Study design and data
In this study, data of 22 Asia-Pacific countries were collected to construct a cigarette demand structure model. Kiribati, North Korea, Nauru, Timor-Leste, and the Marshall Islands were excluded from the study because of lack of data. One dependent variable and three independent variables were considered. Per capita cigarette consumption for those aged 15 and over was chosen as the dependent variable. Independent variables comprised cigarette prices, gross national income (GNI) per capita, and current status of WHO FCTC ratification.
Data regarding cigarette consumption and prices were extracted from the 1999–2015 Euromonitor International market research database [35]. Euromonitor International is recognized as a leading independent provider of global business intelligence, specializing in creating worldwide data and analysis on consumer products and services. Consumption of cigarette products was calculated based on annual cigarette consumption per capita for those aged 15 and over. The retail price for a pack of cigarettes in each country was calculated by dividing cigarette sales revenues by cigarette consumption, which was further deflated using consumer price indexes [36].
The GNI per capita data were accessed from the World Bank’s database, converted to US dollars using the World Bank Atlas method [36], divided by the midyear population, and deflated based on consumer price indexes. The current status of WHO FCTC ratification provides information on whether individual countries have ratified the convention. Countries that have already ratified the convention were given a 1 value. Data regarding the ratification of the WHO FCTC were obtained from the 2015 WHO report on global tobacco epidemic [7].
Data characteristics
Table 1 lists all variables used in the analysis and visualizes their characteristics. The structural composition of excise taxes on tobacco products in the observed countries is also shown in Table 1. Total excise taxes comprise specific excise, ad valorem excise, or mixed excise. Specific excise is the most common form. According to the 2015 WHO report on global prevalence of tobacco products, the specific excise tax proportion of retail price in 2014 was the highest in the Philippines (63.55%), followed by Sri Lanka (59.15%) and Tonga (58.82%), whereas specific excise taxes accounted for less than 50% in the remaining countries. High levels of ad valorem taxes were levied on tobacco products in Thailand (63.72), Bangladesh (61%), Myanmar (50%), Vietnam (32.5%), and China (29.3%). Total taxes were the highest in Thailand (66.58), followed by the Philippines (63.55%), Sri Lanka (63.06) and Bangladesh (61%). The Maldives did not levy taxes on cigarettes. Low total tax rates were also in evidence in Laos (7.65%), Cambodia (13.15%), and Nepal (16.29%).
In 2015, per capita cigarette consumption in the 22 Asia-Pacific countries for those aged 15 years and over was the highest in China at 95.94 packs, followed by Indonesia (50.52 packs), Vietnam (47.97 packs), and the Philippines (42.12 packs), while consumption in the other Asia-Pacific countries was below 40 packs (Table 1). With the exceptions of Indonesia, Mongolia, China, and Cambodia where cigarette consumption showed a rising trend, Indonesia experienced the highest growth (51.6%), followed by Mongolia (50%) and China (28.7%). Consumption in other countries assumed a downward trend with the Solomon Islands exhibiting the greatest decrease (41.5%), followed by Malaysia (35%).
According to WHO estimates, the smoking prevalence rate of populations aged 15 or older in the 22 observed low-income and middle-income countries is below 40%. It is the highest in Samoa at 37.3%, followed by Tonga (35.9%), Laos (35.3%), China (30.5%), Bhutan (28.8%), and Nepal (27.1%). India (13.4%), Sri Lanka (12.8%), and Fiji (10.9%) exhibit the lowest prevalence rates.
As shown in Table 1, in 2015, the average real retail price for a pack of cigarettes was the highest in the Solomon Islands at US$3.67 per pack, followed by Vanuatu (US$3.53). Considering the fluctuation of real retail prices of cigarettes between 1999 and 2015, cigarette prices across the Asia-Pacific region generally showed a rising trend, with China experiencing the greatest increase (150.4%), followed by Bhutan (62%), the Philippines (49.8%) and the Maldives (48.1%), while cigarette prices in Myanmar and Vietnam decreased by 48.3%, and 29.7%, respectively (Table 1).
Empirical specification and analysis
To calculate cigarette price elasticity, a cigarette demand structure model was constructed using cigarette consumption as the dependent variable and cigarette price, gross national income (GNI), and the ratification of WHO FCTC as explanatory variables.
To estimate price elasticities of demand for cigarettes, we have applied a conventional demand model with a linear equation in this study. We assume
$$\ln {C}_{it}={\beta}_{1i}+{\beta}_2\ln {P}_{it}+{\beta}_3\ln {GNI}_{it}+{\beta}_4{FCTC}_{it}+{\varepsilon}_{it}$$
(1)
where Cit is the annual cigarette consumption per capita in the population aged 15 and older in country i in year t (1999–2015), β1i is the intercept for country i, Pit is the cigarette real retail price per pack of 20 cigarettes in country i in year t, GNIit is per capita gross national income in country i in year t, and FCTCit is a dummy variable to describe the state of ratification of the WHO FCTC in country i in year t.
Endogeneity must be considered for the regression analysis to avoid biased estimates. Among the regressors used in our analysis, cigarette price has been reported as the most likely sources of possible endogeneity in studies on cigarette consumption [37, 38]. We addressed this issue by using cigarette price and consumer price indexes in periods t–1 as instruments for cigarette price. A weak identification test (Kleibergen-Paap Wald F) was carried out to verify instrument relevance [39].
A Hausman test was applied to determine which model should be used for the equation estimation. A rejection of the test is taken to mean that the key random-effects assumption is false and in such cases the fixed-effects estimates should be used [40].
To determine the effects of cigarette price increases on cigarette consumption, cigarette consumption in 2015 was set as the baseline for this study. Maximum and mean increments in cigarette prices during 1999–2015 were applied to simulate changes in future cigarette consumption based on the cigarette price elasticity estimated in this study. Changes in tobacco tax revenues were calculated based on changes in consumption due to price increases. Percentages of price increases were calculated using the yearly mean and maximum price increases between 1999 and 2015.
Previous research has shown that cigarette price elasticity is likely to be affected by income levels [20, 41]. To account for this income threshold effect, we performed our analysis using clusters of countries with different income levels. That is, the observed 22 countries were first grouped into two clusters according to World Bank classification: (a) low- and lower-middle income countries as well as (b) upper-middle income countries. The latter group of countries was then divided into two clusters and the first into four. Gross national income per capita data for the year 2015 (Atlas method) were used in the clustering and consideration was given to obtain clusters of approximately equal size and significantly different GNI values (Table 1).
The number of averted smoking-attributable deaths (SADs) derived from the simulated impact of price increments on the reduction in smokers and was adjusted for the fact that smoking cessation still carries considerable risks of early death [42]. The applied mortality adjustment factors were calculated for each country surveyed, assuming that 95%, 75%, 70%, 50% and 10% of those who ceased smoking when aged 15 to 29, 30 to 39, 40 to 49, 50 to 59 and at least 60 years, respectively, would remain unaffected by their previous smoking habits. Data on population stratification were extracted from the World Bank database [36].