We propose a quantile regression method which effectively handles missing values due to non-response. We illustrate the usefulness of our method by two examples. First example is the estimation of income inequality measures when a significant proportion of earnings are missing in survey data....

There has been continuing interest in Bayesian regressions without imposing any parametric assumption on the error distribution, but the asymptotic efficiency of such procedures has not been fully understood yet. In this article, we consider semiparametric Bayesian nonlinear regression models....

This paper develops cluster robust inference methods for panel quantile regression (QR) models with individual fixed effects, allowing arbitrary temporal correlation structure within each individual. The conventional QR standard errors assuming independent outcomes can seriously underestimate...

This study considers an estimator for the asymptotic variance-covariance matrix in time-series quantile regression models which is robust to the presence of heteroskedasticity and autocorrelation. When regression errors are serially correlated, the conventional quantile regression standard...

This online appendix is structured as follows. Section S.1 contains some auxiliary lemmas and proofs for Section 4. Section S.2 develop supporting theoretical results for Section 5. Section S.3 reports additional simulation results. Some tables appear at the end

This paper develops cluster robust inference methods for panel quantile regression (QR) models with individual fixed effects, allowing temporal correlation within each individual. The conventional QR standard errors can seriously underestimate the uncertainty of estimators and therefore...