Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Quantile Regression Models

Matthew Harding, Carlos Lamarche and Mohammad Pesaran

No 7211, CESifo Working Paper Series from CESifo

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 on 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.

Keywords: common correlated effects; dynamic panel; quantile regression; smart meter; randomized experiment (search for similar items in EconPapers)
JEL-codes: C21 C31 C33 D12 L94 (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Common correlated effects estimation of heterogeneous dynamic panel quantile regression models (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_7211

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