Cross-sectional regression analyses of wage gaps may be biased by omission of unobserved worker characteristics. Recent studies therefore have used longitudinal data to "difference out" the effects of such variables. This paper. however. shows that self-selection of job changers may cause...

This paper discusses the estimation of serial correlation in fixed effects models for longitudinal data. Like time series data, longitudinal data often contain serially correlated error terms, but the autocorrelation estimators commonly used for time series, which are consistent as the length of...

Following an influential article by Angrist and Krueger (1992) on two-sample instrumental variables (TSIV) estimation, numerous empirical researchers have applied a computationally convenient two-sample two-stage least squares (TS2SLS) variant of Angrist and Krueger's estimator. In the...

We propose a portmanteau test for serial correlation of the error term in a fixed effects model. The test is derived as a conditional Lagrange multiplier test, but it also has a straightforward Wald test interpretation. In Monte Carlo experiments, the test displays good size and power properties

This paper exposits and relates two distinct approaches to bounding the average treatment effect. One approach, based on instrumental variables, is due to Manski (1990, 1994), who derives tight bounds on the average treatment effect under a mean independence form of the instrumental variables...

This paper describes a range of methods which have been proposed to study interactions in economic and social contexts. By interactions, we refer to interdependences between individual decisions which are not mediated by markets. These types of models have been employed to understand phenomena...

We consider the implications of a specific alternative to the classical measurement error model, in which the data are optimal predictions based on some information set. One motivation for this model is that if respondents are aware of their ignorance they may interpret the question what is the...

This paper considers regression-based tests for encompassing, when none of the models under consideration encompasses all the other models. For both in- and out-of-sample applications, I derive asymptotic distributions and propose feasible procedures to construct confidence intervals and test...

This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix estimators in which the residuals are prewhitened using a vector autoregressive (VAR) filter. We highlight the pitfalls of using an arbitrarily fixed lag order for the VAR filter, and...

This paper specifies a general set of conditions under which the impacts of a policy can be identified using data generated under a different policy regime. We show that some of the policy impacts can be identified under relatively weak conditions on the data and structure of a model. Based on...