Chris Blattman

Are restaurants supersizing America?

super-size-mesimple correlations between restaurant visits and overeating may conflate the impact of changes in supply and demand. People choose where and how much to eat, leaving restaurant consumption correlated with other dietary practices associated with weight gain…

A key question is whether the growth in eating out is contributing to the obesity epidemic, or whether these changes merely reflect consumer preferences.

Although eating McDonald’s food three times a day for 30 days caused Morgan Spurlock to gain 24.5 pounds in the documentary film Super Size Me, this “experiment” is unsuited for measuring the causal effect of restaurant consumption on body weight because Mr. Spurlock intentionally overate and would have experienced similar weight gain following a comparable diet at home.

The interesting causal parameter is how much more an obese person consumes in total because he or she ate at a restaurant.

That is Michael Anderson and David Matsa casting doubt on St. Spurlock. They are applied economists, and so enter the natural experiment:

In rural areas, Interstate Highways provide a shock to the supply of restaurants that is uncorrelated with consumer demand. To serve the large market of highway travelers passing through, a disproportionate number of restaurants locate immediately adjacent to these highways.

For residents of these communities, we find that the highway boosts the supply of restaurants (and reduces the travel cost associated with visiting a restaurant) in a manner that is plausibly uncorrelated with demand or general health practices.

Their result: restaurants – both fast food and full service – show little effect on obesity. Paper is here. Sorry I don’t have an ungated link.

2 Responses

  1. Here’s a paper by Chen and others that uses a similar methodology (distance = price), but in the context of poor urban areas:

    The estimate parameters using ARAR and then use their estimates to run a couple simulations: the effect of 1. randomly removing a fast food restaurant from an overserved area; or 2. adding a chain grocery store to an underserved area.

    Removing a fast food restaurant: -.22 point change in BMI (-1 lbs for the average woman) for those near the deleted restaurant, -.04 point change average across entire population

    Adding a grocery store: -.58 point change in BMI (-3 lbs for the average woman) for those near the grocery store; -.04 point change average across entire population

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