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Instrumental-variable estimation of large-T panel-data models with common factors

机译:具有常见因素的大T面板数据模型的仪器变量估计

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In this article, we introduce the xtivdfreg command, which implements a general instrumental-variables (IV) approach for fitting panel-data models with many time-series observations, T, and unobserved common factors or interactive effects, as developed by Norkute et al. (2021, Journal of Econometrics 220: 416-446) and Cui et al. (2020a, ISER Discussion Paper 1101). The underlying idea of this approach is to project out the common factors from exogenous covariates using principal-components analysis and to run IV regression in both of two stages, using defactored covariates as instruments. The resulting two-stage IV estimator is valid for models with homogeneous or heterogeneous slope coefficients and has several advantages relative to existing popular approaches.In addition, the xtivdfreg command extends the two-stage IV approach in two major ways. First, the algorithm accommodates estimation of unbalanced panels. Second, the algorithm permits a flexible specification of instruments.We show that when one imposes zero factors, the xtivdfreg command can replicate the results of the popular Stata ivregress command. Notably, unlike ivregress, xtivdfreg permits estimation of the two-way error-components panel-data model with heterogeneous slope coefficients.
机译:在本文中,我们介绍了xtivdfreg命令,它实现了一种用于拟合面板数据模型的一般仪器变量(iv)方法,其中包含Norkute等人开发的许多时间序列观测,T和不观察到的常见因素或互动效果。 (2021,核心学报220:416-446)和Cui等人。 (2020A,ISER讨论纸1101)。这种方法的潜在思想是利用主分量分析向外源协变量的常见因素分析,并在两个阶段中运行IV回归,使用缺陷的协变量作为仪器。由此产生的两级IV估计器对于具有均相或异构斜率系数的模型有效,并且相对于现有的流行方法具有若干优点。此外,XtivdFreg命令用两种主要方式扩展了两级IV方法。首先,该算法可容纳不平衡面板的估计。其次,该算法允许灵活的仪器规范.we表明当一个归零因素时,xtivdfreg命令可以复制流行的stata ivregress命令的结果。值得注意的是,与IVEREGERS不同,XtiVDFREG允许估计具有异构斜率系数的双向错误组件面板数据模型。

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