Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: http://hdl.handle.net/10419/185409
Autoren: 
Harding, Matthew
Lamarche, Carlos
Pesaran, M. Hashem
Datum: 
2018
Schriftenreihe/Nr.: 
CESifo Working Paper No. 7211
Zusammenfassung: 
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.
Schlagwörter: 
common correlated effects
dynamic panel
quantile regression
smart meter
randomized experiment
JEL: 
C21
C31
C33
D12
L94
Dokumentart: 
Working Paper

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