Many commonly used treatment effects estimators rely on the unconfoundedness assumption (“selection on observables") which is fundamentally non-testable. When evaluating the effects of labor market policies, researchers need to observe variables that affect both treatment participation and...

Many commonly used treatment effects estimators rely on the unconfoundedness assumption ("selection on observables") which is fundamentally non-testable. When evaluating the effects of labor market policies, researchers need to observe variables that affect both treatment participation and labor...

There is a debate on whether executive pay reflects rent extraction due to quot;managerial powerquot; or is the result of arms-length bargaining in a principal-agent framework. In this paper we offer a test of the managerial power hypothesis by empirically examining the CEO compensation of U.S....

A large and highly used number of treatment effects estimators rely on the unconfoundedness assumption ("selection on observables") which is fundamentally non testable. When evaluating the effects of labor market policies, researchers need to observe both variables that affect treatment...

Although home-ownership has been shown to restrict geographic labor mobility and to affect job search behavior of unemployed, there is no evidence so far on how it affects their future re-employment outcomes. We use two waves of detailed German survey data of newly unemployed individuals to...

This paper focuses on re-examining the gender wage gap and the potential role that reservation wages play. Based on two waves of rich data from the IZA Evaluation Dataset Survey we examine the importance of gender differences in reservation wages to explain the gender gap in realized wages for a...

We consider the problem of using data from several programs, each implemented at a different location, to compare what their effect would be if they were implemented at a specific location. In particular, we study the effectiveness of nonexperimental strategies in adjusting for differences...

We study the effectiveness of nonexperimental strategies in adjusting for comparison group differences when using data from several programs, each implemented at a different location, to compare their effect if implemented at alternative locations. First, we adjust for individual characteristics...

Estimation of average treatment effects under unconfounded or ignorable treatment assignment is often hampered by lack of overlap in the covariate distributions between treatment groups. This lack of overlap can lead to imprecise estimates, and can make commonly used estimators sensitive to the...

A large part of the recent literature on program evaluation has focused on estimation of the average effect of the treatment under assumptions of unconfoundedness or ignorability following the seminal work by Rubin (1974) and Rosenbaum and Rubin (1983). In many cases however, researchers are...