expenditure per capita (fcepc) on production (taxq) andconsumption, while we find significant negative impact of average tax rate (avtax), all at the 1%
significance level. The findings are robust across different estimation models. The positive
significant impact of tax-price ratio seems to be coherent with the fact of beer, who has the highest
tax-price ratio, being dominant in the market. For domestic production, for which data availability islimited to the past 20 years, the impact of sectoral growth is found to be negative at the 1%
significance level. This finding seems to be matching with the fact that the period mostly coincides
with the long recession period after the Bubble Economy. In a few estimations, we found evidences
for tax change dummy variables being significant, although the findings are not robust. This possibly
suggests that different law change had impacts in different directions for different types of alcohols,
rather than having a unified impact across types.
For the sub-groups of alcohols (G1~G3), significant positive impacts of sectoral growth and final
consumption per capita on production and consumption are generally detected, although thesignificance of sectoral growth is not seen for consumption in G3. The magnitude of impact ofsectoral growth is consistently greater for production than for consumption in all estimations. The
negative impact of tax rate is found to be robust in G2 production and consumption, although it isfound only in some of the estimation models in G1 production, and none in G3. Therefore, tax rate
seems to exert fairly different impacts on different types of alcohol. Tax-price ratio is found to berobustly significant only in G1 production, with positive impacts. The positive significant impact of18

tax ratio may imply that cheaper ranges of alcohols within the same type are more present in themarket. Note that taxratio is not included in the estimation for G3, since the data was available only
for beer in this group. Several tax change dummies are found to be significant and robust.
Particularly for G1, S37tax, H1tax are found to have significant positive impacts on production andconsumption, although H15tax is found to have negative impact on domestic production. The first
two tax revisions characterise major reduction in liquor taxes for most alcohol types, while the last
one increased the tax for synthetic saké and wine. There is limited evidence that booms had any
significant impact across different alcohol types.
[Table3~6]
The results of ARMA estimation for each alcohol type are provided in Table7. Possible
heteroskedasticity is also taken into account by using the Huber/White/sandwich estimator for
standard error (SE) calculations. Two estimation results are presented here for production andconsumption of each type, one with tax rate (avtax) and one with final expenditure per capita (fcepc).
We estimated with either of these independent variables because they exhibited extremely highmulticollinearity in these estimations. The results of estimations with taxratio are not presented here
as it was not found significant in any of the estimations, except for AR(1) estimation for wine
production, where taxratio had a negative coefficient of -0.237 with 5% significance. We present theresults of ARMA whenever MA component is found significant and AR results otherwise. Bothspecifications produced similar results. From Table7, we can see that sectoral performance hassignificant positive impacts on both production and consumption, except for one of shōchu
consumption and whisky production estimations. Similar to the panel estimations, the magnitude ofsectoral growth impact is higher for production, and is particularly high for saké, beer and wine. The
impact of tax rate is found significant and negative in saké production and consumption, beer
production and consumption, and wine production, while the effect is found significant and positivein one of shōchu consumption estimation. This finding for shōchu seems strange yet we see from the19

graphs that its tax rate was increased considerably during the 1990s (Graph3), yet both production
and consumption increased during this period (Graph2). Given the historically low tax rate of shōchu,rate increase itself may not have affected the consumption of shōchu, and it is still the cheapest way
to obtain ethanol (see Table2). Tax rate is estimated to have no significant impact on shōchu
production, whisky production and consumption, and wine consumption. Final consumption percapita is found to be positive significant for all production and consumption, except for shōchu, andthe magnitudes are particularly high for beer. Beer production and consumption, both of which are
the top in terms of quantities, indeed seem to correspond well with the general economic
performance (Graph1). The non-significance of fcepc for shōchu suggest a possibility of shōchu
being an inferior good, whose major boom and price increase happened after the Bubble’s burst. We
find positive significant impact of S37tax (major tax reduction) for saké and whisky productions. We
see significant negative effect of H1tax of 1989 for shōchu, reducing production by approximately
36%. As a matter of fact, shōchu was the only alcohol whose tax rate was increased then, andsignificantly so, by 30% and 44% in nominal terms (as aforementioned, there are two kinds ofshōchu), while all other alcohols enjoyed either reduction or no change in tax rate. As for H6tax of
1994, which increased tax rate for saké, synthetic saké, shōchu, beer, wine, significant negative
coefficient is estimated for saké consumption, shōchu production and consumption, as well as
whisky consumption. Finally, we see significant positive effect of polyphenol boom for wine, both inproduction and consumption, with magnitudes of 16~21% increase.
The estimation results from panel and time-series analyses suggest that tax policies had impacts indifferent directions for different types of alcohols, rather than having a unified impact across types,
indicating a possibility of preferential tax rates being beneficial for boosting sectoral performances
for certain alcohols. Differential impacts of economic growth, tax rates and tax-price ratio suggestthat the income and price elasticities of demand are likely to differ amongst different types ofalcohols, which we shall consider in detail in the next section.
20

[Table 7]
Expenditure Elasticity and Price Elasticity of Demand
Estimation results from the previous section suggest that tax policy has significant impacts on
production and consumption of alcoholic beverages in general. At the same time, differing impacts ofeconomic growth, tax rates and tax-price ratio suggest that income and price elasticities of demand
likely vary with alcohol types. As liquor tax as well as sales tax is currently invisible to consumers,
being already inclusive in the price of alcohols, we investigate the impact of price change on alcohol
expenditures. 24 As Ramsey (1927)’s theory of optimal consumption tax suggests that welfare loss is
minimised if tax rate is set higher for inelastically demanded goods, we estimate expenditure andprice elasticities of demand for alcoholic beverages applying double-log model and the AIDS model,
after Deaton and Muellbauer (1980)’s, and its variants, namely, AIDS with demographic
characteristics, QUAIDS and DAIDS. We utilise annual household expenditure data available for
1963-2011.
The Double-Log Estimation
For elasticity estimation, we first calculate expenditure and constant price elasticity of demand in a
log-log multiplicative form, qit = α· Xtβ ptβ ·eγ t, translated into a log-linear form, utilising aggregate121longitudinal data on commodity-wise household expenditures, across alcohol types (panel
estimation) and per alcohol type (time-series estimation). Thus the estimable equation is:(2)

lnqit = lnα + β1lnXit + β2lnpit + γ1t = α’ + β1lnXit + β2lnpit + γ1t,where lnq stands for log of quantity purchased in ml, lnX is log of total household consumption
expenditure, as a proxy of income, lnp is log of average real price of the goods derived by the actual
expended amount divided by the quantity, t takes into account time effects. The estimated coefficient

24

Note however, that historical tax rates have not necessarily been translated well into the price of alcohols forsome items. For available data between 1963 and 2011, partial correlations between tax rate and real average pricefor saké, shōchu, beer, whisky and wine are: 0.358, 0.697, 0.980, 0.871, and 0.498, respectively.

21

β1 and β2 is partial expenditure and price elasticity of demand, respectively. The model is estimatedwith and without time effects, as well as other household characteristics variables which are available
in average terms across households in any given year, namely the number of family member(hhmem), age of household head (agehh), and number of working members (wkmem), as shown in
Table8. As specified earlier, panel estimation is done with FGLS permitting panel-specificautocorrelation and/or heteroskedasticity across panels, and type-wise time-series estimation is donewith AR(1) using variance Huber/White/sandwich variance estimator. A summary of variables andthe estimated results are given in Table8 and Table9, respectively.
[Table8 & Table9]
Based on the consumer demand theory, the income/expenditure elasticities are expected to bepositive for normal goods, while own price elasticities are expected to be negative. The results inTable9 from the double-log estimations show significant positive expenditure elasticities for panel
estimation as well as all for most of time-series estimations. A notable exception is shōchu, which
has significant negative coefficients in all three estimations, suggesting shōchu being an inferior
good. In terms of magnitudes, we see that shōchu, beer and whisky are elastic in terms ofhousehold’s total consumption expenditure. The significance of expenditure elasticities for saké andwine is not robust and seems to be affected by the presence of t variable. Time variable t is foundsignificant in all estimations, negative for panel, saké, beer and whisky, and positive for shōchu andwine. As for own-price elasticities, we find significant negative, inelastic coefficients for all but
shōchu which has significant positive highly elastic estimates. This suggests that while other alcohols
are normal goods, shōchu is possibly a Giffen good, or it could be that shōchu quality has improved,
accompanied not only by its increase in price but also in demand. Since we do not have information
on quality, it is not possible to make a conclusive interpretation. Another possible reason for finding
such result is that shōchu is still a relatively inexpensive alcohol vis-à-vis the others, even for its
price increase, as we have seen. As for household characteristics, only agehh is found to be22

significant with negative coefficients in estimations without t variable.

The Almost Ideal Demand System (AIDS), Quadratic Almost Ideal Demand System (QUAIDS),
and Dynamic Almost Ideal Demand System (DAIDS) Estimations
Although the results from the double-log model seem quite probable, the model is criticised as acrude one which is inconsistent with utility theory except for special cases (Deaton, 1997: ). Thus,
we estimate a conditional demand function and elasticities of demand which is consistent with utility
theory, applying Deaton and Muellbauer (1980)’s (1) Almost Ideal Demand System (AIDS) and its
three variants: (2) quadratic-AIDS (QUAIDS); (3) AIDS/QUAIDS incorporating socio-demographic
factors; (4) dynamic-AIDS (DAIDS). We give short descriptions on each model then proceed toestimation results interpretation.
In AIDS models, demand systems are considered in terms of expenditure shares of different
commodities, here, alcoholic beverage expenditures share of different alcohol types. 25 A household’s
expenditure share for good i is defined as wi ≡piqiX-1, where pi is the price paid for alcohol i, qi is thequantity of alcohol i purchased or consumed, and X is the total expenditure on all alcoholic
beverages in the demand system. With this definition of X, we have ∑𝐾𝐾
𝑖𝑖=1 𝑤𝑤𝑖𝑖 = 1, where K is thenumber of alcoholic beverages in the system. With the indirect utility function where utility isexpressed in terms of price p and total expenditure X, expenditure share equations can be expressed
as:
(3)

𝑋𝑋

𝑤𝑤𝑖𝑖 = 𝛼𝛼𝑖𝑖 + ∑𝐾𝐾
𝑗𝑗=1 𝛾𝛾𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑗𝑗 + 𝛽𝛽𝑖𝑖 ln{𝑃𝑃(𝐩𝐩)} ,where p is the vector of all prices, and P(p) is a price index defined as:
(4)

𝐾𝐾
𝐾𝐾
𝑙𝑙𝑙𝑙𝑙𝑙(𝐩𝐩) = 𝛼𝛼0 + ∑𝐾𝐾
𝑖𝑖=1 𝛼𝛼𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑖𝑖 + 1/2 ∑𝑖𝑖=1 ∑𝑗𝑗=1 𝛾𝛾𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑗𝑗

25

Our estimation results is limited in the sense that synthetic saké, spirits, liquor, fizzy and other alcohols had to be
excluded from the analysis, given unavailability of household expenditure data on these items. Given the fact thatliquor and fizzy consumption are increasing especially in recent years, perhaps in place of beer, our estimation
results are limited in this respect.

