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General-to-Specific Model Selection Procedures for Structural Vector Autoregressions

Listed author(s):
  • Hans-Martin Krolzig

    ()

    (Department of Economics, and Nuffield College, Oxford University)

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper we propose general-to-specific model selection procedures to overcome these limitations. After showing that single-equation procedures are efficient for the reduction of the SVAR, but generally not for the reduction of its reduced form, the proposed reduction procedure is computer-automated using PcGets and its small-sample properties are evaluated in a realistic Monte Carlo experiment. The model selection procedure is shown to recover the DGP specification from a large unrestricted SVAR model with controlled size and power. The impulse responses generated by the selected SVAR are compared to those of the unrestricted and reduced VAR and found to be more precise and accurate. The proposed reduction strategy is then applied to the US monetary system considered by Christiano, Eichenbaum and Evans (1996). Although the selection process is hampered by the misspecification of the unrestricted VAR, the results are consistent with the Monte Carlo and question the validity of the impulses responses generated by the full system.

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File URL: http://www.nuff.ox.ac.uk/economics/papers/2003/W15/hmk03a.pdf
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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2003-W15.

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Length: 24 pages
Date of creation: 01 Mar 2003
Handle: RePEc:nuf:econwp:0315
Contact details of provider: Web page: https://www.nuffield.ox.ac.uk/economics/

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  1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
  2. Brüggemann, Ralf & Krolzig, Hans-Martin & Lütkepohl, Helmut, 2002. "Comparison of model reduction methods for VAR processes," SFB 373 Discussion Papers 2002,80, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  3. Christiano, Lawrence J & Eichenbaum, Martin & Evans, Charles, 1996. "The Effects of Monetary Policy Shocks: Evidence from the Flow of Funds," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 16-34, February.
  4. Selva Demiralp & Kevin D. Hoover, 2003. "Searching for the Causal Structure of a Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 745-767, December.
  5. Sims, Christopher A., 1992. "Interpreting the macroeconomic time series facts : The effects of monetary policy," European Economic Review, Elsevier, vol. 36(5), pages 975-1000, June.
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  7. Kevin D. Hoover & Stephen J. Perez, 1999. "Data mining reconsidered: encompassing and the general-to-specific approach to specification search," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 167-191.
  8. David F. Hendry & Hans-Martin Krolzig, 2005. "The Properties of Automatic "GETS" Modelling," Economic Journal, Royal Economic Society, vol. 115(502), pages 32-61, 03.
  9. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  10. Dungey, Mardi & Pagan, Adrian, 2000. "A Structural VAR Model of the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 76(235), pages 321-342, December.
  11. Krolzig, Hans-Martin & Peter Flaschel, 2003. "Wage and Price Phillips Curves," Royal Economic Society Annual Conference 2003 128, Royal Economic Society.
  12. Hendry, David F, 1980. "Econometrics-Alchemy or Science?," Economica, London School of Economics and Political Science, vol. 47(188), pages 387-406, November.
  13. Hans-Martin Krolzig, 2001. "General--to--Specific Reductions of Vector Autoregressive Processes," Computing in Economics and Finance 2001 164, Society for Computational Economics.
  14. Hendry, David F. & Mizon, Grayham E., 2001. "Reformulating empirical macro-econometric modelling," Discussion Paper Series In Economics And Econometrics 0104, Economics Division, School of Social Sciences, University of Southampton.
  15. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, April.
  16. Omtzigt Pieter, 2002. "Automatic identification and restriction of the cointegration space," Economics and Quantitative Methods qf0213, Department of Economics, University of Insubria.
  17. Swanson, N.R. & Granger, C.W.J., 1994. "Impulse Response Functions Based on Causal Approach to Residual Orthogonalization in Vector Autoregressions," Papers 9-94-1, Pennsylvania State - Department of Economics.
  18. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
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