Health care expenditures and use are challenging to model because these dependent variables typically have distributions that are skewed with a large mass at zero. In this article, we describe estimation and interpretation of the effects of a natural experiment using two classes of nonlinear statistical models: one for health care expenditures and the other for counts of health care use. We extend prior analyses to test the effect of the ACA's young adult expansion on three different outcomes: total health care expenditures, office-based visits, and emergency department visits. Modeling the outcomes with a two-part or hurdle model, instead of a single-equation model, reveals that the ACA policy increased the number of office-based visits but decreased emergency department visits and overall spending.


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Literature Cited

  1. Ai C, Norton EC. 1.  2003. Interaction terms in logit and probit models. Econ. Lett. 80:123–29 [Google Scholar]
  2. Akaike H. 2.  1970. Statistical predictor identification. Ann. Inst. Stat. Math. 22:203–17 [Google Scholar]
  3. Amuedo-Dorantes C, Yaya ME. 3.  2016. The impact of the ACA's extension of coverage to dependents on young adults’ access to care and prescription drugs. South. Econ. J. 83:25–44 [Google Scholar]
  4. Anderson M, Dobkin C, Gross T. 4.  2012. The effect of health insurance coverage on the use of medical services. Am. Econ. J. Econ. Policy 4:1–27 [Google Scholar]
  5. Antón JI, Muñoz de Bustillo R. 5.  2010. Health care utilisation and immigration in Spain. Eur. J. Health Econ. 11:487–98 [Google Scholar]
  6. Barbaresco S, Courtemanche CJ, Qi Y. 6.  2015. Impacts of the Affordable Care Act dependent coverage provision on health-related outcomes of young adults. J. Health Econ. 40:54–68 [Google Scholar]
  7. Belotti F, Deb P, Manning WG, Norton EC. 7.  2015. twopm: two-part models. Stata J 15:3–20 [Google Scholar]
  8. Berk ML, Monheit AC. 8.  2001. The concentration of health care expenditures, revisited. Health Aff 20:9–18 [Google Scholar]
  9. Blough DK, Madden CW, Hornbrook MC. 9.  1999. Modeling risk using generalized linear models. J. Health Econ. 18:153–71 [Google Scholar]
  10. Cameron AC, Trivedi PK. 10.  2013. Regression Analysis of Count Data. Cambridge, UK: Cambridge Univ. Press
  11. Cantor JC, Monheit AC, DeLia D, Lloyd K. 11.  2012. Early impact of the Affordable Care Act on health insurance coverage of young adults. Health Serv. Res. 47:1773–90 [Google Scholar]
  12. Cawley J, Meyerhoefer C. 12.  2012. The medical care costs of obesity: an instrumental variables approach. J. Health Econ. 31:219–30 [Google Scholar]
  13. Claeskens G, Hjort NL. 13.  2008. Model Selection and Model Averaging Cambridge, UK: Cambridge Univ. Press
  14. Deb P, Norton EC, Manning WG. 14.  2017. Health Econometrics Using Stata College Station, TX: Stata Press
  15. Duan N, Manning WG Jr, Morris CN, Newhouse JP. 15.  1984. Choosing between the sample-selection model and the multi-part model. J. Bus. Econ. Stat. 2:283–89 [Google Scholar]
  16. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W. 16.  2009. Annual medical spending attributable to obesity: payer-and service-specific estimates. Health Aff 28:w822–31 [Google Scholar]
  17. Gerdtham UG. 17.  1997. Equity in health care utilization: further tests based on hurdle models and Swedish micro data. Health Econ 6:303–19 [Google Scholar]
  18. Gerdtham UG, Trivedi PK. 18.  2001. Equity in Swedish health care reconsidered: new results based on the finite mixture model. Health Econ 10:565–72 [Google Scholar]
  19. Gourieroux C, Monfort A, Trognon A. 19.  1984. Pseudo maximum likelihood methods: applications to Poisson models. Econometrica 52:701–20 [Google Scholar]
  20. Gourieroux C, Monfort A, Trognon A. 20.  1984. Pseudo maximum likelihood methods: theory. Econometrica 52:681–700 [Google Scholar]
  21. Hardin JW, Hilbe JM. 21.  2007. Generalized Linear Models and Extensions College Station, TX: Stata Press
