Nonparametric estimation of a conditional quantile function in a fixed effects panel data model

Karen X. Yan and Qi Li

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.

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Year of publication:	September 2018
Authors:	Yan, Karen X. ; Li, Qi
Published in:	Journal of risk and financial management : JRFM. - Basel : MDPI, ISSN 1911-8074, ZDB-ID 2739117-6. - Vol. 11.2018, 3, p. 1-10
Subject:	nonparametric method \| conditional quantile function \| panel data \| Panel \| Panel study \| Nichtparametrisches Verfahren \| Nonparametric statistics \| Schätztheorie \| Estimation theory

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Type of publication:	Article
Type of publication (narrower categories):	Aufsatz in Zeitschrift ; Article in journal
Language:	English
Other identifiers:	10.3390/jrfm11030044 [DOI] hdl:10419/238885 [Handle]
Classification:	C14 - Semiparametric and Nonparametric Methods ; C21 - Cross-Sectional Models; Spatial Models
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10011895653