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The impact of the State Innovation Models Initiative on population health

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  • Deb, Partha
  • Gangaram, Anjelica
  • Khajavi, Hoda Nouri

Abstract

In this paper, we examine the effects of the State Innovation Models Initiative (SIM) on population-level health status. SIM provided $250 million to six states in 2013 for broad delivery system reforms. We use data from the Behavioral Risk Factor Surveillance System for the years 2010–2016. Our sample is restricted to individuals ages 45 and older residing in 6 SIM and 15 control states. Treatment effects in a difference-in-difference design are estimated using a latent factor model for multiple indicators of health status. In addition to estimates for the primary sample, we obtain estimates for six subsamples based on strata of age, education, income, race and urban/rural status. We find that individuals in states that implemented SIM show significant improvements in health status. The effects of SIM are greater among older, Medicare eligible individuals, including those living in rural areas. The State Innovation Models Initiative, which provided financial incentives for states to implement health care delivery system reforms, led to population-level improvements in health status.

Suggested Citation

  • Deb, Partha & Gangaram, Anjelica & Khajavi, Hoda Nouri, 2021. "The impact of the State Innovation Models Initiative on population health," Economics & Human Biology, Elsevier, vol. 42(C).
  • Handle: RePEc:eee:ehbiol:v:42:y:2021:i:c:s1570677x2100037x
    DOI: 10.1016/j.ehb.2021.101013
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    as
    1. Jonathan Meer & Jeremy West, 2016. "Effects of the Minimum Wage on Employment Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 51(2), pages 500-522.
    2. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Effects in New," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 71, Elsevier.
    3. Simon Freyaldenhoven & Christian Hansen & Jesse M. Shapiro, 2019. "Pre-event Trends in the Panel Event-Study Design," American Economic Review, American Economic Association, vol. 109(9), pages 3307-3338, September.
    4. Hilary Hoynes & Doug Miller & David Simon, 2015. "Income, the Earned Income Tax Credit, and Infant Health," American Economic Journal: Economic Policy, American Economic Association, vol. 7(1), pages 172-211, February.
    5. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2005. "Welfare Reform and Health," Journal of Human Resources, University of Wisconsin Press, vol. 40(2).
    6. Chang Hyung Lee & Douglas G. Steigerwald, 2018. "Inference for clustered data," Stata Journal, StataCorp LP, vol. 18(2), pages 447-460, June.
    7. Gregory, Christian A. & Deb, Partha, 2015. "Does SNAP improve your health?," Food Policy, Elsevier, vol. 50(C), pages 11-19.
    8. Andrew V. Carter & Kevin T. Schnepel & Douglas G. Steigerwald, 2017. "Asymptotic Behavior of a t -Test Robust to Cluster Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 99(4), pages 698-709, July.
    9. Stephen G. Donald & Kevin Lang, 2007. "Inference with Difference-in-Differences and Other Panel Data," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 221-233, May.
    10. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    11. France Portrait & Maarten Lindeboom & Dorly Deeg, 1999. "Health and mortality of the elderly: the grade of membership method, classification and determination," Health Economics, John Wiley & Sons, Ltd., vol. 8(5), pages 441-458, August.
    12. Puhani, Patrick A., 2012. "The treatment effect, the cross difference, and the interaction term in nonlinear “difference-in-differences” models," Economics Letters, Elsevier, vol. 115(1), pages 85-87.
    13. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    14. James G. MacKinnon & Matthew D. Webb, 2017. "Wild Bootstrap Inference for Wildly Different Cluster Sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 233-254, March.
    15. Lindeboom, Maarten & van Doorslaer, Eddy, 2004. "Cut-point shift and index shift in self-reported health," Journal of Health Economics, Elsevier, vol. 23(6), pages 1083-1099, November.
    16. David H. Autor, 2003. "Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 1-42, January.
    17. Timothy N. Bond & Kevin Lang, 2019. "The Sad Truth about Happiness Scales," Journal of Political Economy, University of Chicago Press, vol. 127(4), pages 1629-1640.
    18. Groot, Wim, 2000. "Adaptation and scale of reference bias in self-assessments of quality of life," Journal of Health Economics, Elsevier, vol. 19(3), pages 403-420, May.
    19. Justin Wolfers, 2006. "Did Unilateral Divorce Laws Raise Divorce Rates? A Reconciliation and New Results," American Economic Review, American Economic Association, vol. 96(5), pages 1802-1820, December.
    20. Hwan Chung & James C. Anthony & Joseph L. Schafer, 2011. "Latent class profile analysis: an application to stage sequential processes in early onset drinking behaviours," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(3), pages 689-712, July.
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    More about this item

    Keywords

    Health care delivery; Health care financing; Medicare; Latent factor models;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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