1163 demand analysis on tobacco consumption.full

Nicotine & Tobacco Research Volume 9, Number 11 (November 2007) 1163–1169

Demand analysis of tobacco consumption in
Malaysia

Hana Ross, Nabilla A. M. Al-Sadat

Received 18 May 2006; accepted 12 February 2007

Downloaded from http://ntr.oxfordjournals.org/ at Perpustakaan Universiti Sains Malaysia on October 24, 2011
We estimated the price and income elasticity of cigarette demand and the impact of cigarette taxes on cigarette
demand and cigarette tax revenue in Malaysia. The data on cigarette consumption, cigarette prices, and public
policies between 1990 and 2004 were subjected to a time-series regression analysis applying the error-correction
model. The preferred cigarette demand model specification resulted in long-run and short-run price elasticities
estimates of 20.57 and 20.08, respectively. Income was positively related to cigarette consumption: A 1% increase
in real income increased cigarette consumption by 1.46%. The model predicted that an increase in cigarette excise
tax from Malaysian ringgit (RM) 1.60 to RM2.00 per pack would reduce cigarette consumption in Malaysia by
3.37%, or by 806,468,873 cigarettes. This reduction would translate to almost 165 fewer tobacco-related lung
cancer deaths per year and a 20.8% increase in the government excise tax revenue. We conclude that taxation is an
effective method of reducing cigarette consumption and tobacco-related deaths while increasing revenue for the
government of Malaysia.

Introduction Tobacco use is currently one of the leading causes
of death in Malaysia, accounting for 19% and 11.5%
Tobacco use has reached epidemic proportions
of deaths among men and women, respectively
worldwide (Jha, 1999). Although the prevalence of
(World Health Organization, 2003). The economic
smoking has decreased in countries with higher per-
costs of tobacco use are equally high and consist
capita income over the past two decades, cigarette
primarily of the healthcare costs of treating tobacco-
use has increased in countries with low- and mid-
related diseases (often covered by public funds) and
level per-capita income (Gajalakshmi, Jha, Ranson,
lower labor productivity.
& Nguyen, 2000). Malaysia is no exception to this
Some government interventions have been shown
trend. Smoking prevalence there has increased from
to reduce tobacco use (Ranson, Jha, Chaloupka, &
21.5% in 1986 to 24.8% in 1996 (Institute of Public
Nguyen, 2000), and the Malaysian government has
Health, 1987, 1997). Smoking is much more pre-
taken steps to leverage that fact. In 2004, the
valent among males than females (49.2% vs. 3.5%;
government introduced a total ban on all forms of
Institute of Public Health, 1997). Youth smoking is a
tobacco advertising and launched a 5-year multi-
particularly acute problem in Malaysia, where as
million-dollar smoking prevention media campaign.
many as 60% of young males from lower socio-
Malaysia also bans smoking in many public areas.
economic backgrounds smoke (Ahmad, Jaafar, &
However, Malaysia does not yet have a clear tobacco
Musa, 1997).
tax policy, which is one of the most effective methods
to combat smoking behavior (Chaloupka, Hu,
Warner, Jacobs, & Yurekli, 2000). The motivation
Hana Ross, Ph.D., International Tobacco Surveillance, American for several cigarette tax increases in the past decade
Cancer Society, Atlanta, GA; Nabilla A. M. Al-Sadat, M.P.H.,
Department of Social and Preventive Medicine, Faculty of Medicine,
was primarily to raise government revenue (Table 1).
University of Malaya, Malaysia. The 2005 excise tax on locally produced cigarettes,
Correspondence: Hana Ross, Ph.D., Epidemiology and Surveillance which constitute over 95% of the market, represents
Research, National Home Office, American Cancer Society, 250
Williams St. NW, Atlanta, GA 30303-1002, USA. Tel: +1 (404) 329-
only about 25% of the retail price. This rate is far
7990; Fax: +1 (404) 327-6450; E-mail: hana.ross@cancer.org below the tax level in some of Malaysia’s neighboring

ISSN 1462-2203 print/ISSN 1469-994X online # 2007 Society for Research on Nicotine and Tobacco
DOI: 10.1080/14622200701648433

1164 DEMAND ANALYSIS OF TOBACCO CONSUMPTION IN MALAYSIA

Table 1. Import, excise, and sales taxes, 1990–2005.

