Compared to the conditional mean or median, conditional quantiles provide a more comprehensive picture of a variable in various scenarios. A semi-parametric quantile estimation method for a double threshold auto-regression with exogenous regressors and heteroskedasticity is considered, allowing...

Bayesian variable selection in quantile regression models is often a difficult task due to the computational challenges and non-availability of conjugate prior distributions. These challenges are rarely addressed via either penalized likelihood function or stochastic search variable selection....

The use of the internet is growing rapidly and has become an engine for economic development. However, few studies have examined the impact of internet use on agricultural production, and the results are not yet conclusive. Employing a dataset of more than 2,000 observations in rural Vietnam,...

We propose a novel approach to calibrate the conditional value-at-risk (CoVaR) of financial institutions based on neural network quantile regression. Building on the estimation results, we model systemic risk spillover effects in a network context across banks by considering the marginal effects...

We present a semiparametric method to estimate group-level dispersion, which is particularly effective in the presence of censored data. We apply this procedure to obtain measures of occupation-specific wage dispersion using top-coded administrative wage data from the German IAB Employment...

Recent work on the conditional mean model offers the possibility of addressing misreporting of participation in social programs, which is common and has increased in all major surveys. However, researchers who employ quantile regression continue to encounter challenges in terms of estimation and...

This paper presents new evidence on intergenerational mobility in the top of the income and earnings distribution. Using a large dataset of matched father-son pairs in Sweden, we find that intergenerational transmission is very strong in the top, more so for income than for earnings. In the...