Theory Versus Data? You Shouldn't Have to Choose

The battle over Economics 101 continues. A while ago, I suggested that introductory courses should feature a lot more empirical data analysis. Currently, they contain essentially none. Given the empirical revolution that is sweeping academic economics and challenging our most basic ideas about theory and policy, that needs to change.

Defenders of the status quo often assume that “theory versus data” is an either-or proposition. In fact, the opposite is true. Without theory, data is very hard to interpret; you may find that immigration has little impact on native-born wages, but without theory, you don’t know why, or even where to look for answers. Similarly, without data, theories can’t be verified, falsified or even effectively modified; only reality can help us choose from a wide variety of competing theories, or tell us that we need to go looking for new ones. We need both. By not teaching our introductory students even the most basic techniques for testing theories, we are asking them to take conventional wisdom -- often, incorrect conventional wisdom -- on faith. That can’t be good.