Dealing with Endogeneity in a Time�?Varying Parameter Model: Joint Estimation and Two�?Step Estimation Procedures
Dealing with Endogeneity in a Time�?Varying Parameter Model: Joint Estimation and Two�?Step Estimation Procedures
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DOI：
10.1111/j.1368-423x.2011.00353.x
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发表时间：
2011-10
期刊：
影响因子：
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通讯作者：
Yunmi Kim;Chang‐Jin Kim
中科院分区：
文献类型：
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作者：
Yunmi Kim;Chang‐Jin Kim
在处理时变参数模型的内生性问题时，我们开发了基于控制函数方法的联合和两步估计程序。我们表明，联合估计过程成功的关键在于模型的适当状态空间表示。另一方面，对生成回归量问题的正确处理在我们的两步估计过程中起着重要作用。蒙特卡罗实验证实了本文提出的估计方法在有限样本下工作良好。关于我们提出的内齐性检验，基于第二步回归的似然比和沃尔德检验的渐近分布即使在有限样本中也可以很好地近似于χ2分布。
In dealing with the problem of endogeneity in a time‐varying parameter model, we develop the joint and two‐step estimation procedures based on the control function approach. We show that a key to the success of the joint estimation procedure is in an appropriate state‐space representation of the model. On the other hand, a correct treatment of the problem of generated regressors plays an important role in our two‐step estimation procedure. Monte Carlo experiments confirm that the estimation procedures proposed in this paper work well in finite samples. Concerning our proposed endogeneity tests, the asymptotic distribution of both the likelihood ratio and Wald tests based on the second‐step regression are reasonably well approximated by a χ2 distribution even in finite samples.