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We present reduced form estimates of the effect of alcohol taxes on employment, weekly work hours, and wages. The reduced form estimates are meaningful in two ways: first, they provide estimates of the effect of an important public policy tool—alcohol taxes—and second, they can be used to evaluate hypotheses about the structural effects of alcohol use on labor market outcomes. Estimates indicate that there is a weak and indeterminate relationship between alcohol taxes and labor market outcomes. This implies that alcohol use does not adversely affect labor market outcomes and is inconsistent with findings from previous studies.

Alcohol consumption has the potential to reduce a person’s physical and psychological well being, and may cause a variety of individual and social problems. The deleterious effects of alcohol consumption have engendered a public interest in measuring the extent of alcohol-related problems, particularly in light of the government’s influence over the distribution and use of alcohol products. The public concern with alcohol consumption also stems from the negative external effects of alcohol consumption—such as drunk driving fatalities—which extend beyond the individual consumer of alcohol to other members of society. In the case of drunk driving, the causal influence of alcohol is indisputable, and public policies aimed at reducing alcohol consumption can be partially justified on this basis (Kenkel, 1993). For other social problems, the causal effect of alcohol consumption is not as clear. For example, the effect of alcohol consumption on employment and income has received considerable attention from researchers, which is not surprising given the critical role that the labor market plays in determining economic prosperity. Several studies have attempted to measure the effect of alcohol use on employment and income.1 Most have found that problem or heavy drinking is associated with less employment and lower earnings, although this finding is not uniform.2 The more significant issue of whether or not this relationship is causal remains unknown. In this case, causality is difficult to establish because alcohol use may be correlated with unmeasured personal factors such as motivation that influence labor market outcomes (i.e. statistical endogeneity), and because some labor market outcomes, such as wage income, influence alcohol consumption (i.e. structural endogeneity). Researchers studying the relationship between alcohol use and labor market outcomes have responded to these empirical problems in a variety of ways. Some simply ignore the problems, and as a result, provide only descriptive evidence about the relationship between alcohol use and labor market outcomes.3 Other researchers have addressed the statistical problems caused by the endogeneity of alcohol consumption by using instrumental variables (Kenkel and Ribar, 1994, Mullahy and Sindelar, 1996, Heien, 1996 and Hamilton and Hamilton, 1997). The efficacy of the instrumental variables (IV) procedure depends critically on the quality of the instruments, which can be evaluated in several ways. Of first order importance is the validity of the exclusion restrictions. In this case, alcohol taxes or prices are considered to be ideal instruments for alcohol use and the validity of these instruments is generally accepted.4 Indeed, all of the researchers using IV have included either prices or taxes among the variables used as instruments. However, the use of alcohol taxes or prices as instruments places other demands on the data that have not been explicitly noted in these studies. Specifically, because the demand for alcohol—particularly among heavy drinkers who are expected to have the most problems—is relatively inelastic, a large number of observations are necessary to obtain credible IV estimates. Variation in alcohol prices or taxes may cause only slight differences in alcohol consumption that will result in small differences in labor market outcomes. In order to detect reliably such small differences many observations are required. An alternative approach to the problem is to estimate the reduced form model that relates labor market outcomes to alcohol taxes. This approach has been used to examine the relationship among a variety of alcohol control policies (e.g. taxes and minimum drinking age laws) and other adverse consequences associated with alcohol consumption such as cirrhosis rates (Cook, 1981 and Cook and Tauchen, 1982), low educational attainment (Cook and Moore, 1993 and Dee and Evans, 1997), traffic fatalities (Saffer and Grossman, 1987, Ruhm, 1996 and Dee, 1999) and violence (Markowitz and Grossman, 1998). The reduced form approach has several advantages. First, from a policy stance, the reduced form effect of alcohol taxes on labor market outcomes may be of more interest than the structural effect of alcohol consumption on labor market outcomes. Policymakers influence alcohol consumption, and the social consequences of such use, indirectly through changes in alcohol control policies such as alcohol taxes. Ultimately, it is the effect of these policies on the social consequences of alcohol use that are relevant to government officials. The public concern is whether or not adverse labor market outcomes associated with alcohol consumption can be improved by government policies limiting the consumption of alcohol (Cook, 1994 and Peltzman, 1994). The reduced form estimate provides an answer to this question with regard to alcohol taxes, which is perhaps the most accessible policy instrument. Second, the reduced form estimate provides information about the structural relationship between alcohol use and labor market outcomes. Indeed, the reduced form estimate of the effect of alcohol taxes on labor market outcomes equals the structural effect of alcohol consumption on labor market outcomes times the effect of alcohol taxes on alcohol consumption.5 Since we know from prior studies that the reduced form estimate of the effect of alcohol taxes on alcohol consumption is negative, we can obtain the sign of the structural effect of alcohol consumption on labor market outcomes from the reduced form estimate of the effect of alcohol taxes on labor market outcomes. In this paper, we obtain reduced form estimates of the effect of beer, wine, and liquor taxes on wages, employment, and hours of work for a nationally representative sample of adult males and females drawn from the outgoing rotation files of the Current Population Survey.

