Common correlated effects estimation of heterogeneous dynamic panel quantile regression models
By Matthew Harding, Carlos Lamarche, M. Pesaran. Journal of applied econometrics, 2020
106 citations recorded by the source corpus.
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.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/30f39fc552b3ffcd487228ff192688843d5f0b27
Citations in the corpus
- Quantile regression with nonadditive fixed effects (2022, unknown): “Following the strategy in Johnson et al. (2006) and Parker et al. (2013), it is necessary to condition on household fixed effects (αi ) to estimate causal parameters.”
- Interplay between technological innovation and environmental quality: Formulating the SDG policies for next 11 economies (2020, unknown): “dependence on the cross sections, we used the Chudik and Pesaran test (2015). This test verifies the null 26 hypothesis of the cross-section independence of the data. The results reported in Table 3 allow accepting 27 the null hypothesis of the cross-section dependence of the variables. Dependence i”
- Investigating the asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint: Novel empirical estimations from highly resource-consuming economies (2021, unknown): “The detailed assumptions and derivation of DQMGR are given in the seminal paper of 603 Harding et al. (2020).”