IDEAS home Printed from https://ideas.repec.org/a/prs/ecstat/estat_0336-1454_2015_num_481_1_10636.html
   My bibliography  Save this article

Intégrer les dépenses de santé dans un modèle de microsimulation dynamique : le cas des dépenses de soins de ville

Author

Listed:
  • Charlotte Geay
  • Grégoire de Lagasnerie
  • Makram Larguem

Abstract

[fre] Anticiper la croissance à long terme des dépenses de santé constitue un des volets des exercices de surveillance budgétaire qui sont régulièrement menés à différents niveaux, notamment dans le cadre européen. Cette projection peut se faire à l’aide de maquettes macroéconomiques raisonnant à un niveau très agrégé. Mais l’exercice peut aussi se faire par microsimulation, ce qui offre un plus grand potentiel en termes de variantes et de types de résultats. La contrepartie est évidemment une certaine complexité puisqu’il faut modéliser des trajectoires individuelles d’état de santé et la distribution des dépenses associées plutôt que des valeurs moyennes. Cet article présente les premières étapes de la construction d’un modèle de ce type, appliqué aux dépenses de soins de ville. Ce modèle comprend deux modules. Le premier est un module «épidémiologique » qui projette un indicateur dichotomique de bonne / mauvaise santé obtenu en croisant données de santé subjectives et objectives. Cet indicateur est évalué sur le panel de l’enquête santé et protection sociale (ESPS) allant de 2002 à 2008. Ce panel permet d’estimer les probabilités de passage entre bonne et mauvaise santé ainsi que les probabilités de décès différenciées selon l’état de santé. Ce sont ces probabilités qui sont ensuite utilisées pour faire vieillir progressivement l’échantillon de 2008, à l’horizon de 2032. Une fois projetés les états de santé individuels, le second module simule les dépenses qui leur sont associées, à l’aide d’une approche séquentielle simulant d’abord le fait d’avoir une dépense non nulle, puis le niveau de cette dépense si elle est positive. L’articulation de ces deux modules est illustrée par quelques projections exploratoires. Ils ont été conçus pour être applicables à d’autres données de base. Ils pourront aussi être couplés avec des outils de microsimulation appliqués aux autres aspects du vieillissement démographique, principalement les retraites.

Suggested Citation

  • Charlotte Geay & Grégoire de Lagasnerie & Makram Larguem, 2015. "Intégrer les dépenses de santé dans un modèle de microsimulation dynamique : le cas des dépenses de soins de ville," Économie et Statistique, Programme National Persée, vol. 481(1), pages 211-234.
  • Handle: RePEc:prs:ecstat:estat_0336-1454_2015_num_481_1_10636
    DOI: 10.3406/estat.2015.10636
    Note: DOI:10.3406/estat.2015.10636
    as

    Download full text from publisher

    File URL: https://doi.org/10.3406/estat.2015.10636
    Download Restriction: no

    File URL: https://www.persee.fr/doc/estat_0336-1454_2015_num_481_1_10636
    Download Restriction: no

