Advertisement

A Further Look at Model Evaluation

  • Bernd Schips
  • Yngve Abrahamsen
Conference paper

Summary

In this chapter we compare the specification tests generally used in econometric model building with recently developed p-step Stone-Geisser prediction tests using jackknife procedures. The comparisons are based on a Monte Carlo study using different structural forms. The structural forms are partly misspecified. Three sets of simulations are presented: A variety of single equation models, a simple multi-equation macro model, and Klein’s Model I using US data. The jackknife based statistics enable a more critical evaluation of the out-of-sample performance of the estimated multi-equation models.

Keywords

Predictive Quality Chow Test Average Percent Error Jackknife Procedure Jackknife Estimate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abrahamsen, Y. (1986), Jackknifed fixpoint estimators for linear and nonlinear econometric models. Paper presented at the International Conference Macromodels’86, Szczyrk, Poland.Google Scholar
  2. Abrahamsen, Y. and Schips, B. (1989), Specification and stability tests versus jackknifing. Some illustrative examples, pp. 37–43 in P. Hackl (ed.), Statistical Analysis and Economic Structural Change. Berlin: Springer-Verlag.Google Scholar
  3. Ball, R.J. (1963), The significance of simultaneous methods of parameter estimates in econometric models. Applied Statistics, 12, 14–25.CrossRefGoogle Scholar
  4. Bergström, R. and Wold, H. (1983), Fixpoint estimation in theory and practice. Göttingen: Vandenhoeck & Ruprecht.Google Scholar
  5. Chong, Y.Y. and Hendry, D.F. (1986), Econometric evaluation of linear macro-economic models. Applied Economics Discussion Paper No. 10, Institute of Economics and Statistics, University of Oxford.Google Scholar
  6. Efron, B. and Gong, G. (1983), A leisurely look at the bootstrap, the jackknife, and cross validation. The American Statistician, 37, 36–48.Google Scholar
  7. Geisser, S. (1974), A predictive approach to the random effect model. Biometrika, 61, 101–107.CrossRefGoogle Scholar
  8. Klein, L.R. (1950), Economic fluctuations in the United States 1921–1941 New York: John Wiley.Google Scholar
  9. Learner, E.E. (1983), Let’s take the con out of econometrics. American Economic Review, 33, 31–43.Google Scholar
  10. Miller, R.G. (1974), The jackknife: A review. Biometrika, 61, 1–15.Google Scholar
  11. Ramsey, J.B. and Gilbert, R. (1972), A Monte Carlo study of some small sample properties of tests for specification errors. Journal of the American Statistical Association, 67, 180–186.CrossRefGoogle Scholar
  12. Stone, M. (1974), Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, B-36, 111–133.Google Scholar
  13. Tukey, J.W. (1958), Bias and confidence in not-quit large samples. Annals of Mathematical Statistics, 29, 614.CrossRefGoogle Scholar
  14. Wold, H. (1969), Econometrics as pioneering in nonexperimental model building. Econo- metrica, 37, 369–381.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Bernd Schips
  • Yngve Abrahamsen

There are no affiliations available

Personalised recommendations