When there are multiple outcome series of interest, Synthetic Control analyses typically proceed by estimating separate weights for each outcome. In this paper, we instead propose estimating a common set of weights across outcomes, by balancing either a vector of all outcomes or an index or...

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...

This paper studies the spatial random effects and spatial fixed effects model. The model includes a Cliff and Ord type spatial lag of the dependent variable as well as a spatially lagged one-way error component structure, accounting for both heterogeneity and spatial correlation across units. We...

More than one third of the European Union's total budget is spent on socalled Cohesion Policy via the structural funds. Its main purpose is to promote the development of the EU and to support convergence between the levels of development of the various European regions. Investigating the impact...

The impact of technology on the demand for heterogeneous labor is controversely discussed throughout the literature. New technology which is said to favor high skilled labor and to substitute low skilled labor is often considered as the main reason for the decline in relative demand for low...

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...

This paper develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pre-treatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment...

The cluster robust variance estimator (CRVE) relies on the number of clusters being large. The precise meaning of 'large' is ambiguous, but a shorthand 'rule of 42' has emerged in the literature. We show that this rule depends crucially on the assumption of equal-sized clusters. Monte Carlo...

Many empirical projects are well suited to incorporating a linear difference-in-differences research design. While estimation is straightforward, reliable inference can be a challenge. Past research has not only demonstrated that estimated standard errors are biased dramatically downwards in...

This paper studies the public sector wage gap in Spain, by gender, skill level and type of contract, using recent administrative data from tax records. We estimate wage distributions in the presence of covariates separately for men and women in the public and in the private sectors, and we take...