مفاهیم مالیات بر نوشیدنی دارای قند شیرین (SSB) زمانی که جایگزینی برای اقلام غیر آشامیدنی در نظر گرفته شده

Using the 2006 Homescan panel, we estimate the changes in energy, fat and sodium purchases resulting from a tax that increases the price of sugar-sweetened beverages (SSBs) by 20% and the effect of such a tax on body weight. In addition to substitutions that may arise with other beverages, we account for substitutions between SSBs and 12 major food categories. Our main findings are that the tax would result in a decrease in store-bought energy of 24.3 kcal per day per person, which would translate into an average weight loss of 1.6 pounds during the first year and a cumulated weight loss of 2.9 pounds in the long run. We do not find evidence of substitution to sugary foods and show that complementary foods could contribute to decreasing energy purchases. Despite their significantly lower price elasticity, the tax has a similar effect on calories for the largest purchasers of SSBs.

Currently, roughly 1 in 3 U.S. adults are obese and forecasts predict that obesity rates could reach 42% by 2030 (Finkelstein et al., 2012). As a result, public health officials are increasingly looking to identify strategies to contain rising rates of obesity. One strategy focuses on reducing consumption of sugar-sweetened beverages (Brownell et al., 2009 and Paterson, 2008); SSBs hereafter. Likely due to their low and declining prices relative to healthier food and beverage items, SSB consumption has increased considerably over the past several decades (Brownell et al., 2009) such that today they account for roughly 7% of all calories consumed (Finkelstein and Zuckerman, 2008). SSB consumption is associated with increased caloric intake, weight gain, and obesity (Finkelstein and Zuckerman, 2008, Ludwig et al., 2001, Malik et al., 2006 and Vartanian et al., 2007) and there is evidence that a reduction in SSB consumption could result in weight loss (Chen et al., 2009). To reduce SSB consumption, a commentary in the British Medical Journal and another in the New England Journal of Medicine recommended a tax of 1 cent per ounce on SSBs (Brownell et al., 2009 and Kamerow, 2010). Assuming the tax is passed through to consumers, it would increase the cost of a 20-oz soft drink by roughly 20% and, based on estimates of the price elasticity of demand, would result in an 8–10% reduction in SSB consumption. The commentary posits that in New York State alone, where a similar tax was proposed and then defeated (New York Post, 2009), it would have prevented 145,000 cases of adult obesity. Whether these taxes would positively influence obesity rates as the commentary suggests remains open to debate. Some, including prominent scholars (Becker, 2009 and Posner, 2009) challenge the very ability of the tax to significantly decrease caloric intake as those consumers who like sugar—or even crave it—would have no difficulty finding substitutes for SSBs. Their beliefs are backed up by recent animal and human studies suggesting an addictive component to sweet foods (e.g., Avena et al., 2012) and (see Gearhardt et al., 2009 for a review). The implications of an SSB tax have been partially addressed by several recent studies that estimated the effect of an SSB tax on the consumption of a wider range of beverages (Dharmasena and Capps, 2011, Finkelstein et al., 2010, Lin et al., 2011, Smith et al., 2010 and Zhen et al., 2011). Yet, none of the above studies allowed for substitution from SSBs to non-beverage products that may result from the tax.1 This is a significant limitation as these studies do not fully address the concern that individual taste or sugar cravings could result in substituting SSBs with sugary, highly caloric foods. Because SSBs are among the most energy dense beverages, any switching away from SSBs to other beverages is almost guaranteed to reduce total beverage calories. The implications of the tax are less predictable when switching to non-beverage items is considered. This results because some food items, such as candy or cookies, are higher in calories per dollar than SSBs. As a result, if someone switches from SSBs to these foods as a result of a tax, net calories could actually increase.Schroeter et al. (2008)’s theoretical model yields similarly counterintuitive results when predicting the effects of a tax on away from home foods. These results stress that to assess the net effect of an SSB (or any food) tax, one needs to compute the change in calories resulting from the taxed product, as well as increases or decreases resulting from complementary or substitute products, and in this case, not only from other beverages. This paper aims to fill this gap by revisiting the extent to which targeted SSB taxes would reduce caloric purchases and weight when considering substitution to other foods