Estimating Household Demand for Tobacco Products in Iran
Subject Areas : Addiction and victimization
mohamad hossein amjadi
1
*
,
Marziye Enhesari
2
1 - Ph.D of Economics, Shahid Bahonar University, Kerman, Iran.
2 - M.A Mathematics, Sistan & Bluchestan University, Zahedan, Iran.
Keywords: Tobacco Demand, Consequences of Tobacco Consumption, Income Elasticity, Household Expenditures, Tobit Model.,
Abstract :
Estimating Household Demand for
Tobacco Products in Iran
Mohammad Hossein Amjadi *
Marziye Enhesari **
Tobacco use poses a significant public health threat. This study estimates the demand function for tobacco products in Iran and calculates their income elasticity. Using data from the 2023 Household Income and Expenditure Survey, we first analyze household nicotine-related expenditures based on socio-economic characteristics. A Tobit regression model is then employed to estimate demand. All variables are statistically significant at the 99% confidence level. Income elasticity is estimated at 0.825, indicating that a 1% income increase leads to a 0.825% rise in tobacco expenditures. Effective intervention requires wide-ranging cooperation across public and private sectors. Proposed recommendations include: monitoring smoking patterns; implementing preventive policies; protecting against secondhand smoke; aiding cessation efforts; raising risk awareness; banning tobacco advertisements; combating smuggling; and enacting effective tax reforms.
Keywords: Tobacco Demand, Consequences of Tobacco Consumption, Income Elasticity, Household Expenditures, Tobit Model.
Introduction
Tobacco consumption has multifaceted social implications, spanning cultural, psychological, economic, and public health domains. It correlates with reduced life quality, as smokers often report lower well-being. Moreover, tobacco use may act as a gateway to other substances.
A household's consumption of tobacco products represents part of its total expenditures, which varies with its socio-economic priorities. Since each tobacco user is a purchaser, expenditure on tobacco serves as a valid proxy for actual consumption. Accurately understanding tobacco prevalence helps inform public health policy. In this context, we employ the 2023 Household Income and Expenditure Survey to estimate smoking prevalence in urban and rural Iran, identify socio-economic determinants of tobacco spending, and calculate income-based demand elasticity.
Consequently, this study addresses three research questions:
- How does household tobacco demand vary across socio-economic groups in Iran?
- What are the socio-economic determinants influencing household tobacco demand?
- What is the income elasticity of tobacco demand among Iranian households?
Systematic reviews of Iranian and international studies reveal a range of socio-economic influences on tobacco consumption (Table1). Findings vary, reflecting differences in population, methodology, and context.
Table1 – Socio-economic Determinants of Tobacco Consumption
(+: positive effect, –: negative effect, /: no significant effect)
|
Study |
Tobacco Type |
Influencing Factors |
|
Aristei & Pieroni (2008) |
Various |
Income (+), Age (+), Education (–), Gender (+), Marital Status (+), Social Class (–) |
|
Reggio et al. (2011) |
Tobacco |
Age (+), Gender (–), Marital Status (–), Residence (+), Unemployment (+), Literacy (+), Ethnicity (+) |
|
WHO (2019) |
Various |
Income (+), Age (+), Residence (+), Gender (+) |
|
Recher (2020) |
Smuggled Cigarettes |
Gender (–), Age (+), Income (+), Employment (–), Education (/), Residence (+) |
|
Nyaguachi et al. (2020) |
Tobacco & Alcohol |
Household Size (+), Education (+), Alcohol Use (+), Income (+) |
|
Gorji et al. (2009) |
Cigarettes |
Price (–), Income (+), Unemployment (+), Literacy (–) |
|
Ebadi et al. (2011) |
Cigarettes |
Age (+), Education (–), Gender (+), Occupation (+), Residence (+) |
|
Kouhbor (2013) |
Various |
Age (+), Education (+), Gender (+), Occupation (+), Income (+), Residence (–), Household Size (–) |
|
Mostafapour & Yazdanpanah (2015) |
Tobacco |
Age (+), Gender (–), Marital Status (–), Income (+) |
|
Pirdehghan et al. (2016) |
Tobacco |
Gender (+), Student Education (–), Head's Education (+), Income (+) |
|
National Institute of Health Research (2018) |
Various |
Age (Men [/] Women [+]), Gender (+), Income (–), Residence (+) |
|
Ziaoddini & Ziaoddini (2018) |
Cigarettes |
Gender (+), Age (+) |
|
Mehri et al. (2023) |
Cigarettes |
Family (+), Education (–), Gender (+), Income (+) |
Methodology
A descriptive-analytical design was used, drawing on the 2023 Household Income and Expenditure Survey. Data were analyzed using Access 2013, SPSS18, and Stata12. The Tobit model was selected to account for censored data where many households report zero tobacco expenditures:
Findings
4.1 Descriptive Statistics
The sample comprised 37,883 households (19,640 urban; 18,243 rural), with 7,311 (19.3%) reporting tobacco use. Urban users constituted 18%, while rural users were 21%. Annual expenditures and tobacco budget shares are reported in Table2.
