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How much Structure in Empirical Models?

In: Palgrave Handbook of Econometrics

Author

Listed:
  • Fabio Canova

Abstract

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways, but solved only if DSGEs are completely reparameterized or respecified. The potential misspecification of the structural relationships gives Bayesian methods an edge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecification of the structural relationships but must firmly tie SVARs to the class of DSGE models which could have generated the data.

Suggested Citation

  • Fabio Canova, 2009. "How much Structure in Empirical Models?," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 2, pages 68-97, Palgrave Macmillan.
  • Handle: RePEc:pal:palchp:978-0-230-24440-5_2
    DOI: 10.1057/9780230244405_2
    as

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