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,...

According to official poverty estimates in Mexico, more than 50 percent of the population was poor in 2016, half of which could not even afford the basic food basket. Whereas most of the existing research analyses poverty focusing exclusively on average income or on the expected probability of...

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...

This paper investigates differences in outcomes between historically black colleges and universities (HBCU) and traditional college and universities (non-HBCUs) using a standard Oaxaca/Blinder decomposition. This method decomposes differences in observed educational and labor market outcomes...

The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen (2005)) is a popular tool for estimating causal quantile effects with endogenous covariates. However, estimation is complicated by the nonsmoothness and nonconvexity of the IVQR GMM objective function. This paper...

The allocation of resources to defence and national security is influenced by several factors, both domestic and external. Empirical findings suggest that military spending is determined by economic, strategic, political, and security factors. Studies that estimate demand functions for such...

We analyze output growth risk with respect to financial conditions across U.S. manufacturing industries. Using a multi-level quantile regression approach, we find strong heterogeneity in growth risk, particularly between the more vulnerable durable goods sector and the more resilient nondurable...

Growth at Risk (GaR) methodology developed by Adrian et al. (2019) has been of special interest by policymakers since it provides a measure of the relationship among macrofinancial variables. GaR requires estimating a set of predictive quantile regressions (QR) where future economic activity...

This article presents an empirical estimation of the effect of fuel prices on vehicle kilometers traveled (VKT) using a panel dataset of 1,138 Swiss households. Elasticities are estimated for different segments of households, based on their socio-demographic and vehicle characteristics, as well...

In this study, I apply a quantile regression model to investigate how gold returns respond to changes in various financial indicators. The model quantifies the asymmetric response of gold return in the tails of the distribution based on weekly data over the past 30 years. I conducted a...