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New distribution theory for the estimation of structural break point in mean

机译:平均结构断点估计的新分布理论

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Based on the Girsanov theorem, this paper obtains the exact distribution of the maximum likelihood estimator of structural break point in a continuous time model. The exact distribution is asymmetric and tri-modal, indicating that the estimator is biased. These two properties are also found in the finite sample distribution of the least squares (LS) estimator of structural break point in the discrete time model, suggesting the classical long-span asymptotic theory is inadequate. The paper then builds a continuous time approximation to the discrete time model and develops an in-fill asymptotic theory for the LS estimator. The in-fill asymptotic distribution is asymmetric and tri-modal and delivers good approximations to the finite sample distribution. To reduce the bias in the estimation of both the continuous time and the discrete time models, a simulation-based method based on the indirect estimation (IE) approach is proposed. Monte Carlo studies show that IE achieves substantial bias reductions. (C) 2018 Elsevier B.V. All rights reserved.
机译:基于Girsanov定理,本文获得了连续时间模型中结构断点的最大似然估计器的精确分布。确切的分布是不对称的和三模态,表明估计器被偏置。在离散时间模型中结构断点的最小二乘(LS)估计的有限样本分布中还发现了这两个性质,表明经典的长跨度渐近理论不足。然后,该文件建立了与离散时间模型的连续时间近似,并为LS估计开发了填充渐近理论。填充渐近分布是不对称的和三模态的,并且对有限样品分布提供良好的近似。为了减少估计连续时间和离散时间模型的估计,提出了一种基于间接估计(IE)方法的基于仿真方法。蒙特卡罗研究表明,即实现大量偏置的偏差。 (c)2018 Elsevier B.v.保留所有权利。

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