Import tax (non-ASEAN Import tax (ASEAN countries) Excise tax (local cigarettes)
Year countries) RM/KG or RM/stick RM/kg or RM/stick RM/kg or RM/stick Sales tax (%)

1990 85 85 13 15
1991 135 135 14 15
1992–1997 162 162 29 15
1998–2000 180 180 40 15
2001–2002 216 216 48 25
2003 259 108 58 25
2004 200 100 58 25
2005 0.20 0.10 0.08 25

Note. ASEAN, Association of Southeast Asian Nations; kg, kilogram; RM, Malaysian Ringgit. Tax in 2005 is in RM/stick; tax for all other
yeas is in RM/kg.

countries. In Thailand, for example, the cigarette smoking prevalence and smoking intensity while

excise tax represents 78% of the retail price. controlling for the population growth, served as the
International research has shown that a 10% dependent variable in our demand model. The real
increase in cigarette prices can reduce cigarette tobacco consumer price index (CPI), which represents
consumption by 4%–8% (Jha, 1999). Most countries the cost of all tobacco products in Malaysia adjusted
fall into this range, but some countries or regions for inflation, was provided by the Department of
may exhibit different price sensitivity because of Statistics. It is based on the price of one of the most
cultural or social factors. Nevertheless, only a few popular cigarette brands in Malaysia, Benson &
low- and middle-income countries have calculated Hedges (ACNielsen, 2002), which was collected
their country-specific estimates of the price respon- monthly by the Department of Statistics in randomly
siveness of the cigarette market. Lack of data or selected shops across the country. We adjusted the
research capacity is often the reason why this tobacco CPI for inflation using the general CPI. Our
information is not available. Having a country- model of cigarette demand controlled for the impact
specific estimate of responsiveness to cigarette tax of income and tobacco control policies on cigarette
changes is useful for planning purposes because the consumption. We measured income by real gross
impact of a tax increase on tax collection can be domestic product (GDP) per capita.
predicted with a higher degree of precision. Tobacco control policies other than cigarette taxes
This study is the first to estimate the responsive- can be important determinants of cigarette consump-
ness of Malaysians to a change in cigarette prices. It tion. We created a set of policy or event variables
demonstrates how cigarette excise tax policy can be that capture the tobacco control environment in
used to curb the tobacco epidemic in Malaysia, Malaysia between 1990 and 2004. Variable ‘‘tlaw1’’
predicts the impact of higher cigarette taxes on future takes the value of 1 for 1994–1996 and the value of 2
tobacco-related mortality, and estimates the impact for 1997–2004 to reflect the adoption of the Control
of cigarette tax policy on budget revenue. of Tobacco Products Regulation law and its amend-
ment in 1997 that expanded smoke-free areas and
banned minors’ smoking. Variable ‘‘relig’’ is assigned
Method the value of 1 for 1995–2002 to mark the National
The secondary aggregate time-series data for 1990 to Fatwa Council announcement that ‘‘Smoking Is
2004 used in this study are summarized in Table 2. Haram (Forbidden),’’ and the value of 2 for 2003–
The per-capita consumption of domestic and 2004 to capture the additional impact of the New
imported cigarettes was calculated using the excise Breath Beginning Ramadan Campaign calling for
tax and import duties collected by the Malaysian smoking cessation during Ramadan. Variable ‘‘ban-
government and the size of the adult population derol’’ takes the value of 1 for 2003, when the
(aged 15 years or older). Since the excise tax and government introduced special stickers to curb illegal
import duties were levied per kilogram until 2004, we tobacco products, and the value of 2 for 2004, when
determined the consumption of both domestic and security marks were placed on cigarette packs to
imported cigarettes in kg per year. To convert the improve the control of cigarette smuggling. Variable
weight amount to the number of cigarettes, we ‘‘taknak’’ assumes the value of 1 for 2004, when the
assumed, as did the Malaysian Department of national media anti-tobacco campaign Tak Nak was
Customs, that each kilogram of cigarettes is equal launched. Variable ‘‘tcmeas’’ is a dichotomous
to 1,100 sticks. Per-capita consumption is obtained indicator for every year in which a new tobacco
by dividing the total consumption (in sticks) by the control policy was adopted or a new tobacco control
size of the adult population (defined as population event occurred. The rationale for this variable is that
aged 15 years or older). This variable, which reflects the impact of a new policy or event lasts only one

