It is common in empirical research to use what appear to be sensible rules of thumb for cleaning data. Measurement error is often the justification for removing (trimming) or recoding (winsorizing) observations whose values lie outside a specified range. This paper considers identification in a...

This article examines match bias arising from earnings imputation. Wage equation parameters are estimated from mixed samples of workers reporting and not reporting earnings, the latter assigned earnings of donors. Regressions including attributes not used as imputation match criteria (e.g.,...

Earnings nonresponse in the Current Population Survey is roughly 30% in the monthly surveys and 20% in the March survey. If nonresponse is ignorable, unbiased estimates can be achieved by omitting nonrespondents. Little is known about whether CPS nonresponse is ignorable. Using sample frame...

In this paper, we consider GMM estimation of the regression and MRSAR models with SAR disturbances. We derive the best GMM estimator within the class of GMM estimators based on linear and quadratic moment conditions. The best GMM estimator has the merit of computational simplicity and asymptotic...

We study a regression model with a binary explanatory variable that is subject to misclassification errors. The regression coefficient is then only partially identified. We derive several results that relate different assumptions about the misclassification probabilities and the conditional...

Hedonic office rent models are estimated using data for Atlanta that span the years 1990-96. Controlling for typical building characteristics and lease terms, we find that variables measuring locational differences in wage rates, transport rates and proximity to concentrations of support...

Making use of performance data for baseball players, this article provides empirical evidence in support of Lazear's (1998) theoretical predictions that (1) risky workers will earn a premium for their upside potential, (2) this risk premium will be higher the longer a worker's work life, and (3)...

It is common practice to use sensible rules of thumb for cleaning data. Measurement error is often the justification for removing (trimming) or recoding (winsorizing) observations where the dependent variable has values that lie outside a specified range. We consider a general measurement error...