This article describes qregsel, a Stata module to implement a copula-based sample selection correction for quantile regression recently proposed by Arellano and Bonhomme (2017, Econometrica 85(1): 1-28). The command allows the user to model selection in quantile regressions using either a...

This paper investigates four topics. (1) It examines the different roles played by the propensity score (probabilitiy of selection) in matching, instrumental variable and control functions methods. (2) It contrasts the roles of exclusion restrictions in matching and selection models. (3) It...

In non-linear regression models, such as the probit model, coefficients cannot be interpreted as marginal effects. The marginal effects are usually non-linear combinations of all regressors and regression coefficients of the model. This paper derives the marginal effects in a probit model with a...

When considering multiple hypothesis tests simultaneously, standard statistical techniques will lead to over-rejection of null hypotheses unless the multiplicity of the testing framework is explicitly considered. In this paper we discuss the Romano-Wolf multiple hypothesis correction, and...

The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) for the staggered treatment adoption design and a Stata tool that implements the approach. This flexible conditional difference-in-differences approach is particularly useful for...

xsmle is a new command for spatial analysis using Stata. We consider the quasi-maximum likelihood estimation of a wide set of both fi xed- and random- eff ects spatial models for balanced panel data. Of special note is that xsmle allows to handle unbalanced panels thanks to its full...

Many economic time series exhibit important systematic fluctuations within the year, i.e. seasonality. Differently from usual practice, we argue that using original data should always be considered, although their process is more complicated than that of seasonally adjusted data. Motivations to...