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

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  • Adrian Pagan
  • M. Hashem Pesaran

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 influential 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 effects. 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 CESifo Group Munich in its series CESifo Working Paper Series with number 1924.

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Date of creation: 2007
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Handle: RePEc:ces:ceswps:_1924

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

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References

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  1. Peter Ireland, 1999. "A Method for Taking Models to the Data," Computing in Economics and Finance 1999, Society for Computational Economics 1233, Society for Computational Economics.
  2. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, American Economic Association, vol. 79(4), pages 655-73, September.
  3. 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.
  4. M Pesaran & Yongcheol Shin, 2004. "Long-Run Structural Modelling," ESE Discussion Papers, Edinburgh School of Economics, University of Edinburgh 44, Edinburgh School of Economics, University of Edinburgh.
  5. 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, Oxford University Press, number 9780199296859, October.
  6. Gonzalo, Jesus & Ng, Serena, 2001. "A systematic framework for analyzing the dynamic effects of permanent and transitory shocks," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 25(10), pages 1527-1546, October.
  7. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780198774501, October.
  8. Michael R. Wickens & Roberto Motto, 2001. "Estimating shocks and impulse response functions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 16(3), pages 371-387.
  9. Alejandro Justiniano & Bruce Preston, 2006. "Can Structural Small Open Economy Models Account For The Influence Of Foreign Disturbances?," CAMA Working Papers 2006-12, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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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, Elsevier, vol. 26(6), pages 1147-1160, November.
  2. Soyoung Kim & Jaewoo Lee, 2008. "International Macroeconomic Fluctuations: A New Open Economy Macroeconomics Interpretation," Working Papers, Hong Kong Institute for Monetary Research 232008, Hong Kong Institute for Monetary Research.
  3. de Mello, Luiz & Moccero, Diego, 2011. "Monetary policy and macroeconomic stability in Latin America: The cases of Brazil, Chile, Colombia and Mexico," Journal of International Money and Finance, Elsevier, Elsevier, vol. 30(1), pages 229-245, February.

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