This paper presents a new method to correct for measurement error in wage data and applies this method to address an old question. How much downward wage flexibility is there in the U.S? We apply standard methods developed by Bai and Perron (1998b) to identify structural breaks in time series...

This paper considers identification and estimation of a nonparametric regression model with an unobserved discrete covariate. The sample consists of a dependent variable and a set of covariates, one of which is discrete and arbitrarily correlates with the unobserved covariate. The observed...

We propose estimators of features of the distribution of an unobserved random variable W. What is observed is a sample of Y; V; X where a binary Y equals one when W exceeds a threshold V determined by experimental design, and X are covariates. Potential applications include bioassay and...

This paper provides numerically trivial estimators for short panels of either binary choices or of linear models that suffer from confounded, nonignorable sample selection. The estimators allow for fixed effects, endogenous regressors, lagged dependent variables, and heterokedastic errors with...

This article examines whether recent college graduates have fared as well as their predecessors. We examine changes in both the wage and occupational distributions. Specifically, we explore the claim that college educated workers are increasingly likely to be in "non-college" occupations. The...

Death statutes in the United States list elements of loss for which a defendant must make compensatory payment. The element that economists as expert witnesses are called upon to calculate is net income, roughly defined as the decedent's income minus personal expenses. The existence of joint or...

The structural consumer demand methods used to estimate the parameters of collective household models are typically either very restrictive and easy to implement or very general and difficult to estimate. In this paper, we provide a middle ground. We adapt the very general framework of Browning,...

The nonparametric censored regression model, with a fixed, known censoring point (normalized to zero), is y = max[0,m(x)+e], where both the regression function m(x) and the distribution of the error e are unknown. This paper provides consistent estimators of m(x) and its derivatives. The...

This paper proposes a new method of obtaining identification in mismeasured regressor models, triangular systems, and simultaneous equation systems. The method may be used in applications where other sources of identification such as instrumental variables or repeated measurements are not...