Template-type: ReDIF-Paper 1.0


Author-Name: Fernando Rios-Avila
Author-Workplace-Name: Universidad Privada Boliviana
Author-Workplace-Email: friosa@gmail.com

Author-Name: Andrey Ramos
Author-Workplace-Name: Bank of Spain
Author-Workplace-Email: andrey.ramos@bde.es

Author-Name: Gustavo Canavire-Bacarreza
Author-Workplace-Name: World Bank and Universidad Privada Boliviana
Author-Workplace-Email: gcanavire@worldbank.org

Author-Name: Leonardo Siles
Author-Workplace-Name: Universidad de Chile
Author-Workplace-Email: lsiles@fen.uchile.cl

Title: Estimation and Inference in Quantile Regressions with Multiple Fixed Effects

Abstract: This paper proposes a method to estimate quantile regression models with multiple fixed effects. We extend the quantile–via–moments estimator of Machado and Santos Silva (2019) and suggest a computationally efficient Frisch–Waugh–Lovell residualization to partial out additive fixed effects in both the location and scale equations. A unified influence-function inference framework is derived, accommodating heteroskedasticity-robust, clustered, and feasible GLS standard errors. Monte Carlo simulations provide strong support for the validity of the proposed procedure in applications with multi-way unobserved heterogeneity and intra-cluster correlated disturbances. An empirical application to Climate Growth-at-Risk illustrates how temperature shocks affect the conditional distribution of macroeconomic outcomes in a panel of 194 countries. Our findings suggest that in low income countries, downside risks to growth are more strongly linked to temperature shocks than the central tendency or upside risks.

Length: 33 pages

Creation-Date: 2026-03

File-URL: http://ayspsrd.gsu.edu/ays/ispwps/paper2615.pdf
File-Format: application/pdf

Handle: RePEc:ays:ispwps:paper2615