IDEAS home Printed from https://ideas.repec.org/p/yor/hectdg/09-05.html
   My bibliography  Save this paper

Health Programme Evaluation by Propensity Score Matching: Accounting for Treatment Intensity and Health Externalities with an Application to Brazil

Author

Listed:
  • Moreno-Serra R

Abstract

Most of the literature on health programme evaluation has estimated average programme impacts relying on either: (i) data on the presence or absence of an intervention in a particular locality, or (ii) data on individual participation in the health programme. By estimating an average health impact which is independent of the programme’s population coverage, the empirical approaches of these studies overlook the important fact that public health interventions create externalities whose magnitude depends crucially on the number of covered individuals in a locality. The main contributions of this paper are to suggest and apply an empirical approach for the impact evaluation of public health interventions which also takes into account treatment externalities, when non-experimental, routine data are available. The proposed framework involves the computation of average treatment effects by a propensity score matching-difference-in-differences estimator adapted to the case of multiple treatments, jointly evaluating the impact of different programme coverage levels. The methods are used to conduct an impact evaluation of the Family Health Programme (Programa Saude da Familia—PSF), the broadest health programme ever launched in Brazil, on adult and child health. I find that exposure to higher PSF coverage levels leads to improvements in individual health outcomes, with relatively small effects for adults but larger estimated impacts for children.

Suggested Citation

  • Moreno-Serra R, "undated". "Health Programme Evaluation by Propensity Score Matching: Accounting for Treatment Intensity and Health Externalities with an Application to Brazil," Health, Econometrics and Data Group (HEDG) Working Papers 09/05, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:09/05
    as

    Download full text from publisher

    File URL: https://www.york.ac.uk/media/economics/documents/herc/wp/09_05.pdf
    File Function: Main text
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    2. Jalan, Jyotsna & Ravallion, Martin, 2003. "Does piped water reduce diarrhea for children in rural India?," Journal of Econometrics, Elsevier, vol. 112(1), pages 153-173, January.
    3. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
    4. Eichler, Martin & Lechner, Michael, 2002. "An evaluation of public employment programmes in the East German State of Sachsen-Anhalt," Labour Economics, Elsevier, vol. 9(2), pages 143-186, April.
    5. Cameron,A. Colin & Trivedi,Pravin K., 2008. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9787111235767, March.
    6. Armecin, Graeme & Behrman, Jere R. & Duazo, Paulita & Ghuman, Sharon & Gultiano, Socorro & King, Elizabeth M. & Lee, Nannette, 2006. "Early childhood development through an integrated program : evidence from the Philippines," Policy Research Working Paper Series 3922, The World Bank.
    7. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    8. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    9. Richard Blundell & Monica Costa Dias, 2000. "Evaluation methods for non-experimental data," Fiscal Studies, Institute for Fiscal Studies, vol. 21(4), pages 427-468, January.
    10. Gustavo Angeles & David Guilkey & Thomas Mroz, 2005. "The determinants of fertility in rural Peru: Program effects in the early years of the national family planning program," Journal of Population Economics, Springer;European Society for Population Economics, vol. 18(2), pages 367-389, June.
    11. Edward Miguel & Michael Kremer, 2004. "Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities," Econometrica, Econometric Society, vol. 72(1), pages 159-217, January.
    12. Kosuke Imai & Gary King & Elizabeth A. Stuart, 2008. "Misunderstandings between experimentalists and observationalists about causal inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 481-502.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. de Preux, L, 2010. "Ex Ante Moral Hazard and Anticipatory Behaviour: Some Evidence," Health, Econometrics and Data Group (HEDG) Working Papers 10/13, HEDG, c/o Department of Economics, University of York.
    2. Islam, Abu Hayat, 2015. "Can Integrated Rice-Fish System Increase Welfare of the Marginalized Extreme Poor in Bangladesh? A DID Matching Approach," 2015 Conference, August 9-14, 2015, Milan, Italy 211792, International Association of Agricultural Economists.
    3. Abebaw, Degnet & Fentie, Yibeltal & Kassa, Belay, 2010. "The impact of a food security program on household food consumption in Northwestern Ethiopia: A matching estimator approach," Food Policy, Elsevier, vol. 35(4), pages 286-293, August.
    4. Salmasi, Luca & Pieroni, Luca, 2015. "Immigration policy and birth weight: Positive externalities in Italian law," Journal of Health Economics, Elsevier, vol. 43(C), pages 128-139.

    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:yor:hectdg:09/05. 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: (Jane Rawlings). General contact details of provider: http://edirc.repec.org/data/deyoruk.html .

    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.