The Calculation of the Limiting Distribution of the Least-Squares Estimator in a Near-Integrated Model
The Calculation of the Limiting Distribution of the Least-Squares Estimator in a Near-Integrated Model
复制标题
近积分模型中最小二乘估计量极限分布的计算
作者：
Pierre Perron
本文给出了一阶自回归模型中最小二乘估计的极限累积分布和概率密度函数，当真实模型是菲利普斯意义下的近似积分时。结果是使用一个精确的数值方法，它集成了适当的极限力矩生成函数。适当的近似检查各种一阶自回归过程的根接近统一。
We tabulate the limiting cumulative distribution and probability density functions of the least-squares estimator in a first-order autoregressive regression when the true model is near-integrated in the sense of Phillips. The results are obtained using an exact numerical method which integrates the appropriate limiting moment generating function. The adequacy of the approximation is examined for various first-order autoregressive processes with a root close to unity.