Long-Term Effects of Tobacco Prices Faced by Adolescents
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M. Christopher Auld
und
Mahmood Zarrabi
Abstract
Tobacco taxes in Canada varied markedly across time and across regions in the early 1990s. We exploit this variation to estimate the long reach of prices faced in adolescence on smoking behavior roughly a decade later in early to mid-adulthood. Results from a variety of econometric approaches suggest that there is a small but detectable long-run effect of price faced during adolescence. A 10% increase in prices faced during adolescence, holding contemporaneous prices constant, leads to roughly a 1% reduction in adult smoking propensity and intensity. The results are somewhat sensitive to specification and to how price during adolescence is measured.
Acknowledgments
Auld thanks the Center for Addictions Research of British Columbia (CARBC) for financial support. An anonymous referee and seminar participants at the University of Calgary and the University of Victoria provided many helpful comments. We thank Statistics Canada for providing access to confidential data.
Appendix
As discussed in Section (2.3), we do not observe province of residence during youth and must assume that the respondent has not moved across provinces when assigning past prices. Here, we report on a small Monte Carlo experiment constructed to investigate the magnitude of the resulting attenuation bias in a sampling environment similar to our data.
To mimic the broad features of the data, we set the number of observations per replication to n=90,000. In each of 30 province-cycle (10 provinces and three cycles) cells we assigned a price pij which ranges from –0.25 to 0.072 in steps of 0.024. These numbers were chosen to yield a mean price of 0.6 and an unconditional price standard deviation of 0.2, matching the moments of the data (Table 1). The data generating process was,
where i indexes simulated observations, pij is the price assigned in province-cycle j, and uij∼N(0, 1). To simulate unobserved moves across provinces, we construct observed price,
In Table A1 we report selected statistics from the simulations. Estimates using mismeasured prices,
Monte Carlo Results.
| Mean | S.D. | S.E. | |
|---|---|---|---|
| Coefficient estimates (true: β=–0.100): | |||
| –0.099 | 0.016 | 0.016 | |
| –0.090 | 0.016 | 0.016 | |
| 0.900 | 0.073 | ||
| t-ratios against false null β=0: | |||
| –6.222 | 1.000 | ||
| –5.598 | 1.000 | ||
Notes: 90,000 observations in each of 10,000 replications. Estimates from model with true prices are denoted with a subscript “true” and models with simulated measurement error arising from cross-province moves are denoted with a subscript “error.” S.D., denotes observed standard deviation and S.E., estimated standard errors.
We conclude from this exercise that, in our case, measurement error resulting from not observing province of residence during adolescence is not trivial but neither is it serious. Our point estimates are attenuated by about 10%, with a resulting small loss in power.
Effect of Tobacco Prices on Adult Smoking Patterns Controlling for Price at Age 25.
| Smoking probability | Number of cigarettes | |||
|---|---|---|---|---|
| Male | Female | Male | Female | |
| Contemporaneous price | 0.162* | –0.031 | –0.282*** | –0.235** |
| (1.72) | (0.138) | (2.98) | (1.99) | |
| Price at age 14 | 0.017 | –0.051 | –0.0034 | –0.002 |
| (0.348) | (1.19) | (0.188) | (0.141) | |
| Observations | 37,727 | 43,098 | 10,137 | 9879 |
| Contemporaneous price | 0.139 | –0.002 | –0.277*** | –0.223* |
| (1.52) | (0.007) | (2.88) | (1.91) | |
| Average price ages 14–16 | –0.031 | –0.142*** | –0.003 | –0.005 |
| (0.526) | (3.04) | (0.126) | (0.25) | |
| Observations | 37,053 | 42,899 | 10,097 | 9864 |
| Contemporaneous price | 0.249* | –0.177 | –0.279*** | –0.206 |
| (1.87) | (0.785) | (2.89) | (1.61) | |
| Average price ages 12–18 | –0.151* | –0.190*** | –0.032 | 0.028 |
| (1.73) | (2.94) | (0.788) | (0.615) | |
| Observations | 31,073 | 36,507 | 8451 | 8400 |
Notes: Model as in Table 3 except also includes price respondent faced at age 25 as an additional covariate. Sample is respondents aged 26 through 40. Each cell denotes a separate regression. Parameter estimates are expressed as elasticities. Smoking probability is estimated using linear probability and OLS is used to estimate number of cigarettes. Asymptotic z-ratios in parentheses are based on robust and clustered at the province-cycle level standard errors. All models also control for immigration status, marital status, country of birth, household size, education, age, family income, province of residence, depression, pregnancy, and cycle of the CCHS. ***, **, *denote significance at the 1%, 5% and 10% levels.
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Artikel in diesem Heft
- Frontmatter
- Long-Term Effects of Tobacco Prices Faced by Adolescents
- The Value of Delaying Alzheimer’s Disease Onset
- Sex-selective Abortion Bans are Not Associated with Changes in Sex Ratios at Birth among Asian Populations in Illinois and Pennsylvania
- Public-Private Partnership as a Path to Affordable Healthcare in Emerging Markets
Artikel in diesem Heft
- Frontmatter
- Long-Term Effects of Tobacco Prices Faced by Adolescents
- The Value of Delaying Alzheimer’s Disease Onset
- Sex-selective Abortion Bans are Not Associated with Changes in Sex Ratios at Birth among Asian Populations in Illinois and Pennsylvania
- Public-Private Partnership as a Path to Affordable Healthcare in Emerging Markets
