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Mean-square-error Calculations for Average Treatment Effects

Author

Listed:
  • Guido W. Imbens
  • Whitney Newey
  • Geert Ridder

Abstract

This paper develops a new efficient estimator for the average treatment effect, if selection for treatment is on observables. The new estimator is linear in the first-stage nonparametric estimator. This simplifies the derivation of the means squared error (MSE) of the estimator as a function of the number of basis functions that is used in the first stage nonparametric regression. We propose an estimator for the MSE and show that in large samples minimization of this estimator is equivalent to minimization of the population MSE.

Suggested Citation

  • Guido W. Imbens & Whitney Newey & Geert Ridder, 2005. "Mean-square-error Calculations for Average Treatment Effects," IEPR Working Papers 05.34, Institute of Economic Policy Research (IEPR).
  • Handle: RePEc:scp:wpaper:05-34
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    Cited by:

    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2008. "Nonparametric Tests for Treatment Effect Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 389-405, August.
    2. de Brauw, Alan & Gilligan, Daniel O. & Hoddinott, John & Roy, Shalini, 2014. "The Impact of Bolsa Família on Women’s Decision-Making Power," World Development, Elsevier, vol. 59(C), pages 487-504.
    3. Matias Busso & Patrick Kline, 2008. "Do Local Economic Development Programs Work? Evidence from the Federal Empowerment Zone Program," Cowles Foundation Discussion Papers 1639, Cowles Foundation for Research in Economics, Yale University.
    4. Kitagawa, Toru & Muris, Chris, 2016. "Model averaging in semiparametric estimation of treatment effects," Journal of Econometrics, Elsevier, vol. 193(1), pages 271-289.
    5. Chunrong Ai & Lukang Huang & Zheng Zhang, 2018. "A Simple and Efficient Estimation of the Average Treatment Effect in the Presence of Unmeasured Confounders," Papers 1807.05678, arXiv.org.
    6. Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.
    7. Yanchun Jin, 2016. "Nonparametric tests for the effect of treatment on conditional variance," KIER Working Papers 948, Kyoto University, Institute of Economic Research.
    8. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    9. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc.
    10. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP61/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2010. "How to Control for Many Covariates? Reliable Estimators Based on the Propensity Score," IZA Discussion Papers 5268, Institute of Labor Economics (IZA).
    12. Vera Chiodi & Gabriel Montes‐Rojas, 2022. "Mentoring as a dose treatment: Frequency matters—Evidence from a French mentoring programme," LABOUR, CEIS, vol. 36(2), pages 145-166, June.
    13. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    14. Michael Lechner & Blaise Melly, 2010. "Partial Idendification of Wage Effects of Training Programs," Working Papers 2010-8, Brown University, Department of Economics.
    15. de Brauw, Alan & Gilligan, Daniel O. & Hoddinott, John & Roy, Shalini, 2015. "The Impact of Bolsa Família on Schooling," World Development, Elsevier, vol. 70(C), pages 303-316.
    16. Cattaneo, Matias D., 2010. "Efficient semiparametric estimation of multi-valued treatment effects under ignorability," Journal of Econometrics, Elsevier, vol. 155(2), pages 138-154, April.
    17. de Brauw, Alan & Gilligan, Daniel O. & Hoddinott, John F. & Roy, Shalini, 2014. "The impact of Bolsa Família on schooling: Girls’ advantage increases and older children gain:," IFPRI discussion papers 1319, International Food Policy Research Institute (IFPRI).
    18. Michael Lechner & Blaise Melly, 2007. "Earnings Effects of Training Programs," University of St. Gallen Department of Economics working paper series 2007 2007-28, Department of Economics, University of St. Gallen.
    19. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
    20. Christian Volpe Martincus & Jerónimo Carballo & Pablo M. Garcia, 2012. "Public programmes to promote firms’ exports in developing countries: are there heterogeneous effects by size categories?," Applied Economics, Taylor & Francis Journals, vol. 44(4), pages 471-491, February.
    21. Garbero, A., 2016. "IFAD RESEARCH SERIES 7 - Measuring IFAD’s impact: background paper to the IFAD9 Impact Assessment Initiative," IFAD Research Series 280045, International Fund for Agricultural Development (IFAD).
    22. Millimet, Daniel L. & Tchernis, Rusty, 2009. "On the Specification of Propensity Scores, With Applications to the Analysis of Trade Policies," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 397-415.
    23. Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 1053-1079.
    24. Alex Karagrigoriou & George-Jason Siouris & Despoina Skilogianni, 2019. "Adjusted Evaluation Measures for Asymmetrically Important Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 4(1), pages 41-66, June.
    25. Kwun Chuen Gary Chan & Sheung Chi Phillip Yam & Zheng Zhang, 2016. "Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 673-700, June.

    More about this item

    Keywords

    Nonparametric Estimation; Imputation; Mean Squared Error; Order Selection;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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