Skip to main content
SpringerLink
Log in

The asymptotic unbiasedness of S2 in the linear regression model with AR(1)-disturbances

  • Notes
  • Published:
Statistical Papers Aims and scope Submit manuscript

Abstract

The OLS-estimator of the disturbance variance in the Linear Regression Model is shown to be asymptotically unbiased in the context of AR(1)-disturbances, although for any given design, E(s2/σ2) tends to zero as correlation increases.

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

Similar content being viewed by others

References

  • DUFOUR, J.M. (1986):“Bias of s 2 in Linear Regression with Dependent Errors”, The American Statistician 40, 284–285.

    Article  MathSciNet  Google Scholar 

  • KIVIET, J and KRÄMER, W. (1990): “Bias of S 2 in the Linear Regression Model with Autocorrelated Errors”, Paper given at the 6th World Congress of the Econometric Society, Barcelona.

  • NEUDECKER, H. (1977): “Bounds for the Bias of the Least Squares Estimator ofσ2 in Case of a First-Order Autoregressive Process (Positive Autocorrelation)”, Econometrica 45, 1258–1262.

    MathSciNet  Google Scholar 

  • NEUDECKER, H. (1978): “Bounds for the Bias of the LS Estimator in the Case of a First-Order (positive) Autoregressive Process where the Regression contains a Constant Term”, Econometrica 46, 1223–1226.

    Article  MATH  Google Scholar 

  • SATHE, S.T. and VINOD, H.D. (1974): “Bounds on the Variance of Regression Coefficients due to Heteroscedastic or Autoregressive Errors”, Econometrica 42, 333–340.

    Article  MATH  Google Scholar 

  • WATSON, G.S. (1955): “Serial Correlation in Regression Analysis I”, Biometrika 42, 327–341.

    MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Statistics, University of Dortmund, Postfach 50 05 00, D-4600, Dortmund 50

    W. Krämer

Authors
  1. W. Krämer
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

Research supported by Deutsche Forschungsgemeinschaft (DFG).

Rights and permissions

Reprints and permissions

About this article

Cite this article

Krämer, W. The asymptotic unbiasedness of S2 in the linear regression model with AR(1)-disturbances. Statistical Papers 32, 71–73 (1991). https://doi.org/10.1007/BF02925481

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02925481

Keywords

Search

Navigation