Health Programme Evaluation by Propensity Score Matching: Accounting for Treatment Intensity and Health Externalities with an Application to Brazil
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.
|Date of creation:|
|Date of revision:|
|Contact details of provider:|| Postal: HEDG/HERC, Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom|
Phone: (0)1904 323776
Web page: http://www.york.ac.uk/economics/postgrad/herc/hedg/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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, 06.
- Guido W. Imbens, 2003.
"Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review,"
NBER Technical Working Papers
0294, National Bureau of Economic Research, Inc.
- 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.
- 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, 01.
- 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.
- Eichler, Martin & Lechner, Michael, 2002.
"An evaluation of public employment programmes in the East German State of Sachsen-Anhalt,"
Elsevier, vol. 9(2), pages 143-186, April.
- Eichler, Martin & Lechner, Michael, 1999. "An Evaluation of Public Employment Programmes in the East German State of Sachsen-Anhalt," IZA Discussion Papers 94, Institute for the Study of Labor (IZA).
- Alberto Abadie & Guido W. Imbens, 2008.
"On the Failure of the Bootstrap for Matching Estimators,"
Econometric Society, vol. 76(6), pages 1537-1557, November.
- Alberto Abadie & Guido W. Imbens, 2006. "On the Failure of the Bootstrap for Matching Estimators," NBER Technical Working Papers 0325, National Bureau of Economic Research, Inc.
- Imbens, Guido & Abadie, Alberto, 2008. "On the Failure of the Bootstrap for Matching Estimators," Scholarly Articles 3043415, Harvard University Department of Economics.
- Jalan, Jyotsna & Ravallion, Martin, 2001.
"Does piped water reduce diarrhea for children in rural India ?,"
Policy Research Working Paper Series
2664, The World Bank.
- 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.
- 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.
- 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.
- 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.
- Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, Junio.
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)
If references are entirely missing, you can add them using this form.