Journal Article

No. 2009-10 | April 07, 2009
The Pre-Eminence of Theory versus the European CVAR Perspective in Macroeconometric Modeling PDF Icon

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.

JEL Classification

B4 C1 C3

Citation

Aris Spanos (2009). The Pre-Eminence of Theory versus the European CVAR Perspective in Macroeconometric Modeling. Economics: The Open-Access, Open-Assessment E-Journal, Vol. 3, 2009-10. http://dx.doi.org/10.5018/economics-ejournal.ja.2009-10

Assessment

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Citations (@RePEc): 6
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Comments and Questions


Anonymous - "theory first"
April 11, 2009 - 20:07

I enjoyed reading the paper, but there are no references to some of the leading DSGE models developed in central banks and academia (Christiano, Eichembaum and Evans...) and latest improvements in estimation techniques (only Ireland 2004 is cited). In addition, there are big improvements in the validation techniques that are ...[more]

... ignored in this paper and not commented (eg. Del Negro, Shorfheide, Smets and Wouters 2007). Thus, "theory first" and "validation" next.

I think it would be easier to write a similar paper in terms of the trade-off between forecast accuracy (and no theory) and economic coherency (and poor forecast accuracy). I dont think DSGE modelers dont care about the empirical support of their theories; they just have a different metric to assess the usefulness of their theories.