Skip to main content
SpringerLink
Log in

Bootstrapping Error Component Models

  • Published:
Computational Statistics Aims and scope Submit manuscript

Summary

This paper proposes several resampling algorithms suitable for error component models and evaluates them in the context of bootstrap testing. In short, all the algorithms work well and lead to tests with correct or close to correct size. There is thus little or no reason not to use the bootstrap with error component models.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1

Similar content being viewed by others

References

  • Baltagi, B. H. (1995), Econometric Analysis of Panel Data, John Wiley & Sons.

  • Bellman, L., Breitung, J. & Wagner, J. (1989), ‘Bias correction and bootstrapping of error component models for panel data: Theory and applications’, Empirical Economics 14, 329–342.

    Article  Google Scholar 

  • Davidson, R. & MacKinnon, J. G. (1996), The power of bootstrap tests, Technical Report 937, Queens Institute of Economic Resarch.

  • Davidson, R. & MacKinnon, J. G. (1999), ‘The size distortion of bootstrap tests’, Econometric Theory 15, 361–376.

    Article  MathSciNet  Google Scholar 

  • Davidson, R. & MacKinnon, J. G. (2000), ‘Bootstrap tests: How many bootstraps?’, Econometric Reviews. forthcoming.

  • Kiviet, J. F. (1995), ‘On bias, inconsistency, and efficiency of various estimators in dynamic panel data models’, Journal of Econometrics 68, 53–78.

    Article  MathSciNet  Google Scholar 

  • Maddala, G. S. & Mount, T. D. (1973), ‘A comparative study of alternative estimators for variance components models used in econometric applications’, Journal of the American Statistical Association 68, 324–328.

    Article  Google Scholar 

  • Ziliak, J. P. (1997), ‘Efficient estimatiom with panel data when instruments are predetermined: An empirical comparison of moment condition estimators’, Journal of Business and Economic Statistics 15, 419–431.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Institute of Economic Research, P.O. Box 3116, SE 103 63, Stockholm, Sweden

    Michael K. Andersson

  2. Department of Economic Statistics, Stockholm School of Economics, P.O. Box 6501, SE 113 83, Stockholm, Sweden

    Sune Karlsson

Authors
  1. Michael K. Andersson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sune Karlsson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael K. Andersson.

Additional information

We have benefited from comments by an anonymous referee. Both authors gratefully acknowledge financial support from HSFR, the Swedish Research Council for the Humanities and the Social Sciences.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Andersson, M.K., Karlsson, S. Bootstrapping Error Component Models. Computational Statistics 16, 221–231 (2001). https://doi.org/10.1007/s001800100061

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s001800100061

Keywords

Search

Navigation