In many applications of the differences-in-differences (DID) method, the treatment increases more in the treatment group, but some units are also treated in the control group. In such fuzzy designs, a popular estimator of treatment effects is the DID of the outcome divided by the DID of the...

We employ a balanced panel dataset representative of the entire Chilean productive structure in order to investigate the relation between the introduction of innovation and subsequent firm growth in terms of sales. Recent contributions examining the returns to innovation on firm performance have...

This paper studies estimation of conditional and unconditional quantile treatment effects based on the instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2004, 2005, 2006). I introduce a class of semiparametric plug-in estimators based on closed form solutions...

Quantile regression and quantile treatment effect methods are powerful econometric tools for considering economic impacts of events or variables of interest beyond the mean. The use of quantile methods allows for an examination of impacts of some independent variable over the entire distribution...

The paper evaluates the distributional effects on earnings and income of requiring young welfare recipients to fulfill conditions related to work and activation. It exploits within-social insurance office variation in policy arising from a geographically staggered reform in Norway. The reform...