Consistency, asymptotic unbiasedness and bounds on the bias of s2 in the linear regression model with error component disturbances

B. H. Baltagi, W. Krämer

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

The OLS estimator of the disturbance variance in the linear regression model with error component disturbances is shown to be weakly consistent and asymptotically unbiased without any restrictions on the regressor matrix. Also, simple exact bounds on the expected value of s2 are given for both the one-way and two-way error component models.

Original languageEnglish (US)
Pages (from-to)323-328
Number of pages6
JournalStatistical Papers
Volume35
Issue number1
DOIs
StatePublished - Dec 1 1994
Externally publishedYes

Keywords

  • Bounds on Bias
  • Error Components Models
  • Variance Estimation

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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