23

For theoretical restriction of expenditure function being linearly homogeneous of degree zero inprices and total expenditure, we must have the following condition: (1) adding up: ∑𝐾𝐾𝑖𝑖 𝛼𝛼𝑖𝑖 =𝐾𝐾
𝐾𝐾
1, ∑𝐾𝐾𝑖𝑖 𝛾𝛾𝑖𝑖𝑖𝑖 = 0, ∑𝑖𝑖 𝛽𝛽𝑖𝑖 =0; (2) homogeneity: ∑𝑗𝑗 𝛾𝛾𝑗𝑗𝑗𝑗 = 0 , and to satisfy (3) Slutsky symmetry:

𝛾𝛾𝑖𝑖𝑖𝑖 = 𝛾𝛾𝑗𝑗𝑗𝑗 for any i ≠ j. As stated by Deaton and Muellbauer (1980), α0 is generally difficult toestimate, and thus is assigned a value a priori as the minimum level of expenditure for subsistence

when all prices were unity. Accordingly, α0 is set as 4.9 throughout the analyses. 26 Based on theestimates, expenditure, as a proxy for income, and price elasticities are calculated. The expenditureelasticity is given by : ei=1+ βi wi-1 , and own/cross price elasticity is given by:

ηij = – δij + { γij –-127
βi(αj +∑𝐾𝐾
These
𝑖𝑖=1 𝛾𝛾𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑖𝑖 )} wi , where δij is Kronecker delta, δij =1if i=j and δij=0 otherwise.

elasticities can be derived straightforwardly by differentiating log of purchased quantity of item i bylog of expenditure (dlnqi/dlnX), and by differentiating log of quantity of item i by log of price of item
i (dlnqi/dlnpi), respectively, applying the chain rules in both cases. Elasticity forms have beenpresented by numerous authors, including Ray (1980) and Green and Alston (1990).
QUAIDS model is devised by Banks et al. (1997) in order to allow the Deaton and Muellbauer(1980)’s AIDS model to be consistent with more realistic Engel curve. An additional component
permitting for a quadratic log of expenditure enables the demand function to differentiate responses
to goods according to different income levels, so that goods can be luxuries or necessities dependingon the income level. The functional form is:
(5)

𝑋𝑋

𝜆𝜆

𝑋𝑋

𝑖𝑖
2
𝑤𝑤𝑖𝑖 = 𝛼𝛼𝑖𝑖 + ∑𝐾𝐾
𝑗𝑗=1 𝛾𝛾𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑗𝑗 + 𝛽𝛽𝑖𝑖 ln �𝑃𝑃(𝒑𝒑)� + 𝑏𝑏(𝐩𝐩) [ln �𝑃𝑃(𝒑𝒑)�] ,where the additional last term to the original AIDS equation (3) above represents a quadratic of log
of expenditure divided by the price index, with b(p), the Cobb-Douglas price aggregator, 𝑏𝑏(𝐩𝐩) =26

Noting that alcoholic may not be necessary goods and that there can be households which do not consume
alcohol at all, we have data only in aggregate form, so do not have any data of zero alcoholic consumption. Also
AIDS does not allow for corner solution that all commodities are to be consumed in some positive amount (Deaton
1997: 304).
27
The presented price elasticities are Marshallian or uncompensated elasticities, where Hicksian or compensatedelasticities that solely represent price/substitution effects can be provided directly from Slutsky equation, ηijC = ηij +Xi_mean wi

24

𝛽𝛽𝛽𝛽
∏𝑁𝑁
and the extra term λi which requires that Σki=1λi = 0 (see Banks, et al. 1997 for details).
𝑖𝑖−1 𝑝𝑝𝑖𝑖

Checking for the likely model fit, nonparametric kernel regressions with Gaussian specification, as in
the case of Banks et al. (1997), are conducted (see Appendix). The results indicate that shares of item
expenditures vis-à-vis log of consumption expenditures have a quasi-linear form for saké
(downward) and beer (upward), a concave form for whisky, and a cubic form for shōchu and wine.
These observations suggest that QUAIDS may not be ideal for the last two items, but may performbetter than AIDS model, which is encompassed in the QUAIDS, as a special case when λi = 0 for alli.
An AIDS model with socio-demographic factors incorporates demographic characteristics using thescaling technique introduced by Ray (1983). Application of a scale allows us to incorporatehousehold characteristics (z) into expenditure analysis across varying households. The scaling
function m0 is composed of two multiplicative factors, a basic component and a price andutility-varying component: m0(p, z, u) = 𝑚
� 0(z) · φ(p, z, u), where the first component captures theincrease in a household’s expenditures as a function of a vector of household characteristics z, andthe second component φ represents the dependence of the general scale on the structure of relative
price and utility, capturing changes in consumption patterns depending on z. The estimable equationof the expenditure share takes the form:(6)

𝑋𝑋

𝑤𝑤𝑖𝑖 = 𝛼𝛼𝑖𝑖 + ∑𝐾𝐾� ,𝑗𝑗=1 𝛾𝛾𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑗𝑗 + (𝛽𝛽𝑖𝑖 + 𝜗𝜗′𝑖𝑖 𝐳𝐳) ln �𝑚𝑚�����(𝐳𝐳)𝑃𝑃(𝒑𝒑)0

where ϑi allows for price and utility variation in scale, whose adding up condition requires that
Σki=1ϑri = 0 for r = 1…s. The basic scale for household characteristics vector z is set as 𝑚
� 0(z) = 1 +σ’z, where σ is a vector of estimable parameters representing a ‘basic’ equivalent scale (Ray, 1983).

For QUAIDS with demographic characteristics, the expenditure share equation becomes as below,
with additional terms (Poi, forthcoming):
(7)

𝑋𝑋

𝜆𝜆

𝑚𝑚

𝑖𝑖
′
𝑤𝑤𝑖𝑖 = 𝛼𝛼𝑖𝑖 + ∑𝐾𝐾� + 𝑏𝑏(𝐩𝐩)𝑐𝑐(𝐩𝐩,𝒛𝒛)[ln �𝑚𝑚�]2 .
𝑗𝑗=1 𝛾𝛾𝑖𝑖𝑖𝑖 𝑙𝑙𝑛𝑛𝑝𝑝𝑗𝑗 + (𝛽𝛽𝑖𝑖 + 𝜗𝜗 𝑖𝑖 𝐳𝐳) ln �𝑚𝑚�����(𝐳𝐳)𝑃𝑃(𝐩𝐩)�����(𝐳𝐳)𝑎𝑎(𝐩𝐩)00The expenditure and own/cross price elasticities for this functional form for QUAIDS version is:
25

(8)
(9)

2𝜆𝜆

𝑚𝑚

𝑖𝑖
ei=1+[ βi + 𝜗𝜗′𝑖𝑖 𝐳𝐳 + 𝑏𝑏(𝐩𝐩)𝑐𝑐(𝐩𝐩,𝒛𝒛)
ln �𝑚𝑚�] wi-1�����(𝐳𝐳)𝑎𝑎(𝐩𝐩)
0

2𝜆𝜆

𝑚𝑚

(𝛽𝛽 +𝜗𝜗′ 𝐳𝐳)𝜆𝜆

𝑖𝑖
𝑖𝑖
𝑖𝑖
𝑖𝑖
ηij = – δij,+ [γij – [βi + 𝜗𝜗′𝑖𝑖 𝐳𝐳 + 𝑏𝑏(𝐩𝐩)𝑐𝑐(𝐩𝐩,𝒛𝒛)
ln �𝑚𝑚�](αj +∑𝐾𝐾
𝑖𝑖=1 𝛾𝛾𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑖𝑖 ) – � 𝑏𝑏� (𝐩𝐩)𝑐𝑐(𝐩𝐩,𝐳𝐳) ������(𝐳𝐳)𝑎𝑎(𝐩𝐩)𝑚𝑚[ln �𝑚𝑚
�]2 ] wi-1
�����(𝐳𝐳)𝑎𝑎(𝐩𝐩)00

As in the double-log estimations, household characteristics the number of family member (hhmem),age of household head (agehh), and number of working members (wkmem), as shown in Table 8.
Finally, we consider a dynamic AIDS (DAIDS) model, presented by Ray (1984), which
incorporates past expenditure terms after Phlips’ (1972) and Pollak’s (1970) linear habit formation
models. The estimable expenditure share equation and the price index become:
(10)
(11)

𝑋𝑋

𝑡𝑡
𝑤𝑤𝑖𝑖𝑖𝑖 = 𝛼𝛼𝑖𝑖 + ∑𝐾𝐾
𝑗𝑗=1(𝛾𝛾𝑖𝑖𝑖𝑖 + 𝜃𝜃𝑖𝑖𝑖𝑖 𝑋𝑋𝑡𝑡−1 )𝑙𝑙𝑙𝑙𝑝𝑝𝑗𝑗𝑗𝑗 + (𝛽𝛽𝑖𝑖 + 𝜂𝜂𝑖𝑖 𝑋𝑋𝑡𝑡−1 )ln{𝑃𝑃 (𝐩𝐩)} ,
𝑡𝑡

𝐾𝐾
𝐾𝐾
𝐾𝐾
𝑙𝑙𝑙𝑙𝑃𝑃𝑡𝑡 (𝐩𝐩) = 𝜗𝜗0 + ∑𝐾𝐾
𝑖𝑖=1 𝛿𝛿𝑖𝑖 𝑋𝑋𝑖𝑖,𝑡𝑡−1 + ∑𝑖𝑖=1 𝛼𝛼𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑖𝑖𝑖𝑖 + 1/2 ∑𝑖𝑖=1 ∑𝑗𝑗=1(𝛾𝛾𝑖𝑖𝑖𝑖 + 𝜃𝜃𝑖𝑖𝑖𝑖 𝑋𝑋𝑡𝑡−1 )𝑙𝑙𝑙𝑙𝑝𝑝𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑝𝑝𝑗𝑗𝑗𝑗 ,𝐾𝐾
𝐾𝐾
where adding-up restrictions require that for all j: ∑𝐾𝐾𝑖𝑖 𝛼𝛼𝑖𝑖 = 1, ∑𝑖𝑖 𝛾𝛾𝑖𝑖𝑖𝑖 = ∑𝑖𝑖 𝜃𝜃𝑖𝑖𝑖𝑖 = 0, and
𝐾𝐾
𝐾𝐾
𝐾𝐾
∑𝐾𝐾
𝑖𝑖 𝛽𝛽𝑖𝑖 =∑𝑖𝑖 𝜂𝜂𝑖𝑖 = 0. The homogeneity restrictions require that for all i: ∑𝑖𝑖 𝛾𝛾𝑖𝑖𝑖𝑖 = ∑𝑖𝑖 𝜃𝜃𝑖𝑖𝑖𝑖 = 0. The

symmetry restrictions require that for all i and all j: 𝛾𝛾𝑖𝑖𝑖𝑖 = 𝛾𝛾𝑗𝑗𝑗𝑗 , 𝜃𝜃𝑖𝑖𝑖𝑖 = 𝜃𝜃𝑗𝑗𝑗𝑗 . Here, θij and ηi capture thedegree to which past total group expenditure exerts on the current expenditure. While θij is defined insubsistence utility terms, ηi is defined additional utility terms, what is called ‘bliss’ by Deaton andMuellebauer (1980). On the other hand, δi captures the effect of previous purchase on the individual
items, what is called ‘memory coefficient’ by Pollack (1970). 28 Allowing for autocorrelated
disturbances with autocorrelation coefficients ρi, where the estimation equation’s disturbances are
assumed to take a form, uit =ρit-1 + εt, with εt ~ IID (0, σ2), the expenditure share equation becomes:
(12)

