Premium
Dummy Endogenous Variables in Weakly Separable Models
Author(s) -
Vytlacil Edward,
Yildiz Nese
Publication year - 2007
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.1111/j.1468-0262.2007.00767.x
Subject(s) - separable space , nonparametric statistics , parametric statistics , mathematics , term (time) , econometrics , class (philosophy) , identification (biology) , instrumental variable , parametric model , discrete choice , variable (mathematics) , statistics , computer science , artificial intelligence , mathematical analysis , physics , botany , quantum mechanics , biology
In this paper, we consider the nonparametric identification and estimation of the average effect of a dummy endogenous regressor in models where the regressors are weakly but not additively separable from the error term. The model is not required to be strictly increasing in the error term, and the class of models considered includes limited dependent variable models such as discrete choice models. Conditions are established conditions under which it is possible to identify the average effect of the dummy endogenous regressor in a weakly separable model without relying on parametric functional form or distributional assumptions and without the use of large support conditions.