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

Investigators of social differentials in health outcomes commonly augment incomplete micro data by appending socioeconomic characteristics of residential areas (such as median income in a zip code) to proxy for individual characteristics. However, little empirical attention has been paid to how...

In this paper we draw attention to two problems associated with the use of instrumental variables (IV) whose importance for empirical work has not been fully appreciated. First, using potential instruments that explain little of the variation in the: endogenous explanatory variables can lead to...