NICOTINE & TOBACCO RESEARCH 1165

Table 2. Cigarette consumption, cigarette prices, and real income in Malaysia, 1990–2004.

Consumption (cigarettes/
Year person) Real tobacco CPI Real GDP per capita (RM) Tobacco policy index

1990 1,476 77.6 8,292 0
1991 1,679 78.3 8,504 0
1992 1,034 81.2 8,610 0
1993 1,554 91.8 8,887 0
1994 1,456 94.0 9,110 1
1995 1,549 93.1 9,398 2
1996 1,579 92.5 9,762 2
1997 1,607 92.0 9,977 3
1998 1,179 91.6 8,576 3
1999 1,393 98.8 8,642 3
2000 1,360 100.0 9,000 3
2001 1,175 105.6 9,027 3
2002 1,278 111.1 9,397 3

2003 1,335 112.7 9,895 5
2004 1,402 124.6 10,588 7
Mean (SD) 1,404 (181.6) 96.3 (13.1) 9,178 (651.0) 2.13 (1.60)

Note. CPI, consumer price index; RM, Malaysian Ringgit; GDP, gross domestic product.

period because of its weak enforcement, and that the selecting the two model versions can be found in
impact is related mostly to publicity and public the Results section.
health advocates’ lobbying efforts surrounding pol- We began by evaluating stationarity of our time-
icy enactment or a tobacco control event. All events series data. A nonstationary time series can lead to
and policies are summarized by a tobacco policy spurious regression, which confuses long-term rela-
index (variable ‘‘tcindex’’) defined as the sum of tionships, such as correlation over time, with causal
dichotomous indicators ‘‘tlaw1,’’ ‘‘relig,’’ ‘‘ban- relationships. We applied the Dickey–Fuller test for
derol,’’ and ‘‘taknak.’’ unit root and found that our measure of consump-
To estimate the demand for cigarettes, we used the tion was integrated at zero order I (0), that is, it was
following conventional model in linear functional stationary since the 10% critical value for the
form: reported Z(t) test statistic was 22.630. The price
and income variables were integrated at first order I
Yst ~azb0 Xpt zb1 Xgt zb2 Xtct zeð1Þ (1); they were stationary in their first differences.
Since the variables were not integrated at the same
WhereYst5aggregate consumption of cigarettes order, we proceeded with the Engle–Granger test for
per capita; Xpt5real tobacco CPI; Xgt5real GDP cointegration. This test is based on the stationarity of
per capita; Xtct5tobacco control policy/event. the model’s residuals and detects a possibility of
We estimated several versions of this model in a spurious regression. We found that the model’s
search for our preferred specification. We were residuals were stationary and that cointegration
limited by the degrees of freedom and thus could existed, given that the 10% critical value for the
not estimate a model controlling for all individual reported Z(t) test statistics was 21.60. This allowed
policies and events. Therefore, we adopted three us to proceed with the ordinary least squares (OLS)
different strategies: First, we estimated a model that model.
included only price and income variables to assess Given that our OLS model describes tobacco use
the impact of price on cigarette consumption without in the entire country (macro level), the market
a possible distortion related to the high degree of clearance price could be determined by the interac-
correlation between price and other tobacco control tion of both demand and supply sides of the market.
policies or events. Second, we augmented the model In that case, price would be determined endogen-
by controlling for one policy or event variable at a ously and OLS estimates would be biased. We tested
time. Third, we estimated the model with the tobacco this possibility using Hausman’s test. The m test
policy index representing the summary measure for statistic for Model II was 23.447, which is below the
all tobacco control policies and events. critical value of 6.63. Therefore, we could not reject
We subjected our key variables and two selected the null hypothesis of exogenous price. This result is
model versions to a battery of tests to verify the consistent with the theory of open economy and
accuracy of our specifications (Table 3 and Table 4). perfect competition, whereby cigarette price is
Model I included only price and income variables. determined exogenously by costs of production at
Model II was similar to Model I but controlled for the world market and by cigarette taxes. Hausman’s
the impact of tobacco control policies or events by test could not be performed on Model I because
the tobacco policy index. The justification for of the small number of independent variables.


