Demography

, 48:749 | Cite as

Microcredit, Family Planning Programs, and Contraceptive Behavior: Evidence From a Field Experiment in Ethiopia

Article

Abstract

The impact of community-based family planning programs and access to credit on contraceptive use, fertility, and family size preferences has not been established conclusively in the literature. We provide additional evidence on the possible effect of such programs by describing the results of a randomized field experiment whose main purpose was to increase the use of contraceptive methods in rural areas of Ethiopia. In the experiment, administrative areas were randomly allocated to one of three intervention groups or to a fourth control group. In the first intervention group, both credit and family planning services were provided and the credit officers also provided information on family planning. Only credit or family planning services, but not both, were provided in the other two intervention groups, while areas in the control group received neither type of service. Using pre- and post-intervention surveys, we find that neither type of program, combined or in isolation, led to an increase in contraceptive use that is significantly greater than that observed in the control group. We conjecture that the lack of impact has much to do with the mismatch between women’s preferred contraceptive method (injectibles) and the contraceptives provided by community-based agents (pills and condoms).

Keywords

Family planning Microcredit Randomized controlled trial Community health workers Ethiopia 

References

  1. Amin, R., Hill, R. B., & Li, Y. (1995). Poor women’s participation in credit-based self employment: The impact on their empowerment, fertility, contraceptive use, and fertility desire in rural Bangladesh. Pakistan Development Review, 34, 93–119.Google Scholar
  2. Angeles, G., Guilkey, D., & Mroz, T. (1998). Purposive program placement and the estimation of family planning program effects in Tanzania. Journal of the American Statistical Association, 93, 884–899.CrossRefGoogle Scholar
  3. Angeles, G., Guilkey, D., & Mroz, T. (2005a). The determinants of fertility in rural Peru: Program effects in the early years of the national family planning program. Journal of Population Economics, 18, 367–389.CrossRefGoogle Scholar
  4. Angeles, G., Guilkey, D., & Mroz, T. (2005b). The effects of education and family planning programs on fertility in Indonesia. Economic Development and Cultural Change, 54(1), 165–201.CrossRefGoogle Scholar
  5. Bang, S. (1971). KOREA: The relationship between IUD retention and check-up visits. Studies in Family Planning, 2, 110–112.CrossRefGoogle Scholar
  6. Baum, C. F., Schaffer, M. E., & Stillman, S. (2007). Enhanced routines for instrumental variables/generalized method of moments estimation and testing. Stata Journal, 7, 465–506.Google Scholar
  7. Bauman, K. E. (1997). The effectiveness of family planning programs evaluated with true experimental designs. American Journal of Public Health, 87, 666–669.CrossRefGoogle Scholar
  8. Bauman, K. E., Viadro, C. I., & Tsui, A. O. (1994). Use of true experimental designs for family planning program evaluation: Merits, problems and solutions. International Family Planning Perspectives, 20, 108–113.CrossRefGoogle Scholar
  9. Binka, F. N., Nazzar, A., & Phillips, J. F. (1995). The Navrongo community health and family planning project. Studies in Family Planning, 26, 121–139.CrossRefGoogle Scholar
  10. Bongaarts, J. (1994). The impact of population policies: Comment. Population and Development Review, 20, 616–620.CrossRefGoogle Scholar
  11. Buttenheim, A. (2006). Microfinance Programs and Contraceptive Use: Evidence from Indonesia (Working Paper CCPR-020-06). Los Angeles, CA: California Center for Population Research.Google Scholar
