Charles Courtemanche

Supersizing Supercenters? The Impact of Wal-Mart Supercenters on Body Mass Index and Obesity

Research attributes much of the rise in obesity to technological progress reducing the cost of food consumption. We examine this hypothesis in the context of Walmart Supercenters, whose advancements in retail logistics have translated to substantial reductions in food prices. Using data from the Behavioral Risk Factor Surveillance System matched with Walmart Supercenter entry dates and locations, we examine the effects of Supercenters on body mass index (BMI) and obesity. We account for the endogeneity of Walmart Supercenter locations with an instrumental variables approach that exploits the unique geographical pattern of Supercenter expansion around Walmart’s headquarters in Bentonville, Arkansas. An additional Supercenter per 100,000 residents increases average BMI by 0.25 units and the obesity rate by 2.4 percentage points. These results imply that the proliferation of Walmart Supercenters explains 11% of the rise in obesity since the late 1980s, but the resulting increase in medical expenditures offsets only a small portion of consumers’ savings from shopping at Supercenters.

Rising cigarette prices and rising obesity: Coincidence or unintended consequence?

Economists have begun to debate if the rise in cigarette prices in the U.S. in recent decades has contributed to the nations rise in obesity, reaching conclusions that are surprisingly sensitive to specification. I show that allowing for the effect to occur gradually over several years leads to the conclusion that a rise in cigarette prices is actually associated with a long-run reduction in body mass index and obesity. This result is robust to the different methodologies used in the literature. I also provide evidence that indirect effects on exercise and food consumption may explain the counterintuitive result.

A Silver Lining? The Connection Between Gasoline Prices And Obesity

I find evidence of a negative association between gasoline prices and body weight using a fixed effects model with several robustness checks. I also show that increases in gas prices are associated with additional walking and a reduction in the frequency with which people eat at restaurants, explaining their effect on weight. My estimates imply that 8% of the rise in obesity between 1979 and 2004 can be attributed to the concurrent drop in real gas prices, and that a permanent

Does Wal-Mart reduce social capital?

1 increase in gasoline prices would reduce overweight and obesity in the United States by 7% and 10%.

Adjusting body mass for measurement error with invalid validation data.

Social capital has attracted increasing attention in recent years. We use county-level and individual survey data to study how Wal-Mart affects social capital. Estimates using several proxies for social capital—such as club membership, religious activity, time with friends, and other measures—do not support the thesis that “Wal-Mart destroys communities” by reducing social capital. We measure exposure to Wal-Mart two ways: Wal-Marts per 10,000 residents and Wal-Marts per 10,000 residents aggregated over the years since 1979 to capture a more cumulative “Wal-Mart Effect.” We find that the coefficients on Wal-Mart’s presence are statistically insignificant in most specifications.

Does competition from ambulatory surgical centers affect hospital surgical output

We propose a new method for using validation data to correct self-reported weight and height in surveys that do not measure respondents. The standard correction in prior research regresses actual measures on reported values using an external validation dataset, and then uses the estimated coefficients to predict actual measures in the primary dataset. This approach requires the strong assumption that the expectations of measured weight and height conditional on the reported values are the same in both datasets. In contrast, we use percentile ranks rather than levels of reported weight and height. Our approach requires the weaker assumption that the conditional expectations of actual measures are increasing in reported values in both samples. This makes our correction more robust to differences in measurement error across surveys as long as both surveys represent the same population. We examine three nationally representative datasets and find that misreporting appears to be sensitive to differences in survey context. When we compare predicted BMI distributions using the two validation approaches, we find that the standard correction is affected by differences in misreporting while our correction is not. Finally, we present several examples that demonstrate the potential importance of our correction for future econometric analyses and estimates of obesity rates.

Can Changing Economic Factors Explain the Rise in Obesity

This paper estimates the effect of ambulatory surgical centers (ASCs) on hospital surgical volume using hospital and year fixed effects models with several robustness checks. We show that ASC entry only appears to influence a hospitals outpatient surgical volume if the facilities are within a few miles of each other. Even then, the average reduction in hospital volume is only 2-4%, which is not nearly large enough to offset the new procedures performed by an entering ASC. The effect is, however, stronger for large ASCs and the first ASCs to enter a market. Additionally, we find no evidence that entering ASCs reduce a hospitals inpatient surgical volume.

Does procedure profitability impact whether an outpatient surgery is performed at an ambulatory surgery center or hospital

A growing literature examines the effects of economic variables on obesity, typically focusing on only one or a few factors at a time. We build a more comprehensive economic model of body weight, combining the 1990–2010 Behavioral Risk Factor Surveillance System with 27 state-level variables related to general economic conditions, labor supply, and the monetary or time costs of calorie intake, physical activity, and cigarette smoking. Controlling for demographic characteristics and state and year fixed effects, changes in these economic variables collectively explain 37% of the rise in body mass index (BMI), 43% of the rise in obesity, and 59% of the rise in Class II/III obesity. Quantile regressions also point to large effects among the heaviest individuals, with half the rise in the 90th percentile of BMI explained by economic factors. Variables related to calorie intake—particularly restaurant and supercenter/warehouse club densities—are the primary drivers of the results.

Who Gained Insurance Coverage in 2014, the First Year of Full ACA Implementation?

Ambulatory surgery centers (ASCs) are small (typically physician owned) healthcare facilities that specialize in performing outpatient surgeries and therefore compete against hospitals for patients. Physicians who own ASCs could treat their most profitable patients at their ASCs and less profitable patients at hospitals. This paper asks if the profitability of an outpatient surgery impacts where a physician performs the surgery. Using a sample of Medicare patients from the National Survey of Ambulatory Surgery, we find that higher profit surgeries do have a higher probability of being performed at an ASC compared to a hospital. After controlling for surgery type, a 10% increase in a surgerys profitability is associated with a 1.2 to 1.4 percentage point increase in the probability the surgery is performed at an ASC.

Modeling Area-Level Health Rankings

Abstract The most significant pieces of the Affordable Care Act (exchanges, subsidies, Medicaid expansion, and individual mandate), implemented in 2014, were associated with sizable gains in coverage nationally that were divided equally between gains in Medicaid and private coverage. These national trends mask heterogeneity in gains by state Medicaid expansion status, age, income level, and source of coverage.