Identification with averaged data and implications for hedonic regression studies

In the estimation of models with averaged data, weighted least squares is often used and recommended as a way of improving the efficiency of the estimator. However, if the size of the different groups is not conditionally independent of the regressand, consistent estimation may not be possible at all. It is argued that in the case of some leading examples of averaged data regression, consistent estimation is possible using the usual weighted estimator.Endogenous sampling; Functional form; Weighted least squares.

Quantiles for Counts

This paper studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness has to be artificially imposed on the problem. The methods currently available to estimate quantiles of count data either assume that the counts result from the discretization of a continuous process, or are based on a smoothed objective function. However, these methods have several drawbacks. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimator are illustrated by simulations and an application.Asymmetric maximum likelihood, Jittering, Maximum score estimator, Quantile regression, Smoothing.

The Reservation Wage Unemployment Duration Nexus

A thorny problem in identifying the determinants of reservation wages and particularly the role of continued joblessness in their evolution is the simultaneity issue. We deploy a control function approach to the problem that involves conditioning elapsed duration on completed unemployment duration in the reservation wage equation. Our analysis confirms that the use of elapsed duration alone compounds two separate and opposing influences. Only with the inclusion of completed duration is the negative effect of continued joblessness on reservation wages apparent