  12. Chan, K. C. (1971). Hong Kong: Report of the IUD reassurance project. Studies in Family Planning, 2, 225–233.CrossRefGoogle Scholar
  13. Deaton, A. (2010). Instruments, randomization, and learning about development. Journal of Economic Literature, 48, 424–455.CrossRefGoogle Scholar
  14. Debpuur, C., Phillips, J. F., Jackson, E. F., Nazzar, A., Ngom, P., & Binka, F. N. (2002). The impact of the Navrongo project on contraceptive knowledge and use, reproductive preferences, and fertility. Studies in Family Planning, 33, 141–164.CrossRefGoogle Scholar
  15. Duflo, E., Glennerster, R., & Kremer, M. (2008). Using randomization in development economics research: A toolkit. In T. P. Schultz & J. Strauss (Eds.), Handbook of development economics (Vol. 4, pp. 3895–3962). Amsterdam, The Netherlands: Elsevier.Google Scholar
  16. Family Health International. (2007). Linking Access to Credit and Family Planning Services in Ethiopia. Final Report. Prepared for the David and Lucile Packard Foundation Population Program in Ethiopia.Google Scholar
  17. Foster, A., & Roy, N. (1997). The dynamics of education and fertility: Evidence from a family planning experiment (Economics Department Working Paper). Philadelphia, PA: University of Pennsylvania.Google Scholar
  18. Freedman, R. (1997). Do family planning programs affect fertility preferences? A literature review. Studies in Family Planning, 28, 1–13.CrossRefGoogle Scholar
  19. Freedman, D. (2008). On regression adjustments to experimental data. Advances in Applied Mathematics, 40, 180–193.CrossRefGoogle Scholar
  20. Freedman, R., & Takeshita, J. Y. (1969). Family planning in Taiwan: An experiment in social change. Princeton, NJ: Princeton University Press.Google Scholar
  21. Gertler, P., & Molyneaux, J. (1994). How economic development and family planning programs combined to reduce Indonesian fertility. Demography, 31, 33–63.CrossRefGoogle Scholar
  22. Hashemi, S. M., Schuler, S. R., & Riley, A. P. (1996). Rural credit programs and women’s empowerment in Bangladesh. World Development, 24, 635–653.CrossRefGoogle Scholar
  23. Hayashi, F. (2000). Econometrics (1st ed.). Princeton, NJ: Princeton University Press.Google Scholar
  24. Heckman, J., LaLonde, R., & Smith, J. (1999). The economics and econometrics of active labor market programs. In O. Ashenfelter & D. Card (Eds.), Handbook of labor economics, Vol. 3A. Amsterdam, The Netherlands: Elsevier Science.Google Scholar
  25. Joshi, S., & Schultz, T. P. (2007). Family planning as an investment in development: Evaluation of a program’s consequences in Matlab, Bangladesh (Center Discussion Paper No. 951). New Haven, CT: Economic Growth Center, Yale University.Google Scholar
  26. Katz, K., West, C., Doumbia, F., & Kané, F. (1998). Increasing access to family planning services in rural Mali through community-based distribution. International Family Planning Perspectives, 24, 104–110.CrossRefGoogle Scholar
  27. Kleibergen, F., & Paap, R. (2006). Generalized reduced rank tests using the singular value decomposition. Journal of Econometrics, 127, 97–126.CrossRefGoogle Scholar
  28. Luck, M., Jarju, E., Nell, M. D., & George, M. O. (2000). Mobilizing demand for contraception in rural Gambia. Studies in Family Planning, 31, 325–335.CrossRefGoogle Scholar
  29. Macro International Inc. (2007). Trends in demographic and reproductive health indicators in Ethiopia. Calverton, MD: Macro International Inc.Google Scholar
  30. Mayoux, L. (1999). Questioning virtuous spirals: Microfinance and women’s empowerment in Africa. Journal of International Development, 11, 957–984.CrossRefGoogle Scholar
  31. Miller, G. (2010). Contraception as development? New evidence from family planning in Colombia. The Economic Journal, 120, 709–736.CrossRefGoogle Scholar
