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Data Mining Reconsidered: Encompassing And The General-To-Specific Approach To Specification Search

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Kevin D. Hoover
Stephen J. Perez

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Abstract

The effectiveness of one aspect of the London School of Economics (LSE) approach to econometrics is assessed in a simulation study. The paper uses a data set and nine models analogous to those in Lovell's (1983) study of data mining. A simplified general-to-specific algorithm is tested in a simulation framework. While the study documents some of the pitfalls of the general-to-specific approach, it is, on the whole, supportive of the effectiveness of the LSE methodology as applied to stationary data with relatively simple dynamics. The general-to-specific methodology clearly dominates the alternative search methodologies investigated by Lovell.

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Paper provided by California Davis - Department of Economics in its series Department of Economics with number 97-27.

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Handle: RePEc:fth:caldec:97-27

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Postal: University of California Davis - Department of Economics. One Shields Ave., California 95616-8578
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Hendry, D.F. & Richard, J.-F., 1987. "Recent developments in the theory of encompassing," CORE Discussion Papers 1987022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220 National Bureau of Economic Research, Inc. [Downloadable!]
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  3. Hoover, Kevin D, 1988. "On the Pitfalls of Untested Common-Factor Restrictions: The Case of the Inverted Fisher Hypothesis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(2), pages 125-38, May.
  4. Pagan, Adrian, 1987. " Three Econometric Methodologies: A Critical Appraisal," Journal of Economic Surveys, Blackwell Publishing, vol. 1(1), pages 3-24.
  5. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February. [Downloadable!] (restricted)
  6. Hendry, David F & Mizon, Grayham Ernest, 1985. "Procrustean Econometrics: Stretching and Squeezing Data," CEPR Discussion Papers 68, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  7. Mizon, Grayham E & Richard, Jean-Francois, 1986. "The Encompassing Principle and Its Application to Testing Non-nested Hypotheses," Econometrica, Econometric Society, vol. 54(3), pages 657-78, May. [Downloadable!] (restricted)
  8. Stock, James H & Watson, Mark W, 1988. "Variable Trends in Economic Time Series," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 147-74, Summer. [Downloadable!] (restricted)
  9. Phillips, P C B, 1988. "Reflections on Econometric Methodology," The Economic Record, The Economic Society of Australia, vol. 64(187), pages 344-59, December.
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  10. Neil R. Ericsson & Julia Campos & Hong-Anh Tran, 1991. "PC-give and David Hendry's econometric methodology," International Finance Discussion Papers 406, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  11. Gregory D. Hess & Christopher S. Jones & Richard D. Porter, 1994. "The predictive failure of the Baba, Hendry and Starr model of the demand for M1 in the United States," Research Working Paper 94-06, Federal Reserve Bank of Kansas City.
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  12. Mayer, Thomas, 1980. "Economics as a Hard Science: Realistic Goal or Wishful Thinking?," Economic Inquiry, Oxford University Press, vol. 18(2), pages 165-78, April.
  13. Dolado, Juan J & Jenkinson, Tim & Sosvilla-Rivero, Simon, 1990. " Cointegration and Unit Roots," Journal of Economic Surveys, Blackwell Publishing, vol. 4(3), pages 249-73.
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