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A quasi-Monte-Carlo comparison of parametric and semiparametric regression methods for heavy-tailed and non-normal data: an application to healthcare costs

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  • Andrew M. Jones
  • James Lomas
  • Peter T. Moore
  • Nigel Rice

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  • Andrew M. Jones & James Lomas & Peter T. Moore & Nigel Rice, 2016. "A quasi-Monte-Carlo comparison of parametric and semiparametric regression methods for heavy-tailed and non-normal data: an application to healthcare costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 951-974, October.
    • Handle: RePEc:bla:jorssa:v:179:y:2016:i:4:p:951-974
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    1. Holly, Alberto & Monfort, Alain & Rockinger, Michael, 2011. "Fourth order pseudo maximum likelihood methods," Journal of Econometrics, Elsevier, vol. 162(2), pages 278-293, June.
    2. Gilleskie, Donna B. & Mroz, Thomas A., 2004. "A flexible approach for estimating the effects of covariates on health expenditures," Journal of Health Economics, Elsevier, vol. 23(2), pages 391-418, March.
    3. Cummins, J. David & Dionne, Georges & McDonald, James B. & Pritchett, B. Michael, 1990. "Applications of the GB2 family of distributions in modeling insurance loss processes," Insurance: Mathematics and Economics, Elsevier, vol. 9(4), pages 257-272, December.
    4. Andrew M. Jones & James Lomas & Nigel Rice, 2014. "Applying Beta‐Type Size Distributions To Healthcare Cost Regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(4), pages 649-670, June.
    5. Manning, W. G. & Duan, N. & Rogers, W. H., 1987. "Monte Carlo evidence on the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 35(1), pages 59-82, May.
    6. Johnson, Elizabeth & Dominici, Francesca & Griswold, Michael & L. Zeger, Scott, 2003. "Disease cases and their medical costs attributable to smoking: an analysis of the national medical expenditure survey," Journal of Econometrics, Elsevier, vol. 112(1), pages 135-151, January.
    7. Manning, Willard G. & Basu, Anirban & Mullahy, John, 2005. "Generalized modeling approaches to risk adjustment of skewed outcomes data," Journal of Health Economics, Elsevier, vol. 24(3), pages 465-488, May.
    8. James B. Mcdonald & Jeff Sorensen & Patrick A. Turley, 2013. "Skewness And Kurtosis Properties Of Income Distribution Models," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59(2), pages 360-374, June.
    9. Andrew M. Jones & James Lomas & Nigel Rice, 2015. "Healthcare Cost Regressions: Going Beyond the Mean to Estimate the Full Distribution," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1192-1212, September.
    10. Mullahy, John, 1997. "Heterogeneity, Excess Zeros, and the Structure of Count Data Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 337-350, May-June.
    11. Jeffrey S. Hoch & Andrew H. Briggs & Andrew R. Willan, 2002. "Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 415-430, July.
    12. Partha Deb & James F. Burgess, Jr., 2003. "A Quasi-experimental Comparison of Econometric Models for Health Care Expenditures," Economics Working Paper Archive at Hunter College 212, Hunter College Department of Economics.
    13. Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
    14. Anirban Basu & Willard G. Manning & John Mullahy, 2004. "Comparing alternative models: log vs Cox proportional hazard?," Health Economics, John Wiley & Sons, Ltd., vol. 13(8), pages 749-765, August.
    15. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-336, May-June.
    16. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
    17. James J. Heckman, 2001. "Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture," Journal of Political Economy, University of Chicago Press, vol. 109(4), pages 673-748, August.
    18. Steven C. Hill & G. Edward Miller, 2010. "Health expenditure estimation and functional form: applications of the generalized gamma and extended estimating equations models," Health Economics, John Wiley & Sons, Ltd., vol. 19(5), pages 608-627, May.
    19. Anirban Basu & Bhakti V. Arondekar & Paul J. Rathouz, 2006. "Scale of interest versus scale of estimation: comparing alternative estimators for the incremental costs of a comorbidity," Health Economics, John Wiley & Sons, Ltd., vol. 15(10), pages 1091-1107, October.
    20. repec:hal:journl:peer-00815562 is not listed on IDEAS
    21. Kenneth J. Arrow & Robert C. Lind, 1974. "Uncertainty and the Evaluation of Public Investment Decisions," Palgrave Macmillan Books, in: Chennat Gopalakrishnan (ed.), Classic Papers in Natural Resource Economics, chapter 3, pages 54-75, Palgrave Macmillan.
    22. Duan, Naihua, et al, 1983. "A Comparison of Alternative Models for the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 115-126, April.
    23. Cawley, John & Meyerhoefer, Chad, 2012. "The medical care costs of obesity: An instrumental variables approach," Journal of Health Economics, Elsevier, vol. 31(1), pages 219-230.
    24. Blough, David K. & Madden, Carolyn W. & Hornbrook, Mark C., 1999. "Modeling risk using generalized linear models," Journal of Health Economics, Elsevier, vol. 18(2), pages 153-171, April.
    25. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
    26. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.
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    Cited by:

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    2. Yi Yao & Joan Schmit & Julie Shi, 2019. "Promoting sustainability for micro health insurance: a risk-adjusted subsidy approach for maternal healthcare service," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 44(3), pages 382-409, July.
    3. Alexandre Vimont & Henri Leleu & Isabelle Durand-Zaleski, 2022. "Machine learning versus regression modelling in predicting individual healthcare costs from a representative sample of the nationwide claims database in France," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(2), pages 211-223, March.
    4. Longden, Thomas & Wong, Chun Yee & Haywood, Philip & Hall, Jane & van Gool, Kees, 2018. "The prevalence of persistence and related health status: An analysis of persistently high healthcare costs in the short term and medium term," Social Science & Medicine, Elsevier, vol. 211(C), pages 147-156.
    5. Julie Shi & Yi Yao & Gordon Liu, 2018. "Modeling individual health care expenditures in China: Evidence to assist payment reform in public insurance," Health Economics, John Wiley & Sons, Ltd., vol. 27(12), pages 1945-1962, December.
    6. Sriubaite, I. & Harris, A. & Jones, A.M. & Gabbe, B., 2020. "Economic Consequences of Road Traffic Injuries. Application of the Super Learner algorithm," Health, Econometrics and Data Group (HEDG) Working Papers 20/20, HEDG, c/o Department of Economics, University of York.
    7. Sungchul Park & Anirban Basu, 2018. "Alternative evaluation metrics for risk adjustment methods," Health Economics, John Wiley & Sons, Ltd., vol. 27(6), pages 984-1010, June.
    8. Elena Arroyo-Borrell & Gemma Renart-Vicens & Marc Saez & Marc Carreras, 2017. "Hospital Costs of Foreign Non-Resident Patients: A Comparative Analysis in Catalonia, Spain," IJERPH, MDPI, vol. 14(9), pages 1-13, September.

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