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Estimating Heterogeneity in the Benefits of Medical Treatment Intensity

  • William N. Evans

    (Department of Economics, University of Notre Dame)

  • Craig Garthwaite

    (Department of Management and Strategy, Kellogg School of Management, Northwestern University)

We exploit increases in postpartum length of stay generated by legislative changes in the late 1990s to identify the impact of greater hospital care on the health of newborns. Using all births in California over the 1995–2000 period, two-stage least-square estimates show that increased treatment intensity had a modest impact on readmission probabilities for the average newborn. Allowing the treatment effect to vary by two objective measures of medical need demonstrates that the law had large impacts for those with the greatest likelihood of a readmission. The results suggest that the returns to average and marginal patients vary considerably in this context. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00198
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Article provided by MIT Press in its journal Review of Economics and Statistics.

Volume (Year): 94 (2012)
Issue (Month): 3 (August)
Pages: 635-649

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Handle: RePEc:tpr:restat:v:94:y:2012:i:3:p:635-649
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  1. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2009. "Understanding Instrumental Variables in Models with Essential Heterogeneity," Working Papers 200941, Geary Institute, University College Dublin.
  2. Evans, William N. & Garthwaite, Craig & Wei, Heng, 2008. "The impact of early discharge laws on the health of newborns," Journal of Health Economics, Elsevier, vol. 27(4), pages 843-870, July.
  3. Mark G. Duggan & William N. Evans, 2005. "Estimating the Impact of Medical Innovation: A Case Study of HIV Antiretroviral Treatments," NBER Working Papers 11109, National Bureau of Economic Research, Inc.
  4. Amitabh Chandra & Douglas O. Staiger, 2007. "Productivity Spillovers in Health Care: Evidence from the Treatment of Heart Attacks," Journal of Political Economy, University of Chicago Press, vol. 115, pages 103-140.
  5. Alberto Abadie & Joshua Angrist & Guido Imbens, 2002. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Econometrica, Econometric Society, vol. 70(1), pages 91-117, January.
  6. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1133-1157.
  7. James Heckman & Justin L. Tobias & Edward Vytlacil, 2003. "Simple Estimators for Treatment Parameters in a Latent-Variable Framework," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 748-755, August.
  8. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects and Econometric Policy Evaluation," NBER Working Papers 11259, National Bureau of Economic Research, Inc.
  9. Amy Finkelstein & Robin McKnight, 2005. "What Did Medicare Do (And Was It Worth It)?," NBER Working Papers 11609, National Bureau of Economic Research, Inc.
  10. Douglas Almond & Joseph J. Doyle & Amanda E. Kowalski & Heidi Williams, 2010. "Estimating Marginal Returns to Medical Care: Evidence from At-risk Newborns," The Quarterly Journal of Economics, Oxford University Press, vol. 125(2), pages 591-634.
  11. David M. Cutler & Mark McClellan & Joseph P. Newhouse & Dahlia Remler, 1998. "Are Medical Prices Declining? Evidence from Heart Attack Treatments," The Quarterly Journal of Economics, Oxford University Press, vol. 113(4), pages 991-1024.
  12. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 487-535.
  13. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: An application in breast cancer patients," Health, Econometrics and Data Group (HEDG) Working Papers 07/07, HEDG, c/o Department of Economics, University of York.
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