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

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:	2018
Authors:	Yan, Karen X. ; Li, Qi
Published in:	Journal of Risk and Financial Management. - Basel : MDPI, ISSN 1911-8074. - Vol. 11.2018, 3, p. 1-10
Publisher:	Basel : MDPI
Subject:	nonparametric method \| conditional quantile function \| panel data

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Type of publication:	Article
Type of publication (narrower categories):	Article
Language:	English
Other identifiers:	10.3390/jrfm11030044 [DOI] 1030120765 [GVK] hdl:10419/238885 [Handle]
Classification:	C14 - Semiparametric and Nonparametric Methods ; C21 - Cross-Sectional Models; Spatial Models
Source:	EconStor

Persistent link: https://www.econbiz.de/10012611026