Misspecification in Dynamic Panel Data Models and Model-free Inferences
Misspecification in Dynamic Panel Data Models and Model-free Inferences
复制标题
动态面板数据模型和无模型推理中的错误指定
DOI：
10.1111/jere.12080
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发表时间：
2016
影响因子：
1.2
通讯作者：
Ryo Okui
中科院分区：
文献类型：
--
作者：
徳井 丞次;牧野 達治;深尾 京司;宮川 努;荒井 信幸;新井 園枝;乾 友彦;川崎 一泰;児玉 直美 ;野口 尚洋;Ryo Okui
本文讨论了动态面板数据分析中的模型错误指定和无模型方法的问题。我们主要回顾现有结果，但也提供了一些新结果。当动态均匀时，我们表明，即使在错误指定的情况下，面板一阶自回归 AR(1) 模型的几种广泛使用的估计量也会收敛于一阶自相关。在异质性下，这些估计量收敛于一阶自协方差和方差的均值之比。我们还讨论了自协方差的估计、面板 AR(∞) 模型的估计以及异质均值和自协方差分布的估计。
This paper discusses the issue of model misspecification and model-free methods in dynamic panel data analysis. We primarily review existing results, but also provide several new results. When the dynamics are homogeneous, we show that several widely used estimators for panel first-order autoregressive AR(1) models converge to first-order autocorrelation, even under misspecification. Under heterogeneity, these estimators converge to the ratio of the means of the first-order autocovariances and variances. We also discuss the estimation of autocovariances, the estimation of panel AR(∞) models, and the estimation of the distribution of the heterogeneous mean and autocovariances.