Abstract
Multidimensional heterogeneity and endogeneity are important features of a wide class of econometric models. We consider heterogenous coefficients models where the outcome is a linear combination of known functions of treatment and heterogenous coefficients. We use control variables to obtain identification results for average treatment effects. With discrete instruments in a triangular model we find that average treatment effects cannot be identified when the number of support points is less than or equal to the number of coefficients. A sufficient condition for identification is that the second moment matrix of the treatment functions given the control is nonsingular with probability one. We relate this condition to identification of average treatment effects with multiple treatments.
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