Researchers have spent considerable efforts trying to determine whether or not alcohol consumption causes adverse labor market outcomes. To date there is no definitive answer to this question because of the statistical issues underlying the study of this problem. Most research has attempted to measure directly the effect of alcohol consumption or abuse on labor market outcomes. The best of these studies acknowledge the endogeneity of alcohol consumption and address the problems caused by it using instrumental variables. In this paper, we have chosen an alternative, although related, approach. We chose to estimate the reduced form model that relates alcohol taxes to labor market outcomes. Reduced form estimates provide policy relevant information about the relationship between an important policy tool—alcohol taxes—and outcomes of particular social importance—namely employment and wages. Reduced form estimates also provide information about the structural estimates of the effect of heavy alcohol consumption on labor market outcomes. Reviewed uncritically, the results of the analysis suggest that alcohol taxes tend to be negatively related to employment and hours of work, and positively related to wages. However, ample evidence was presented to undermine such a conclusion. First, the pattern of results is unexpected since it was hypothesized that alcohol taxes would have similarly signed effects on labor supply and wages. Previous studies have shown that alcohol taxes are negatively related to alcohol consumption, which is hypothesized to be negatively related to labor supply and wages. Thus, alcohol taxes are expected to be positively related to both labor market outcomes. The absence of such a finding suggests that either or both sets of estimates may be misleading. Second, estimates of the effect of alcohol taxes on labor market outcomes were large and imprecise, and characterized by significant variation in sign and magnitude across samples and types of alcohol taxes. This suggests that there is a weak and indeterminate relationship between alcohol taxes and labor market outcomes. Thus, we believe that there is little systematic evidence suggesting a causal effect of alcohol taxes. One important caveat to these conclusions relates to the specification error that was apparent from the implausibly large “simulated” IV estimates of the effect of alcohol taxes on labor market outcomes. The bias caused by this problem may have obscured the true effects of alcohol taxes on labor market outcomes. Our conclusions about the effect of alcohol taxes also imply that there is no causal effect of alcohol consumption on labor supply and wages. This conclusion is inconsistent with findings from previous studies that examined directly the effect of alcohol consumption on labor supply and wages, and which in general, find adverse effects. However, as we have stressed throughout this paper, the most credible estimates of the effect of alcohol consumption were obtained using an instrumental variables procedure that is closely related to the reduced form used in this paper. The imprecision and instability of the estimates in this paper raise questions about the reliability of these previous studies’ estimates. The fundamental identification strategy used in these papers relies to a large extent on the relationship between alcohol taxes and labor market outcomes. Our estimates of this relationship clearly show that it is relatively weak and unstable. Therefore, it is unlikely that previous studies that use instrumental variables estimates have produced credible estimates of the effect of alcohol use on labor market outcomes. Moreover, these studies have used samples that were too small to obtain reliable estimates. Finally, the specification error that may have biased our estimates is also likely to have biased previous studies’ instrumental variables estimates.