2010
DOI: 10.1016/j.jeconom.2010.05.002
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A flexible approach to parametric inference in nonlinear and time varying time series models

Abstract: This version is available at https://strathprints.strath.ac.uk/28119/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any pro… Show more

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Cited by 16 publications
(14 citation statements)
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“…In previous work (see Koop and Potter, 2007), we developed a simple modeling framework that is extremely ‡exible, exactly or approximately nesting a wide variety of nonlinear time series and structural break models. We use this framework here.…”
Section: Flexible Parametric Modelingmentioning
confidence: 99%
See 4 more Smart Citations
“…In previous work (see Koop and Potter, 2007), we developed a simple modeling framework that is extremely ‡exible, exactly or approximately nesting a wide variety of nonlinear time series and structural break models. We use this framework here.…”
Section: Flexible Parametric Modelingmentioning
confidence: 99%
“…Bayesian methods for carrying out econometric inference in this model are described in the appendix. For complete details (and additional motivation for this ‡exible parametric approach), see Koop and Potter (2007). As a …rst step, consider extending (1) to be a time varying parameter (TVP) regression model, written in state space form with measurement equation given by:…”
Section: Flexible Parametric Modelingmentioning
confidence: 99%
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