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DSGE Model Restrictions for Structural VAR Identification

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  • Philip Liu

    (International Monetary Fund)

  • Konstantinos Theodoridis

    (Bank of England)

Abstract

The identification of reduced-form VAR models has been the subject of numerous debates in the literature. Different sets of identifying assumptions can lead to very different conclusions regarding the effects of shocks. This paper proposes a theoretically consistent identification strategy using restrictions implied by a DSGE model. Monte Carlo simulations suggest that both quantitative and qualitative restrictions work well together, where they act as complements to each other, in minimizing errors in finding the correct VAR identification. When using misspecified model restrictions, the data tend to push the identified VAR responses away from the misspecified model and closer to the true data-generating process.

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Bibliographic Info

Article provided by International Journal of Central Banking in its journal International Journal of Central Banking.

Volume (Year): 8 (2012)
Issue (Month): 4 (December)
Pages: 61-95

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Handle: RePEc:ijc:ijcjou:y:2012:q:4:a:3

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  1. Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramírez & Thomas Sargent, 2005. "A, B, C’s, (and D’s) for understanding VARs," Working Paper 2005-09, Federal Reserve Bank of Atlanta.
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Cited by:
  1. Gehrke, Britta & Yao, Fang, 2013. "Sources of Real Exchange Rate Fluctuations: The Role of Supply Shocks Revisited," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79821, Verein für Socialpolitik / German Economic Association.
  2. Tim Robinson, 2013. "Estimating and Identifying Empirical BVAR-DSGE Models for Small Open Economies," RBA Research Discussion Papers rdp2013-06, Reserve Bank of Australia.
  3. Theodoridis, Konstantinos, 2011. "An efficient minimum distance estimator for DSGE models," Bank of England working papers 439, Bank of England.

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