254
The crowding-out effect of tobacco expenditure on household spending patterns in Bangladesh
Methods: We analyzed data from the 2010 Household Income and Expenditure Survey from Bangladesh, a nationally representative survey conducted among 12,240 households (7,840 rural and 4,400 urban). The survey collected consumption information on over 300 food and non-food items, which were separated into 11 subgroups (tobacco, food, clothing, housing, education, health, lifestyle and hygiene, energy and utility, transport and communication, entertainment, and miscellaneous). A household was considered to have a tobacco-user if a respondent from that household reported any expenditure on tobacco. We compared the mean expenditure shares of each category between tobacco user and non-user households. A system of Engel curves was estimated to evaluate the ‘crowding- out’ hypothesis of tobacco expenditure; the estimation used the Quadratic Almost Ideal Demand System (Banks, Blundell, and Lewbel, 1997) for each non-tobacco consumption category, conditional on the tobacco-expenditure and controlling for household demographic and socio-economic characteristics and region fixed-effects. The outcome variable was the expenditure share. We applied instrumental variable regressions, an analytical method that ensures consistent and unbiased estimates to establish a causal interpretation. Crowding-out was considered to have occurred if the coefficient (β, indicating ‘percentage point’) of the tobacco-use indicator variable was negative and statistically significant (p<0.05). Comparisons were made between tobacco user and non-user households among the full sample, as well as among low income (bottom 50%), high income (top 50%), rural, and urban households. Additionally, the tobacco non-user households were assessed separately with mutually exclusive household tobacco use categories: smoking-only, smokeless-only, and both smoking and smokeless.
Results: On average, a tobacco-user household allocates 3% of the household budget to tobacco-expenditures. The average budget shares for clothing, housing, education, lifestyle and hygiene, energy and utility, transport and communication, entertainment, and miscellaneous are higher among tobacco non-user households compared to the tobacco-user households (p<0.01). The OLS estimates produce significant negative coefficients for the tobacco-user households for clothing (β=-0.68, p<0.0001), housing (β=-1.39, p<0.0001), education (β=-0.72, p<0.0001), lifestyle and hygiene (β=-.07, p<0.02), energy and utility (β=-0.36, p<0.0001), and transport and communication (β=-0.51, p<0.0001). The instrumental variable regression estimates indicated crowding-out effects attributable to tobacco expenditure for: housing (β=-11.08, p<0.0001), education (β=-2.52, p<0.05), lifestyle and hygiene (β=-0.47, p<0.03), and energy and utility (β=-2.61, p<0.0001). In general, similar patterns were observed for other subgroup comparisons.
Conclusion: Policy measures that reduce tobacco use could reduce displacement of commodities by households with tobacco users, including those commodities that can contribute to human capital investments.
Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.