We provide a finite sample inference method for the structural parameters of a semiparametric binary response model … under a conditional median restriction originally studied by Manski (1975, 1985). Our inference method is valid for any … to the lack of a continuously distributed covariate with large support. Our inference approach exploits distributional …

Cluster-robust inference is widely used in modern empirical work in economics and many other disciplines. The key unit … identify datasets and regression designs in which cluster-robust inference is likely to be challenging. The measures of …

This paper presents a test for exogeneity of explanatory variables in a nonparametric instrumental variables (IV) model … variables in a quantile regression model are exogenous can lead to highly misleading results. In addition, a test of exogeneity … based on an incorrectly specified parametric model can produce misleading results. This paper presents a test of exogeneity …

This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental … that our results can be easily extended to a test of missing completely at random (MCAR) and miss- ing completely at random … conditional on covariates X (MCAR(X)). A Monte Carlo study examines finite sample performance of our test statistic. An empirical …

This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental … of our test statistic. An empirical illustration analyzes the nonresponse mechanism in labor income questions. …

We propose a specification test for a wide range of parametric models for the conditional distribution function of an … outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted … an empirical application, we use our test to study the validity of various models for the conditional distribution of …