𝑋𝑋

𝑡𝑡
𝑤𝑤𝑖𝑖𝑖𝑖 = 𝜌𝜌𝑖𝑖 𝑤𝑤𝑖𝑖𝑖𝑖−1 + 𝛼𝛼𝑖𝑖 (1 − 𝜌𝜌𝑖𝑖 ) + ∑𝐾𝐾
𝑗𝑗=1(𝛾𝛾𝑖𝑖𝑖𝑖 + 𝜃𝜃𝑖𝑖𝑖𝑖 𝑋𝑋𝑡𝑡−1 )𝑙𝑙𝑙𝑙𝑝𝑝𝑗𝑗𝑗𝑗 + (𝛽𝛽𝑖𝑖 + 𝜂𝜂𝑖𝑖 𝑋𝑋𝑡𝑡−1 )ln{𝑃𝑃 (𝐩𝐩)}

𝑋𝑋

𝑡𝑡−1
−𝜌𝜌𝑖𝑖 ∑𝐾𝐾
𝑗𝑗=1(𝛾𝛾𝑖𝑖𝑖𝑖 + 𝜃𝜃𝑖𝑖𝑖𝑖 𝑋𝑋𝑡𝑡−2 )𝑙𝑙𝑙𝑙𝑝𝑝𝑗𝑗𝑗𝑗−1 + 𝜌𝜌𝑖𝑖 (𝛽𝛽𝑖𝑖 + 𝜂𝜂𝑖𝑖 𝑋𝑋𝑡𝑡−2 )ln{𝑃𝑃 (𝐩𝐩)}.

𝑡𝑡

𝑡𝑡−1

While Ray (1984) puts restriction on ρi to be identical across all items in his estimations, he
Pollack assumes that δi is same for all i, in order to achieve stability, and that δi =[ 0,1 ). However, if such
restrictions are applied, some parameters turn inestimable within the equation systems in our case.

28

26

recognises also that this is not a realistic assumption. We estimate two versions of the demandsystems, with a single ρ and ρi. The corresponding expenditure and own/cross price elasticities ofdemand are:
(13)
(14)

ei = 1+( βi +ηiXt-1) wi-1
-1
ηij = – δij + {( γij + θijXt-1) –( βi+ηiXt-1) (αj +∑𝐾𝐾
𝑖𝑖=1 𝛾𝛾𝑖𝑖𝑖𝑖 + 𝜃𝜃𝑖𝑖𝑖𝑖 𝑋𝑋𝑡𝑡−1 ) 𝑙𝑙𝑙𝑙𝑝𝑝𝑖𝑖 )} wi ,where, as before, Kronecker delta δij =1if i=j and δij=0 otherwise.

Estimation of AIDS function fits a system of nonlinear equations by iterative feasible generalized
nonlinear least-squares (IFGNLS). Table10 presents estimation results and corresponding
expenditure and own price elasticities from six models: (1) AIDS; (2) AIDS-hh; (3) QUAISD-hh; (4)DAIDS-a with single autocorrelation coefficient (ρ); (5) DAIDS-b with item-wise autocorrelation
coefficients (ρi). 29 We see estimated coefficients are fairly different among the models. For instance,
we have negative βi implying necessities, with at least 5% significance level, for saké in AIDS and
AIDS-hh, while we have it for shōchu in AIDS-hh, QUAIDS-hh, DAIDS-a and DAIDS-b.
Significant positive βi implying luxuries, are observed for beer, whisky and wine in AIDS, beer andwine in AIDS-hh, and beer in QUAIDS. The finding of beer being luxury seems fit more to ahistorical view of beer being imported expensive goods, which has given the reason for the high tax
rate, but may also be applicable in current period – beer is regarded as luxurious alcohol vis-à-vis its
cheaper alternatives of recently invented non-malt or law-malt beer (fizzy and liquor), and price ofbeer in terms of 1 degree of ethanol is the most expensive as we have seen (Table 2). We present
only γii here due to limited space, yet γij indicate the impact of change in the price of good j on the
expenditure share of i, with (X/P(p)) held constant. With γii here, the estimated coefficients suggestthat own compensated price elasticities are likely to be positive for most alcohols in AIDS andQUAIDS, and for saké and beer in DAIDS.
29

We present the results with hhmem, but also estimated with other demographic variables. With agehh, theestimated coefficients for σ was negative significant in AIDS yet did not have estimated SE for QUIADS. With
wkmem, both AIDS and QUAIDS had insignificant positive σ. Inclusion of two or three demographic variables
seem to make estimation improper that those SE are not reported for most cases.

27

Regarding the extra parameter for QUAIDS-hh estimations, we have significant positive λi for beer,
significant negative λi for whisky and significant positive λi for wine. These results are somewhat
matching with the expectation from the nonparametric kernel regressions discussed above. The
parameters of AIDS-hh and QUIADS-hh, ϑi and σ are both found significant at the 1% level,
however, the signs are opposite for saké, beer and wine, depending on the estimation model. Yet,given the fact that ϑi indicates the impact of relative price of i on the scale effect of σ, opposite signsof estimated ϑi and σ actually produce impacts of the demographic variable in the same direction. For
instance, positive ϑ for saké indicates that the impact of relative price of saké exert positive impact
on the household member scale effect σ, which is negative in AIDS-hh. On the other hand, we havenegative ϑ for saké and positive scale effect σ in QUAIDS-hh, which imply that the combined impact
is also negative. If we look only at the household member scale effect σ though, the results areinconclusive. It seems that negative σ of AISD-hh is more reasonable that, an additional household
member who is likely a child, would induce less alcohol consumption by 20%. 30
Turning to DAIDS, the estimated coefficients all show 0.00 for δi and θii, as those coefficients havesmall actual numbers with five to six zeros after the decimal point. Some of these δi and θii are foundto be significant, indicating that there are minute previous individual-item purchase effects (δi) on
saké, shōchu and beer in DAIDS-a, and on beer in DAIDS-b, and minute previous total expenditureeffects (θii) in subsistence utility terms on shōchu in DAIDS-b. These findings can be reasonable,
given consumption patterns of these alcohols which have been more widely taken for a longer periodof time compared to whisky or wine. Looking at ηi, the estimation results are rather strange. For
DAIDS-a, we have saké and wine coefficients both being significant, with same coefficients of large
magnitudes (0.94) yet with opposite signs. For DAIDS-b, we have all items being significant at the
0.1% level with all coefficients having large magnitudes. As a matter of fact, using these estimated ηi,30

To remind, the data are for households of at least two persons that are likely to consist of two adults. In ourestimations, an AIDS model seems to be more appropriate for estimation with demographic characteristics than its
QUAIDS counterpart.

28

both expenditure and price elasticity calculations by (13) and (14) produce extremely large figures,indicating inappropriate estimation results for ηi in our case. Given these, we present DAIDS
elasticities, calculated with the AIDS elasticity functional form, setting ηi = θii =0. As for the
autocorrelation coefficient ρi, it is not found significant in DAIDS-a, and found significant andpositive for shōchu and wine in DAIDS-b, although the impacts are minute having five zeros after
the decimal point.
The expenditure elasticities calculated at the means, also shown in Table10, exhibit differencesamong the models, particularly between static AIDS, and the rest. Saké is found to have significant
negative expenditure elasticity only in AIDS, while shōchu is found to have negative expenditureelasticities in other four estimations, although the estimates are insignificant in DAIDS models. The
estimated negative expenditure elasticity for shōchu suggesting it being an inferior good matches theresults from the double-log estimations and the tax policy estimations in terms of the final
consumption expenditure per capita. The only item which is found to be robustly elastic is beer – themost drunken alcohol in Japan. This coincides with the tax policy regression results where beer
consumption was found to be particularly affected by the level of final consumption per capita. It issuggested that an increase in expenditure is likely to increase the consumption of beer, whisky andwine, while the impact on saké and shōchu is unclear.
As for own price elasticities, calculated at the means, we have ‘positive’ estimates for saké, shōchu
and wine in AIDS and AIDS-hh estimations, although all the estimates are statistically insignificant
in AIDS-hh. Positive and elastic own-price elasticity for shōchu matches the results for earlier
double-log estimations. Positive elasticity for saké was also found in Takahashi et al. (2009), cited
above, although inelastic. Beer and whisky have negative price elasticities, although none issignificant at the 5% level. For QUAIDS-hh, we have significant positive elasticity for saké, which iselastic, and significant negative elasticity for beer, which is inelastic. The other items are
insignificant, implying that elasticities are not statistically different from zero. Looking at the29cross-price elasticities, almost all ηij are significant in the AIDS model suggesting that most alcohol
items are either substitute or complement to each other, results which may be unlikely. Concentratingon the statistically significant results that are robust across AIDS/QUAIDs models, we see that
increase in price of shōchu and beer decrease the consumption of saké, while increase in the price ofbeer is found to increase the demand for shōchu by 1.5~ 2% and to decrease the demand for saké by
1~1.5%. Whisky and wine are estimated to be complements to each other with the statisticalsignificance at 1%.
Turning to price-elasticity estimates in DAIDS, all coefficients have negative signs except forshōchu in DAIDS-b The results are more coherent with other literature findings that alcohols arenormal goods, although estimates for saké and shōchu exhibit no statistical significance in both
estimations. We have significant negative elastic estimate for whisky and wine in both DAIDS
models, and significant negative inelastic estimate for beer in DAIDS-b. Although we must be
cautious in using the results from DAIDS as the elasticity formula had to be changed to that of AIDS,
the results suggest that it would be particularly inefficient to impose excise tax on whisky or wine,
yet efficient to impose tax on saké and shōchu. The estimated cross-price elasticities suggest thatsaké and beer are complements to each other in both DAIDS, results that are also seen in AIDs
estimations. Shōchu is estimated to be a substitute for saké and wine a substitute for whisky in
DAIDS-a, both at the 5% significance level.
Having few robust estimation results across models, we should note possible instability of AIDS
model application in the case of alcoholic beverages in Japan. Particularly, the complexity ofextended AIDs models considered here, although they are supposed to be more realistic models,seems to impose certain strain on estimations, and that results may significantly differ depending on
the models employed. 31 Our results seem to signify the importance of distinguishing the31

For instance, Andrikopoulos and Loizides (2010) cited earlier also had different estimations results for three
DAIDS models they employed. Also, the estimation result table present in the paper shows missing SE (t-values)
for some parameters in their DAIDS estimations, which may indicate that the model applied was not appropriate.