and beverages. This includes, in addition to the beverages taken into account by Finkelstein et al. (2010), candies and cookies, which are both higher in calories per dollar spent than SSBs, and several other commonly purchased foods that are potential substitutes or complements to SSBs. Using these data, we estimate the changes not only in calories, but also in fat and sodium purchases resulting from a tax that increases SSB prices by 20%. These extensions are important as a healthy diet requires limiting not only caloric, but also fat and sodium intake (U.S. Department of Agriculture and U.S. Department of Health and Human Services, 2010). Because SSBs are low in both, it is possible that an SSB tax could increase consumption of both fat and sodium, thus reducing any health gains that may be achieved through reduced caloric intake. Unlike prior studies, we estimate the effects of SSB taxes using an instrumental variables technique which controls for potential price endogeneity. This is an important advancement as the prices used in prior studies may not be truly exogenous to the purchaser (i.e., driven by changes in both supply and demand), may be correlated with unobservable factors that influence demand, or may suffer from significant measurement error. An instrumental variables approach addresses these concerns. Finally, we estimate quantile regressions to explore the extent to which SSB taxes differentially affect those who are the largest purchasers of calories from both SSBs and all included food categories. The former explores whether the taxes work better among the highest SSB consumers, presumably the intended target, whereas the latter explores the extent to which the tax may differentially affects those who purchase the most calories (from stores) and therefore may be more likely to be obese. Section 2 presents the data sources, variable definitions and descriptive statistics. Section 3 covers our econometric models, identification strategy, and energy-to-weight loss computation methods. Section 4 presents our estimates for both aggregate and detailed changes in store-bought nutrients caused by the SSB tax along with the weight loss predictions. Section 5 concludes.

In this paper, we estimate the changes in energy, fat and sodium purchases resulting from a tax that increases SSB prices by 20% as well as the effect of such a tax on body weight. Although other papers have explored the direct and indirect effects of such a tax on beverages, the contribution of this paper is to account for potential substitutions/complementarity between SSBs and 12 food categories, in addition to other beverages. We specifically included cookies and candies as these categories are greater in calories per dollar and hypothesized to be substitutes for SSBs due to their high sugar content. As such, we allow for a potential increase in calories that may result from an SSB tax. Our estimates are generated using a 2 stage residual inclusion IV method to correct for the potential endogeneity of the price variables. We also run quantile regressions to measure the impact of the SSB tax on high SSB or overall calorie purchasers. Our main findings are that a 20% price increase on SSBs would result in a decrease in energy purchased in stores of 24.3 kcal per day per household member across the 19 included food and beverage categories. This equates to a roughly 4.7% reduction. Following the recent methodology proposed by Lin et al. (2011), this would translate into an average weight loss of 1.6 pounds during the first year of implementation and a cumulated weight loss of 2.9 pounds over 10 years. The IV results reveal that substitution to other beverages was limited and only involved fruit juices. Furthermore, we did not find any evidence of substitution to sugary foods and even found a decrease in calories from ice cream and salty snacks. These decreases could amount to almost half of the total decrease in energy purchased resulting from the SSB tax. In addition, due to the high fat content of these two complementary foods, the SSB tax also leads to a small reduction in the consumption thereof. These estimates suggest the tax would have no effect on total sodium purchased. Finally, we found the tax would reduce the energy purchased by both heavy SSB and total calorie purchasers despite their lower price-elasticities. Because our analysis includes food categories, the calorie and weight change estimates are not directly comparable to those from prior studies. However, the own calorie elasticity estimates for SSBs are comparable. Our exogenous model yields a direct elasticity of −1.32 for the energy purchased through SSBs. This estimates falls into the middle of the range of prior studies: Finkelstein et al. (2010), −0.87, Lin et al. (2011), −0.95 and −1.29 for lower and higher income