Table 3. Test for nonstationarity. Engle–Granger method. ECM is based on the notion
that deviations from long-run equilibrium tend to
Consumption
Yst Price Xpt Income Xgt partially revert to the equilibrium position in the
following period. ECM uses stationary data (in this
Autocorrelation No Test No case, first differences of price and income measures)
inconclusive
Dickey–Fuller 23.939 0.753 20.918 and includes the lagged residuals (of the long-run
test: Z(t) relationship) as an explanatory variable. Coefficients
Dickey–Fuller 22.717 22.836 from ECM represent the relationship in the short
test first
difference: Z(t) run, and the coefficient on the lagged residual
Results Variable Variable Variable measures the speed of convergence to the long-run
integrated at integrated at integrated at equilibrium (as a percentage).
zero order I (0) first order I (1) first order I (1)
Long-run price elasticity is derived by multiplying
the relevant price coefficient estimated in the first
However, the exogeneity of price has been confirmed step of the Engle–Granger method by the fitted

in Model II and its variations with different policy values of price, and then dividing this expression by
the fitted values for quantity. The use of fitted values
variables.
instead of actual average values is required to obtain
Further, we applied the Ramsey regression speci-
results based on the long-run equilibrium. Income
fication error test and the omitted variable test. The
elasticity is calculated similarly but using the income
omitted variable test is conducted by regressing
coefficient and the income fitted values instead.
trend-stationary variables on time and using (sta-
Short-run elasticities are calculated using coefficients
tionary) residuals from this regression in the model
from the short-run ECM equation and the means of
with a time trend. Both tests indicated that we did
variables representing consumption, price, and
not exclude any important variables from our model.
income.
Such exclusion would result in biased estimates.
The Durbin–Watson test assessed the autocorrela-
tion of OLS model residuals. If residuals are
Results
correlated, OLS estimates are unbiased and consis-
tent, but they are inefficient. We found the value of Results for different versions of our model are
the reported d -statistic to be closer to the value 2 (no summarized in Table 5. Each model includes price,
serial correlation) than to the value 0 (positive serial income and one of the policy or event variables,
correlation) or 4 (negative serial correlation). except for Model I. The results in Table 5 show that
The Breusch–Pagan/Cook–Weisberg test deter- price has a negative and statistically significant
mined that residuals of the OLS model have constant impact on cigarette use in four out of seven model
variance. Therefore, no heteroscedasticity exists that specifications. The impact of income is quite
would reduce the reliability of our hypothesis testing consistent across different model specifications. Its
and cause OLS estimators to be inefficient. coefficient is statistically significant in six out of
Because our model passed the specification tests, seven model specifications. The lack of the signifi-
we proceeded with estimating both long-run and cance of the price variable can be explained by the
short-run relationships in the tobacco market using high degree of correlation between the measure of
the Engle–Granger two-step method (Engle & price and policies or events, given that in most cases
Granger, 1987). The first step estimates a long-run the adoption of a new policy also has been
equation without time trend. Given that a cointe- accompanied by a price increase. For example, the
grating relationship exists, we proceeded with an correlation coefficient between price and the tobacco
error-correction model (ECM), the second step of the
Table 5. Linear demand model: Impact of tobacco control
policies and events.
Table 4. Test results.
Policy/
Model I Model II Model: Price Income event
Yst5a+b0Xpt+b1Xgt+b3Xtct+e coefficient coefficient coefficient
Engle–Granger test for 26.248 25.965
cointegration: Z(t) Xtct not included (Model I) 211.05** 0.21** —
Hausman test: m — 23.447 Xtct5tlaw1 29.18 0.21** 233.64
Ramsey specification error 0.05 0.23 Xtct5relig 29.18 0.23** 258.33
test: F Xtct5banderol 210.80* 0.22** 213.29
Omitted variable test: time 213.85 (21.45) 240.36 (21.05 ) Xtct5taknak 211.15** 0.21** 14.91
coefficient (t value) Xtct5tcmeas 210.75** 0.19 32.86
Durbin–Watson test: d 2.98 1.85 Xtct5tcindex (Model II) 28.31 0.22** 228.96
Breusch–Pagan/Cook– 0.21 0.01
2 Note. *Statistically significant at 10% level; **statistically sig-
Weisberg test: x
nificant at 5% level.


