AN INTEGRAL INEQUALITY ON C([0,1]) AND DISPERSION OF OLS UNDER NEAR-INTEGRATION
证明了[0,1]上向量布朗运动及其相关Ornstein-Uhlenbeck过程的样本方差不等式，并将其应用于含近单位根回归量的回归中，发现极限情况下最小二乘估计量的离散度在近单位根情形下大于单位根情形。
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.