We present a semiparametric method to estimate group-level dispersion, which is particularly effective in the presence of censored data. We apply this procedure to obtain measures of occupation-specific wage dispersion using top-coded administrative wage data from the German IAB Employment...

We compare the income and wage trajectories of women in relation to their male partners before and after parenthood. Focusing on the within-couple gap allows us to control for both observed and unobserved attributes of the spouse and to estimate both short-and long-term effects of entering...

We present a semiparametric method to estimate group-level dispersion, which is particularly effective in the presence of censored data. We apply this procedure to obtain measures of occupation-specific wage dispersion using top-coded administrative wage data from the German IAB Employment...

Our research examines individual differences in the effects of medical malpractice tort reforms on pre-trial settlement speed and settlement amounts by age and most likely settlement size. Findings of note include that, unlike previously assumed, both absolute and percentage losses from tort...

An emerging literature on international activities of heterogeneous firms documents that exporting firms are more productive than firms that only sell on the national market. This positive exporter productivity premium shows up in a large number of empirical studies after controlling for...

Performance pay is of growing importance to the wage structure as it applies to a rising share of employees. At the same time wage dispersion is growing continuously. This leads to the question of how the growing use of performance pay schemes is related to the increase in wage inequality?...

Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to the tails, is of interest in many...

In this paper we develop procedures for performing inference in regression models about how potential policy interventions affect the entire marginal distribution of an outcome of interest. These policy interventions consist of either changes in the distribution of covariates related to the...

Analyses using aggregated data may bias inference. In this work we show how to avoid or at least reduce this bias when estimating quantile regressions using aggregated information. This is possible by considering the unconditional quantile regression recently introduced by Firpo et al (2009) and...

This paper employs quantile panel regression to the study of fuel price elasticities. Contrasting with standard panel approaches, this method reveals the impact of explanatory variables across all points in the conditional distribution of the response variable while controlling for unobserved...