30‘subsistence’ and the ‘bliss’ within the same category of goods in an AIDS analysis. 32[Table 10]
Conclusions
Utilising the data from 1948 to 2011, we saw that liquor tax rates used to be discriminative to
expensive alcohols through ad valorem tax and class systems, although such system was abolishedby early 1990. The liquor tax policy revisions have had different implications on each alcohol, whichwere indeed observed in the tax policy regressions investigating the impacts of tax policies on
alcoholic beverage production and consumption through panel and time-series analyses.
In the tax policy analyses, sectoral growth is found to have significant positive impacts on
production in general, except for domestic production. The impacts of final consumption per capita
are found to be positive with statistical significance for most production and consumption, with anotable exception of shōchu in time-series estimations, suggesting that shōchu is an inferior good.
The results from demand system analyses provide supporting evidences for this finding that increasein expenditure level raise the level of consumption for most alcohols except for shōchu. Tax rate isfound to have mixed impacts depending on the type of alcohol. It is found to have significant
negative impacts particularly for saké and beer, while it is estimated to be significant and positive forshōchu. These findings suggest that shōchu is possibly a Giffen good, whose income effects are
greater than its substitution effects. Nonetheless, there can be other factors at function that are notevident from the available data, such as quality improvement and price increase taking place during
the period of recession. The analyses suggest the possibility of preferential tax rates being beneficial
for boosting sectoral performances for certain alcohols.
In order to estimate the demand elasticities of alcohols, the double-log, AIDS and its variant models
Thompson (2004) raises the issue of unrealistic assumption of AIDS models in particular that the expenditure levelis independent of item price change, when we are looking at group expenditure. However, applying his suggested
remedies did not principally change the estimated results.
32
We initially attempted to estimate the AIDS models with such differential quality categories for saké and whisky
for which data are available, but the data were not for long enough period to allow the estimations.

31

are applied for five alcohols. In terms of total alcohol expenditure, shōchu, beer and whisky arefound to be elastic in double-log and static AIDS estimations, where shōchu has negative elasticities
across models except for the original AIDS. The result reinforces the earlier findings of shōchu being
an inferior good. Regarding price elasticities in the double-log estimations, all items but shōchu arefound to have significant negative own-price elasticities, with least elastic being wine. Shōchu isfound to have significant positive and elastic own-price elasticity in the double-log model, indicatingthat the item is the most ideal subject for taxation. The AIDS/QUAIDS estimations on own-priceelasticities essentially suggest that any alcohol item can be subject to taxation, without distorting thewelfare level, since they are either positive with statistical significance or negative without statisticalsignificant. On the other hand, DAIDS estimations suggest that imposing tax on whisky and wine isparticularly inefficient. At least from the estimated result we have at hands, the safest taxable item
seems to be shōchu. Taking together with alcohol trend and tax policy analyses conducted, there
might be differential quality and other issues at work in the background for such elasticity findings,
as well as possible inappropriateness of AIDS model application to the alcoholic beverages data weused. The results signify the importance of distinguishing the qualities within the same category of
goods in the demand system analyses.
References
Andrikopoulos, Andreas. A. and John Loizides. (2000). “The demand for home-produced andimported alcoholic beverages in Cyprus: The AIDS approach,” Applied Economics, 32(9):1111-1119.
Banks, James, and, Richard Blundell, and Arthur Lewbel. 1997. “Quadratic Engel Curves andConsumer Demand,” Review of Economics and Statistics, 79(4): 527-539.
Chaloupka, Frank J., Henry Saffer, and Michael Grossman. (1993) “Alcohol-Control Policies andMotor-Vehicle Fatalities,” Journal of Legal Studies, 22(1): 161-186.
Chetty, Ray, Adam Looney, and Kory Kroft. (2009) “Salience and taxation: Theory and evidence,”
American Economic Review, 99(4): 1145-1177.
32

Clements, Kenneth W., Wana Yang and Simon W. Zheng. (1997) “Is Utility Additive? The Case of
Alcohol,” Applied Economics, 29(9): 1163-1167
Cook, Philip J. and Michael J. Moore. (2002) “The Economics of Alcohol Abuse And
Alcohol-Control Policies,” Health Affairs, 21(2): 120-133.
Cook, Philip J., and George Tauchen. (1982) “The Effect of Liquor Taxes on Heavy Drinking,” Bell
Journal of Economics, 13(2): 379-390.
Corlett, W. J. and D. C. Hargue. (1953/1954) “Complementarity and the Excess Burden of Taxation,”
Review of Economic Studies, 21(1): 21-30.
Deaton, Angus. (1997) The Analysis of Household Surveys: A Microeconometric Approach to
Development Policy. Washington, D.C.: The International Bank for Reconstruction andDevelopment.
Deaton, Angus and John Muellbauer. (1980) “An Almost Ideal Demand System,” American
Economic Review, 70(3):. 312-326.
Development Bank of Japan (Minami-Kyushu Branch). 2003. “ Shōchu boom no Kensho – Boom deOwarasenai Tameni ‘Minami-Kyushu Honkaku Shochu Kigyou Enquette Chōsa’ (Verification of
Shōchu Boom – from A Boom to Sustainable Demand ‘A Survey of South Kyushu Authentic
Shōchu Companies’),” Minami Kyushu regional development report, Vol.5. (in Japanese; title
translated by the author) Available at:
http://www.dbj.jp/reportshift/area/s_kyusyu_s/pdf_all/20030603_ank.pdf
Drukker, David M. (2003) “Testing for serial correlation in linear panel-data models,” Stata Journal,
3(2): 168-177.
Eakins, John M. and Liam A. Gallagher. (2003) “Dynamic almost ideal demand systems: An
empirical analysis of alcohol expenditure in Ireland,” Applied Economics, 35(9): 1025-1036.
Elder, Randy W., Briana Lawrence, Aneeqah Ferguson, Timothy S. Naimi, Robert D. Brewer, Sajal
K. Chattopadhyay, Traci L. Toomey, Jonathan E. Fielding, and the Task Force on Community
Preventive Services. (2010) “The Effectiveness of Tax Policy Interventions for Reducing Excessive
Alcohol Consumption and Related Harms,” American Journal of Preventive Medicine, 38(2): 217–
229.
Green, Richard and Julian M. Alston. (1990) “Elasticities in AIDS Models,” American Journal of
Agricultural Economics, 72(2): 442-445.

33

Japan Cabinet Office. (2000) “Wagakokuzeisei no Genjo to Kadai – 21Seiki nimuketa Kokumin no
Sanka to Sentaku (The Current Status and Challenges for Our National Tax System – Public
Participation and Choice Towards the 21st Century),” The Tax Commission Report (14th July). (inJapanese, title translated by the author)Kaji, Yoshitaka. (2013) “Shuzeiseido no Gaiyou oyobi Ronten nitsuite – Alcohol Kanren Mondai
oyobi Keizairiron karano Shiten (A Summary and Issues Regarding the Liquor Tax: From
Alcohol-Related Problems and Economic Perspectives)”, Reference (National Diet Library), 750(July). (in Japanese; title translated by the author) Available at:
http://dl.ndl.go.jp/view/download/digidepo_8238144_po_075003.pdf?contentNo=1
Kenkel, Donald S. (1996). “New Estimates of the Optimal Tax on Alcohol,” Economic Inquiry, 34(2): 296–319.
Manning, Willard G, Linda Blumberg and Lawrence H. Moulton. (1995) “The demand for alcohol:
The differential response to price,” Journal of Health Economics, 14(2): 123-148.
Mast, Brent D., Bruce L. Benson and David W. Rasmussen (1999). “Beer taxation andalcohol-related traffic fatalities,” Southern Economic Journal, 66 (2): 214-249.
Mori, Hiroshi, Hayden Stewart and Yoshiharu Saegusa. 2012. “An Augmented A/P/C Cohort
Model : Applications,” Economic Bulletin of Senshu University, Vol. 47, No. 2, 37-65.
Nakamura, K., A. Tanaka and T. Takano. (1993) “The social cost of alcohol abuse in Japan,” Journalof Studies on Alcohol, 54(5): 618-625.
National Tax Agency. (2003, 2006, 2013) Saké no Shiori (The Liquor Guide, H15, H18, H25). (inJapanese, title translated by the author)
Poi, Brian P. (forthcoming) “Easy Demand System Estimation with quaids,” Stata Journal.
Phlips, Louis. (1972) “A Dynamic Version of the Linear Expenditure Model,” Review of Economics
and Statistics, 54(4): 450-458.
Pollack, Robert A. (1970) “Habit Formation and Dynamic Demand Functions,” Journal of Political
Economy, 78(4): 745-763.
Ramsey, F. P. (1927) “A Contribution to the Theory of Taxation,” Economic Journal, 37(145):
47-61.
Ray, Ranjan. (1980) “Analysis of a Time Series of Household Expenditure Surveys for India,” Review
of Economics and Statistics, 62(4): 595-602.
34

Ray, Ranjan. (1983) “Measuring the Cost of Children: An alternative Approach,” Journal of Public
Economics, 22: 89-102.
Ray, Ranjan. (1984) “A Dynamic Generalisation of the Almost Ideal Demand System,” Economic
Letters, 14:235-239.
Takahashi, Yosuke, Won Park and Yoshinobu Ishizuka. (2009) “Economic grounds for excise and thealcohol tax in Japan,” Journal of Economics and Sociology, Kagoshima University, 73 (September):
49 -89. (in Japanese) Available at: http://ir.kagoshima-u.ac.jp/handle/10232/10079
Thompson, Wyatt. 2004. “Using Elasticities from an Almost Ideal Demand System? Watch Out forGroup Expenditure!,” American Journal of Agricultural Economics, 86(4): 1108–1116.
WANDS. (1996) “Nihonseifu no Taiou ni Ikari Arawa: Oubei no Jouryushu Seinsanshadaihyo ga
Rainichi, shuzeihou Kaitei wo Tshoyoku Semaru (Open Anger Against the Japanese Government:
Western Spirits Producers Visit Japan and Put Strong Pressures for a Liquor Tax Revision),”December, WANDS. (in Japanese, title translation by the author) Available at:
http://www.wine.or.jp/wands/1996/12/mnews1.html
Wooldridge, Jeffrey M. (2002) Econometric Analysis of Cross Section and Panel Data. Cambridge,
MA: MIT Press.

35

Table 1 Summary of the Liquor Tax Evolution (1962~2013)
Year

Major Change (in terms of nominal rate)

1962 (S37)

Major tax rate reduction for all& subsequent increase

1989 (H1)

Abolishment of special class for saké, class for wine, whisky
Abolishment of ad valorem tax
Major tax rate reduction for all except for shōchu
Major tax rate increase for shōchu
Other: introduction of consumer tax (3%, increased to 5% in
1997)1992 (H4)

Abolishment of class for saké

1994 (H6)

Increased tax for saké, synthetic saké, shōchu, beer, wine
Revised definition of fizzy drinks (third beer), other alcohols

2003(H15)

Increased tax for synthetic saké, wine, fizzy drinks, other alcohols

2006(H18)

Reduced tax for saké, synthetic saké, beer, whisky
Increased tax for shōchu, wine, other alcohol

Source: Saké no Shiori, H25 and other documents, National Tax Agency (2013)36

General Tax Trend

Table 2. Summary Statistics (for Tax Impact Estimation)
Variable

Obs

Mean

S.D.

