Double filter instrumental variable estimation of panel data models with weakly exogenous variables
Double filter instrumental variable estimation of panel data models with weakly exogenous variables
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DOI：
10.2139/ssrn.2965277
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发表时间：
2018-06
影响因子：
1.2
通讯作者：
Kazuhiko Hayakawa;Meng Qi;J. Breitung
中科院分区：
文献类型：
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作者：
Kazuhiko Hayakawa;Meng Qi;J. Breitung
摘要本文对具有弱外生变量的面板数据模型提出了工具变量(IV)估计和广义矩方法(GMM)估计。除标准固定效应(FE)外，该模型还允许包括不同的时间趋势。所提出的IV和GMM估计器是通过对模型应用前向滤波，对仪器应用后向滤波来去除FE而得到的，因此称为双滤波IV和GMM估计器。我们得到了在固定T和大N，以及大T和大N渐近下所提出的估计量的渐近性质，其中N和T分别表示横截面和时间序列的维度。结果表明，当N和T都较大时，所提出的IV估计量与偏差修正FE估计量具有相同的渐近分布。蒙特卡罗模拟结果表明，该估计器在有限样本下表现良好，在许多情况下优于传统的基于水平工具的IV/GMM估计器。
Abstract In this article, we propose instrumental variables (IV) and generalized method of moments (GMM) estimators for panel data models with weakly exogenous variables. The model is allowed to include heterogeneous time trends besides the standard fixed effects (FE). The proposed IV and GMM estimators are obtained by applying a forward filter to the model and a backward filter to the instruments in order to remove FE, thereby called the double filter IV and GMM estimators. We derive the asymptotic properties of the proposed estimators under fixed T and large N, and large T and large N asymptotics where N and T denote the dimensions of cross section and time series, respectively. It is shown that the proposed IV estimator has the same asymptotic distribution as the bias corrected FE estimator when both N and T are large. Monte Carlo simulation results reveal that the proposed estimator performs well in finite samples and outperforms the conventional IV/GMM estimators using instruments in levels in many cases.