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Minimizing Bias in Selection on Observables Estimators When Unconfoundness Fails

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Author Info

  • Daniel Millimet

    ()
    (Southern Methodist University)

  • Rusty Tchernis

    ()
    (Indiana University Bloomington)

Abstract

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using simulated data, as well as a timely application examining the causal effect of the School Breakfast Program on childhood obesity. We find our new estimator to be quite advantageous in many situations, even when selection is only on observables.

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File URL: http://www.iub.edu/~caepr/RePEc/PDF/2008/CAEPR2008-008.pdf
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Bibliographic Info

Paper provided by Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington in its series Caepr Working Papers with number 2008-008.

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Length: 38 pages
Date of creation: Apr 2008
Date of revision:
Handle: RePEc:inu:caeprp:2008-008

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Keywords: Treatment Effects; Propensity Score; Bias; Unconfoundedness; Selection on Unobservables;

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References

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  1. Jay Bhattacharya & Janet Currie & Steven Haider, 2004. "Breakfast of Champions? The School Breakfast Program and the Nutrition of Children and Families," Working Papers 189, RAND Corporation Publications Department.
  2. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
  3. Daniel Millimet & Rusty Tchernis & Muna Hussain, 2007. "School Nutrition Programs and the Incidence of Childhood Obesity," Caepr Working Papers 2007-014, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  4. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects and Econometric Policy Evaluation," NBER Technical Working Papers 0306, National Bureau of Economic Research, Inc.
  5. Daniel Millimet & Rusty Tchernis, 2008. "On the Specification of Propensity Scores: with Applications to the Analysis of Trade Policies," Caepr Working Papers 2006-013_Updated, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  6. Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20035, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
  7. Dan A. Black & Jeffrey Smith, 2003. "How Robust is the Evidence on the Effects of College Quality? Evidence From Matching," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20033, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
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Citations

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Cited by:
  1. Sampaio, Breno Ramos & Sampaio, Gustavo Ramos & Sampaio, Yony, 2012. "On Estimating The Effects of Legalization: Do Agricultural Workers Really Benefit?," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126858, International Association of Agricultural Economists.
  2. Owusu, Victor & Abdulai, Awudu & Abdul-Rahman, Seini, 2011. "Non-farm work and food security among farm households in Northern Ghana," Food Policy, Elsevier, vol. 36(2), pages 108-118, April.
  3. Gurun, Ayfer & Millimet, Daniel L., 2008. "Does Private Tutoring Payoff?," IZA Discussion Papers 3637, Institute for the Study of Labor (IZA).

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