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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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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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  1. 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.
  2. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2002. "Instrumental variables and GMM: Estimation and testing," Boston College Working Papers in Economics 545, Boston College Department of Economics, revised 14 Feb 2003.
  3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  4. 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.
  5. Thorsten Beck & Ross Levine, 2002. "Stock Markets, Banks, and Growth: Panel Evidence," NBER Working Papers 9082, National Bureau of Economic Research, Inc.
  6. 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.).
  7. Calderon, Cesar & Chong, Alberto & Loayza, Norman, 2000. "Determinants of current account deficits in developing countries," Policy Research Working Paper Series 2398, The World Bank.
  8. Torben G. Andersen & Hyung-Jin Chung & Bent E. Sorensen, . "EMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study," Computing in Economics and Finance 1997 6, Society for Computational Economics.
  9. 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.
  10. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  11. 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.
  12. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-26, November.
  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. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
  15. 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.
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