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On determining the importance of a regressor with small and undersized samples

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Author Info
Peter Sandholt Jensen
Allan H. Würtz () (Department of Economics, University of Aarhus, Denmark)

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Abstract

A problem encountered in, for instance, growth empirics is that the number of explanatory variables is large compared to the number of observations. This makes it infeasible to condition on all variables in order to determine the importance of a variable of interest. We prove identifying assumptions under which the problem is not ill-posed. Under these assumptions, we derive properties of the most commonly used methods: Extreme bounds analysis, Sala-i-Martin’s method, BACE, generalto- specific, minimum t-statistics, BIC and AIC. We propose a new method and show that it has good finite sample properties.

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Publisher Info
Paper provided by School of Economics and Management, University of Aarhus in its series Economics Working Papers with number 2006-08.

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Length: 39
Date of creation: 14 Jul 2006
Date of revision:
Handle: RePEc:aah:aarhec:2006-08

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Related research
Keywords: AIC; BACE; BIC; extreme bounds analysis; general-to-specific; identification; ill-posed inverse problem; robustness; sensitivity analysis;

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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References listed on IDEAS
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  1. Bleaney, Michael & Nishiyama, Akira, 2002. " Explaining Growth: A Contest between Models," Journal of Economic Growth, Springer, vol. 7(1), pages 43-56, March. [Downloadable!] (restricted)
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    Other versions:
  4. Durlauf, Steven N. & Johnson, Paul A. & Temple, Jonathan R.W., 2005. "Growth Econometrics," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 8, pages 555-677 Elsevier. [Downloadable!] (restricted)
    Other versions:
  5. Durlauf, Steven N., 2001. "Manifesto for a growth econometrics," Journal of Econometrics, Elsevier, vol. 100(1), pages 65-69, January. [Downloadable!] (restricted)
  6. Carrasco, Marine & Florens, Jean-Pierre & Renault, Eric, 2007. "Linear Inverse Problems in Structural Econometrics Estimation Based on Spectral Decomposition and Regularization," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 77 Elsevier. [Downloadable!] (restricted)
  7. Bruce E. Hansen, 1999. "Discussion of 'Data mining reconsidered'," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 192-201.
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    Other versions:
  9. McAleer, Michael & Pagan, Adrian, 1985. "What Will Take the Con Out of Econometrics?," CEPR Discussion Papers 39, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  10. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  11. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-83, May. [Downloadable!] (restricted)
  12. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December. [Downloadable!] (restricted)
  13. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February. [Downloadable!] (restricted)
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  14. Levine, Ross & Renelt, David, 1992. "A Sensitivity Analysis of Cross-Country Growth Regressions," American Economic Review, American Economic Association, vol. 82(4), pages 942-63, September. [Downloadable!] (restricted)
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  15. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March. [Downloadable!] (restricted)
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  16. Granger, Clive W. J. & Uhlig, Harald F., 1990. "Reasonable extreme-bounds analysis," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 159-170. [Downloadable!] (restricted)
    Other versions:
  17. repec:att:wimass:1920418 is not listed on IDEAS
  18. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December. [Downloadable!] (restricted)
  19. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Economics Papers 2004-W17, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
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Cited by:
(explanations, 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. Stanislav Anatolyev, 2009. "Inference in Regression Models with Many Regressors," Working Papers w0125, Center for Economic and Financial Research (CEFIR). [Downloadable!]
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