Supersize Me?

This is not required, but if you are interested in the brand new article whose estimates indicate that fast food is not related to obesity, it is available in the library. The cite is:

Anderson, Michael L., and David A. Matsa. 2011. "Are Restaurants Really Supersizing America?" American Economic Journal: Applied Economics, 3(1): 152–88.

DOI:10.1257/app.3.1.152

Here are some of the relevant ideas. People who like to eat out tend to be fat:

… The frequency of eating out is positively associated with greater fat, sodium, and total energy intake, as well as with greater body fat.

But it isn’t clear if restaurants cause people to be fatter, or that fatter people like to go to restaurants more:

But simple 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 …

This sort of situation where causation could go either way is devlishly hard to sort out — which is why it’s really important at this level to start thinking about how you might do that. Too much of our policy analysis is done by people whose thinking stops before learning to figure that out.

Broadly, these are called identification problems: you’re trying to identify the direction of causality when it isn’t readily apparent. The standard way in economics to do identification is to find a variable to include in your model that is 1) correlated with the data you are trying to explain, but 2) not correlated with theories who’s causality you are trying to sort out. Here’s what the authors do:

In rural areas, Interstate Highways provide a variation in the supply of restaurants that is arguably 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. Using original survey data based on a smaller sample, we show that differences in travel costs generate large differences in restaurant consumption.

Basically, people in Beryl shouldn’t be as fat as people in Cedar City because it’s more expensive in time and money to eat out. This is why people from Cedar City don’t eat at Red Lobster and Olive Garden as much as people from St. George.

The estimates suggest that restaurants—both fast food and full service—have little
effect on adult obesity. The distributions of BMI in highway and nonhighway areas
are virtually identical, and point estimates of the causal effect of restaurants on the prevalence of obesity are close to zero and precise enough to rule out any meaningful effects.

…

… The existence of restaurants increases BMI by only 0.2 BMI points for the typical obese consumer.