The Pre-Eminence of Theory versus the European CVAR Perspective in Macroeconometric Modeling
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.
Volume (Year): 3 (2009)
Issue (Month): ()
|Contact details of provider:|| Postal: Kiellinie 66, D-24105 Kiel|
Phone: +49 431 8814-1
Fax: +49 431 8814528
Web page: http://www.economics-ejournal.org/
More information through EDIRC
References listed on IDEAS
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.:
- 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 (IfW), vol. 3, pages 1-21.
- David Colander, 2009. "Economists, Incentives, Judgment, and the European CVAR Approach to Macroeconometrics," Middlebury College Working Paper Series 0912, Middlebury College, Department of Economics.
- Ireland, Peter N., 2004. "A method for taking models to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1205-1226, March.
- Peter Ireland, 1999. "A Method for Taking Models to the Data," Computing in Economics and Finance 1999 1233, Society for Computational Economics.
- Peter N. Ireland, 1999. "A Method for Taking Models to the Data," Boston College Working Papers in Economics 421, Boston College Department of Economics.
- Peter N. Ireland, 1999. "A method for taking models to the data," Working Paper 9903, Federal Reserve Bank of Cleveland.
- Peter Ireland, 1999. "Matlab code for A Method for Taking Models to the Data," QM&RBC Codes 46, Quantitative Macroeconomics & Real Business Cycles.
- Kevin D. Hoover & Soren Johansen & Katarina Juselius, 2008. "Allowing the Data to Speak Freely: The Macroeconometrics of the Cointegrated Vector Autoregression," American Economic Review, American Economic Association, vol. 98(2), pages 251-255, May.
- 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.
- Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124, August.
- 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.
- Spanos, Aris, 1995. "On theory testing in econometrics : Modeling with nonexperimental data," Journal of Econometrics, Elsevier, vol. 67(1), pages 189-226, May.
- 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.
- Spanos, Aris, 1990. "The simultaneous-equations model revisited : Statistical adequacy and identification," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 87-105.
- Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, December. Full references (including those not matched with items on IDEAS)