Partial Identification of Individual-Level Parameters Using Aggregate Data in a Nonparametric Model

Abstract

I develop a methodology to partially identify linear combinations of conditional mean outcomes when the researcher only has access to aggregate data. Unlike the existing literature, I only allow for marginal, not joint, distributions of covariates in my model of aggregate data. Identified sets are very wide in an empirical illustration, suggesting that in order to obtain useful results when only using aggregate data, researchers may have no option other than to impose strong assumptions.

Tasks

Reproductions