Min

Max

Taxed quantity (in 1,000 kl)
Saké

64

1082.2

Obs

Mean

S.D.

Min

Max

220

1675

Consumption (in 1,000 kl)
459.7

127

1766

61

1099.4411.8

Synth. Saké

64

60.0

39.4

20

139

61

55.9

35.5

20

129

Shōchu

64

451.0

276.9

39

968

61

461.3

283.1

175

1005

Beer

64

3492.12124.7

79

7086

61

3541.2

2006.7

196

7057

Whisky

64

134.8

102.5

5

379

61

159.5

108.8

9

377

Wine

64

58.5

34.6

4

158

61

59.5

38.1

7

313

Spirits

64

33.0

64.9

0

297

61

30.5

49.1

1

233

Liquor

64

233.0

424.6

1

1819

61

232.7

424.3

1

1871

Fizzy

58

414.9

754.4

0

2600

61

374.5

706.7

0

2465

Other

64

98.6

269.0

0

1058

61
1089.0279.2
0Real Average Tax Rate per L (in JPY)
(1955-2011)a)1032

147.02

33.69

102.47243.35

57

288.6

199.1

122.5

837.8

Average tax rate (JPY per litre)
Saké

64

Synth. Saké

64

79.36

20.38

60.43

138.75

57

160.9

136.5

62.4

552.9

Shōchu64

109.89

70.11

44.40

238.42

57

180.1

101.5

68.0

435.5

Beer

64

166.10

54.37

94.98

238.82

57

295.9

124.5

183.8

643.6

Whisky64593.18347.2964.86

1291.0257

1024.4

412.9

381.1

1735.9

Wine

64

63.66

16.69

11.67

120.25

57

126.0

78.3

48.9

342.8

Spirits

61

213.15

82.01

84.91

360.74

57

425.8

284.4

99.4

1284.7

Liquor64

107.60

25.99

29.00

202.00

57

239.0

208.0

83.2

755.3

Fizzy

40

88.64

42.56

8.00

159.00

33

155.3

54.9

82.7

281.9

Other

36

85.25

21.37

41.00

148.33

Tax-Price Ratio (1963-2011)b)

36
95.0
25.3
63.9
166.7
Real ethanol price (JPY per 1 degree of alcohol)c)

Saké

49

0.21

0.07

0.14

0.36

49

66.3

7.8

57.2

80.6

Shōchu

49

0.22

0.09

0.10

0.35

49

27.7

2.3

23.4

33.0

Beer

49

0.44

0.04

0.38

0.53

49

112.6

13.4

93.9

149.8

60.9

12.6

38.8

75.1

105.0

11.8

79.7

123.5

Whisky

49

0.37

0.10

0.21

0.52

49

Wine

49

0.07

0.03

0.03

0.15

49

Fizzy
Fcepc

12
0.38
0.04
0.30
0.42
Real final consumption per capita (in million JPY)
57

1.58

0.70

0.36

2.63

Notes: a) Fizzy drinks and others data available from 1978 and 1975, respectively. Average tax rates for whisky, wine, sprits, liquor
during (1948-1962) extrapolated with the corresponding ratio data in 1963 as figures are available only in an aggregate form for thesetypes; b) Fizzy drinks data available since 2000 only. To calculate average prices of alcohols, three data sets are utilised: (1) 1963 to2007 from 20-3-a Annual Household Expenditures and Quantity Purchased by Commodity (Non-agricultural, forestry and fishery
Households with 2 or more; 1963-2007 All Japan); (2) 2008 to 2010 from 20-3-b Annual Household Expenditures and Quantity
Purchased by Commodity, (Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All
Japan); (3) 2011 from Annual Household Expenditures and Quantity Purchased by Commodity (Households with 2 or more) - All
Japan(1990-2012); c) Not used in the estimation. Because there are divergences in alcoholic contents of each type, the most genericalcoholic contents are assumed: saké 15º, shōchu 25º, beer 5º, whisky 40º, and wine 13º. Real prices are calculated by using a
combined the deflators for Final Consumption Expenditure.
Data Source: A) Alcohol Related Data: Long-Term Time Series Data (1948-2011) and Liquor Tax information from the National Tax
Agency (2013); B) Real Tax Values calculated using Deflator for Final Consumption Expenditure (1) FY1955~1979 (1990/H2constant: 64SNA, adjusted to match (2)); (2) FY1980～2009 (2000/H12-constant: 93SNA); (3) 2010～2011(2005/H17-constant:
93SNA, adjusted to match (2); C) Final Consumption Expenditure Per Capita used Final Consumption Expenditure, for (1) 1963-2007:
20-3-a Annual Household Expenditures and Quantity Purchased by Commodity (Non-agricultural, forestry and fishery Householdswith 2 or more; 1963-2007 All Japan); (2) 2008-2010: 20-3-b Annual Household Expenditures and Quantity Purchased by Commodity(Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All Japan); (3) 2011: H2~H22 YearlyAmount of Expenditures, Quantities and Average Prices per Household (1990-2012 all Japan), and Total Population of Japan (2013)
from the Statistical Bureau of Japan (2013).

37

Table 3. Panel Estimation Results: All Alcoholic Beverages: G0 All (Saké ~ Other Alcohols, 10 types)
Production/Supply
1955-2011

MA(3) growth rate
tax valueln average tax rate
(real)

S37tax
H1tax
H6tax
H15taxH18taxPolyphe. Boom
Shōchu boom
Constant

1966-2011

1955-2011

Production (Domestic Only)

1966-2011a)

1991-2011 b)

(1)

(2)

(3)

(4)

(5)

(6)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

0.786***[0.00]

0.843***[0.00]

0.772***[0.00]

0.849***[0.00]

0.772***[0.00]

0.796***[0.00]

0.387***[0.00]

0.444***[0.00]

0.399***[0.00]

0.410***[0.00]

0.361***[0.00]

0.473***

0.650***-0.266[0.38]-0.4310.820***

0.916***[0.00][0.00]-0.381***-0.488***-0.721***-0.852***-0.221**-0.605***-0.571***-0.209***[0.00][0.00][0.00][0.00][0.01][0.00][0.00][0.01]

0.923***

0.921***

0.223***

0.138

0.611***

0.545***

0.101[0.00][0.00][0.01][0.11][0.00][0.00][0.15]

ln Tax ratio a)ln final
consumption pc

Consumptiona)[0.00]

0.854***

0.512***

0.849***

0.666***

1.008***

0.731***

1.601**[0.00][0.00][0.00][0.00][0.00][0.00][0.01].

.

[0.16][0.00]-1.502***[0.01]

.

0.004

0.024

0.099*

0.054

0.056

0.046

[0.94][0.70][0.09][0.24][0.39][0.38].

.

.

-0.0160.140***-0.061-0.0220.087**

0.105

0.127

0.044

0.036

[0.49][0.81][0.04][0.11][0.18][0.24][0.46][0.74][0.00]-0.0320.044.

0.131*

0.234**

.

.

.

.

[0.75][0.67].

[0.09][0.03]

.

.

.

.

0.095

-0.115

0.011

0.112

-0.143**-0.0470.144-0.0520.009[0.91][0.24][0.04][0.54][0.14][0.40][0.92][0.25][0.15]-0.004-0.041

0.058

0.018

-0.048

0.014

0.012

-0.0350.036[0.95][0.46][0.16][0.68][0.40][0.70][0.81][0.46][0.44]

0.004

0.036

0.022

0.026

0.018

0.03

0.013

0.026

0.027

0.027

0.006

-0.004-0.005

0.013

0.02

[0.49][0.65][0.39][0.68][0.38][0.39][0.39][0.88][0.89][0.83][0.60][0.56][0.91][0.29][0.55]

0.004-0.068-0.013-0.0130.087-0.0140.033-0.091

0.025

-0.01

-0.0080.033-0.0460.051-0.036[0.95][0.39][0.69][0.65][0.13][0.65][0.60][0.25][0.62][0.67][0.74][0.65][0.50][0.44][0.31]

7.111***

7.442***

8.882***[0.00][0.00][0.00]

6.477***

6.882***

10.509***11.351***6.035***

5.759***

4.272***

5.490***

10.058***9.705***

5.964***

4.694***[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00]

200
200
95
95
N
525
525
257
257
257
257
540
516
257
257
257
Note: p-value in brackets (* p<0.05, ** p<0.01, *** p<0.001); Estimation (1) exhibits an evidence of multicollinearity; a) Tax ratio data available for 1963-2011 for saké, shōchu, beer, whisky and wine only, soother types are dropped from the analysis using this variable; b) domestic tax data available for 1989-2011 only (1991-2011 taking MA(3) growth rate tax value).
Data Source: A) Alcohol Related Data: Long-Term Time Series Data (1948-2011) and Liquor Tax information from the National Tax Agency (2013); B) Real Tax Values calculated using Deflator for Final
Consumption Expenditure (1)FY1955~1979(1990/H2-constant: 64SNA, adjusted to match (2))；(2)FY1980～2009(2000/H12-constant：93SNA)；(3) 2010～2011(2005/H17-constant：93SNA, adjusted tomatch (2)); C) Final Consumption Expenditure Per Capita and Price data for tax ratio used Final Consumption Expenditure data, for (1) 1963-2007: 20-3-a Annual Household Expenditures and Quantity
Purchased by Commodity (Non-agricultural, forestry and fishery Households with 2 or more; 1963-2007 All Japan); (2) 2008-2010: 20-3-b Annual Household Expenditures and Quantity Purchased by Commodity(Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All Japan); (3) 2011: H2~H22 Yearly Amount of Expenditures, Quantities and Average Prices per Household(1990-2012 all Japan) , and Total Population of Japan (2013) from the Statistical Bureau of Japan.

38

Table 4. Panel Estimation Results: G1 – Dinner Alcohols (Saké, Synthetic Saké, Shōchu, Wine)
Production/Supply
1955-2011

Consumption

1966-2011a)1955-2011

Production (Domestic Only)

1966-2011a)

1991-2011 b)

(1)

(2)

(3)

(4)

(5)

(6)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

MA(3) growth rate
tax value

0.946***

0.966***

0.881***

0.876***

0.744***

0.873***

0.463***

0.487***

0.410***

0.389***

0.410***

0.357

0.630*-0.819*-1.552***[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.01][0.00][0.21][0.09][0.10][0.00]

ln average tax rate
(real)

0.102

0.082

-0.464**-0.790***0.068-0.257-0.1981.292***[0.33][0.42][0.05][0.00][0.42][0.21][0.31][0.00]

0.469**

0.859***

0.348*

0.262

1.194***

1.185***[0.03][0.00][0.08][0.19]

ln Tax ratio a)ln final
consumption pc
S37tax
H1tax
H6tax
H15taxH18taxPolyphe. Boom
Shōchu boom
Constant

0.457***

0.09

0.027

[0.00][0.42]

0.446***

0.347*

0.771***

0.425**

0.438***

0.445***

0.917-2.375***[0.00][0.09][0.00][0.04][0.00][0.01][0.23][0.00]

0.162***

0.183***

0.260**

0.080**

0.130**-0.04[0.77][0.00].

