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Computer Automation of General-to-Specific Model Selection Procedures

  • Hans-Martin Krolzig

    ()

    (University of Oxford)

  • David Hendry

    ()

    (Nuffield College, Oxford)

Over the last three decades, the LSE methodology (see Hendry, 1993, for an overview) has emerged as a leading approach for pursuing econometrics. One of its main tenets is the concept of general-to-specific modelling: Starting from a general dynamic statistical model, which captures the essential characteristics of the underlying data set, standard testing procedures are used to reduce its complexity by eliminating statistically insignificant variables and to check the validity of the reductions in order to ensure the congruency of the model. As the reduction process is inherently iterative, many reduction paths can be considered, which may lead to different terminal specifications. Encompassing is then used to test between these, usually non-nested, specifications, and only models which survive the encompassing step are kept for further consideration. If more than one model survives the "testimation" process, it becomes the new general model, and the specification process is re-applied to it. This paper proposes a computer automation of the general-to-specific model-selection process, which we call PcGets (GEneral-To-Specific). Written in Ox (see Doornik, 1998), it is a package designed for general-to-specific modelling of economic processes. In Monte Carlo experiments, the general-to-specific approach of PcGets recovers the specification of the DGP with a remarkable accuracy. The empirical size and power of the specification found by PcGets are investigated and found to be as one would expect if the DGP were known.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 314.

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Date of creation: 01 Mar 1999
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Handle: RePEc:sce:scecf9:314
Contact details of provider: Postal: CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA
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  1. Nicholls, D F & Pagan, A R, 1983. "Heteroscedasticity in Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 51(4), pages 1233-42, July.
  2. 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.
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  5. 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.
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  8. Hendry, David F. & Ericsson, Neil R., 1991. "Modeling the demand for narrow money in the United Kingdom and the United States," European Economic Review, Elsevier, vol. 35(4), pages 833-881, May.
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