IDEAS home Printed from https://ideas.repec.org/a/wly/hlthec/v11y2002i5p415-430.html
   My bibliography  Save this article

Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost‐effectiveness analysis

Author

Listed:
  • Jeffrey S. Hoch
  • Andrew H. Briggs
  • Andrew R. Willan

Abstract

Economic evaluation is often seen as a branch of health economics divorced from mainstream econometric techniques. Instead, it is perceived as relying on statistical methods for clinical trials. Furthermore, the statistic of interest in cost‐effectiveness analysis, the incremental cost‐effectiveness ratio is not amenable to regression‐based methods, hence the traditional reliance on comparing aggregate measures across the arms of a clinical trial. In this paper, we explore the potential for health economists undertaking cost‐effectiveness analysis to exploit the plethora of established econometric techniques through the use of the net‐benefit framework – a recently suggested reformulation of the cost‐effectiveness problem that avoids the reliance on cost‐effectiveness ratios and their associated statistical problems. This allows the formulation of the cost‐effectiveness problem within a standard regression type framework. We provide an example with empirical data to illustrate how a regression type framework can enhance the net‐benefit method. We go on to suggest that practical advantages of the net‐benefit regression approach include being able to use established econometric techniques, adjust for imperfect randomisation, and identify important subgroups in order to estimate the marginal cost‐effectiveness of an intervention. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:hlthec:v:11:y:2002:i:5:p:415-430
    DOI: 10.1002/hec.678
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/hec.678
    Download Restriction: no

    File URL: https://libkey.io/10.1002/hec.678?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Tambour, Magnus & Zethraeus, Niklas & Johannesson, Magnus, 1997. "A Note on Confidence Intervals in Cost-Effectiveness Analysis," SSE/EFI Working Paper Series in Economics and Finance 181, Stockholm School of Economics.
    3. Daniel Polsky & Henry A. Glick & Richard Willke & Kevin Schulman, 1997. "Confidence Intervals for Cost–Effectiveness Ratios: A Comparison of Four Methods," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 243-252, May.
    4. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    5. Andrew M. Jones, 2012. "health econometrics," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
    6. Aaron A. Stinnett & A. David Paltiel, 1997. "Estimating CE Ratios under Second-order Uncertainty," Medical Decision Making, , vol. 17(4), pages 483-489, October.
    7. Andrew Briggs & Paul Fenn, 1998. "Confidence intervals or surfaces? Uncertainty on the cost‐effectiveness plane," Health Economics, John Wiley & Sons, Ltd., vol. 7(8), pages 723-740, December.
    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. Andrew R. Willan & Andrew H. Briggs & Jeffrey S. Hoch, 2004. "Regression methods for covariate adjustment and subgroup analysis for non‐censored cost‐effectiveness data," Health Economics, John Wiley & Sons, Ltd., vol. 13(5), pages 461-475, May.
    2. Simon Eckermann & Andrew R. Willan, 2009. "Globally optimal trial design for local decision making," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 203-216, February.
    3. Zhang, Yinjunjie & Palma, Marco A., 2018. "Revisiting the Effects of Sugar Tax on Demand Elasticities - Evidence from the BLP Demand Model," 2018 Annual Meeting, August 5-7, Washington, D.C. 273978, Agricultural and Applied Economics Association.
    4. Jacques Mairesse & Bronwyn H. Hall & Benoît Mulkay, 1999. "Firm-Level Investment in France and the United States: An Exploration of What We Have Learned in Twenty Years," Annals of Economics and Statistics, GENES, issue 55-56, pages 27-67.
    5. Hamilton, James D. & Wu, Jing Cynthia, 2012. "Identification and estimation of Gaussian affine term structure models," Journal of Econometrics, Elsevier, vol. 168(2), pages 315-331.
    6. Niklas Zethraeus & Magnus Johannesson & Bengt Jönsson & Mickael Löthgren & Magnus Tambour, 2003. "Advantages of Using the Net-Benefit Approach for Analysing Uncertainty in Economic Evaluation Studies," PharmacoEconomics, Springer, vol. 21(1), pages 39-48, January.
    7. Emma McIntosh, 2006. "Using Discrete Choice Experiments within a Cost-Benefit Analysis Framework," PharmacoEconomics, Springer, vol. 24(9), pages 855-868, September.
    8. Martin Henriksson & Fredrik Lundgren & Per Carlsson, 2006. "Informing the efficient use of health care and health care research resources ‐ the case of screening for abdominal aortic aneurysm in Sweden," Health Economics, John Wiley & Sons, Ltd., vol. 15(12), pages 1311-1322, December.
    9. Joshua Graff Zivin, 2001. "Cost‐effectiveness analysis with risk aversion," Health Economics, John Wiley & Sons, Ltd., vol. 10(6), pages 499-508, September.
    10. Sebastian Kripfganz & Claudia Schwarz, 2019. "Estimation of linear dynamic panel data models with time‐invariant regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 526-546, June.
    11. Richard M. Nixon & David Wonderling & Richard D. Grieve, 2010. "Non‐parametric methods for cost‐effectiveness analysis: the central limit theorem and the bootstrap compared," Health Economics, John Wiley & Sons, Ltd., vol. 19(3), pages 316-333, March.
    12. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
    13. Antonio Diez de Los Rios, 2015. "A New Linear Estimator for Gaussian Dynamic Term Structure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 282-295, April.
    14. Aurélien Saussay, 2019. "Dynamic heterogeneity: rational habits and the heterogeneity of household responses to gasoline prices," Post-Print hal-03632598, HAL.
    15. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    16. Elamin H. Elbasha, 2005. "Risk aversion and uncertainty in cost‐effectiveness analysis: the expected‐utility, moment‐generating function approach," Health Economics, John Wiley & Sons, Ltd., vol. 14(5), pages 457-470, May.
    17. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    18. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers CWP03/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Lemieux, Thomas, 1998. "Estimating the Effects of Unions on Wage Inequality in a Panel Data Model with Comparative Advantage and Nonrandom Selection," Journal of Labor Economics, University of Chicago Press, vol. 16(2), pages 261-291, April.
    20. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.

    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:wly:hlthec:v:11:y:2002:i:5:p:415-430. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/5749 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.