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How to Do xtabond2: An Introduction to "Difference" and "System" GMM in Stata

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Author Info
David Roodman ()

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Abstract

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 paper closes with some tips for proper use.

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Publisher Info
Paper provided by Center for Global Development in its series Working Papers with number 103.

Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Length: 42 pages
Date of creation: Nov 2006
Date of revision:
Handle: RePEc:cgd:wpaper:103

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Web page: http://www.cgdev.org

For technical questions regarding this item, or to correct its listing, contact: (David Roodman).

Related research
Keywords: dynamic panel estimation difference GMM system GMM Stata Arellano-Bond Blundell-Bond generalized method of moments autocorrelation

Find related papers by JEL classification:
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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  1. Yi Wu & Li Zeng, 2008. "The Impact of Trade Liberalization on the Trade Balance in Developing Countries," IMF Working Papers 08/14, International Monetary Fund. [Downloadable!]
  2. W. Robert Reed & Haichun Ye, 2007. "A Monte Carlo Evaluation of Some Common Panel Data Estimators when Serial Correlation and Cross-sectional Dependence are Both Present," Working Papers in Economics 07/01, University of Canterbury, Department of Economics. [Downloadable!]
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