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Matching methods for estimating treatment effects using Stata

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  • Guido W. Imbens

    () (Harvard University)

Abstract

I will give a brief overview of modern statistical methods for estimating treatment effects that have recently become popular in social and biomedical sciences. These methods are based on the potential outcome framework developed by Donald Rubin. The specific methods discussed include regression methods, matching, and methods involving the propensity score. I will discuss the assumptions underlying these methods and the methods for assessing their plausability. I will then discuss using the Stata command nnmatch to estimate average treatment effects. I will illustrate this approach by using data from a job training program. A general survey of these methods can be found in Imbens, G. 2004. Nonparametric estimation of average treatment effects under exogeneity: A review. Review of Economics and Statistics 86: 4–30.

Suggested Citation

  • Guido W. Imbens, 2006. "Matching methods for estimating treatment effects using Stata," North American Stata Users' Group Meetings 2006 13, Stata Users Group.
  • Handle: RePEc:boc:asug06:13
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    1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    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. Beck, Thorsten & Levine, Ross, 2004. "Stock markets, banks, and growth: Panel evidence," Journal of Banking & Finance, Elsevier, vol. 28(3), pages 423-442, March.
    5. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1989. "The Revenues-Expenditures Nexus: Evidence from Local Government Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 415-429, May.
    6. 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, pages 328-352.
    7. Calderon Cesar Augusto & Chong Alberto & Loayza Norman V., 2002. "Determinants of Current Account Deficits in Developing Countries," The B.E. Journal of Macroeconomics, De Gruyter, pages 1-33.
    8. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    9. Ruth Judson & Ann L. Owen, "undated". "Estimating Dynamic Panel Data Models: A Practical Guide for Macroeconomists," Finance and Economics Discussion Series 1997-03, Board of Governors of the Federal Reserve System (U.S.).
    10. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    11. Bowsher, Clive G., 2002. "On testing overidentifying restrictions in dynamic panel data models," Economics Letters, Elsevier, vol. 77(2), pages 211-220, October.
    12. Theodore H. Moran & Edward M. Graham & Magnus Blomstrom, 2005. "Does Foreign Direct Investment Promote Development?," Peterson Institute Press: All Books, Peterson Institute for International Economics, number 3810.
    13. 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, February.
    14. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    15. 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.
    16. 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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