.

[0.00].

[0.01][0.01][0.02][0.04][0.03][0.58].

.

.

0.191**

0.228**

0.195**

0.077

0.186**

0.016

0.053

0.176**

0.269***[0.04][0.03][0.02][0.16][0.03][0.77][0.41][0.01][0.01]

0.116

0.184*.

0.058

0.210**

.

.

.

.

[0.25][0.09].

[0.38][0.02].

.

.

.

-0.160*-0.11-0.136-0.092-0.0310.018-0.145-0.412***-0.237**[0.07][0.25][0.29][0.15][0.70][0.84][0.17][0.00][0.05]

0.048

0.029

0.049

0.036

0.015

-0.007

0.054

0.102

0.05

[0.35][0.60][0.33][0.75][0.90][0.37][0.12][0.58]

0.022

0.015

0.048

0.016

0.035

0.049

0.005

-0.002

0.003

0.001

0.02

0.034

0.03

0.062

0.032

[0.53][0.72][0.33][0.71][0.53][0.33][0.86][0.95][0.94][0.99][0.59][0.39][0.53][0.39][0.68]

0.101

0.071

-0.001-0.0080.091-0.006

0.069

0.035

-0.018-0.006

0.006

0.131

0.230**

0.167

0.02

[0.53][0.16][0.37][0.99][0.85][0.40][0.91][0.19][0.60][0.80][0.86][0.86][0.13][0.01][0.14][0.79]

4.071***

4.695***

8.061***

10.917***

6.227***

4.963***

4.541***

5.290***

7.733***

7.410***

5.478***

4.191***-0.5828.296***

10.285***[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.41][0.00][0.00]

N
228
228
147
147
147
147
228
228
147
147
147
80
80
57
57
Note: p-value in brackets (* p<0.05, ** p<0.01, *** p<0.001). Estimation (1) exhibits an evidence of multicollinearity; a) Tax ratio data available for 1963-2011 for saké, shōchu and wine only, so syntheticr saké isdropped from the analysis using this variable; b) domestic tax data available for 1989-2011 only (1991-2011 taking MA(3) growth rate tax value).
Data Source: A) Alcohol Related Data: Long-Term Time Series Data (1948-2011) and Liquor Tax information from the National Tax Agency (2013); B) Real Tax Values calculated using Deflator for Final
Consumption Expenditure (1)FY1955~1979(1990/H2-constant: 64SNA, adjusted to match (2))；(2)FY1980～2009(2000/H12-constant：93SNA)；(3) 2010～2011(2005/H17-constant：93SNA, adjusted tomatch (2)); C) Final Consumption Expenditure Per Capita and Price data for tax ratio used Final Consumption Expenditure data, for (1) 1963-2007: 20-3-a Annual Household Expenditures and Quantity
Purchased by Commodity (Non-agricultural, forestry and fishery Households with 2 or more; 1963-2007 All Japan); (2) 2008-2010: 20-3-b Annual Household Expenditures and Quantity Purchased by Commodity(Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All Japan); (3) 2011: H2~H22 Yearly Amount of Expenditures, Quantities and Average Prices per Household(1990-2012 all Japan) , and Total Population of Japan (2013) from the Statistical Bureau of Japan.

39

Table 5. Panel Estimation Results: G2 - Hard Liquor (Shōchu, Whisky, Spirits)
Production/Supply
1955-2011

Consumption

1966-2011a)1955-2011

Production (Domestic Only)
1966-2011a)

1991-2011b)

(1)

(2)

(3)

(4)

(5)

(6)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

MA(3) growth rate
tax value

1.276***

1.295***

0.791***

0.931***

0.717***

0.908***

0.579***

0.640***

0.408**

0.440***

0.419***

0.388

0.556*-0.221[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.02][0.00][0.00][0.20][0.07][0.57]

ln average tax rate
(real)-0.505***-0.563***-0.285-0.572***-0.167*-0.686***-0.428**-0.275**[0.00][0.00][0.20][0.00][0.07][0.00][0.01][0.04]

0.306

0.445

0.859***

0.436*[0.28][0.11][0.00][0.06]

ln Tax ratioa)
ln final
consumption pc
S37tax
H1tax
H6tax
H15taxH18taxPolyphe. Boom
Shōchu boom
Constant-0.06-0.235*-0.061

0.057[0.63][0.09]

0.911***

0.890***

1.124***

0.973***

1.060***

1.033***

0.244[0.00][0.00][0.00][0.00][0.00][0.00][0.80]-0.055-0.0130.538***

0.008

0.031

0.11

[0.54][0.78].

.

.

[0.52][0.88][0.00][0.90][0.70][0.33].

.

.

-0.286**-0.1970.136**-0.043

0.029

0.069

0.142*

0.102

0.098

[0.02][0.11][0.05][0.65][0.78][0.41][0.07][0.17][0.27]-0.389***-0.265*.

-0.152

-0.02

.

.

.

.

[0.01][0.07].

[0.19][0.87]

.

.

.

.

0.121

0.238*-0.043-0.034

0.108

0.131

0.098

0.176

-0.034[0.38][0.09][0.71][0.76][0.38][0.31][0.47][0.13][0.80]

0.002-0.049

0.063

0.037

-0.024-0.0160.026-0.0120.051[0.98][0.56][0.57][0.74][0.84][0.74][0.86][0.54]-0.011

-0.02

0.023

0.003

[0.35]
0.02

0.008

0.003

-0.019-0.005-0.013-0.002-0.001-0.0090.015[0.84][0.73][0.73][0.96][0.68][0.88][0.95][0.72][0.93][0.81][0.95][0.99][0.86][0.80]-0.035-0.123

0.021

0.011

0.075

0.022

0.043

-0.059-0.065

0.011

0.015

0.018

-0.0460.067[0.76][0.29][0.74][0.87][0.43][0.70][0.64][0.56][0.55][0.83][0.71][0.87][0.63][0.56]

7.716***

8.232***

7.494***

9.346***

5.340***

5.387***

4.890***

5.992***

10.532***8.477***

5.544***

4.360***

6.116***

5.673***[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00]

N
171
171
98
98
98
98
171
171
98
98
98
60
60
38
Note: p-value in brackets (* p<0.05, ** p<0.01, *** p<0.001); Estimation (1) and (15) exhibit an evidence of multicollinearity; a) Tax ratio data available for 1963-2011 for shōchu and whisky only, so spirits is
dropped from the analysis using this variable; b) domestic tax data available for 1989-2011 only (1991-2011 taking MA(3) growth rate tax value).
Data Source: A) Alcohol Related Data: Long-Term Time Series Data (1948-2011) and Liquor Tax information from the National Tax Agency (2013); B) Real Tax Values calculated using Deflator for Final
Consumption Expenditure (1)FY1955~1979(1990/H2-constant: 64SNA, adjusted to match (2))；(2)FY1980～2009(2000/H12-constant：93SNA)；(3) 2010～2011(2005/H17-constant：93SNA, adjusted tomatch (2)); C) Final Consumption Expenditure Per Capita and Price data for tax ratio used Final Consumption Expenditure data, for (1) 1963-2007: 20-3-a Annual Household Expenditures and Quantity
Purchased by Commodity (Non-agricultural, forestry and fishery Households with 2 or more; 1963-2007 All Japan); (2) 2008-2010: 20-3-b Annual Household Expenditures and Quantity Purchased by Commodity(Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All Japan); (3) 2011: H2~H22 Yearly Amount of Expenditures, Quantities and Average Prices per Household(1990-2012 all Japan) , and Total Population of Japan (2013) from the Statistical Bureau of Japan.

40

Table 6. Panel Estimation Results: G3 - Beer & Third Beer (Beer, Liquor, Fizzy Drinks)

MA(3) growthrate tax value

(1)
0.079

(2)
0.319**

Production/Supply
1955-2011(3)
0.286**[0.56][0.04][0.02](4)
0.352**[0.02]

(5)

(1)
0.121

Consumption
1955-2011(2)(3)
0.205**
0.071(4)-0.123

Production (Domestic Only)
1991-2011 a)
(1)
(2)
(3)
-0.544**-0.546**-0.587**[0.18][0.05][0.47][0.05]

ln average tax
rate (real)ln final
consumption pc[0.67][0.04][0.03]

0.006-0.241-0.499-0.307-0.168-0.36
0.207**
0.294***[0.99][0.24][0.18][0.11][0.49][0.41][0.04][0.00]
2.101***
1.856***
1.906***
1.745***
1.612***
1.566***
1.658***
3.533*[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.06]
0.017
0.277
0.091
0.106
.
.
S37tax[0.94][0.26][0.54][0.72].
.
0.242
0.651*
0.227
0.435-0.339**-0.277*
H1tax[0.48][0.09][0.28][0.33][0.03][0.06]
0.748*
1.460***
0.459*
1.231**.
.
H6tax[0.05][0.00][0.07][0.01].
.
0.4
0.897**
0.105
0.822**
0.068
0.324
H15tax[0.21][0.01][0.67][0.04][0.80][0.14]-0.161-0.333-0.077-0.284-0.085-0.19
H18tax[0.41][0.13][0.59][0.25][0.59][0.18]-0.021-0.012-0.018-0.014-0.021-0.023-0.008-0.025-0.027-0.097-0.115-0.09
Polyphe. Boom
[0.88][0.89][0.91][0.86][0.80][0.82][0.91][0.81][0.88][0.37][0.27][0.39]-0.2440.005-0.568*0.002-0.003-0.081-0.0020.016-0.476-0.03-0.252-0.007
Shōchu boom
[0.36][0.96][0.06][0.98][0.97][0.69][0.98][0.88][0.15][0.89][0.18][0.94]
3.249*
5.727***
5.968***
4.423***
6.860***
3.677***
5.256***
5.553***
5.915**
3.903**
5.796***
5.607***
Constant[0.10][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.02][0.01][0.00][0.00]
N
147
147
147
147
147
142
142
138
138
60
60
60
Note: p-value in brackets (* p<0.05, ** p<0.01, *** p<0.001); Estimation (1) exhibits an evidence of multicollinearity; tax ratio not included as it is available for beer only. ; a) domestic tax data available for
1989-2011 only (1991-2011 taking MA(3) growth rate tax value).
Data Source: A) Alcohol Related Data: Long-Term Time Series Data (1948-2011) and Liquor Tax information from the National Tax Agency (2013); B) Real Tax Values calculated using Deflator for Final
Consumption Expenditure (1)FY1955~1979(1990/H2-constant: 64SNA, adjusted to match (2))；(2)FY1980～2009(2000/H12-constant：93SNA)；(3) 2010～2011(2005/H17-constant：93SNA, adjusted tomatch (2)); C) Final Consumption Expenditure Per Capita and Price data for tax ratio used Final Consumption Expenditure data, for (1) 1963-2007: 20-3-a Annual Household Expenditures and Quantity
Purchased by Commodity (Non-agricultural, forestry and fishery Households with 2 or more; 1963-2007 All Japan); (2) 2008-2010: 20-3-b Annual Household Expenditures and Quantity Purchased by
Commodity (Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All Japan); (3) 2011: H2~H22 Yearly Amount of Expenditures, Quantities and Average Prices per
Household (1990-2012 all Japan) , and Total Population of Japan (2013) from the Statistical Bureau of Japan.

