Smoothed quantile regression for panel data

Antonio Galvao and Kengo Kato

Journal of Econometrics, 2016, vol. 193, issue 1, 92-112

Abstract: This paper studies fixed effects estimation of quantile regression models for panel data. Under an asymptotic framework where both the numbers of individuals and time periods grow at the same rate, we show that the fixed-effects estimator for the smoothed objective function has a limiting normal distribution with a bias in the mean, and provide the analytic form of the asymptotic bias. We propose a one-step bias correction estimator based on the analytic bias formula obtained from the asymptotic analysis. Importantly, our results cover the case that observations are dependent over time. We illustrate the effects of the bias correction through simulations.

Keywords: Bias correction; Incidental parameters problem; Panel data; Quantile regression; Smoothing (search for similar items in EconPapers)
JEL-codes: C13 C23 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (78)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:193:y:2016:i:1:p:92-112

DOI: 10.1016/j.jeconom.2016.01.008

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