We develop a regression decomposition technique for hazard rate models, where the difference in observed rates is decomposed into components attributable to group differences in characteristics and group differences in effects. The baseline hazard is specified using a piecewise constant...

The Wooldridge method is based on a simple and novel strategy to deal with the initial values problem in the nonlinear dynamic random-effects panel data models. This characteristic of the method makes it very attractive in empirical applications. However, its finite sample performance is not...

We propose a novel selectivity correction procedure to deal with survey attrition, at the crossroads of the "Heckit" and of the bounding approach of Lee (2009). As a substitute for the instrument needed in sample selectivity correction models, we use information on the number of attempts that...

Many microeconometric models of discrete labour supply include alternative-specific constants meant to account for (possibly besides other factors) the density or accessibility of particular types of jobs (e.g. part-time jobs vs. full-time jobs). The most common use of these models is the...

The randomized trial literature has helped to renew the fields of microeconometric policy evaluation by emphasizing identification issues raised by endogenous program participation. Measurement and attrition issues have perhaps received less attention. This paper analyzes the dramatic impact of...

In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses – conclusions based on a sample with and without these...

The paper investigates the effects of nursing overtime on nosocomial infections and medical accidents in a neonatal intensive care unit (NICU). The literature lacks clear evidence on this issue and we conjecture that this may be due to empirical and methodological factors. We thus focus on a...

In this article we propose and implement an instrumental variable estimation procedure to obtain treatment effects on duration outcomes. The method can handle the typical complications that arise with duration data of time-varying treatment and censoring. The treatment effect we define is in...

A fundamental identification problem in program evaluation arises when idiosyncratic gains from participation and the treatment decision depend on each other. Imbens and Angrist (1994) were the first to exploit a monotonicity condition in order to identify an average treatment effect parameter...

This paper investigates the method of matching regarding two crucial implementation choices, the distance measure and the type of algorithm. We implement optimal full matching - a fully efficient algorithm - and present a framework for statistical inference. The implementation uses data from the...