The weighted least absolute deviation (WLAD) regression estimation method and the adaptive least absolute shrinkage and selection operator (LASSO) are combined to achieve robust parameter estimation and variable selection in regression simultaneously. Compared with the LAD-LASSO method, the...

A nonparametric procedure for quantile regression, or more generally nonparametric M-estimation, is proposed which is completely data-driven and adapts locally to the regularity of the regression function. This is achieved by considering in each point M-estimators over different local...

Econometric analyses in the happiness literature typically use subjective well-being (SWB) data to compare the mean of observed or latent happiness across samples. Recent critiques show that com-paring the mean of ordinal data is only valid under strong assumptions that are usually rejected by...

We develop uniformly valid confidence regions for a regression coefficient in a high-dimensional sparse LAD (least absolute deviation or median) regression model. The setting is one where the number of regressors p could be large in comparison to the sample size n, but only s n of them are...

Cultural factors and especially common languages are well-known determinants of trade. By contrast, the knowledge of foreign languages was not explored in the literature so far. We combine traditional gravity models with data on fluency in the main languages used in EU and candidate countries....

Using the Reinhart-Rogoff dataset, we find a debt threshold not around 90 percent but around 30 percent above which the median real GDP growth falls abruptly. Our work is the first to formally test for threshold effects in the relationship between public debt and median real GDP growth. The null...