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Estimating structural macroeconomic shocks through long-run recursive restrictions on vector autoregressive models: the problem of identification

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  • Mark P. Taylor

    (Department of Economics, University of Warwick, and Centre for Economic Policy Research, UK)

Abstract

We demonstrate that a popular method of estimating underlying structural macroeconomic shocks and their impulse-response functions through recursive long-run structural restrictions on a vector autoregressive representation is not uniquely identified. We show, however, that it may be possible to infer additional qualitative restrictions to achieve identification. We illustrate with two applied examples, corresponding to a simple aggregate supply-aggregate demand framework for the USA and to a stochastic Mundell-Fleming-Dornbusch framework for the USA and Japan. The second example also illustrates how over-identifying restrictions of the underlying framework may be examined informally. Copyright © 2004 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/ijfe.247
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal International Journal of Finance & Economics.

Volume (Year): 9 (2004)
Issue (Month): 3 ()
Pages: 229-244

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Handle: RePEc:ijf:ijfiec:v:9:y:2004:i:3:p:229-244

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  1. Ahmed, Shaghil & Ickes, Barry W. & Ping Wang & Byung Sam Yoo, 1993. "International Business Cycles," American Economic Review, American Economic Association, vol. 83(3), pages 335-59, June.
  2. Jordi Galí & Richard Clarida, 1993. "Sources of real exchage rate fluctuations: How important are nominal shocks?," Economics Working Papers 66, Department of Economics and Business, Universitat Pompeu Fabra, revised Jan 1994.
  3. Bayoumi, Tamim & Taylor, Mark P, 1995. "Macro-economic Shocks, the ERM, and Tri-polarity," The Review of Economics and Statistics, MIT Press, vol. 77(2), pages 321-31, May.
  4. Kilian, Lutz, 2001. "Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(3), pages 161-79, April.
  5. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
  6. repec:cup:macdyn:v:5:y:2001:i:4:p:466-81 is not listed on IDEAS
  7. Matthew D. Shapiro & Mark W. Watson, 1989. "Sources of Business Cycle Fluctuations," NBER Working Papers 2589, National Bureau of Economic Research, Inc.
  8. Granger, Clive W.J., 2001. "Overview Of Nonlinear Macroeconometric Empirical Models," Macroeconomic Dynamics, Cambridge University Press, vol. 5(04), pages 466-481, September.
  9. Lothian, James R. & Taylor, Mark P., 1997. "Real exchange rate behavior," Journal of International Money and Finance, Elsevier, vol. 16(6), pages 945-954, December.
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Cited by:
  1. Alexius, Annika & Post, Erik, 2005. "Exchange Rates and Asymmetric Shocks in Small Open Economies," Working Paper Series 2005:10, Uppsala University, Department of Economics.
  2. Clarida, Richard H. & Mark P. Taylor, 2002. "Nonlinear Permanent -Temporary Decompositions in Macroeconomics and Finance," Royal Economic Society Annual Conference 2002 51, Royal Economic Society.
  3. Helmut Lütkepohl, 2012. "Reducing Confidence Bands for Simulated Impulse Responses," Discussion Papers of DIW Berlin 1235, DIW Berlin, German Institute for Economic Research.
  4. Ossama Mikhail, 2005. "What Happens After A Technology Shock? A Bayesian Perspective," Macroeconomics 0510016, EconWPA.

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