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Donald Kenkel
;
Joseph V. Terza

the effect of physician advice on alcohol consumption: count regression with an endogenous treatment effect (replication data)

Although there are encouraging trends, alcohol abuse continues to be a significant public health problem. Econometric studies of alcohol demand have yielded a great deal of information for alcohol abuse prevention policy. These studies suggest that higher alcohol taxes and stricter drunk-driving policies can reduce heavy drinking and drunk driving. In this paper we explore the role physician advice plays in the campaign to prevent alcohol-related problems. Compared to alcohol taxation, physician advice is a more precisely targeted intervention that does not impose extra costs on responsible drinkers. Compared to the resource costs of arresting, processing, and punishing drunk drivers, physician advice may be a lower-cost intervention. To provide a basis for alcohol policy analysis, we use an alcohol demand framework to test whether physician-provided information about the adverse consequences of alcohol abuse shifts demand to more moderate levels. There are three aspects of our alcohol demand model that complicate the estimation: (1) the dependent variable is non-negative (it is a count variable-number of drinks consumed); (2) a non-trivial number of sample observations have zero values for the dependent variable; and (3) because the data we use is non-experimental, the treatment variable indicating receipt of advice from a physician may be endogenous. We implement an estimation method that is specifically designed to deal with these three complicating factors. Our results show that advice has a substantial and significant impact on alcohol consumption by males with hypertension, and that failing to account for the endogeneity of advice masks this result.

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Suggested Citation

Kenkel, Donald; Terza, Joseph V. (2001): The effect of physician advice on alcohol consumption: count regression with an endogenous treatment effect (replication data). Version: 1. Journal of Applied Econometrics. Dataset. http://dx.doi.org/10.15456/jae.2022314.0708760896