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On Econometric Analysis of Structural Systems with Permanent and Transitory Shocks and Exogenous Variables

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  • Pagan, A.
  • Pesaran, M.H.

Abstract

This paper considers the implications of the permanent/transitory decomposition of shocks for identification of structural models in the general case where the model might contain more than one permanent structural shock. It provides a simple and intuitive generalization of the in.uential work of Blanchard and Quah (1989), and shows that structural equations for which there are known permanent shocks must have no error correction terms present in them, thereby freeing up the latter to be used as instruments in estimating their parameters. The proposed approach is illustrated by a re-examination of the identification scheme used in a monetary model by Wickens and Motta (2001), and in a well known paper by Gali (1992) which deals with the construction of an IS-LM model with supply-side e¤ects. We show that the latter imposes more short-run restrictions than are needed because of a failure to fully utilize the cointegration information.

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Bibliographic Info

Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0662.

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Length: 29
Date of creation: Jan 2007
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Handle: RePEc:cam:camdae:0662

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Related research

Keywords: Permanent shocks; structural identification; error correction models; IS-LM models.;

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References

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  1. Olivier Jean Blanchard & Danny Quah, 1990. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," NBER Working Papers 2737, National Bureau of Economic Research, Inc.
  2. Alejandro Justiniano & Bruce Preston, 2008. "Can Structural Small Open Economy Models Account for the Influence of Foreign Disturbances?," NBER Working Papers 14547, National Bureau of Economic Research, Inc.
  3. M Pesaran & Yongcheol Shin, 2004. "Long-Run Structural Modelling," ESE Discussion Papers 44, Edinburgh School of Economics, University of Edinburgh.
  4. A. R. Pagan & J. C. Robertson, 1998. "Structural Models Of The Liquidity Effect," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 202-217, May.
  5. Gonzalo, Jesús & Ng, Serena, . "A systematic framework for analyzing the dynamic effects of permanent and transitory shocks," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/6203, Universidad Carlos III de Madrid.
  6. Peter N. Ireland, 1999. "A Method for Taking Models to the Data," Boston College Working Papers in Economics 421, Boston College Department of Economics.
  7. Michael R. Wickens & Roberto Motto, 2001. "Estimating shocks and impulse response functions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 371-387.
  8. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
  9. Garratt, Anthony & Lee, Kevin & Pesaran, M. Hashem & Shin, Yongcheol, 2006. "Global and National Macroeconometric Modelling: A Long-Run Structural Approach," OUP Catalogue, Oxford University Press, number 9780199296859.
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Cited by:
  1. Dungey, Mardi & Fry, Renée, 2009. "The identification of fiscal and monetary policy in a structural VAR," Economic Modelling, Elsevier, vol. 26(6), pages 1147-1160, November.
  2. Luiz de Mello & Diego Moccero, 2007. "Monetary Policy and Macroeconomic Stability in Latin America: The Cases of Brazil, Chile, Colombia and Mexico," OECD Economics Department Working Papers 545, OECD Publishing.
  3. Soyoung Kim & Jaewoo Lee, 2008. "International Macroeconomic Fluctuations: A New Open Economy Macroeconomics Interpretation," Working Papers 232008, Hong Kong Institute for Monetary Research.

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