Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables
AbstractMacroeconomists working with multivariate models typically face uncertainty over which (if any) of their variables have long run steady states which are subject to breaks. Furthermore, the nature of the break process is often unknown. In this paper, we draw on methods from the Bayesian clustering literature to develop an econometric methodology which: i) finds groups of variables which have the same number of breaks; and ii) determines the nature of the break process within each group. We present an application involving a five-variate steady-state VAR.
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Bibliographic InfoPaper provided by University of Strathclyde Business School, Department of Economics in its series Working Papers with number 1111.
Length: 17 pages
Date of creation: Apr 2011
Date of revision:
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More information through EDIRC
mixtures of normals; steady state VARs; Bayesian;
Other versions of this item:
- Chan, Joshua C.C. & Koop, Gary, 2011. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," SIRE Discussion Papers 2011-22, Scottish Institute for Research in Economics (SIRE).
- Joshua C.C. Chan & Gary Koop, 2013. "Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables," ANU Working Papers in Economics and Econometrics 2013-603, Australian National University, College of Business and Economics, School of Economics.
- Joshua C C Chan & Gary Koop, 2012. "Modelling Breaks And Clusters In The Steady States Of Macroeconomic Variables," CAMA Working Papers 2012-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-06-11 (All new papers)
- NEP-ECM-2011-06-11 (Econometrics)
- NEP-ETS-2011-06-11 (Econometric Time Series)
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.:
- Marco Del Negro & Frank Schorfheide, 2008.
"Forming priors for DSGE models (and how it affects the assessment of nominal rigidities),"
320, Federal Reserve Bank of New York.
- Del Negro, Marco & Schorfheide, Frank, 2008. "Forming priors for DSGE models (and how it affects the assessment of nominal rigidities)," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1191-1208, October.
- Frank Schorfheide & Marco Del Negro, 2007. "Forming Priors for DSGE Models (and How It Affects the Assessment of Nominal Rigidities)," 2007 Meeting Papers 283, Society for Economic Dynamics.
- Marco Del Negro & Frank Schorfheide, 2006. "Forming priors for DSGE models (and how it affects the assessment of nominal rigidities)," Working Paper 2006-16, Federal Reserve Bank of Atlanta.
- Del Negro, Marco & Schorfheide, Frank, 2007. "Forming Priors for DSGE Models (and How It Affects the Assessment of Nominal Rigidities)," CEPR Discussion Papers 6119, C.E.P.R. Discussion Papers.
- Marco Del Negro & Frank Schorfheide, 2008. "Forming Priors for DSGE Models (and How it Affects the Assessment of Nominal Rigidities)," NBER Working Papers 13741, National Bureau of Economic Research, Inc.
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