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An Integral Inequality On C([0,1]) And Dispersion Of Ols Under Near-Integration

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  • Bailey, Ralph W.
  • Burridge, Peter
  • Nandeibam, Shasikanta

Abstract

We obtain an inequality for the sample variance of a vector Brownian motion on [0,1] and an associated Ornstein–Uhlenbeck process. The result is applied to a regression involving near-integrated regressors, and establishes that in the limit the dispersion of the least squares estimator is greater in the near-integrated than in the integrated case. Our proof uses a quite general integral inequality, which appears to be new.

Suggested Citation

  • Bailey, Ralph W. & Burridge, Peter & Nandeibam, Shasikanta, 2001. "An Integral Inequality On C([0,1]) And Dispersion Of Ols Under Near-Integration," Econometric Theory, Cambridge University Press, vol. 17(2), pages 471-474, April.
  • Handle: RePEc:cup:etheor:v:17:y:2001:i:02:p:471-474_17
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    Cited by:

    1. Bailey, Ralph W. & Burridge, Peter, 2007. "Ordering the dispersion of ordinary least squares under near-integration," Statistics & Probability Letters, Elsevier, vol. 77(6), pages 594-597, March.

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