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...

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...

Quantile regression and quantile treatment effect methods are powerful econometric tools for considering economic impacts of events or variables of interest beyond the mean. The use of quantile methods allows for an examination of impacts of some independent variable over the entire distribution...

Using the Ensenada Cadastre, a unique database on Castilian households circa 1750, we measure the effect of human capital on the structure of male labor earnings. Human capital is proxied by individual indicators of basic skills (literacy and numeracy) and of occupational skills. We employ a...

This study investigates the factors that may influence the obesity in Turkey which is a developing country by implementing Quantile Regression (QR) methodology. The control factors that we consider are education, labor market outcomes, household income, age, gender, region and marital status....