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Estimating Heterogeneity in the Benefits of Medical Treatment Intensity

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  • William N. Evans
  • Craig L. Garthwaite

Abstract

Federal and state laws passed in the late 1990 increased considerably postpartum stays for newborns. Using all births in California over the 1995-2001 period, 2SLS estimates suggest that for the average newborn impacted by the law, increased treatment intensity had modest and statistically insignificant (p-value>0.05) impacts on readmission probabilities. Allowing the treatment effect to vary by pre-existing conditions or the pre-law propensity score of being discharged early, two objective measures of medical need, demonstrates that the law had large and statistically significant impacts for those with the greatest likelihood of a readmission. These results demonstrate heterogeneity in the returns to greater treatment intensity, and the returns to the average and marginal patient vary considerably.

Suggested Citation

  • William N. Evans & Craig L. Garthwaite, 2009. "Estimating Heterogeneity in the Benefits of Medical Treatment Intensity," NBER Working Papers 15309, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:15309
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    1. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2006. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," American Economic Review, American Economic Association, vol. 96(4), pages 988-1012, September.
    2. 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.
    3. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    4. 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, President and Fellows of Harvard College, vol. 125(2), pages 591-634.
    5. 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.
    6. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    7. Duggan Mark G & Evans William N, 2008. "Estimating the Impact of Medical Innovation: A Case Study of HIV Antiretroviral Treatments," Forum for Health Economics & Policy, De Gruyter, vol. 11(2), pages 1-39, January.
    8. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    9. David M. Cutler & Ellen Meara, 2000. "The Technology of Birth: Is It Worth It?," NBER Chapters, in: Frontiers in Health Policy Research, Volume 3, pages 33-68, National Bureau of Economic Research, Inc.
    10. Amy Finkelstein & Robin McKnight, 2005. "What Did Medicare Do (And Was It Worth It)?," NBER Working Papers 11609, National Bureau of Economic Research, Inc.
    11. Douglas Almond & Joseph J. Doyle, 2011. "After Midnight: A Regression Discontinuity Design in Length of Postpartum Hospital Stays," American Economic Journal: Economic Policy, American Economic Association, vol. 3(3), pages 1-34, August.
    12. 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.
    13. 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(1), pages 103-140.
    14. 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, President and Fellows of Harvard College, vol. 113(4), pages 991-1024.
    15. 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.
    16. 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.
    17. Cutler David M. & Meara Ellen, 2000. "The Technology of Birth: Is It Worth It?," Forum for Health Economics & Policy, De Gruyter, vol. 3(1), pages 1-37, January.
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    Cited by:

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    2. David B. Audretsch, 2015. "Knowledge spillovers and future jobs," IZA World of Labor, Institute of Labor Economics (IZA), pages 218-218, December.
    3. N. Meltem Daysal & Jonas Cuzulan Hirani, 2021. "Early-life medical care and human capital accumulation," IZA World of Labor, Institute of Labor Economics (IZA), pages 217-217, September.
    4. Daysal, N. Meltem & Trandafir, Mircea & van Ewijk, Reyn, 2016. "Heterogeneous Effects of Medical Interventions on the Health of Low-Risk Newborns," IZA Discussion Papers 9810, Institute of Labor Economics (IZA).
    5. Seojeong Lee, 2018. "A Consistent Variance Estimator for 2SLS When Instruments Identify Different LATEs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(3), pages 400-410, July.
    6. Dzhamilya Nigmatulina & Charles Becker, 2016. "Is high-tech care in a middle-income country worth it?," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 24(4), pages 585-620, October.
    7. Sievertsen, Hans Henrik & Wüst, Miriam, 2017. "Discharge on the day of birth, parental response and health and schooling outcomes," Journal of Health Economics, Elsevier, vol. 55(C), pages 121-138.
    8. Mindy Marks & Kate Choi, 2011. "Baby Boomlets and Baby Health: Hospital Crowdedness, Treatment Intensity, and Infant Health," Working Papers 201440, University of California at Riverside, Department of Economics.

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    More about this item

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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