Estimation of the Rigidity and Expectational Model

S. Lu, Shiyu Xie, Takao Ito
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引用次数: 1

Abstract

The rigidity and expectational model is one of the geometric lag models which may cause problems of parameters estimation. In order to consistently estimate the model’s parameters in the ML approach, we propose an easy-to-compute procedure. This new procedure makes the polynomials in the lag operator to be fractionally integrated. A parsimonious model will be obtained when this proposed procedure is applied. And it also will be applied to very general specifications of the error term. In this paper, we employ this new procedure to analyze U.S. consumption function, and then we discuss some interesting results.
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刚性与期望模型的估计
刚性期望模型是一种会引起参数估计问题的几何滞后模型。为了在机器学习方法中一致地估计模型的参数,我们提出了一个易于计算的过程。这种新方法使得滞后算子中的多项式是分数积分的。应用该方法可得到一个简洁的模型。它也可以应用到误差项的一般描述中。在本文中,我们使用这个新方法来分析美国的消费函数,然后讨论一些有趣的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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