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Bounds for the bias of the LS estimator of o^2 in the case of a first-order autoregressive process

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  • Neudecker, H.

Abstract

The LS-estimator Ti7.7i of a 2 and its bias are considered. Bounds are then established for 2- by means of a well-known theorem by Anderson. a2 n-k The same bounds can be derived by a direct applicant of the Courant-Fischer min-max theorem. Following Anderson and Grenander-Szeg6 one can find approximations to these bounds.

Suggested Citation

  • Neudecker, H., 1978. "Bounds for the bias of the LS estimator of o^2 in the case of a first-order autoregressive process," University of Amsterdam, Actuarial Science and Econometrics Archive 293026, University of Amsterdam, Faculty of Economics and Business.
    • Handle: RePEc:ags:amstas:293026
    DOI: 10.22004/ag.econ.293026
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    Cited by:

    1. Musser, Wesley N., 1992. "A Historical Overview of Estimation of Historical Risk Coefficients," 1992 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, March 22-25, 1992, Orlando, Florida 307862, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    2. Gotu, Butte, 1999. "The consistency of s2 in the linear regression model when the disturbances are spatially correlated," Technical Reports 1999,07, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Song, Seuck Heun & Lee, Jaejun, 2008. "A note on S2 in a spatially correlated error components regression model for panel data," Economics Letters, Elsevier, vol. 101(1), pages 41-43, October.

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    Research Methods/ Statistical Methods;

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