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.
Original language | English |
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Pages (from-to) | 471-474 |
Number of pages | 4 |
Journal | Econometric Theory |
Volume | 17 |
Publication status | Published - Apr 2001 |