respectively, Zhen et al. (2011), −1.06 and −1.54, and Dharmasena and Capps (2011), −2.26. However, when using the IV model, our price-elasticity drops to −0.90 which is more in line with earlier studies (see Andreyeva et al., 2010 for a review). Note that, with the exception of Finkelstein et al. (2010), the above studies also found very little substitution to other beverages. The inclusion of food categories and other covariates, use of a different functional form, or the application of monthly (as opposed to quarterly) prices explain the inconsistency with the study by Finkelstein et al. (2010). As for data limitations in this study, it should be mentioned that the data are self-reported, which may lead to underreporting. Second, the data are limited to store-bought food and beverage purchases for 19 food categories, amounting to 518 kcal per day per individual on average. Extending the model to include non-store purchases and additional food categories, including random weight foods (i.e., those without barcodes) that are difficult to capture using the current methodology, would generate more robust conclusions of the net effect of a 20% price increase on SSBs and should be an area of future research. Because store-bought purchases represent a diminishing fraction of total and SSB calories purchased, the effect of a 20% price increase on SSBs is likely to be larger than the estimates presented in the analysis. For example, the Nielsen data reveal that 64.9 kcal per day of SSBs are purchased from stores whereas Popkin (2010) reports overall daily SSB purchases, that is including food-away-from-home, in excess of twice this amount. An important question not addressed in this paper concerns the size of a tax that would generate a 20% price increase on SSBs. Under perfect competition, taxes undershift in the sense that a 20% tax would result in a smaller price increase, unless demand is perfectly inelastic, which the above estimates reveal is not the case for SSBs, or supply is perfectly elastic. In these instances, the tax is fully passed along to consumers (Musgrave, 1959). However, under imperfect competition, economic theory predicts that taxes can also increase prices by more than their nominal value---or overshift---which has been demonstrated for the monopoly (Cournot, 1960 and Stern, 1987) and various types of oligopoly (see for instance Anderson et al., 2001, Besley, 1989, Delipalla and Keen, 1992 and Seade, 1985). The above theoretical literature reveals that milder conditions are required for excise taxes to overshift compared with ad valorem taxes. Overshifting of SSBs taxes is a possibility given that the soft-drink and related retail industries are highly concentrated. However, to date, empirical evidence on the effect of select SSB taxes on retail prices is scarce. In the US, Besley and Rosen (1999) find that sales taxes on sodas that were implemented during the 1982–1990 period overshifted by as much as 29%. In Denmark, Bergman and Hansen (2012) find evidence of overshifting during the 1998 and 2001 excise tax hikes on soft drinks there. Finally, Bonnet and Réquillart (2012) apply a structural econometric model that takes into account the strategic price response to taxation of both manufacturers and retailers. Using French home-scan data they predict that an excise tax on soft drinks would overshift by 7% to 33% depending on the brand. On the other hand, an equivalent ad valorem tax would undershift by 10% to 40%. Empirical evidence on other sin taxes is consistent with the overshifting of excise taxes in concentrated markets. Excise taxes on alcohol (Kenkel, 2005 and Young and Bielinska-Kwapisz, 2002) and tobacco (Delipalla and O’Donnell, 2001, Hanson and Sullivan, 2009 and Harris, 1987) have been found to overshift. Also, studying the incidence of taxes on saturated fat, Griffith et al. (2010) find that excise taxes overshift while ad valorem taxes undershift. Most sin taxes are implemented as excise taxes, perhaps because they are more likely to raise retail prices, but also because they avoid substitutions from more to less expensive items. The extent of under- or overshifting of SSB taxes in the US market will likely only be known with certainty if the taxes are implemented and their effect on retail prices can be directly assessed. From a methodological perspective, unlike most other recent studies that account for substitutions with other beverages (Dharmasena and Capps, 2011, Lin et al., 2011, Smith et al., 2010 and Zhen et al., 2011), we do not perform our analysis in the setting of a utility-theoretic demand system. Consequently, this analysis does not account for the income effect resulting from an SSB tax. However, this effect is likely to be limited considering the low budget share of SSBs. On the other hand, our approach offers several advantages. The