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How to Do xtabond2

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  • David Roodman

    ()
    (Center for Global Development)

Abstract

xtabond2 may hold the record among user-written Stata modules for the most confused users (and perhaps the most-confused too). In this presentation, I motivate and describe, in pedagogic fashion, the Arellano-Bond and Blundell-Bond linear GMM dynamic panel estimators, drawing lessons from a steady stream of correspondence with users. And I provide an overview of how to implement them with xtabond2. I first introduce linear GMM as an extension of OLS. Then I describe how limited time span, the potential for fixed effects, endogeneity, and the dangers of dynamic panel bias all shape these estimators—in particular, in their use of differences, lags as instruments, and GMM. I explain how xtabond2 commands should be constructed, with particular attention to the various options and sub-options for controlling instrument matrix construction. I discuss the need to limit the number of instruments and options for doing so.

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File URL: http://repec.org/nasug2006/How2Do_xtabond2.ppt
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Bibliographic Info

Paper provided by Stata Users Group in its series North American Stata Users' Group Meetings 2006 with number 8.

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Date of creation: 23 Jul 2006
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Handle: RePEc:boc:asug06:8

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Web page: http://www.stata.com/meeting/5nasug
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  1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2002. "Instrumental variables and GMM: Estimation and testing," United Kingdom Stata Users' Group Meetings 2003 02, Stata Users Group.
  2. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
  4. Andersen, Torben G & Sorensen, Bent E, 1996. "GMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 328-52, July.
  5. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
  6. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, 02.
  7. Beck, Thorsten & Levine, Ross, 2004. "Stock markets, banks, and growth: Panel evidence," Journal of Banking & Finance, Elsevier, vol. 28(3), pages 423-442, March.
  8. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  9. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
  10. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-26, November.
  11. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  12. César Calderón & Alberto Chong & Norman Loayza, 1999. "Determinants of Current Account Deficits in Developing Countries," Working Papers Central Bank of Chile 51, Central Bank of Chile.
  13. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
  14. Ruth A. Judson & Ann L. Owen, 1997. "Estimating dynamic panel data models: a practical guide for macroeconomists," Finance and Economics Discussion Series 1997-3, Board of Governors of the Federal Reserve System (U.S.).
  15. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
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