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...

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...

Progress in narrowing black-white earnings differences has been far from continuous, with some of the apparent progress resulting from labor force withdrawal among lower-skilled African Americans. This paper builds on prior research and documents racial and ethnic differences in male earnings...

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...

This paper compares two approaches to analyzing longitudinal discrete-time binary outcomes. Dynamic binary response models focus on state occupancy and typically specify low-order Markovian state dependence. Multi-spell duration models focus on transitions between states and typically allow for...

This paper is concerned with the nonparametric estimation of regression quantiles where the response variable is randomly censored. Using results on the strong uniform convergence of U-processes, we derive a global Bahadur representation for the weighted local polynomial estimators, which is...

This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant...

Regression analyses of cross-country economic growth data are complicated by two main forms of model uncertainty: the uncertainty in selecting explanatory variables and the uncertainty in specifying the functional form of the regression function. Most discussions in the literature address these...