This paper considers inference in log-linearized dynamic stochastic general equilibrium (DSGE) models with weakly (including un-) identified parameters. The framework allows for analysis using only part of the spectrum, say at the business cycle frequencies. First, we characterize weak...

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...

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