Estimation in Semiparametric Time Series Models

In this paper, we consider a semiparametric time series regression model and establish a set of identification conditions such that the model under discussion is both identifiable and estimable. We then discuss how to estimate a sequence of local alternative functions nonparametrically when the null hypothesis does not hold. An asymptotic theory is established in each case. An empirical application is also included

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Year of publication:	2010
Authors:	Gao, Jiti ; Chen, Jia ; Li, Degui
Publisher:	[S.l.] : SSRN
Subject:	Zeitreihenanalyse \| Time series analysis \| Schätztheorie \| Estimation theory \| Nichtparametrisches Verfahren \| Nonparametric statistics

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Extent:	1 Online-Ressource (17 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments September 15, 2010 erstellt
Other identifiers:	10.2139/ssrn.1677748 [DOI]
Classification:	C14 - Semiparametric and Nonparametric Methods ; C32 - Time-Series Models
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014191158