Semiparametric structural models of binary response : shape restrictions and partial identification

The paper studies the partial identifying power of structural single equation threshold crossing models for binary responses when explanatory variables may be endogenous. The paper derives the sharp identified set of threshold functions for the case in which explanatory variables are discrete and provides a constructive proof of sharpness. There is special attention to a widely employed semiparametric shape restriction which requires the threshold crossing function to be a monotone function of a linear index involving the observable explanatory variables. It is shown that the restriction brings great computational benefits, allowing direct calculation of the identified set of index coefficients without calculating the nonparametrically specified threshold function. With the restriction in place the methods of the paper can be applied to produce identified sets in a class of binary response models with mis-measured explanatory variables. -- Binary Response ; Endogeneity ; Incomplete models ; Index Restrictions ; Instrumental variables ; Measurement Error Models ; Partial Identification ; Probit Models ; Shape Restrictions ; Threshold Crossing Models