    References listed on IDEAS

    as
    1. Brigitte Dormont & Michel Grignon & Hélène Huber, 2006. "Health expenditure growth: reassessing the threat of ageing," Health Economics, John Wiley & Sons, Ltd., vol. 15(9), pages 947-963, September.
    2. Albouy, Valerie & Davezies, Laurent & Debrand, Thierry, 2010. "Health expenditure models: A comparison using panel data," Economic Modelling, Elsevier, vol. 27(4), pages 791-803, July.
    3. Bound, John & Schoenbaum, Michael & Stinebrickner, Todd R. & Waidmann, Timothy, 1999. "The dynamic effects of health on the labor force transitions of older workers," Labour Economics, Elsevier, vol. 6(2), pages 179-202, June.
    4. Zucchelli, E. & Harris, M. & Zhao, X., 2012. "Ill-health and transitions to part-time work and self-employment among older workers," Health, Econometrics and Data Group (HEDG) Working Papers 12/04, HEDG, c/o Department of Economics, University of York.
    5. Mullahy, John, 1998. "Much ado about two: reconsidering retransformation and the two-part model in health econometrics," Journal of Health Economics, Elsevier, vol. 17(3), pages 247-281, June.
    6. 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.
    7. Fabrice Etilé & Carine Milcent, 2006. "Income‐related reporting heterogeneity in self‐assessed health: evidence from France," Health Economics, John Wiley & Sons, Ltd., vol. 15(9), pages 965-981, September.
    8. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
    9. John Mullahy, 1998. "Much Ado About Two: Reconsidering Retransformation and the Two-Part Model in Health Economics," NBER Technical Working Papers 0228, National Bureau of Economic Research, Inc.
    10. Disney, Richard & Emmerson, Carl & Wakefield, Matthew, 2006. "Ill health and retirement in Britain: A panel data-based analysis," Journal of Health Economics, Elsevier, vol. 25(4), pages 621-649, July.
    11. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    12. S. P. Thi颡ut & T. Barnay & B. Ventelou, 2013. "Ageing, chronic conditions and the evolution of future drugs expenditure: a five-year micro-simulation from 2004 to 2029," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1663-1672, May.
    13. Claire Marbot & Delphine Roy, 2015. "Projections du coût de l’APA et des caractéristiques de ses bénéficiaires à l’horizon 2040 à l’aide du modèle Destinie," Économie et Statistique, Programme National Persée, vol. 481(1), pages 185-209.
    14. repec:dau:papers:123456789/3881 is not listed on IDEAS
    15. Leung, Siu Fai & Yu, Shihti, 1996. "On the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 197-229.
    16. Eugenio Zucchelli & Andrew M Jones & Nigel Rice, 2012. "The evaluation of health policies through dynamic microsimulation methods," International Journal of Microsimulation, International Microsimulation Association, vol. 5(1), pages 2-20.
    17. Jones, Andrew M. & Rice, Nigel & Roberts, Jennifer, 2010. "Sick of work or too sick to work? Evidence on self-reported health shocks and early retirement from the BHPS," Economic Modelling, Elsevier, vol. 27(4), pages 866-880, July.
    18. 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.
    19. Didier Blanchet & Thierry Debrand, 2007. "Souhaiter prendre sa retraite le plus tôt possible : santé, satisfaction au travail et facteurs monétaires," Économie et Statistique, Programme National Persée, vol. 403(1), pages 39-62.
    20. Teresa Bago d'Uva & Eddy Van Doorslaer & Maarten Lindeboom & Owen O'Donnell, 2008. "Does reporting heterogeneity bias the measurement of health disparities?," Health Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 351-375, March.
    21. William Greene, 2003. "A Interpreting Estimated Parameters and Measuring Individual Heterogeneity in Random Coefficient Models," Working Papers 03-19, New York University, Leonard N. Stern School of Business, Department of Economics.
    22. Martin Spielauer, 2007. "Dynamic microsimulation of health care demand, health care finance and the economic impact of health behaviours: survey and review," International Journal of Microsimulation, International Microsimulation Association, vol. 1(1), pages 35-53.
    23. Roberto Astolfi & Luca Lorenzoni & Jillian Oderkirk, 2012. "A Comparative Analysis of Health Forecasting Methods," OECD Health Working Papers 59, OECD Publishing.
    24. repec:cai:popine:popu_p1998_10n1_0136 is not listed on IDEAS
    25. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
    26. repec:dau:papers:123456789/3883 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Charlotte Geay & Grégoire de Lagasnerie & Makram Larguem, 2014. "Evolution of outpatient healthcare expenditure due to ageing in 2030, a dynamic micro-simulation model for France," Sciences Po publications 28, Sciences Po.
    2. Valerie Albouy & Laurent Davezies & Thierry Debrand, 2009. "Dynamic Estimation of Health Expenditure: A new approach for simulating individual expenditure," Working Papers DT20, IRDES institut for research and information in health economics, revised Jan 2009.
    3. 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.
    4. Silva João M. C. Santos & Tenreyro Silvana & Windmeijer Frank, 2015. "Testing Competing Models for Non-negative Data with Many Zeros," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 1-18, January.
    5. Besstremyannaya, Galina, 2017. "Measuring income equity in the demand for healthcare with finite mixture models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 5-29.
    6. Liu, Lei & Strawderman, Robert L. & Cowen, Mark E. & Shih, Ya-Chen T., 2010. "A flexible two-part random effects model for correlated medical costs," Journal of Health Economics, Elsevier, vol. 29(1), pages 110-123, January.
    7. 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.
    8. Albouy, Valerie & Davezies, Laurent & Debrand, Thierry, 2010. "Health expenditure models: A comparison using panel data," Economic Modelling, Elsevier, vol. 27(4), pages 791-803, July.
    9. Kostas Mavromaras & Joanne Flavel, 2017. "An Analysis of the Impact of Health on Occupation," The Economic Record, The Economic Society of Australia, vol. 93, pages 86-104, June.
    10. Oscar Mitnik, 2008. "How do Training Programs Assign Participants to Training? Characterizing the Assignment Rules of Government Agencies for Welfare-to-Work Programs in California," Working Papers 0907, University of Miami, Department of Economics.
    11. Brigitte Dormont & Hélène Huber, 2006. "Ageing and changes in medical practices : reassessing theinfluence of demography," Post-Print halshs-00274723, HAL.
    12. Rémi Lardellier & Renaud Legal & Denis Raynaud & Guillaume Vidal, 2011. "Un outil pour l’étude des dépenses de santé et des « restes à charge » des ménages : le modèle Omar," Économie et Statistique, Programme National Persée, vol. 450(1), pages 47-77.
    13. Martijn van Hasselt, 2005. "Bayesian Sampling Algorithms for the Sample Selection and Two-Part Models," Computing in Economics and Finance 2005 241, Society for Computational Economics.
    14. Kathleen Carey & Theodore Stefos, 2011. "Measuring the cost of hospital adverse patient safety events," Health Economics, John Wiley & Sons, Ltd., vol. 20(12), pages 1417-1430, December.
    15. 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.
    16. Randall P. Ellis & Pooja G. Mookim, 2013. "K-Fold Cross-Validation is Superior to Split Sample Validation for Risk Adjustment Models," Boston University - Department of Economics - Working Papers Series wp2013-026, Boston University - Department of Economics.
    17. 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.
    18. Heres-Del-Valle, David & Niemeier, Deb, 2011. "CO2 emissions: Are land-use changes enough for California to reduce VMT? Specification of a two-part model with instrumental variables," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 150-161, January.
    19. Johnston, David W. & Propper, Carol & Shields, Michael A., 2009. "Comparing subjective and objective measures of health: Evidence from hypertension for the income/health gradient," Journal of Health Economics, Elsevier, vol. 28(3), pages 540-552, May.
    20. Puhani, Patrick A., 1997. "Foul or Fair? The Heckman Correction for Sample Selection and Its Critique. A Short Survey," ZEW Discussion Papers 97-07, ZEW - Leibniz Centre for European Economic Research.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:prs:ecstat:estat_0336-1454_2015_num_481_1_10636. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Equipe PERSEE). General contact details of provider: https://www.persee.fr/collection/estat .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.