The Work of Raj Chetty - by Nicholas Decker
Raj Chetty is best known for extremely labor-intensive studies, with dozens of research assistants assembling and cleaning datasets to answer enormous questions. This approach can answer questions that nobody else can really answer, because no one else has the data! Who else has the tax records of millions of people, linked to their home address over decades? Archimedes said that with a long enough lever he could move the world; with a detailed enough administrative dataset, one can answer anything. Chetty’s work is much deeper than mere regressions, though. Reading his work, what I was most impressed by was its depth. It is often clever, ingenious, and gives insights far beyond simply answering a specific question.
A theme of his early work is trying to find sufficient statistics. Given a model of the economy with a few assumptions, what is the minimum of facts which we have to find in order to infer the welfare effects of some change? Sufficient statistics are a bridge between what are called structural models, and reduced form strategies. Reduced form strategies are likely the ones you have seen the most of, as it is a term encompassing all of the standard causal methods toolkit which economists use all the time. It is kind of going from the top down, being agnostic about mechanisms, and simply sees what happened when certain things changed. Structural models work from the bottom up, and try to measure deep, underlying parameters about people’s nature and preferences. With those “primitives” in hand, you can plug them into a model and try out counterfactual policies.
That all was a bit abstract, so to make it concrete, let’s take Chetty’s 2008 paper on unemployment insurance and unemployment. Increasing payouts for unemployment do indeed make unemployment spells last longer. However, there are two reasons for this to be so. On the one hand, you have the obvious channel where paying people to be unemployed leads them to be unemployed. On the other hand, let’s imagine that matching with the right job takes time. If households are liquidity constrained, then shortening their unemployment spell is bad. In order to tell whether increasing unemployment insurance is good or bad, we need to tell which effect dominates the other, and by how much.
