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dc.contributor.authorCamarero, Mariam
dc.contributor.authorSapena, Juan
dc.contributor.authorTamarit, Cecilio
dc.date.accessioned2019-04-10T06:57:19Z
dc.date.available2019-04-10T06:57:19Z
dc.date.issued2019
dc.identifier.citationCAMARERO, Mariam; SAPENA, Juan; TAMARIT, Cecilio. Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle. Computational Economics, 2019, p. 1-28ca_CA
dc.identifier.issn0927-7099
dc.identifier.issn0927-7099
dc.identifier.urihttp://hdl.handle.net/10234/182272
dc.descriptionThis is a pre-print of an article published in Computational Economics. The final authenticated version is available online at: https://doi.org/10.1007/s10614-019-09879-x
dc.description.abstractIn this paper, we develop a very flexible and comprehensive state-space framework for modeling time series data. Our research extends the simple canonical model usually employed in the literature, into a panel-data time-varying parameters framework, combining fixed (both common and country-specific) and varying components. Under some specific circumstances, this setting can be understood as a mean-reverting panel time-series model, where the mean fixed parameter can, at the same time, include a deterministic trend. Regarding the transition equation, our structure allows for the estimation of different autoregressive alternatives, and include control instruments, whose coefficients can be set-up either common or idiosyncratic. This is particularly useful to detect asymmetries among individuals (countries) to common shocks. We develop a GAUSS code that allows for the introduction of restrictions regarding the variances of both the transition and measurement equations. Finally, we use this empirical framework to test for the Feldstein–Horioka puzzle in a 17-country panel. The results show its usefulness for solving complexities in macroeconomic empirical research.ca_CA
dc.format.extent28 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherSpringerca_CA
dc.relation.isPartOfComputational Economics, 2019,ca_CA
dc.rights© Springer Science+Business Media, LLC, part of Springer Nature 2019ca_CA
dc.subjectFeldstein–Horioka puzzleca_CA
dc.subjectpanel unit root testsca_CA
dc.subjectmultiple structural breaksca_CA
dc.subjectcommon factorsca_CA
dc.subjectKalman filterca_CA
dc.subjecttime varying parametersca_CA
dc.titleModelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzleca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1007/s10614-019-09879-x
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://link.springer.com/article/10.1007/s10614-019-09879-xca_CA
dc.contributor.funderThe authors gratefully acknowledge the financial support from AEI/Ministerio de Economía, Industria y Competitividad (MINEIC) and FEDER Project ECO2017-83255-C3-3-P and the Generalitat Valenciana (PROMETEO/2018/102 and GV/2017/052). Authors are also indebted to the Chair “Betelgeux” for a Sustainable Economic Development, for its specific funding of this research. This paper has been developed within the research thematic network ECO2016-81901-REDT financed by MINEIC. The usual disclaimer applies.ca_CA
dc.type.versioninfo:eu-repo/semantics/submittedVersionca_CA


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