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Semi-automatic Non-linear Model selection

  • Jennifer Castle
  • David Hendry

We consider model selection for non-linear dynamic equations with more candidate variables than observations, based on a general class of non-linear-in-the-variables functions, addressing possible location shifts by impulse-indicator saturation.� After an automatic search delivers a simplified congruent terminal model, an encompassing test can be implemented against an investigator's preferred non-linear function.� When that is non-linear in the parameters, such as a threshold model, the overall approach can only be semi-automatic.� The method is applied to re-analyze an empirical model of real wages in the UK over 1860-2004, updated and extended to 2005-2011 for forecast evaluation.

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File URL: http://www.economics.ox.ac.uk/materials/papers/12731/paper654.pdf
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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 654.

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Date of creation: 16 May 2013
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Handle: RePEc:oxf:wpaper:654
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  1. Ericsson, Neil R & Hendry, David F & Prestwich, Kevin M, 1998. " The Demand for Broad Money in the United Kingdom, 1878-1993," Scandinavian Journal of Economics, Wiley Blackwell, vol. 100(1), pages 289-324, March.
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  3. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207, March.
  4. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Ragnar Nymoen, 2012. "Mis-specification Testing: Non-Invariance of Expectations Models of Inflation," Working Paper Series 50_12, The Rimini Centre for Economic Analysis.
  5. Clements, Michael P & Smith, Jeremy, 1996. "A Monte Carlo Study of the Forecasting Performance of Empirical Setar Models," The Warwick Economics Research Paper Series (TWERPS) 464, University of Warwick, Department of Economics.
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  7. Perez-Amaral, Teodosio & Gallo, Giampiero M. & White, Halbert, 2005. "A COMPARISON OF COMPLEMENTARY AUTOMATIC MODELING METHODS: RETINA AND PcGets," Econometric Theory, Cambridge University Press, vol. 21(01), pages 262-277, February.
  8. Ricardo Reis, 2006. "Inattentive Producers," Review of Economic Studies, Oxford University Press, vol. 73(3), pages 793-821.
  9. 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.
  10. Milton Friedman & Anna J. Schwartz, 1982. "Monetary Trends in the United States and United Kingdom: Their Relation to Income, Prices, and Interest Rates, 1867–1975," NBER Books, National Bureau of Economic Research, Inc, number frie82-2, 07.
  11. Castle, Jennifer L. & Hendry, David F., 2009. "The long-run determinants of UK wages, 1860-2004," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 5-28, March.
  12. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C47-C75.
  13. Nielsen, Heino Bohn, 2009. "Comment on "The long-run determinants of UK wages, 1860-2004"," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 29-34, March.
  14. Castle, Jennifer L. & Hendry, David F., 2010. "A low-dimension portmanteau test for non-linearity," Journal of Econometrics, Elsevier, vol. 158(2), pages 231-245, October.
  15. Grayham E. Mizon & David F. Hendry, 1998. "Exogeneity, causality, and co-breaking in economic policy analysis of a small econometric model of money in the UK," Empirical Economics, Springer, vol. 23(3), pages 267-294.
  16. Layard, Richard & Nickell, Stephen & Jackman, Richard, 1991. "Unemployment: Macroeconomic Performance and the Labour Market," OUP Catalogue, Oxford University Press, number 9780198284345, March.
  17. Quandt, Richard E., 1983. "Computational problems and methods," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 12, pages 699-764 Elsevier.
  18. Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011. "Evaluating Automatic Model Selection," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-33, February.
  19. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
  20. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2008. "Model Selection when there are Multiple Breaks," Economics Series Working Papers 407, University of Oxford, Department of Economics.
  21. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-10, November.
  22. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
  23. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, School of Economics and Management, University of Aarhus.
  24. De Gooijer, Jan G. & Kumar, Kuldeep, 1992. "Some recent developments in non-linear time series modelling, testing, and forecasting," International Journal of Forecasting, Elsevier, vol. 8(2), pages 135-156, October.
  25. David Hendry & Carlos Santos, 2010. "An Automatic Test of Super Exogeneity," Economics Series Working Papers 476, University of Oxford, Department of Economics.
  26. Jennifer L. Castle, 2005. "Evaluating PcGets and RETINA as Automatic Model Selection Algorithms," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 837-880, December.
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