Arbeitspapier

Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Quantile Regression Models

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.

Language
Englisch

Bibliographic citation
Series: CESifo Working Paper ; No. 7211

Classification
Wirtschaft
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models
Consumer Economics: Empirical Analysis
Electric Utilities
Subject
common correlated effects
dynamic panel
quantile regression
smart meter
randomized experiment

Event
Geistige Schöpfung
(who)
Harding, Matthew
Lamarche, Carlos
Pesaran, M. Hashem
Event
Veröffentlichung
(who)
Center for Economic Studies and ifo Institute (CESifo)
(where)
Munich
(when)
2018

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Harding, Matthew
  • Lamarche, Carlos
  • Pesaran, M. Hashem
  • Center for Economic Studies and ifo Institute (CESifo)

Time of origin

  • 2018

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