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The Pre-Eminence of Theory versus the European CVAR Perspective in Macroeconometric Modeling

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  • Spanos, Aris

Abstract

The primary aim of the paper is to place current methodological discussions in macroeconometric modeling contrasting the 'theory first' versus the 'data first' perspectives in the context of a broader methodological framework with a view to constructively appraise them. In particular, the paper focuses on Colander's argument in his paper 'Economists, Incentives, Judgement, and the European CVAR Approach to Macroeconometrics' contrasting two different perspectives in Europe and the US that are currently dominating empirical macroeconometric modeling and delves deeper into their methodological/philosophical underpinnings. It is argued that the key to establishing a constructive dialogue between them is provided by a better understanding of the role of data in modern statistical inference, and how that relates to the centuries old issue of the realisticness of economic theories. --

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Bibliographic Info

Article provided by Kiel Institute for the World Economy in its journal Economics: The Open-Access, Open-Assessment E-Journal.

Volume (Year): 3 (2009)
Issue (Month): 10 ()
Pages: 1-14

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Handle: RePEc:zbw:ifweej:7596

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Keywords: Econometric methodology; 'general-to-specific'; pre-eminence of theory; cointegrated VAR; statistical adequacy; realisticness of a theory;

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References

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  1. Colander, David C., 2009. "Economists, incentives, judgment, and the European CVAR approach to macroeconometrics," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 3(9), pages 1-21.
  2. Kevin D. Hoover & Katarina Juselius & Søren Johansen, 2007. "Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression," Discussion Papers 07-35, University of Copenhagen. Department of Economics.
  3. Peter Ireland, 1999. "A Method for Taking Models to the Data," Computing in Economics and Finance 1999 1233, Society for Computational Economics.
  4. Aris Spanos, 2001. "Revisiting data mining: 'hunting' with or without a license," Journal of Economic Methodology, Taylor & Francis Journals, vol. 7(2), pages 231-264.
  5. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124.
  6. Aris Spanos, 2006. "Revisiting the omitted variables argument: Substantive vs. statistical adequacy," Journal of Economic Methodology, Taylor & Francis Journals, vol. 13(2), pages 179-218.
  7. Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, December.
  8. Spanos, Aris, 1990. "The simultaneous-equations model revisited : Statistical adequacy and identification," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 87-105.
  9. Spanos, Aris, 1995. "On theory testing in econometrics : Modeling with nonexperimental data," Journal of Econometrics, Elsevier, vol. 67(1), pages 189-226, May.
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Citations

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Cited by:
  1. David Colander, 2009. "Economists, Incentives, Judgment, and the European CVAR Approach to Macroeconometrics," Middlebury College Working Paper Series 0912, Middlebury College, Department of Economics.
  2. Julio Lopez-Gallardo & Luis Reyes-Ortiz, 2011. "Effective Demand in the Recent Evolution of the US Economy," Economics Working Paper Archive wp_673, Levy Economics Institute.
  3. Katarina Juselius & Niels Framroze & Finn Tarp, 2011. "The Long-Run Impact of Foreign Aid in 36 African Countries: Insights from Multivariate Time Series Analysis," Working Paper Series UNU-WIDER Working Paper W, World Institute for Development Economic Research (UNU-WIDER).
  4. Jusélius, Katarina, 2009. "Special Issue on Using Econometrics for Assessing Economic Models: An Introduction," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 3(28), pages 1-20.
  5. Spanos, Aris, 2010. "Statistical adequacy and the trustworthiness of empirical evidence: Statistical vs. substantive information," Economic Modelling, Elsevier, vol. 27(6), pages 1436-1452, November.

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