The determinants of CO2 emissions have attracted many researchers over the past few decades. Most of studies, however, ignore the possibility that effect of independent variables on CO2 emissions could vary throughout the CO2 emission distribution. We address this issue by applying quantile...

This paper illustrates application of Bayesian inference to quantile regression. Bayesian inference regards unknown parameters as random variables, and we describe an MCMC algorithm to estimate the posterior densities of quantile regression parameters. Parameter uncertainty is taken into account...