first is that our models directly explain the variables of interest. These are the quantities of nutrients purchased which we have matched in great detail at the product level. Another advantage of our approach is that by estimating each food and beverage category separately without imposing utility-theoretic restrictions such as homogeneity and symmetry, we avoid possible spillover of specification error in one equation to other equations. We exploit this extra flexibility by using a two-part model that allows the participation decision and quantity decision to be different processes. Note that the two-part specification straightforwardly deals with zero purchases which is a complex issue in the context of a demand system. Notwithstanding this, we are currently in the process of extending this research to a demand system specifically to test for differential effects by income strata (Zhen et al., 2011). In this context, a demand system would be more appropriate as it allows for income effects and welfare analysis. The principal finding of this research is that an increase of 20% in the price of SSBs would induce a cumulative per capita weight loss of 2.9 pounds, on average, after 10 years, ceteris paribus If the revenue raised from these taxes were used to further fund obesity prevention efforts, the weight losses could be even greater. However, any benefits of such a tax must be weighed against the potential costs. These taxes are almost certainly regressive as lower income households spend a larger share of their food budget on SSBs (Finkelstein et al., 2010). An excise tax would likely be more regressive than a sales tax of equal magnitude because lower income households tend to purchase lower priced beverages (same cite). As noted in the introduction, SSB taxes are increasingly being considered in efforts to raise revenue and/or to positively influence weight outcomes. As such, the implications of these taxes are of economic interest. This is despite the fact that many economists have called into question the very justification for such a tax. Although it may have beneficial effects on weight and health, it is difficult to justify an SSB tax using the classical Pigovian approach to taxation, as the traditional rationale for market failures appears not to apply (Bhattacharya and Sood, 2011). However, there still may be grounds for such a tax based on behavioral economic principals. There is overwhelming evidence showing that people's food consumption behavior can be influenced by very subtle cues, thus calling into question people's ability to make utility maximizing decisions when it comes to what and how much to consume. For example, consumers’ judgment of optimal portion size is influenced by the size of the container it comes in. Larger containers generate increased consumption by altering norms for what is perceived as an appropriate portion size (Wansink and van Ittersum, 2007). The average size of SSB containers has increased over the past few decades as suppliers increase sizes in efforts to take advantage of decreasing marginal costs (Marchiori et al., 2012). Although SSBs are not the only product whose container size has increased, SSBs and other highly sweetened products may be more appropriate targets for government intervention because, for genetic reasons, consumers are predisposed to have a visceral response to these foods and are thus more easily tempted to overconsume (Gilhooly et al., 2007). For these foods, the capacity for self-control is most limited and the market has no incentive to correct for potential overconsumption, and in fact, encourages it through aggressive marketing campaigns in efforts to increase profits. Advertisements for highly processed foods make up the second largest share of all advertising revenue (Story and French, 2004). In the behavioral economics literature, lack of self-control is seen as a form of time inconsistency and has been modeled using hyperbolic discounting (Laibson, 1994 and Laibson, 1997). Using such models, O’Donoghue and Rabin (2006) have shown that taxing sin goods can be welfare enhancing when individuals have heterogeneous tastes and where some of them have time-inconsistent preferences. The above discussion, combined with the high degree of regret for many consumers, as evidenced by the multi-billion dollar weight loss industry, suggests that government intervention to decrease consumption on SSBs and other foods with a large degree of added sugars and added fats may be justified on economic grounds, at least from a behavioral perspective. As shown in this analysis, a tax that increases prices by 20%, thus generating a 10 year cumulative per capita average weight loss of 2.9 pounds, would need to be weighed against the distortionary nature of the tax and other unexpected and potentially undesirable effects.