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Making a match: combining theory and evidence in policy-oriented macroeconomic modelling

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  • Alasdair Scott
  • George Kapetanios
  • Adrian Pagan

Abstract

A persistent question arising in the development of models for the analysis of macroeconomic policy has been the relative role of economic theory and evidence (data) in their construction. This paper looks at some strategies for transforming a Conceptual Model to become a Data-Adjusted Model, and how to adjust further to an Operational Model for policy analysis. Using a typical dynamic GE small open economy calibrated to UK data, we examine how some simple but formal econometric tests can be applied to test the match of the CM to the data. We also use the CM as a laboratory to assess model-building strategies. Our example suggests that, since one will never be sure that the choice of variables is appropriate, it is better to start with a CM and work towards making it match the data than attempting the converse

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 462.

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Date of creation: 11 Nov 2005
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Handle: RePEc:sce:scecf5:462

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Keywords: economic model;

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Cited by:
  1. Leung, Charles Ka Yui & Shi, Song & Tang, Edward Chi Ho, 2013. "Commodity house prices," MPRA Paper 49489, University Library of Munich, Germany.
  2. Dufour, Jean-Marie & Taamouti, Abderrahim, 2010. "Short and long run causality measures: Theory and inference," Journal of Econometrics, Elsevier, vol. 154(1), pages 42-58, January.
  3. Mala Raghavan & George Athanasopoulos & Param Silvapulle, 2013. "Canadian Monetary Policy Analysis using a Structural VARMA Model," Monash Econometrics and Business Statistics Working Papers 4/13, Monash University, Department of Econometrics and Business Statistics.
  4. Massimo Franchi & Anna Vidotto, 2012. "A simple check for VAR representations of DSGE models," DSS Empirical Economics and Econometrics Working Papers Series 2012/5, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
  5. Philip Liu & Konstantinos Theodoridis, 2012. "DSGE Model Restrictions for Structural VAR Identification," International Journal of Central Banking, International Journal of Central Banking, vol. 8(4), pages 61-95, December.
  6. Syed Abul Basher & Alfred Haug & Perry Sadorsky, 2010. "Oil Prices, Exchange Rates and Emerging Stock Markets," Working Papers 1014, University of Otago, Department of Economics, revised Sep 2010.
  7. Philippe Jeanfils & Koen Burggraeve, 2005. "Noname - A new quarterly model for Belgium," Working Paper Research 68, National Bank of Belgium.
  8. Franchi, Massimo & Vidotto, Anna, 2013. "A check for finite order VAR representations of DSGE models," Economics Letters, Elsevier, vol. 120(1), pages 100-103.
  9. Jarkko Jääskelä & David Jennings, 2010. "Monetary Policy and the Exchange Rate: Evaluation of VAR Models," RBA Research Discussion Papers rdp2010-07, Reserve Bank of Australia.
  10. Martin Fukac & Adrian Pagan, 2010. "Limited information estimation and evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 55-70.
  11. Jääskelä, Jarkko P. & Jennings, David, 2011. "Monetary policy and the exchange rate: Evaluation of VAR models," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1358-1374.
  12. D.S. Poskitt & Wenying Yao, 2012. "VAR Modeling and Business Cycle Analysis: A Taxonomy of Errors," Monash Econometrics and Business Statistics Working Papers 11/12, Monash University, Department of Econometrics and Business Statistics.

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