Back from spring break which, even though I am on leave this semester, I used to take a break from blogging and travel to (i) Peru, to assess the feasibility of field experiments I am planning on conducting there and (ii) Ithaca, NY, to present my work on farmers markets and food-borne illness at the Dyson School of Applied Economics and Management in the future Cornell College of Business.
For today’s installment of ‘Metrics Monday, suppose you have data that consists of repeated cross sections. To take an example from my own work, suppose you have 10 years worth of a nationally representative household survey, but the data are not longitudinal. That is, for each year, whoever was in charge of collecting the data collected them on a brand new sample of households.
Obviously, because the data are not longitudinal, the usual panel data tricks (e.g., household fixed effects) are not available. So what can you do if you want to get closer to credible identification? Continue reading