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“Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Quantile Regression Models”
Autor: Carlos Lamarche
Abstract
This paper proposes a quantile regression estimator for a heterogeneous panel model with lagged dependent variables and interactive effects. The paper adopts the Common Correlated Effects (CCE) approach proposed by Pesaran (2006) and Chudik and Pesaran (2015) and demonstrates that the extension to the estimation of dynamic quantile regression models is feasible under similar conditions to the ones used in the literature. We establish consistency and derive the asymptotic distribution of the new quantile regression estimator. Monte Carlo studies are carried out to study the small sample behavior of the proposed approach. The evidence shows that the estimator can significantly improve the performance of existing estimators as long as the time series dimension of the panel is large. We present an application to the evaluation of Time-of-Use pricing using a large randomized control trial.
Carlos Lamarche es Gatton Endowed Associate Professor of Economics en la University of Kentucky desde 2015. Su área de interés es la econometría tanto teórica como empírica, en particular se ha enfocado en el estudio de regresiones por cuantiles para datos de panel. Obtuvo si PhD en la University of Illinois at Urbana-Champaign.
19 de junio de 2017