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Health expenditure estimation and functional form: applications of the generalized gamma and extended estimating equations models

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  • Steven C. Hill
  • G. Edward Miller

Abstract

Health‐care expenditure regressions are used in a wide variety of economic analyses including risk adjustment and program and treatment evaluations. Recent articles demonstrated that generalized gamma models (GGMs) and extended estimating equations (EEE) models provide flexible approaches to deal with a variety of data problems encountered in expenditure estimation. To date there have been few empirical applications of these models to expenditures. We use data from the US Medical Expenditure Panel Survey to compare the bias, predictive accuracy, and marginal effects of GGM and EEE models with other commonly used regression models in a cross‐validation study design. Health‐care expenditure distributions vary in the degree of heteroskedasticity, skewness, and kurtosis by type of service and population. To examine the ability of estimators to address a range of data problems, we estimate models of total health expenditures and prescription drug expenditures for two populations, the elderly and privately insured adults. Our findings illustrate the need for researchers to examine their assumptions about link functions: the appropriate link function varies across our four distributions. The EEE model, which has a flexible link function, is a robust estimator that performs as well, or better, than the other models in each distribution. Published in 2009 by John Wiley & Sons, Ltd.

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  • 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.
  • Handle: RePEc:wly:hlthec:v:19:y:2010:i:5:p:608-627
    DOI: 10.1002/hec.1498
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Jones, A. & Lomas, J. & Rice, N., 2014. "Going Beyond the Mean in Healthcare Cost Regressions: a Comparison of Methods for Estimating the Full Conditional Distribution," Health, Econometrics and Data Group (HEDG) Working Papers 14/26, HEDG, c/o Department of Economics, University of York.
    3. 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.
    4. Noémi Kreif & Richard Grieve & M. Zia Sadique, 2013. "Statistical Methods For Cost‐Effectiveness Analyses That Use Observational Data: A Critical Appraisal Tool And Review Of Current Practice," Health Economics, John Wiley & Sons, Ltd., vol. 22(4), pages 486-500, April.
    5. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2012. "The Influence of BMI, Obesity and Overweight on Medical Costs: A Panel Data Approach," Working Papers 2012-08, FEDEA.
    6. Christopher S. Brunt, 2015. "Medicare Part B Intensity and Volume Offset," Health Economics, John Wiley & Sons, Ltd., vol. 24(8), pages 1009-1026, August.
    7. 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.
    8. 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.
    9. Hui Zhang & Wenjing Zhou & Donglan Zhang, 2022. "Direct Medical Costs of Parkinson’s Disease in Southern China: A Cross-Sectional Study Based on Health Insurance Claims Data in Guangzhou City," IJERPH, MDPI, vol. 19(6), pages 1-19, March.
    10. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2012. "The Influence of BMI, Obesity and Overweight on Medical Costs: A Panel Data Approach," Working Papers 2012-08, FEDEA.
    11. 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.
    12. Courbage, Christophe & Rey, Béatrice, 2012. "Priority setting in health care and higher order degree change in risk," Journal of Health Economics, Elsevier, vol. 31(3), pages 484-489.
    13. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2015. "The influence of obesity and overweight on medical costs: a panel data perspective," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(2), pages 161-173, March.
    14. Marcel Bilger & Willard G. Manning, 2015. "Measuring Overfitting In Nonlinear Models: A New Method And An Application To Health Expenditures," Health Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 75-85, January.
    15. 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.
    16. Kasteridis, Panagiotis & Rice, Nigel & Santos, Rita, 2022. "Heterogeneity in end of life health care expenditure trajectory profiles," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 221-251.
    17. Jones, A.M, 2010. "Models For Health Care," Health, Econometrics and Data Group (HEDG) Working Papers 10/01, HEDG, c/o Department of Economics, University of York.
    18. Claudia Geue & James Lewsey & Paula Lorgelly & Lindsay Govan & Carole Hart & Andrew Briggs, 2012. "Spoilt For Choice: Implications Of Using Alternative Methods Of Costing Hospital Episode Statistics," Health Economics, John Wiley & Sons, Ltd., vol. 21(10), pages 1201-1216, October.
    19. 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.
    20. Anne Mason & Idaira Rodriguez Santana & María José Aragón & Nigel Rice & Martin Chalkley & Raphael Wittenberg & Jose-Luis Fernandez, 2019. "Drivers of health care expenditure: Final report," Working Papers 169cherp, Centre for Health Economics, University of York.
    21. Jongsay Yong & Ou Yang, 2021. "Does socioeconomic status affect hospital utilization and health outcomes of chronic disease patients?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(2), pages 329-339, March.
    22. 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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