Abstract
Smoking is an expensive habit. Smoking households spend, on average, more than $US1000 annually on cigarettes. When a family member quits, in addition to the former smoker’s improved long-term health, families benefit because savings from reduced cigarette expenditures can be allocated to other goods. For households in which some members continue to smoke, smoking expenditures crowd-out other purchases, which may affect other household members, as well as the smoker. We empirically analyse how expenditures on tobacco crowd-out consumption of other goods, estimating the patterns of substitution and complementarity between tobacco products and other categories of household expenditure. We use the Consumer Expenditure Survey data for the years 1995–2001, which we complement with regional price data and state cigarette prices. We estimate a consumer demand system that includes several main expenditure categories (cigarettes, food, alcohol, housing, apparel, transportation, medical care) and controls for socioeconomic variables and other sources of observable heterogeneity. Descriptive data indicate that, comparing smokers to nonsmokers, smokers spend less on housing. Results from the demand system indicate that as the price of cigarettes rises, households increase the quantity of food purchased, and, in some samples, reduce the quantity of apparel and housing purchased.
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Notes
1Representative items in the expenditure categories include food (food at home, food away from home), housing (rent, mortgage interest, property taxes, maintenance and repairs, utilities, household operations, house furnishings), apparel (men’s, boys’, women’s and girls’ apparel; footwear; other apparel services), transportation (vehicle purchases [both new and used], gas, motor oil, vehicle finance charges, insurance, repairs, vehicle rentals) and healthcare (health insurance, medical supplies, medical services, prescription drugs). For further specific classifications, see US Department of Labor, Bureau of Labor Statistics.[13]
2Low income is defined as less than 200% of the US federal poverty line.
3In work currently in progress, we are exploiting the longitudinality of the dataset and controlling for the correlation of the error terms over time.
4Note that given the formula for the elasticities, we can obtain their variances (and statistical level of significance) as a linear combination of the variances of the estimated coefficients.
5For example, when we estimated the model including the selection bias correction terms, the own price elasticity of tobacco in the full sample was −0.977, compared with −0.986 when we did not include them.
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Acknowledgements
We would like to acknowledge financial support from the Robert Wood Johnson Foundation (#039787) and the National Institute on Drug Abuse (NIDA RO1-DA14471). We also thank Frank Chaloupka for providing ciga-rette price data and Meg Wise for programming assistance. ## The authors have provided no information on conflicts of interest directly relevant to the content of this article.
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Busch, S.H., Jofre-Bonet, M., Falba, T.A. et al. Burning a hole in the budget. Appl Health Econ Health Policy 3, 263–272 (2004). https://doi.org/10.2165/00148365-200403040-00009
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DOI: https://doi.org/10.2165/00148365-200403040-00009