Table 2 – Average Annual Household Expenditure by Area (2023)
|
Indicator |
Rural |
Urban |
|
% Using Any Tobacco |
21% |
18% |
|
Domestic Cigarette Users |
8.9% |
8.2% |
|
Foreign Cigarette Users |
8.7% |
7.5% |
|
Tobacco/Pipe/Rolling Paper Users |
2.4% |
1.5% |
|
Other Tobacco Product Users |
2.7% |
1.5% |
|
Avg. Annual Total Expenditure (IRR) |
206,525,000 |
110,659,000 |
|
Avg. Annual Tobacco Expenditure (IRR) |
863,300 |
1,103,000 |
|
Tobacco Share of Total Expenses |
0.42% |
1.00% |
4.2 Tobit Model Estimation
The likelihood ratio (LR) test was significant (LR chi²=1386.09), confirming the model's adequacy. Results are summarized in Table3 below.
Table 3 – Tobit Estimation Results for Tobacco Expenditures
|
Variable |
Coefficient |
Std. Error |
z-Value |
p-Value |
|
Log Household Income |
0.825 |
0.234 |
3.530 |
0.000 |
|
Household Size |
1.083 |
0.149 |
7.260 |
0.000 |
|
Head’s Age |
1.099 |
0.067 |
16.500 |
0.000 |
|
Age² |
–0.010 |
0.001 |
–15.570 |
0.000 |
|
Number of Literate Members |
–0.786 |
0.178 |
–4.410 |
0.000 |
|
Male Head (Dummy) |
12.360 |
0.590 |
20.940 |
0.000 |
|
Urban Residence (Dummy) |
–2.315 |
0.418 |
–5.540 |
0.000 |
|
Head’s Employment Status |
1.049 |
0.384 |
2.730 |
0.006 |
|
Constant |
–73.616 |
4.509 |
–16.330 |
0.000 |
Censored: 30,917; Uncensored: 6,966.
Discussion and Conclusion
Results confirm that tobacco is a normal good in Iran, with income elasticity of 0.825—less than unity but significantly positive, indicating that consumption increases with income. A larger household size also raises tobacco spending.
The negative coefficient for literate members highlights the protective effect of education, likely due to health literacy and risk awareness. Older heads exhibit higher consumption up to a point, after which it tapers off (as shown by the negative Age² coefficient).
Male-headed households spend notably more on tobacco than female-headed households, aligning with gender-based smoking patterns. And in rural settings, per-household expenditures are higher despite lower total income—likely due to less stringent regulation or cultural acceptance. This study establishes that income, household composition, education, gender, and geographic residence significantly influence tobacco expenditures in Iran. Price-based and socio-economic interventions, particularly directed at rural and less-educated populations, could substantially reduce smoking rates.
Policy recommendations include:
- Implementing higher tobacco excise taxes to deter consumption.
- Introducing public health education, especially among youth and in rural areas.
- Enforcing strict bans on tobacco advertising and public smoking.
- Supporting smoking cessation programs at local levels.
- Strengthening anti-smuggling and border control measures.
- Promoting inter-sectoral collaboration, consistent with recommendations from the WHO FCTC and World Bank.
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*Corresponding Author: Ph.D of Economics, Shahid Bahonar University, Kerman, Iran.
** M.A Mathematics, Sistan & Bluchestan University, Zahedan, Iran.
m.enhesari90@gmail.com
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