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General--to--Specific Reductions of Vector Autoregressive Processes

  • Hans-Martin Krolzig

Unrestricted reduced form vector autoregressive (VAR) models have become a dominant research strategy in empirical macroeconomics since Sims (1980) critique of traditional macroeconometric modeling. They are however subjected to the curse of dimensionality. In this paper we propose general-to-specific reductions of VAR models and consider computer-automated model selection algorithms embodied in PcGets (see Krolzig and Hendry, 2000) for doing so. Starting from the unrestricted VAR, standard testing procedures eliminate statistically-insignificant variables, with diagnostic tests checking the validity of reductions, ensuring a congruent final selection. Since jointly selecting and diagnostic testing eludes theoretical analysis, we evaluate the proposed strategy by simulation. The Monte Carlo experiments show that PcGets recovers the DGP specification from a large unrestricted VAR model with size and power close to commencing from the DGP itself. The application of the proposed reduction strategy to a US monetary system demonstrates the feasibility of PcGets for the analysis of large macroeconomic data sets.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 164.

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Date of creation: 01 Apr 2001
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Handle: RePEc:sce:scecf1:164
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  1. Hans-Martin Krolzig, 2000. "Computer Automation of General-to-Specific Model Selection Procedures," Econometric Society World Congress 2000 Contributed Papers 0411, Econometric Society.
  2. 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.
  3. David F. Hendry & Hans-Martin Krolzig, 1999. "Improving on 'Data mining reconsidered' by K.D. Hoover and S.J. Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 202-219.
  4. repec:cup:cbooks:9780521650694 is not listed on IDEAS
  5. Hendry, David F, 1980. "Econometrics-Alchemy or Science?," Economica, London School of Economics and Political Science, vol. 47(188), pages 387-406, November.
  6. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, March.
  7. Lawrence J. Christiano & Martin Eichenbaum & Charles Evans, 1994. "The effects of monetary policy shocks: evidence from the Flow of Funds," Working Paper Series, Macroeconomic Issues 94-2, Federal Reserve Bank of Chicago.
  8. 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 113-44, January.
  9. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, March.
  10. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976 Elsevier.
  11. Ralf Brueggemann & Helmut Leutkepohl, 2000. "Lag Selection in Subset VAR Models with an Application to a U.S. Monetary System," Econometric Society World Congress 2000 Contributed Papers 0821, Econometric Society.
  12. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
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