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Improved estimators in some linear errors-in-variables models in finite samples

Journal Article


Abstract


  • The paper uses a Monte Carlo study to demonstrate the dominance under mean squared errors or quadratic loss of a new improved estimator for some linear errors-in-variables models in finite samples. The new estimator is non-linear and biased in a conventional sense and has a smaller risk than the least squares and the Stein estimators. Standard errors for this estimator can be conveniently obtained by bootstrapping methods. © 1986.

UOW Authors


  •   Tran, Jimmy Van Hoa. (external author)

Publication Date


  • 1986

Citation


  • Van Hoa, T. (1986). Improved estimators in some linear errors-in-variables models in finite samples. Economics Letters, 20(4), 355-358. doi:10.1016/0165-1765(86)90012-1

Scopus Eid


  • 2-s2.0-38249042237

Web Of Science Accession Number


Start Page


  • 355

End Page


  • 358

Volume


  • 20

Issue


  • 4

Abstract


  • The paper uses a Monte Carlo study to demonstrate the dominance under mean squared errors or quadratic loss of a new improved estimator for some linear errors-in-variables models in finite samples. The new estimator is non-linear and biased in a conventional sense and has a smaller risk than the least squares and the Stein estimators. Standard errors for this estimator can be conveniently obtained by bootstrapping methods. © 1986.

UOW Authors


  •   Tran, Jimmy Van Hoa. (external author)

Publication Date


  • 1986

Citation


  • Van Hoa, T. (1986). Improved estimators in some linear errors-in-variables models in finite samples. Economics Letters, 20(4), 355-358. doi:10.1016/0165-1765(86)90012-1

Scopus Eid


  • 2-s2.0-38249042237

Web Of Science Accession Number


Start Page


  • 355

End Page


  • 358

Volume


  • 20

Issue


  • 4