Partial Identification in Triangular Systems of Equations with Binary Dependent Variables
نویسندگان
چکیده
This paper studies models for binary outcome variables that contain a binary endogenous regressor. More specifically, we consider a nonparametric, triangular system of equations with binary dependent variables. The main assumption we impose is a weak separability condition on each equation, or, equivalently, a threshold crossing model on each equation. In this setting, we construct upper and lower bounds on the Average Structural Function (ASF) and the Average Treatment Effect (ATE) under weak regularity conditions. The resulting bounds are narrower the greater the strength of the instrument and the greater the degree to which the exogenous covariates that enter the outcome equation can compensate for variation in the endogenous regressor. We show further that the bounds on the ASF and ATE are sharp under an additional restriction on the support of the covariates and the instrument. JEL Codes: C14, C35
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