Separate estimation of spatial dependence parameters and variance parameters in a spatial model

dc.contributor.author	Arnold, Matthias
dc.contributor.author	Wied, Dominik
dc.date.accessioned	2010-04-06T08:52:44Z
dc.date.available	2010-04-06T08:52:44Z
dc.date.issued	2010-04-06T08:52:44Z
dc.description.abstract	This paper suggests a two step estimation procedure for a spatial model with different kinds of spatial dependence and heteroscedastic innovations. Since maximum likelihood estimation is cumbersome due to the large number of parameters, we use a generalized method of moments approach to estimate the parameters of spatial correlation which does not need the large number of variance parameters to be known. For illustration purposes, we apply our estimation procedure to daily stock returns of the Euro Stoxx 50 members. JEL subject classifications: C13, C51, G12	en
dc.identifier.uri	http://hdl.handle.net/2003/27018
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-12672
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823;08/2010
dc.subject	GMM estimation	en
dc.subject	Heteroscedasticity	en
dc.subject	Spatial dependence	en
dc.subject	Stock returns	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.title	Separate estimation of spatial dependence parameters and variance parameters in a spatial model	en
dc.type	Text	de
dc.type.publicationtype	report	de
dcterms.accessRights	open access
eldorado.dnb.deposit	true

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