4. Results
4.1 Weight-Related Health Investments
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we modify equation (3) by studying as our outcome variable the number of McDonald’s restaurants per state (total and separately by franchise-owned and company-owned). For both the QCEW and UFOC analyses we continue to cluster standard errors at the state level, and we weight these regressions by annual state population counts.16
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obese. Notably, 3 percent of the sample satisfies the definition of Class-3 obesity (i.e., BMI>40). In general we find few meaningful differences in average outcomes and characteristics for people in states with CCAs compared to those in states without CCAs.
In Table 3 we present estimates of the effects of CCAs that take explicit advantage of the plausibly exogenous variation in the timing of policy adoption across states on three measures of weight-related investments in health: the likelihood that an individual reports trying to lose weight (top panel), the number of servings of fruits and vegetables per day the individual reports consuming (middle panel), and the likelihood the person reported vigorous exercise in the past month (bottom panel).
Each estimate in the table is the coefficient on the CCA variable from a separate difference in differences model with linear state trends. The first column reports estimates for the full sample, and the subsequent columns report estimates for models that restrict attention to people in each of the various (mutually exclusive) weight categories. We also report in the row just above each panel of estimates the average for each outcome variable across the various weight categories (and for the full sample for column 1). Notably, stated weight loss attempts are increasing in objective weight category, while fruit and vegetable consumption and exercise are both decreasing in objective weight category conditional on being at least normal weight. These patterns lend face validity that the data are plausibly measuring meaningful underlying constructs.
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The results in the top panel of Table 3 provide strong evidence that Commonsense Consumption Acts increased stated weight loss attempts among heavy individuals. For example, the estimate in the top panel of column 7 of Table 3 indicates that CCAs were associated with a 3.3 percentage point increase in the likelihood an individual with Class-3 obesity reports trying to lose weight. Relative to the average rate for this group, this represents about a 4.3 percent effect. For obese individuals in column 5 we find a 4 percentage point increase in weight loss intentions, or a 6.2 percent effect relative to the mean, and this estimate is statistically significant.
Notably, we find that most of the estimated effects of CCAs on weight loss attempts for individuals in the lighter weight categories are smaller in magnitude and statistically insignificant.
The middle and bottom panels of Table 3 further investigate investments in weight-related health by examining healthy food consumption and exercise, respectively, from the preferred specification with state and year fixed effects and linear state trends. For fruit and vegetable consumption in the middle panel of Table 3, we find strong evidence that CCAs were associated with statistically significant increases in healthy food consumption, and these effects are particularly large in magnitude and statistically significant for the heaviest individuals. Among individuals with Class-3 obesity in column 7, we estimate that CCAs increased consumption of fruits and vegetables by a statistically significant 0.25 servings per day, or about 7.3 percent relative to the sample average for that group. We estimate smaller (in both
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absolute and relative terms) but statistically significant increases for overweight individuals in column 4 and for the full sample in column 1, while the estimates for underweight and normal weight individuals are both small and statistically insignificant.18 Turning to exercise participation in the bottom panel, we find no effects of CCAs: none of the estimates in the bottom panel of Table 3 are economically or statistically significant, indicating that CCAs did not meaningfully affect exercise activity for any group, let alone those most likely to have been treated by CCAs (i.e., heavy individuals).19
In Table 4 we report results for the effects of CCAs on weight for the full sample period 2000-2012. All estimates are from the preferred specification with state and year fixed effects and linear state trends. Notably, we find no meaningful effects of CCAs on average BMI, and these null findings are precise: the estimate in column 1 can rule out reductions in BMI larger than about 0.05, or about 0.2 percent relative
18 Sample sizes differ across the panels of Table 3 because the weight intentions questions were only asked by a subset of states and were not asked in 2004 or after 2005. There is an emerging understanding of appropriate inference in settings with a small number of clusters; when we estimated p-values using the Wild-cluster bootstrap method (Cameron et al. 2008), the estimate in the top panel of Table 3 is no longer statistically significant at conventional levels. Note that the weight intention outcome is the only one for which we have a small number of clusters due to the BRFSS sampling structure.
19 Results for the number of minutes of exercise similarly did not indicate any meaningful effects of CCAs on exercise. In results not reported but available upon request we performed many robustness exercises for the results in Table 3. Restricting the healthy food consumption analysis to the same years the weight loss attempts questions were asked (2000-2003 and 2005) did not change the main result on healthy food consumption. Those same results were also robust to excluding 2011 and 2012 to account for a change in the BRFSS sampling structure that accounts for cellphones. Results were also robust to the choice of included states; for example, dropping each CCA adopter one at a time did not change the results. Results were also similar when we excluded the linear state trends, as well as when we allowed for quadratic state trends in addition to linear trends. Adding a control for whether the state would adopt a CCA in the next year did not materially alter the significant coefficients in the top and middle panels of Table 3, and the coefficient on future CCA adoption itself was not statistically significant.
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to the average BMI in the population (27.9).20 We similarly find very small CCA estimates on the likelihood of being at or above any of the standard weight thresholds.
Even when measured against the very low rate of Class-3 obesity in the population (3.81 percent), the estimate in column 7 of Table 4 can rule out reductions in the likelihood of Class-3 obesity larger than about 2.6 percent.21