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We Ran One Regression

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  • David Hendry
  • Hans-Martin Krolzig

Abstract

The recent controversy over model selection in the context of `growth regressions` has led to some remarkably numerous `estimation` strategies, including 4 million regressions by Sala-i-Martin (1997b). Only one regression is really needed, namely the general unrestricted model, appropriately reduced to a parsimonious encompassing congruent representation. Such an outcome was achieved in one run on PcGets, within 15 minutes of receiving from Professor Ley the data set in Fernández et al (2001). We reproduce that equation, and corroborate the findings in Hoover and Perez (2004), who also adopt an automatic general-to-simple approach.

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Bibliographic Info

Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 2004-W17.

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Date of creation: 01 Mar 2004
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Handle: RePEc:oxf:wpaper:2004-w17

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  1. Halbert L. White & Giampiero M. Gallo & Teodosio Pérez Amaral, 2002. "A flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)," Documentos de Trabajo del ICAE 0201, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  2. Carmen Fernandez & Eduardo Ley & Mark Steel, 2001. "Model uncertainty in cross-country growth regressions," Econometrics 0110002, EconWPA.
  3. Kevin Hoover & Harris Dellas, 2003. "Truth and Robustness in Cross-country Growth Regressions," Working Papers 11, University of California, Davis, Department of Economics.
  4. David F. Hendry & Hans-Martin Krolzig, 2005. "The Properties of Automatic "GETS" Modelling," Economic Journal, Royal Economic Society, vol. 115(502), pages C32-C61, 03.
  5. Peter C.B. Phillips, 1995. "Automated Forecasts of Asia-Pacific Economic Activity," Cowles Foundation Discussion Papers 1103, Cowles Foundation for Research in Economics, Yale University.
  6. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  7. Phillips, Peter C B, 1996. "Econometric Model Determination," Econometrica, Econometric Society, vol. 64(4), pages 763-812, July.
  8. 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.
  9. McAleer, Michael & Pagan, Adrian R & Volker, Paul A, 1985. "What Will Take the Con out of Econometrics?," American Economic Review, American Economic Association, vol. 75(3), pages 293-307, June.
  10. Leamer, Edward E & Leonard, Herman B, 1983. "Reporting the Fragility of Regression Estimates," The Review of Economics and Statistics, MIT Press, vol. 65(2), pages 306-17, May.
  11. Levine, Ross & Renelt, David, 1991. "A sensitivity analysis of cross-country growth regressions," Policy Research Working Paper Series 609, The World Bank.
  12. Jerzy Mycielski & Michal Kurcewicz, 2004. "A Specification Search Algorithm for Cointegrated Systems," Computing in Economics and Finance 2004 321, Society for Computational Economics.
  13. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, October.
  14. Julia Campos & David F. Hendry & Hans-Martin Krolzig, 2003. "Consistent Model Selection by an Automatic "Gets" Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 803-819, December.
  15. Temple, Jonathan, 2000. "Growth Regressions and What the Textbooks Don't Tell You," Bulletin of Economic Research, Wiley Blackwell, vol. 52(3), pages 181-205, July.
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