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J. Risk Financial Manag. 2018, 11(3), 44; https://doi.org/10.3390/jrfm11030044

Nonparametric Estimation of a Conditional Quantile Function in a Fixed Effects Panel Data Model

1
and
1,2,*
1
Department of Economics, Texas A&M University, College Station, TX 77845, USA
2
International School of Economics and Management (ISEM), Capital University of Economics and Business, Beijing 100070, China
*
Author to whom correspondence should be addressed.
Received: 11 July 2018 / Revised: 31 July 2018 / Accepted: 1 August 2018 / Published: 3 August 2018
(This article belongs to the Special Issue Nonparametric Econometric Methods and Application)
Full-Text   |   PDF [324 KB, uploaded 6 August 2018]   |  

Abstract

This paper develops a nonparametric method to estimate a conditional quantile function for a panel data model with an additive individual fixed effects. The proposed method is easy to implement, it does not require numerical optimization and automatically ensures quantile monotonicity by construction. Monte Carlo simulations show that the proposed estimator performs well in finite samples. View Full-Text
Keywords: nonparametric method; conditional quantile function; panel data nonparametric method; conditional quantile function; panel data
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Yan, K.X.; Li, Q. Nonparametric Estimation of a Conditional Quantile Function in a Fixed Effects Panel Data Model. J. Risk Financial Manag. 2018, 11, 44.

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