The effects of soft drink taxes on child and adolescent consumption and weight outcomes☆
Introduction
While soft drink taxes have been used for decades as a way to raise revenues, lately there have been an increasing number of proposals to considerably increase these taxes in order to combat the rapidly growing obesity epidemic in the United States. These proposals have often framed soda taxation as a “sin tax” and made comparisons between soft drink taxation and cigarette taxation, which has both lowered tobacco consumption and raised considerable revenues. The price elasticity for soda is estimated to range between −0.8 and −1.0 (Andreyeva et al., 2010), which indicates that further taxation could lead to substantial consumption reduction. Additionally, soft drink revenues in the United States are approximately $70.1 billion per year, suggesting a relatively large tax revenue potential, even accounting for the drop in consumption from a soda tax (Sicher, 2007); in comparison tobacco revenues are approximately $93.1 billion per year (Tobacco-NAFTA Industry Guide, 2009). Thus soft drink taxation could improve health by lowering consumption, as well as generate substantial revenues to relax government budget constraints and could potentially be used for further obesity prevention or reduction. However, the potential behavioral responses to increasing soda taxes have not been fully examined. There is relatively weak information on the tax elasticity on consumption of soft drink taxes, and, importantly, the substitution patterns between soft drinks and other (potentially high calorie) beverages has not been adequately explored in this context. Thus soda taxes could have unintended consequences and may be an ineffective “obesity tax”.
There are multiple examples documenting how behavioral responses to public policies can counteract the intent of the policies or lead to unintended consequences. One of the best known examples in the economics literature is an evaluation of a set of automobile safety regulations in the late 1960s, where Peltzman (1975) shows that drivers responded to increased safety regulations by driving faster, which completely offset any reductions in highway fatalities. More recently, Adams and Cotti (2008) show that smoking bans in bars have lead to increases in fatal accidents due to an increase in the distance driven to bars that allow smoking. Adda and Cornaglia (2010) find that smoking bans increase the exposure of non-smokers to tobacco smoke as a result of the relocation of smokers away from bars and restaurants. There is also some evidence documenting an unintended rise in obesity and weight due to smoking bans (Fletcher, 2009) and higher cigarettes taxes, although there is mixed evidence on taxes (Chou et al., 2004, Chou et al., 2006, Gruber and Frakes, 2006, Baum, 2009). Courtemanche (2009) seeks to harmonize these disparate findings and has shown a counterintuitive reduction in obesity following cigarette taxation, where the proposed behavioral mechanisms are through changes in exercise and food consumption. Additionally, Evans and Farrelly (1998) find that smokers respond to higher cigarette taxes by smoking cigarettes with higher tar and nicotine content. Similarly, Adda and Cornaglia (2006) find that smokers adjust their behavior to smoke more intensely in response to higher taxes. Finally, recent theoretical and simulation research by Schroeter et al. (2008) shows there are plausible scenarios where taxes on certain types of food (e.g. food away from home) could lead to increases in body weight simply due to substitution among types of food. Likewise, soda taxes could cause substitution to other, high-calorie beverages and increase or have no effect on net caloric intake. In the extreme, these potential substitution patterns could result in a case where individuals consume no soda but offset soda consumption with other high-calorie beverages, such as fruit juice, juice drinks, or whole milk. The impact of these behavioral responses would be no tax revenues as well as no weight reduction and the policy would accomplish neither of its proposed goals.
In this paper we combine newly collected soft drink tax data between 1989 and 2006 with the restricted-access version of the nationally representative National Health Examination and Nutrition Survey (NHANES) in order to examine the effects of soft drink taxes on child and adolescent soft drink consumption, substitution patterns, and weight outcomes. We use standard empirical specifications from the cigarette taxation literature (Chaloupka and Warner, 2000), including year and state fixed effects, and conduct a series of robustness checks to increase confidence in the results. Overall, we find evidence of moderate reductions in soft drink consumption from current soda tax rates. However, we also show that reductions in calories from soda are completely offset by increases in calories from other beverages. Thus, we find that, as currently practiced, soda taxes do not reduce weight in children and adolescents and is, therefore, likely an ineffective “obesity tax”. These results suggest that public health policymakers should consider behavioral responses when crafting policies to reduce obesity.
Section snippets
Background literature
The rise in childhood and adolescent obesity in the US and other developed countries has been the source of considerable debate and public policy effort. The effects of obesity on chronic health conditions have been compared to the effects of aging twenty years in adults, and the health costs associated with obesity are even greater than two other behaviors widely recognized to cause significant harm: cigarette smoking and alcohol consumption (Sturm, 2002). Since childhood and adolescent
Conceptual and empirical framework
We conceptualize the demand for soft drinks by child i in state s as a function of individual and family socio-demographic characteristics (X), household income (I), and the prices of soda (Ps) and other beverages (Po):where soft drink prices are a function of soft drink taxes imposed by the state (τs). Our focus in this paper is estimating the effects on soda consumption and weight from increasing soda tax rates.6
Soft drink taxes
States currently tax soft drinks through excise taxes, sales taxes, and special exceptions to food exemptions from sales taxes. For this paper, we define the soft drink tax as the tax on soft drinks net of taxes on other food items.
To determine the soft drink tax rate, we combine sales tax information with details on other soft drink taxes. The “Book of the States” (The Council of State Governments, 1990–2007) is used to identify state sales tax information. Published annually, it lists tax
Results
Table 3 presents the baseline associations between soft drink tax rates and soft drink consumption. The soft drink tax coefficients represent the effects of a one percentage point increase in the tax rate on the probability of consuming a soft drink, the total grams of soft drinks consumed, and the total calories from soft drinks consumed. All regression models throughout the paper include year, quarter, and state fixed effects (unreported), and standard errors are clustered at the state level.
Conclusion
In this paper, we present the first evidence of whether soft drink taxes are linked with consumption decisions and weight outcomes of children and adolescents. We use a national sample that contains weight outcomes and consumption patterns of children and adolescents between 1989 and 2006. We then merge newly collected state-level soft drink tax data for this time period with the survey data in order to use a quasi-natural experimental design to estimate the short term effects of soft drink
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This study was supported, in part, by the Robert Wood Johnson Foundation and the Emory Global Health Institute. We thank Alexandra Ehrlich and Stephanie Robinson for support with the restricted NHANES data and Jeremy Green, Alejandra Carrillo Roa, and John Zimmerman for excellent research assistance. We also thank Meena Fernandes, Lori Kowaleski-Jones, seminar participants at Bowdoin College, Mt. Holyoke College, Rudd Center for Food Policy and Obesity at Yale University, and Washington and Lee University, and participants at the 2009 International Health Economics Association World Congress, 2009 Robert Wood Johnson Foundation Healthy Eating Conference, 2009 Association for Policy Analysis and Management fall conference, 2010 Population Association of America Annual Meeting, and 2010 American Society of Health Economists conference for helpful comments. The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the Research Data Center, the National Center for Health Statistics, or the Centers for Disease Control and Prevention.