  22. Jhamb J, Dave D, Colman G. 22.  2015. The Patient Protection and Affordable Care Act and the utilization of health care services among young adults. Int. J. Health Econ. Dev. 1:8–25 [Google Scholar]
  23. Kadane JB, Lazar NA. 23.  2004. Methods and criteria for model selection. J. Am. Stat. Assoc. 99:279–90 [Google Scholar]
  24. King G. 24.  1988. Statistical models for political science event counts: bias in conventional procedures and evidence for the exponential Poisson regression model. Am. J. Pol. Sci. 32:838–63 [Google Scholar]
  25. Lahiri K, Xing G. 25.  2004. An econometric analysis of veterans’ health care utilization using twopart models. Empir. Econ. 29:431–49 [Google Scholar]
  26. Lê Cook B, McGuire TG, Lock K, Zaslavsky AM. 26.  2010. Comparing methods of racial and ethnic disparities measurement across different settings of mental health care. Health Serv. Res. 45:825–47 [Google Scholar]
  27. Leroux BG. 27.  1992. Consistent estimation of a mixing distribution. Ann. Stat. 20:1350–60 [Google Scholar]
  28. McCullagh P, Nelder JA. 28.  1989. Generalized Linear Models. Boca Raton, FL: CRC Press. , 2nd ed..
  29. Mihaylova B, Briggs A, O'Hagan A, Thompson SG. 29.  2011. Review of statistical methods for analysing healthcare resources and costs. Health Econ 20:897–916 [Google Scholar]
  30. Mullahy J. 30.  1998. Much ado about two: reconsidering retransformation and the two-part model in health economics. J. Health Econ. 17:3247–81 [Google Scholar]
  31. Newhouse JP, Phelps CE. 31.  1976. New estimates of price and income elasticities of medical care services. The Role of Health Insurance in the Health Services Sector, ed. RN Rosett, pp. 261–320 Cambridge, MA: Natl. Bur. Econ. Res. [Google Scholar]
  32. Norton EC, Dowd BE. 32.  2017. Log odds and the interpretation of logit models. Health Serv. Res. https://doi.org/10.1111/1475-6773.12712. In press [Crossref]
  33. Park RE. 33.  1966. Estimation with heteroscedastic error terms. Econometrica 34:888 [Google Scholar]
  34. Pohlmeier W, Ulrich V. 34.  1995. An econometric model of the two-part decisionmaking process in the demand for health care. J. Hum. Resour. 30:339–61 [Google Scholar]
  35. Pregibon D. 35.  1980. Goodness of link tests for generalized linear models. J. R. Stat. Soc. C 29:15–23 [Google Scholar]
  36. Puhani PA. 36.  2012. The treatment effect, the cross difference, and the interaction term in nonlinear “difference-in-differences” models. Econ. Lett. 115:85–87 [Google Scholar]
  37. Ramsey JB. 37.  1969. Tests for specification errors in classical linear least-squares regression analysis. J. R. Stat. Soc. Ser. B 31:350–71 [Google Scholar]
  38. Rao CR, Wu Y, Konishi S, Mukerjee R. 38.  2001. On model selection. Lect. Notes-Monogr. Ser. 38:1–64 [Google Scholar]
  39. Sarma S, Simpson W. 39.  2006. A microeconometric analysis of Canadian health care utilization. Health Econ 15:219–39 [Google Scholar]
  40. Schmid C. 40.  2015. Consumer health information and the demand for physician visits. Health Econ 24:1619–31 [Google Scholar]
  41. Schwarz G. 41.  1978. Estimating the dimension of a model. Ann. Stat. 6:461–64 [Google Scholar]
  42. Sin C-Y, White H. 42.  1996. Information criteria for selecting possibly misspecified parametric models. J. Econom. 71:207–25 [Google Scholar]
  43. Sommers BD, Buchmueller T, Decker SL, Carey C, Kronick R. 43.  2013. The Affordable Care Act has led to significant gains in health insurance and access to care for young adults. Health Aff 32:165–74 [Google Scholar]
  44. Ware JE Jr, Kosinski M, Keller SD. 44.  1996. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med. Care 34:220–33 [Google Scholar]
  45. Winkelmann R. 45.  2004. Health care reform and the number of doctor visits—an econometric analysis. J. Appl. Econom. 19:455–72 [Google Scholar]
  46. Winkelmann R. 46.  2008. Econometric Analysis of Count Data Berlin/Heidelberg: Springer

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