policy index is 0.87. Both price and income are impact of price was statistically significant at a 5%
statistically significant in the model that does not level in all models except for the long-term relation-
include a tobacco control policy. None of the policy ship based on Model II (because of the high degree of
variables were statistically significant. This finding correlation, as explained earlier). The impact of
can be explained by the lack of enforcement of the income was statistically significant at a 5% level in all
policies and the short-lived impact of health promo- models. As expected, the long-run elasticities were
tion campaigns. greater than the short-run elasticities, which is typical
We selected two model specifications to calculate for an addictive product such as cigarettes. Price
our price and income elasticity estimates. Model I elasticity was larger in Model I because this
included only price and income variables, thus specification does not control for the impact of
avoiding the problem of the high degree of correlation policies or events, and we considered this value to be
between price and a policy or event. Both price and the upper bound of our price elasticity estimate.
income coefficients were significant in Model I. The Model II price elasticity was considered the lower
results based on Model I can be considered an upper bound of our estimate because of the high level of

bound of our price elasticity estimate since the impact correlation between price and the tobacco policy
of a tobacco control policy or event was not taken into index.
account. Model II was similar to Model I, but it The coefficients on the lagged residual of the short-
controlled for the impact of tobacco control policies run equations were 20.89 and 20.86 for Model I and
or events by including the tobacco policy index, the Model II, respectively. This indicates that, on
most comprehensive measure of these policies and average, about 86% to 89% of the deviation from
events. Model II may underestimate the impact of long-run equilibrium will be corrected in the follow-
price because of the high degree of correlation ing year. This is a large speed of adjustment,
between the index and the price variable. Therefore, reflecting the addictive nature of tobacco use.
the results based on Model II are considered the lower We used our price elasticity estimate to calculate
bound of our price elasticity estimate. This lower the impact of a 25% cigarette tax increase (raising the
bound is used for predicting the impact of a tax tax to RM0.1 per stick from its current level of
increase on budget revenue and on reduced mortality. RM0.08) on cigarette consumption, revenue from
The impact of income on the demand for tobacco tobacco taxes, and long-term health outcomes. First,
seemed to be quite stable across models. To be we estimated the impact of this tax increase on the
consistent, we also used the income elasticity based average cigarette price using the 2005 tax incidence,
on Model II in our simulation of future growth in average cigarette price of Benson & Hedges brand
tobacco consumption because of GDP growth. (the base for our tobacco CPI), and market share of
Table 6 summarizes results of the long-run and domestic and imported cigarettes. If the tobacco
short-run elasticities based on Model I and Model II. industry passes all of the tax increase on to
The results for long-run elasticities also have been consumers, cigarette prices can be expected to
bootstrapped to calculate the confidence interval for increase by about 5.9%. We applied the lower bound
the estimates. The bootstrap method failed in of our price elasticity estimate, 20.57, to predict the
calculating the results for short-run price elasticities impact of a tax increase to compensate for a possible
because of an insufficient number of observations upward bias in our estimates. This bias could have
(one data point is lost in the short-run equation since occurred because we were unable to control for
first differences of income and price are used). The cigarette smuggling in the model. We predict that the
proposed tax increase will result in a 3.37% reduction
in cigarette consumption in the long run. This change
Table 6. Price elasticity estimates. translates to a reduction of about 47 cigarettes per
Model I Model II person per year, or 806,468,873 fewer cigarettes
consumed in Malaysia per year.
Price elasticity
Long-run 20.758* 20.571
The reduced consumption of cigarettes would have
Long-run bootstrapped 20.745 20.537 many health benefits for the Malaysian population.
(¡ 0.059)* (¡0.079) Research shows that for every cigarette per person
Short-run 20.083* 20.077*
Income elasticity
not smoked, lung cancer mortality decreases by
Long-run 1.403* 1.464* 0.0248 per 100,000 adults aged 35–69 years within 20
Long-run bootstrapped 1.413 1.495 years (Gajalakshmi et al., 2000). This estimate is
(¡ 0.089)* (¡0.124)*
Short-run 0.028* 0.025* based on regressing 1990 tobacco-attributable lung
Coefficient on lagged 20.891 20.862 cancer mortality per 100,000 adults aged 35–69 years
residual (¡0.772)* (¡0.809) * on 1970 cigarette consumption in industrialized
Note. *Two-tailed test used to determine 5% level of statistical countries with a history of prolonged smoking.
significance. Assuming that the current population growth of


