Latent Variable Models for Time Series: A Frequency Domain Approach with an Application to the Permanent Income Hypothesis

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dc.contributor.author Geweke, John en_US
dc.contributor.author Singleton, K. en_US
dc.contributor.editor en_US
dc.date.accessioned 2011-02-07T06:26:17Z
dc.date.available 2011-02-07T06:26:17Z
dc.date.issued 1981 en_US
dc.identifier 2008008399 en_US
dc.identifier.citation Geweke John and Singleton K. 1981, 'Latent Variable Models for Time Series: A Frequency Domain Approach with an Application to the Permanent Income Hypothesis', Elsevier Science Publishers B.V., vol. 17, no. 3, pp. 287-304. en_US
dc.identifier.issn 0304-4076 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/13952
dc.description.abstract Abstract: The theory of estimation and inference in a very general class of latent variable models for time series is developed by showing that the distribution theory for the finite Fourier transform of the observable variables in latent variable models for time series is isomorphic to that for the observable variables themselves in classical latent variable models. This implies that analytic work on classical latent variable models can be adapted to latent variable models for time series, an implication which is illustrated here in the context of a general canonical form. To provide an empirical example a latent variable model for permanent income is developed, its parameters are shown to be identified, and a variety of restrictions on these parameters implied by the permanent income hypothesis are tested. en_US
dc.language en_US
dc.publisher Elsevier Science Publishers B.V. en_US
dc.relation.isbasedon http://dx.doi.org/10.1016/0304-4076(81)90003-8 en_US
dc.title Latent Variable Models for Time Series: A Frequency Domain Approach with an Application to the Permanent Income Hypothesis en_US
dc.parent Journal of Econometrics en_US
dc.journal.volume 17 en_US
dc.journal.number 3 en_US
dc.publocation Amsterdam en_US
dc.identifier.startpage 287 en_US
dc.identifier.endpage 304 en_US
dc.cauo.name BUS.Faculty of Business en_US
dc.conference Verified OK en_US
dc.for 140305 en_US
dc.personcode 101228 en_US
dc.personcode 0000053819 en_US
dc.percentage 100 en_US
dc.classification.name Time-Series Analysis en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA en_US


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