41

Table 7. Time-Series (ARMA) Estimation Results: Saké, Shōchu, Beer, Whisky, Wine (1955-2011)
ShōchuSaké

Beer

WhiskyWine

production

consumption

production

consumption

production

consumption

production

consumption

production

consumption

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

MA(3)
grw rate
tax val.

1.079***

0.903***

0.322***

0.260***

0.627***

0.656***

0.045

0.237***

1.656***

0.841**

1.176***

0.623*

0.477

0.404

0.246***

0.244***

1.071***

0.742***

0.156***

0.156***[0.00][0.00][0.00][0.00][0.00][0.00][0.50][0.00][0.00][0.02][0.00][0.08][0.10][0.24][0.00][0.00][0.00][0.00][0.00][0.00]

ln av.
tax rate-0.321**-0.187***0.07

0.263**-1.034***-0.627***-0.266-0.018-0.594***0.003[0.02][0.01][0.71][0.01][0.00][0.00][0.19][0.84][0.00][0.96]

ln final
consumption pc

0.657***

0.655***

0.333

0.271

1.401***

1.357***

0.971***

0.960***

0.877***

1.053***[0.00][0.00][0.20][0.41][0.00][0.00][0.00][0.00][0.00][0.00]

0.090**

0.112*

0.046

0.081**

0.116

0.093

0.171***

0.077

0.075

0.066

0.058

0.074

0.205***

0.253***-0.055-0.04

0.056***

0.026

0.055

0.062***[0.02][0.05][0.25][0.01][0.17][0.14][0.00][0.21][0.17][0.15][0.30][0.14][0.00][0.00][0.24][0.13][0.00][0.84][0.11][0.01]

0.004

0.048

-0.0080.030*-0.358***-0.358***-0.060**-0.0370.022

0.077*

0.007

0.066*-0.090**-0.05-0.039-0.02-0.0410.106-0.0040.009[0.94][0.41][0.72][0.10][0.00][0.00][0.04][0.35][0.52][0.05][0.84][0.08][0.02][0.40][0.14][0.26][0.20][0.23][0.91][0.56]-0.047-0.059-0.037***-0.041**-0.165***-0.164***-0.076***-0.065**-0.0060.02

0.02

0.029**-0.045-0.025-0.064***-0.071***-0.015-0.051***0.026**

0.018[0.23][0.25][0.01][0.03][0.00][0.00][0.00][0.02][0.71][0.15][0.14][0.02][0.39][0.72][0.00][0.00][0.69][0.00][0.04][0.12]

0.025

0.033

0.035

0.033

-0.022-0.025-0.009-0.0180.017-0.0020.016-0.003

0.029

0.03

0.033

0.017

0.013

-0.0280.013-0.004[0.65][0.61][0.25][0.41][0.52][0.43][0.81][0.52][0.46][0.97][0.55][0.96][0.53][0.68][0.40][0.77][0.79][0.80][0.78][0.94]-0.0070.005-0.034-0.009

0.039

0.049

0.017

0.026

-0.027***-0.001-0.023*

0.014

0.034

0.054

-0.0240.026-0.033-0.066-0.085*-0.03[0.91][0.94][0.32][0.80][0.22][0.14][0.64][0.38][0.00][0.98][0.06][0.71][0.43][0.39][0.49][0.61][0.50][0.58][0.06][0.59]PolypheBoom-0.028-0.017-0.036-0.024-0.036-0.029-0.071*-0.045**0.002

0.027*

0.007

0.026

0.016

0.052

0.014

0.031

0.159*

0.210**

0.188*

0.204**[0.46][0.65][0.13][0.31][0.23][0.21][0.05][0.03][0.93][0.06][0.76][0.22][0.79][0.12][0.65][0.29][0.09][0.04][0.05][0.04]

Shōchuboom-0.022-0.032-0.039-0.033

0.072

0.079

0.072

0.069

-0.015-0.01-0.028-0.008-0.0090.006-0.059-0.024-0.059-0.043-0.086-0.045[0.73][0.67][0.51][0.64][0.32][0.26][0.33][0.27][0.56][0.88][0.39][0.91][0.93][0.96][0.39][0.82][0.28][0.74][0.33][0.67]

8.321***

6.382***

7.532***

6.352***

5.755***

6.069***

4.643***

6.098***

13.309***7.136***

10.767***7.084***

5.726***

3.957***

4.136***

4.078***

6.680***

3.700***

4.241***

4.147***[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00]

0.987***

0.994***

0.988***

0.995***

0.985***

0.973***

0.989***

0.982***

0.986***

0.988***

0.993***

0.987***

0.985***

0.974***

0.992***

0.983***

0.983***

0.873***

0.996***

0.966***[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00]

0.569***

0.537***

0.485***

0.502***

1.000***

0.698**

1.000***

0.304***

1.000***

0.462***

0.532**

0.294**

1.000***

1.000***

1.000***

1.000***[0.00][0.00][0.00][0.00][0.00][0.01][0.00][0.00][0.00][0.00][0.01][0.05][0.00][0.00][0.00][0.00]

S37tax
H1tax
H6tax
H15taxH18taxConst.

AR(1)
MA(1)

sigma
_cons

0.062***

0.058***

0.039***

0.034***

0.070***

0.070***

0.049***

0.053***

0.055***

0.055***

0.049***

0.052***

0.097***

0.093***

0.060***

0.054***

0.089***

0.094***

0.061***

0.056***[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00]

N

57

57

57

57

57

57

57

57

57

57

57

57

57

57

57

57

57

57

57

57

42

bic

-102.77-110.45-150.67-165.61-83.79-85.17-120.29-115.47-107.41-111.83-119.86-118.92-46.66-52.53-96.56-109.96-61.57-58.2-94.59-105.94aic-127.28-134.97-177.23-192.17-110.35-111.73-146.85-142.03-133.97-138.39-146.42-145.48-73.22-79.09-123.12-136.52-86.09-82.71-121.15-132.5
Note: p-value in brackets (* p<0.05, ** p<0.01, *** p<0.001)
Data Source: A) Alcohol Related Data: Long-Term Time Series Data (1948-2011) and Liquor Tax information from the National Tax Agency (2013); B) Real Tax Values calculated using Deflator for Final
Consumption Expenditure (1)FY1955~1979(1990/H2-constant: 64SNA, adjusted to match (2))；(2)FY1980～2009(2000/H12-constant：93SNA)；(3) 2010～2011(2005/H17-constant：93SNA, adjusted tomatch (2)); C) Final Consumption Expenditure Per Capita and Price data for tax ratio used Final Consumption Expenditure data, for (1) 1963-2007: 20-3-a Annual Household Expenditures and Quantity
Purchased by Commodity (Non-agricultural, forestry and fishery Households with 2 or more; 1963-2007 All Japan); (2) 2008-2010: 20-3-b Annual Household Expenditures and Quantity Purchased by Commodity(Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All Japan); (3) 2011: H2~H22 Yearly Amount of Expenditures, Quantities and Average Prices per Household(1990-2012 all Japan) , and Total Population of Japan (2013) from the Statistical Bureau of Japan.

Table 8. Summary Statistics of Variables (for Elasticity Estimation)
Variable
Obs
Mean
Real Annual Expenditure (JPY)saké
48
8306.35
shōchu48
2721.75
beer
48
15818.50
whisky48
2913.55
wine
48
1150.36
Consumed Quantity (L)
saké
48
15.61
shōchu
48
5.08
beer
48
40.90
whisky
48
1.79
wine
48
1.12

Std. Dev.

Min

Max

3763.60
2204.8110381.05
2124.231004.461255.66
112.58733.93120.16
54.07

12666.18
6504.60
33793.78
6600.243553.80

4.77
2.87
11.80
0.81
0.74

7.91
1.78
17
0.73
0.36

22.84
11.00
62
3.46
2.90

Variable
Obs
Real Price per Litre (JPY)

Mean

Std. Dev.

Min

Max

603.86saké
48
437.37shōchu48
349.41beer
48
1546.06
whisky48
878.21
wine
48
Household (hh) Characteristics
3.63
no of member
48
48.54
age of hh head48
1.55
work member
48

303.35234.81
187.82870.83465.23

69.69
47.58
43.26
164.1479.55

930.34685.63555.213095.80
1495.00

0.36
4.23
0.94

3.09
43.7
1.35

4.3
56.3
1.67

Data: (1) 1963 to 2007 from 20-3-a Annual Household Expenditures and Quantity Purchased by Commodity (Non-agricultural, forestry and fishery Households with 2 or more;
1963-2007 All Japan); (2) 2008 to 2010 from 20-3-b Annual Household Expenditures and Quantity Purchased by Commodity, (Households with 2 or more, including
agricultural, forestry and fisheries households; 2000-2010 All Japan)
Data source: Japan National Statistical Bureau (2013)43

Table 9. Expenditure and Own Price Elasticities of Demand: Double Log Estimation (1963-2011)
Panel

AR(1)/ARMA(1)lnq 5 types

lnq shōchu

lnq saké

lnq beerlnq whisky

lnq wine

(1)

(2)

(1)

(2)

(3)

(1)

(2)

(3)

(1)

(2)

(3)

(1)

(2)

(3)

(1)

(2)

(3)

ln total
exp.a)

0.726***

0.586***

0.846**

0.743***

0.498**-1.115***-1.261***-1.059***1.076***

1.092***

0.994***

1.522***

1.264***

1.003***

0.295

0.414*

0.553**[0.00][0.00][0.01][0.00][0.03][0.01][0.00][0.01][0.00][0.00][0.00][0.00][0.00][0.00][0.20][0.06][0.01]

ln price-0.599***-0.530***-0.891*-0.844***-0.669**1.336**

1.437***

1.401***-0.899***-0.907***-0.893***-0.945***-0.828***-0.706***-0.583***-0.598***-0.616***[0.00][0.00][0.06][0.00][0.02][0.02][0.01][0.01][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00]-0.023***-0.035***-0.043***0.039***

0.058***-0.018***-0.025-0.066***-0.042**0.045***

0.043[0.00][0.00][0.00][0.00][0.01][0.01][0.21][0.00][0.02][0.00][0.11]

b)

t
no hh

0.096

-0.718***-0.1270.051-0.589-0.165

0.18

-0.61

-0.096

0.908

0.217

member

[0.62][0.00][0.42][0.95][0.58][0.65][0.60][0.17][0.80][0.23][0.70]

age of-0.030**-0.023-0.090***-0.047

0.058

0.008

-0.025-0.101**-0.148**0.064

0.122***

hh head[0.03][0.26][0.00][0.52][0.45][0.84][0.31][0.01][0.02][0.20][0.00]

15.609***constant

3.377***

5.410***

3.842**

8.936***

11.448***18.766**14.713

0.626

0.838

1.886

-6.117***

3.332

5.543

5.282**-2.674-3.782[0.00][0.00][0.05][0.00][0.00][0.00][0.03][0.13][0.55][0.80][0.55][0.00][0.43][0.22][0.02][0.61][0.44]

0.813***

0.31

0.354**

0.715***

0.766***

0.665**

0.868***

0.864***

0.893***

0.918***

0.893***

0.917***

0.806***

0.784***

0.764***[0.00][0.25][0.02][0.00][0.00][0.02][0.00][0.00][0.00][0.00][0.00][0.00]

AR component
AR(1)
MA(1)
sigma

[0.00][0.00][0.00]

0.257***

0.263***

0.273***[0.00][0.00][0.01]

0.035***

0.033***

0.042***

0.089***

0.088***

0.094***

0.058***

0.057***

0.059***

0.077***

0.070***

0.074***

0.124***

0.121***

0.124***[0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00][0.00]

N

240

240

48

48

48

48

48

48

48

48

48

48

48

48

48

48

48

AIC

.

