Bayesian Inference in the Time Varying Cointegration Model
AbstractThere are both theoretical and empirical reasons for believing that the pa- rameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit coin- tegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.
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Bibliographic InfoPaper provided by National Graduate Institute for Policy Studies in its series GRIPS Discussion Papers with number 08-01.
Length: 48 pages
Date of creation: May 2008
Date of revision:
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More information through EDIRC
Bayesian; time varying cointegration; error correctionmodel; reduced rank regression; Markov Chain Monte Carlo.;
Other versions of this item:
- Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2011. "Bayesian Inference in the Time Varying Cointegration Model," Working Papers 1121, University of Strathclyde Business School, Department of Economics.
- Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2008. "Bayesian Inference in the Time Varying Cointegration Model," Working Paper Series 23-08, The Rimini Centre for Economic Analysis, revised Jan 2008.
- Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2008. "Bayesian Inference in the Time Varying Cointegration Model," SIRE Discussion Papers 2008-60, Scottish Institute for Research in Economics (SIRE).
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Centoni, Marco & Cubadda, Gianluca, 2003. "Measuring the business cycle effects of permanent and transitory shocks in cointegrated time series," Economics Letters, Elsevier, vol. 80(1), pages 45-51, July.
- Jochmann, Markus & Koop, Gary, 2011.
SIRE Discussion Papers
2011-36, Scottish Institute for Research in Economics (SIRE).
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- Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).
- Markus Jochmann & Gary Koop, 2011. "Regime-Switching Cointegration," Working Papers 1125, University of Strathclyde Business School, Department of Economics.
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- Matteo Barigozzi & Antonio Conti, 2013. "On the Stability of Euro Area Money Demand and its Implications for Monetary Policy," LEM Papers Series 2013/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
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