The triangular model is a very popular way to allow for causal inference in the presence of
endogeneity. In this model, an outcome is determined by an endogenous regressor, which …

Linearity in a causal relationship between a dependent variable and a set of regressors is a
common assumption throughout economics. In this paper we consider the case when the …

This paper establishes nonparametric identification of individual treatment effects in a
nonseparable model with a binary endogenous regressor. The outcome variable may be …

Triangular systems with nonadditively separable unobserved heterogeneity provide a
theoretically appealing framework for the modeling of complex structural relationships …

In this paper, we study a random‐coefficients model for a binary outcome. We allow for the
possibility that some or even all of the explanatory variables are arbitrarily correlated with …

We introduce several estimators for nonparametric functions with nonadditive unobservable
random terms in models with endogenous explanatory variables and, more generally, in …

The control function approach which employs an instrumental variable excluded from the
outcome equation is a very common solution to deal with the problem of endogeneity in …

We show how to nonparametrically identify the distribution of unobservables, such as
random coefficients, that characterizes the heterogeneity among consumers in multinomial …

A unifying framework to test for causal effects in nonlinear models is proposed. We consider
a generalized linear‐index regression model with endogenous regressors and no …

Heckman and MaCurdy (1985) first showed that binary outcomes are compatible with linear
econometric models of interactions. This key insight was unduly discarded by the literature …