弱爆炸二阶自回归模型的渐近分布
Asymptotic distributions related to mildly-explosive second order autoregressive models
摘要：
本文研究了具有相依误差的一阶自回归模型中参数的归一化最小二乘估计，模型被建模为一个弱爆炸AR（1）过程。我们证明了估计有一个柯西极限定律，它提供了一个桥梁之间的中度偏差渐近性和早期的结果，当地团结和爆炸自回归模型。特别地，这些结果可以应用于理解近积分二阶自回归过程。模拟研究也进行了评估的性能最小二乘估计在有限样本。
英文摘要：
In this paper, we consider the normalized least squares estimator of the parameter in a mildly-explosive first-order autoregressive model with dependent errors which are modeled as a mildly-explosive AR(1) process. We prove that the estimator has a Cauchy limit law which provides a bridge between moderate deviation asymptotics and the earlier results on the local to unity and explosive autoregressive models. In particular, the results can be applied to understand the near-integrated second order autoregressive processes. Simulation studies are also carried out to assess the performance of least squares estimation in finite samples.
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