Working Paper Number 103 December 2006 How to Do xtabond 2 : An Introduction to “ Difference ” and “ System ” GMM in Stata By David Roodman
Working Paper Number 103 December 2006 How to Do xtabond 2 : An Introduction to “ Difference ” and “ System ” GMM in Stata By David Roodman
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工作论文 2006 年 12 月 103 号 如何做 xtabond 2：Stata 中“差异”和“系统”GMM 简介 作者：David Roodman
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
D. Roodman
中科院分区：
文献类型：
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作者：
D. Roodman
Arellano-Bond (1991) 和 Arellano-Bover (1995)/Blundell-Bond (1998) 线性广义矩法 (GMM) 估计器越来越受欢迎。两者都是通用估计器，专为“小 T，大 N”面板的情况而设计，这意味着时间段少，个体多；自变量不是严格外生的，意味着与过去和可能当前的错误实现相关；具有固定效应；并具有个体内部的异方差和自相关性。这篇教学论文首先介绍了线性 GMM。然后，它展示了有限的时间跨度以及固定效应和内生回归量的潜力如何推动感兴趣的估计量的设计，并在此过程中提供基于 Stata 的示例。接下来，它展示了如何将这些估计器与 xtabond2 一起应用。它还解释了如何在其他 Stata 命令之后使用 abar 在面板中执行 Arellano-Bond 测试以进行自相关。全球发展中心是一个独立的智库，致力于通过严谨的研究和与政策界的积极参与来减少全球贫困和不平等。鼓励使用和传播本工作文件，但复制件不得用于商业目的。根据知识共享许可的条款允许进一步使用。本文表达的观点仅代表作者的观点，不应归咎于全球发展中心的董事或资助者。 www.cgdev.org ________________________________________________________________________ 如何做 xtabond2：Stata 中的差分和系统 GMM 简介
The Arellano-Bond (1991) and Arellano-Bover (1995)/Blundell-Bond (1998) linear generalized method of moments (GMM) estimators are increasingly popular. Both are general estimators designed for situations with “small T, large N” panels, meaning few time periods and many individuals; with independent variables that are not strictly exogenous, meaning correlated with past and possibly current realizations of the error; with fixed effects; and with heteroskedasticity and autocorrelation within individuals. This pedagogic paper first introduces linear GMM. Then it shows how limited time span and the potential for fixed effects and endogenous regressors drive the design of the estimators of interest, offering Stata-based examples along the way. Next it shows how to apply these estimators with xtabond2. It also explains how to perform the Arellano-Bond test for autocorrelation in a panel after other Stata commands, using abar. The Center for Global Development is an independent think tank that works to reduce global poverty and inequality through rigorous research and active engagement with the policy community. Use and dissemination of this Working Paper is encouraged, however reproduced copies may not be used for commercial purposes. Further usage is permitted under the terms of the Creative Commons License. The views expressed in this paper are those of the author and should not be attributed to the directors or funders of the Center for Global Development. www.cgdev.org ________________________________________________________________________ How to Do xtabond2: An Introduction to Difference and System GMM in Stata
用面板数据估计向量自回归
影响因子：
6.1
作者：
HOLTZEAKIN, D;NEWEY, W;ROSEN, HS
通讯作者：
ROSEN, HS