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.
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