This paper considers identification and estimation of ceteris paribus effects of continuous regressors in nonseparable panel models with time homogeneity. The effects of interest are derivatives of the average and quantile structural functions of the model. We find that these derivatives are...

This paper considers identification and estimation of ceteris paribus effects of continuous regressors in nonseparable panel models with time homogeneity. The effects of interest are derivatives of the average and quantile structural functions of the model. We find that these derivatives are...

We study identification and estimation in a binary response model with random coefficients B allowed to be correlated with regressors X. Our objective is to identifiy the mean of the distribution of B and estimate a trimmed mean of this distribution. Like Imbens and Newey (2009), we use...

This paper is concerned with testing rationality restrictions using quantile regression methods. Specifically, we consider negative semidefiniteness of the Slutsky matrix, arguably the core restriction implied by utility maximization. We consider a heterogeneous population characterized by a...

This paper contributes to the understanding of the source of identification in panel data models. Recent research has established that few time periods suffice to identify interesting structural effects in nonseparable panel data models even in the presence of complex correlated unobservables,...

This paper studies the identification of nonseparable models with continuous, endogenous regressors, also called treatments, using repeated cross sections. We show that several treatment effect parameters are identified under two assumptions on the effect of time, namely a weak stationarity...

This paper proposes a framework to model empirically welfare effects that are associated with a price change in a population of heterogeneous consumers. Individual demands are characterized by a nonseparable model which is nonparametric in the regressors, as well as monotonic in unobserved...

In this paper we study nonparametric estimation in a binary treatment model where the outcome equation is of unrestricted form, and the selection equation contains multiple unobservables that enter through a nonparametric random coefficients specification. This specification is flexible because...

Individual players in a simultaneous equation binary choice model act differently in different environments in ways that are frequently not captured by observables and a simple additive random error. This paper proposes a random coefficient specification to capture this type of heterogeneity in...

In structural economic models, individuals are usually characterized as solving a decision problem that is governed by a finite set of parameters. This paper discusses the nonparametric estimation of the probability density function of these parameters if they are allowed to vary continuously...