Fixed Effects Infatuation
The fashionable thing to do in applied econometrics, going on 15 years or so, is to find a gigantic panel data set, come up with a cute question about whether some variable x causes another variable y , and test this hypothesis by running a regression of y on x plus a huge number of fixed effects to control for "unobserved heterogeneity" or deal with "omitted variable bias." I've done a fair amount of work like this myself. The standard model is: y_i,t = x_i,t + a_i + b_t + u_i,t where a_i are fixed effects that span the cross section, b_t are fixed effects that span the time series, and u_i,t is the model error, which we hope is not associated with the causal variable x_i,t, once a_i If you're really clever, you can find geographic or other kinds of groupings of individuals, like counties, and include group-by-year fixed effects: y_i,t = x_i,t + a_i + b_g,t + u_i,t The generalizable point of my lengthy post the other day on storage and