2.8% continues for the next 20 years, there will be lower bound of our elasticity estimate for predicting
14.17 million people in Malaysia in the 35–69 age the impact of a tax increase on cigarette consumption
category by 2026. Therefore, a 25% cigarette tax and government revenue.
increase in 2006 would prevent about 165 premature Simulation of the impact of a 25% cigarette excise
lung cancer deaths per year among that age group by tax increase predicted a 5.9% increase in the average
2026. Additional premature deaths would be pre- price of cigarettes and a 3.37% reduction in cigarette
vented thanks to reduced mortality from other consumption. This reduced cigarette consumption
tobacco-related diseases. could prevent about 165 premature tobacco-related
In addition to reducing the number of premature deaths related to lung cancer per year by 2026 and
deaths, the cigarette tax increase would raise increase government tax revenue by RM434 million,
government revenue. With the current cigarette tax or 20.8%.
level, population, and income growth, Malaysia can The estimate of the tax revenue increase is close to
expect to collect about RM2,088 million in cigarette the World Bank’s prediction of 17.5% (Jha, 1999),
excise tax in 2006. A 25% tax increase would generate based on its global experience, and in accordance

RM2,522 million in cigarette tax revenue in 2006, an with a mathematical model of tax revenue and price
increase of Malaysian ringgit (RM)434 million elasticity (Merriman, 2002) predicting a 20.5%
(US$115 million using the exchange rate increase in tax revenue. We conclude that a cigarette
US$15RM3.77), or 20.8%. tax increase in Malaysia will result in improved
public health and increased tax revenue. Ideally these
newly obtained resources would be used to help
Discussion smokers quit, strengthen the enforcement of the
current tobacco control laws, and to public health in
Our preferred lower bound estimate of price elasticity
general. They also could be used to support tobacco
of 20.57 based on macro-level data is comparable
farmers in switching to alternative crops.
with results from neighboring countries based on
micro-level data, such as Thailand (price elasti-
city520.39; Sarntisart, 2003) or Vietnam (price
Acknowledgments
elasticity520.53; Eozenou, 2001). According to our
results, a 1% increase in income in Malaysia will lead The authors gratefully acknowledge funding support from the
Rockefeller Foundation and from the ThaiHealth Foundation.
to a 1.46% increase in cigarette demand. Again, this
estimate is comparable with those from other middle-
income countries (Sarntisart, 2003; Van Walbeek,
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