  32. Omu, A. E., Weir, S. S., Janowitz, B., Covington, D. L., Lamptey, P. R., & Burton, N. N. (1989). The effect of counseling on sterilization acceptance by high-parity women in Nigeria. International Family Planning Perspectives, 15, 66–71.CrossRefGoogle Scholar
  33. Phillips, J., Bawah, A., & Binka, F. (2006). Accelerating reproductive and child health programme impact with community-based services: The Navrongo experiment in Ghana. Bulletin of the World Health Organization, 84, 949–955.CrossRefGoogle Scholar
  34. Phillips, J., Greene, W., & Jackson, E. (1999). Lessons from community-based distribution of family planning in Africa (Policy Research Division Working Paper 121). New York: The Population Council.Google Scholar
  35. Pitt, M., Khandker, S., Mckernan, S.-M., & Abdul Latif, M. (1999). Credit programs for the poor and reproductive behavior in low-income countries: Are the reported causal relationships the result of heterogeneity bias? Demography, 36, 1–21.CrossRefGoogle Scholar
  36. Pitt, M., Rosenzweig, M., & Gibbons, D. (1993). The determinants and consequences of the placement of government programs in Indonesia. World Bank Economic Review, 7, 319–348.CrossRefGoogle Scholar
  37. Pritchett, L. (1994). Desired fertility and the impact of population policies. Population and Development Review, 20, 1–55.CrossRefGoogle Scholar
  38. Rosenfield, A. G., & Limcharoen, C. (1972). Auxiliary midwife prescription of oral contraceptives: An experimental project in Thailand. American Journal of Obstetrics and Gynecology, 114, 942–949.Google Scholar
  39. Schuler, S. R., & Hashemi, S. M. (1994). Credit programs, women’s empowerment, and contraceptive use in rural Bangladesh. Studies in Family Planning, 25, 65–76.CrossRefGoogle Scholar
  40. Schuler, S. R., Hashemi, S. M., & Riley, A. P. (1997). The influence of women’s changing roles and status in Bangladesh’s fertility transition: Evidence from a study of credit programs and contraceptive use. World Development, 25, 563–575.CrossRefGoogle Scholar
  41. Schultz, T. P. (1997). Demand for children in low income countries. In M. R. Rosenzweig & O. Stark (Eds.), Handbook of population and family economics. Amsterdam, The Netherlands: Elsevier Science.Google Scholar
  42. Schultz, T. P. (2005). Fertility and income (Center Discussion Paper No. 925). New Haven, CT: Economic Growth Center, Yale University.Google Scholar
  43. Sinha, N. (2005). Fertility, child work, and schooling consequences of family planning programs: Evidence from and experiment in rural Bangladesh. Economic Development and Cultural Change, 54, 97–128.CrossRefGoogle Scholar
  44. Steele, F., Amin, S., & Naved, R. T. (2001). Savings/credit group formation and change in contraception. Demography, 38, 267–282.CrossRefGoogle Scholar
  45. Stock, J., Wright, J., & Yogo, M. (2002). A survey of weak instruments and weak identification in generalized method of moments. Journal of Business and Economic Statistics, 20, 518–529.CrossRefGoogle Scholar
  46. Stock, J., & Yogo, M. (2002). Testing for weak instruments in linear IV regression (NBER Technical Working Paper 284). Cambridge, MA: National Bureau of Economic Research.Google Scholar
  47. Thomas, D., & Maluccio, J. (2001). Fertility, contraceptive choice, and public policy in Zimbabwe. The World Bank Economic Review, 10, 189–222.Google Scholar
  48. Yang, J. M., Bang, S., Kim, M. H., & Lee, M. G. (1965). Fertility and family planning in rural Korea. Population Studies, 18, 237–250.CrossRefGoogle Scholar

Copyright information

© Population Association of America 2011

Authors and Affiliations

  1. 1.Health Services Research Centre, School of GovernmentVictoria University of WellingtonWellingtonNew Zealand
  2. 2.Department of EconomicsDuke UniversityDurhamUSA

Personalised recommendations