.

-172.08-176.49-153.75-83.19-80.01-76.06-124.3-120.59-119.91-95.52-101.13-98.32-48.42-47.03-47.04

constant

BIC.
.
-160.85-161.52-140.65-71.96-65.04-62.96-113.08-105.62-106.81-84.29-86.16-85.22-35.32-30.19-32.07
Note: p-value in brackets (* p<0.05, ** p<0.01, *** p<0.001); a) expenditure elasticity; b) price elasticity.
Data: (1) 1963-2007: 20-3-a Annual Household Expenditures and Quantity Purchased by Commodity (Non-agricultural, forestry and fishery Households with 2 or more; 1963-2007 All Japan); (2) 2008-2010: 203-b Annual Household Expenditures and Quantity Purchased by Commodity (Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All Japan); (3) 2011: H2~H22 YearlyAmount of Expenditures, from Japan National Statistical Bureau (2013).

44

Table 10. Expenditure and Own Price Elasticities of Demand: AIDS Estimations (1963-2011)
saké

shōchuAIDSbeerwhisky

wine

αi

-0.91

0.38

1.25

0.09

0.18

0.08

0.23

0.65

βi

[0.00]-0.72[0.00]
0.01[0.00]
0.53[0.22]
0.14[0.00]
0.04[0.68]
0.25[0.00]
0.80[0.01]
0.05[0.00]
0.06[0.00]-0.40[0.00][0.00]
2.04[0.00]

γii[0.00]
1.25[0.08]-1.89[0.00]

0.06[0.00][0.00][0.00][0.14][0.00]

0.47[0.00]

0.35[0.00]

saké

wine

saké

QUAIDS w hhmem
shōchu beer whisky

wine

saké

DAIDS-a ( single ρ)
shōchu beer whisky

wine

saké

DAIDS-b (5ρi)
shōchu beer whisky

wine

-0.08

0.12

-0.82

-0.01

2.28

-0.84

0.39

0.23

0.06

0.56

0.14

0.00

0.00

1.33

0.62

-0.43

-0.53

[0.10]
0.14[0.00]
0.11[0.00]
0.12[0.91]-0.61[0.00]
0.51[0.00]
0.05[0.00]-0.07[0.00]
0.07[0.14]-0.09[0.00]
0.01[0.00]
0.02[0.85]-0.02[0.97]
0.05[0.02]-0.10[0.00]
0.02[0.39]
0.04[0.01]-0.01[0.52]
0.16[0.04]
0.04[0.38]
0.92[0.00]
0.07[0.00]
1.18[0.77]
0.41[0.17]
0.06[0.11]
0.30[0.04]-0.02[0.73]
0.28[0.35]-0.04[0.16]-0.03[0.33]
0.29[0.00]-0.03[0.80]
0.24[0.39]-0.02[0.78]-0.03[0.01][0.00][0.00]-0.04[0.11]
0.01[0.00]
0.11[0.00]-0.12[0.00]0.04

δi[0.02]
0.00[0.78]
0.00[0.02]
0.00[0.38]
0.00[0.27]
0.00[0.02]
0.00[0.73]
0.00[0.04]
0.00[0.63]
0.00[0.39]
0.00[0.12]-0.21[0.22]
0.15[0.00]
0.21[0.00]-0.25[0.00]
0.10

θii[0.02]
0.00[0.01]
0.00[0.00]
0.00[0.63]
0.00[0.07]
0.00[0.06]
0.00[0.18]
0.00[0.02]
0.00[0.26]
0.00[0.24]
0.00[0.00]
0.73[0.00][0.00][0.00][0.00]
ηi[0.36]
0.94[0.63]
0.00[0.11]
0.00[0.91]
0.00[0.20]-0.94[0.96]
0.97[0.04]
1.00[0.56]
0.95[0.57]-3.92[0.34]
1.00[0.00]
0.00[0.13][0.10][0.09][0.00]

ρi[0.00]
0.00[0.00]
0.00[0.00]
0.00[0.00]
0.00[0.00]
0.00[0.93] [0.01] [0.13]
Expenditure and Own/Cross-Price Elasticities[0.08][0.04]AIDS w hhmem
shōchu beer whisky[0.28]

λi
ϑi_
hh

0.52
[0.00]

σ_
hh

-0.20
[0.00]

0.05[0.02]-0.51[0.00]-0.03[0.57]-0.04[0.00][0.01][0.24]
Expenditure and Own/Cross-Price Elasticities
ei

-1.18
[0.00]

1.14[0.00]

2.14[0.00]

2.51[0.00]

2.08[0.00]

0.95[0.00]-1.62[0.00]

1.44[0.00]

1.43[0.01]

0.39[0.27]-0.11[0.28]-0.93[0.00]

2.09[0.00]

0.84[0.06]

1.80[0.00]

1.22[0.00]-0.08[0.88]

1.03[0.00]

1.21[0.00]

0.43[0.29]

1.17[0.00]-0.30[0.49]

1.04[0.00]

1.39[0.00]

0.76[0.37]

ηij
saké

2.68
[0.00]-3.96[0.00]-0.77[0.00]-1.52[0.00]

0.95[0.00]-0.15[0.00]-0.28[0.01]-1.09[0.00]-0.12[0.33]

0.10[0.05]-0.97[0.00]-0.11[0.29]

0.09[0.04]-1.12[0.00]-0.15[0.35]-0.14[0.29]-0.80[0.00]-0.11[0.48]-0.01[0.92]

1.49[0.00]

0.42[0.17]-0.09[0.37]

0.11[0.37]

0.11[0.33]-0.42[0.40]

0.00[1.00]

0.43[0.67]-0.28[0.68]-0.54[0.25]

0.15[0.72]-0.91[0.00]-0.15[0.13]

0.04[0.21]-1.40[0.00]-0.03[0.25]-0.73[0.00]

0.07[0.38]-0.50[0.01]-0.24[0.39]

0.01[0.94]

0.11[0.37]-0.93[0.00]-0.78[0.05]-0.09[0.37]-0.52[0.36]-0.46[0.29]-0.69[0.28]-0.46[0.56]

1.12[0.01]

0.23[0.31]

0.33[0.29]

0.09[0.39]-0.36[0.27]-0.22[0.29]-1.15[0.38]-0.02[0.99]

1.24[0.25]-1.95[0.03]-1.04[0.45]

2.43[0.09]-0.09[0.94]-1.03[0.02]-0.16[0.82]

0.20[0.51]-0.39[0.29]-1.43[0.00]
1.45[0.05]

0.49[0.07]

1.19[0.05]-0.25[0.37]-1.65[0.00]-0.54[0.00]

0.65[0.04]

0.72[0.24]-2.53[0.00]-0.50[0.03]
0.60[0.24]

0.19[0.09]-0.55[0.26]-0.42[0.10]
0.71[0.20]

0.16[0.17]-1.11[0.00]-0.79[0.00]
0.81[0.03]

0.02[0.38]-0.68[0.15]-3.09[0.00]-0.41[0.00]-0.78[0.03]-1.23[0.24]-0.12[0.38]-0.14[0.86]

0.12[0.00]-0.17[0.38]
0.11[0.08]

1.97[0.00]-0.22[0.01]

0.23[0.37]-0.01[0.40]-0.13[0.75]
0.55[0.54]-0.12[0.69]

0.55[0.04]-0.16[0.68]
1.87[0.04]

0.35[0.13]-1.76[0.00]

1.43[0.00]-1.10[0.00]-0.34[0.00]

1.94[0.00]

0.43[0.12]-0.43[0.27]

shōch
u
beer

-2.17
[0.00]

2.09[0.00]
0.25[0.01]

whis
ky

2.12
[0.00]-1.60[0.00]-0.13[0.12]-1.24[0.00]

wine-2.58[0.00]

1.24[0.05]

1.70[0.00]-1.90[0.02]

Note: p-value in parentheses; elasticities are calculated at mean of variables; Own-price elasticities are in diagonal, shown in bold; Cross-price elasticity matrix are shown for elasticity of good in row i with respect
to changes in price of good in column j; Own/cross-price elasticities for DAIDS model use the ordinal AIDS elasticity formula (explanation given in the article). AIDS, QUAIDS and DAIDS models are estimatedwith IFGNLS using nonlinear systems of equations estimations.
Data: (1) 1963-2007: 20-3-a Annual Household Expenditures and Quantity Purchased by Commodity (Non-agricultural, forestry and fishery Households with 2 or more; 1963-2007 All Japan); (2) 2008-2010: 203-b Annual Household Expenditures and Quantity Purchased by Commodity (Households with 2 or more, including agricultural, forestry and fisheries households; 2000-2010 All Japan); (3) 2011: H2~H22 YearlyAmount of Expenditures, from Japan National Statistical Bureau (2013).

45

APPENDIX
Nonparametric Kernel Regressions with Gaussian Specification
1. y = expenditure share for saké, x = log of total alcohol consumption expenditure
Kernel regression, bw = __00000F, k = 6.542998.238547
11.6619

15.2294
Grid points

2. y = expenditure share for shōchu, x = log of total alcohol consumption expenditure
Kernel regression, bw = __00000F, k = 6.106964.027988
11.6619

15.2294
Grid points46

3. y = expenditure share for beer, x = log of total alcohol consumption expenditure
Kernel regression, bw = __00000F, k = 6.529703.333201
11.6619

15.2294
Grid points

4. y = expenditure share for whisky, x = log of total alcohol consumption expenditure
Kernel regression, bw = __00000F, k = 6.140577.06162
11.6619

15.2294
Grid points47

5. y = expenditure share for wine, x = log of total alcohol consumption expenditure
Kernel regression, bw = __00000F, k = 6.044684.010869
11.6619

15.2294
Grid points

48