This paper proposes new ℓ1-penalized quantile regression estimators for panel data, which explicitly allows for individual heterogeneity associated with covariates. We conduct Monte Carlo simulations to assess the small sample performance of the new estimators and provide comparisons of new...

In this paper we use a relatively new panel data quantile regression technique to examine native-immigrant earnings differentials 1) throughout the conditional wage distribution, and 2) controlling for individual heterogeneity. No previous papers have simultaneously considered these factors. We...

Recent studies have used a distributional analysis of welfare reform experiments suggesting that some individuals reduce hours in order to opt into welfare, an example of behavioral-induced participation. Using data on Connecticut's Jobs First experiment, we find no evidence of...

This paper proposes a quantile regression estimator for a panel data model with interactive effects potentially correlated with the independent variables. We provide conditions under which the slope parameter estimator is asymptotically Gaussian. Monte Carlo studies are carried out to...

This paper proposes new ℓ1-penalized quantile regression estimators for panel data, which explicitly allows for individual heterogeneity associated with covariates. We conduct Monte Carlo simulations to assess the small sample performance of the new estimators and provide comparisons of new...

Recent studies have used a distributional analysis of welfare reform experiments suggesting that some individuals reduce hours in order to opt into welfare, an example of behavioral-induced participation. Using data on Connecticut's Jobs First experiment, we find no evidence of...

This paper proposes a quantile regression estimator for a panel data model with interactive effects potentially correlated with the independent variables. We provide conditions under which the slope parameter estimator is asymptotically Gaussian. Monte Carlo studies are carried out to...

This paper proposes new ℓ1-penalized quantile regression estimators for panel data, which explicitly allows for individual heterogeneity associated with covariates. We conduct Monte Carlo simulations to assess the small sample performance of the new estimators and provide comparisons of new...