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Estimation of Treatment Effects Without an Exclusion Restriction: with an Application to the Analysis of the School Breakfast Program

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  • Daniel L. Millimet
  • Rusty Tchernis

Abstract

While the rise in childhood obesity is clear, the policy ramifications are not. School nutrition programs such as the School Breakfast Program (SBP) have come under much scrutiny. However, the lack of experimental evidence, combined with non-random selection into these programs, makes identification of the causal effects of such programs difficult. In the case of the SBP, this difficulty is exacerbated by the apparent lack of exclusion restrictions. Here, we compare via Monte Carlo study several existing estimators that do not rely on exclusion restrictions for identification. In addition, we propose two new estimation strategies. Simulations illustrate the usefulness of our new estimators, as well as provide applied researchers several practical guidelines when analyzing the causal effects of binary treatments. More importantly, we find consistent evidence of a beneficial causal effect of SBP participation on childhood obesity when applying estimators designed to circumvent selection on unobservables.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 15539.

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Date of creation: Nov 2009
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Handle: RePEc:nbr:nberwo:15539

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  1. Imbens, Guido W. & Wooldridge, Jeffrey M., 2008. "Recent Developments in the Econometrics of Program Evaluation," IZA Discussion Papers 3640, Institute for the Study of Labor (IZA).
  2. David S. Lee & Thomas Lemieux, 2009. "Regression Discontinuity Designs In Economics," Working Papers 1118, Princeton University, Department of Economics, Industrial Relations Section..
  3. 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.
  4. Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers 1166, Econometric Society.
  5. James J. Heckman & Salvador Navarro-Lozano, 2003. "Using Matching, Instrumental Variables and Control Functions to Estimate Economic Choice Models," NBER Working Papers 9497, National Bureau of Economic Research, Inc.
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  7. Roger Klein & Francis Vella, 2009. "A semiparametric model for binary response and continuous outcomes under index heteroscedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 735-762.
  8. Sara Bleich & David Cutler & Christopher Murray & Alyce Adams, 2007. "Why Is The Developed World Obese?," NBER Working Papers 12954, National Bureau of Economic Research, Inc.
  9. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  10. 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.
  11. Daniel L. Millimet & Rusty Tchernis & Muna Husain, 2008. "School Nutrition Programs and the Incidence of Childhood Obesity," NBER Working Papers 14297, National Bureau of Economic Research, Inc.
  12. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
  13. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2000. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," NBER Working Papers 7831, National Bureau of Economic Research, Inc.
  14. Black, Dan A. & Smith, J.A.Jeffrey A., 2004. "How robust is the evidence on the effects of college quality? Evidence from matching," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 99-124.
  15. Alberto Abadie & Guido W. Imbens, 2009. "Matching on the Estimated Propensity Score," NBER Working Papers 15301, National Bureau of Economic Research, Inc.
  16. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-29, October.
  17. Odelia Rosin, 2008. "The Economic Causes Of Obesity: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(4), pages 617-647, 09.
  18. Guthrie, Joanne F. & Newman, Constance & Ralston, Katherine L., 2009. "USDA School Meal Programs Face New Challenges," Choices, Agricultural and Applied Economics Association, vol. 24(3).
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Cited by:
  1. Berg, Claudia & Emran, M. Shahe & Shilpi, Forhad, 2013. "Microfinance and moneylenders : long-run effects of MFIs on informal credit market in Bangladesh," Policy Research Working Paper Series 6619, The World Bank.
  2. Millimet, Daniel L. & McDonough, Ian K., 2013. "Dynamic Panel Data Models with Irregular Spacing: With Applications to Early Childhood Development," IZA Discussion Papers 7359, Institute for the Study of Labor (IZA).
  3. Daniel L. Millimet & Rusty Tchernis, 2013. "The Origins of Early Childhood Anthropometric Persistence," NBER Working Papers 19554, National Bureau of Economic Research, Inc.

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