Skip to main content

Advertisement

SpringerLink
Log in

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

  • Published:
Demography

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).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. There is not much consensus, however, on the overall effectiveness of such programs in achieving these goals. While Pritchett (1994) is skeptical of family planning programs, others like Bongaarts (1994) have argued for an important albeit nondominant role. An intermediate position is taken by Freedman (1997), whose literature survey concluded that, while an impact on fertility preferences has rarely been documented convincingly, several family planning services have allowed families to meet existing demand for fertility control.

  2. Alternatively, Eq. 1 could be estimated directly using PA-fixed effects. An earlier draft of this paper used this approach and led to almost identical results.

  3. More specifically, we calculate the weights as the mean number of observations from a given PA in the baseline and in the follow-up. These numbers are not always identical, although they are always very similar (the correlation is approximately .97 in both regions). Note also that the dependent variable in Model 2 is a weighted PA-specific mean, where all observations are weighted using the village-specific sampling weights.

  4. Alternatively, Eq. 1 could be estimated with 2SLS and PA fixed effects. This estimation strategy, which we adopted in an earlier version of the paper, leads to almost identical results.

  5. We note, however, that in small samples, the inclusion of pre-intervention characteristics does not necessarily increase the precision of the estimates, even in situations in which the randomization was done carefully. On the one hand, the R 2 of the regression will, by construction, increase. However, in small samples, the orthogonality between assigned treatment and the residuals usually does not hold exactly, with the consequence that the inclusion of other covariates is not guaranteed to decrease the standard errors. We also note that, although the inclusion of additional covariates is often advocated by randomized controlled trials practitioners (see, e.g., Duflo et al. 2008), the practice has been criticized by others as an ex-post adjustment not justified by randomization (see Deaton 2010; Freedman 2008).

  6. The changes in socioeconomic status described in Table 4 were relatively similar across treatment groups with the exception of borrowing, which, not surprisingly, shows significantly larger increases in areas where microcredit was introduced. For almost all other variables, we cannot reject the null hypothesis that the changes were the same across the four (actual) treatment groups. The detailed results are available upon request from the authors.

  7. For a description of the test, which is identical to a Hausman test under conditional homoskedasticity, see Hayashi 2000:200–201 or Baum et al. 2007:16.

  8. A version of the test, robust to the presence of heteroskedasticity or clustering, can be performed by using the Stata command ivreg2. This test can be considered as a generalization of the Anderson canonical correlation rank statistic to the non-i.i.d. case. The null hypothesis is that the smallest canonical correlation is zero, in which case the equation is not identified. A rejection of the null hypothesis indicates instead that the excluded instruments are relevant. The results of the first-stage regressions are available upon request from the authors.

  9. In the presence of more than one endogenous variable, multivariate versions of the test have been developed that evaluate the first stage for all endogenous variables jointly. Critical values for such tests have been developed only for specific combinations of the number of instruments and endogenous variables (see Tables 1 and 2 in Stock and Yogo 2002). Unfortunately, such critical values do not exist for a case such as ours, where there are three endogenous variables and three excluded.

  10. In the model with pre-intervention controls estimated in columns 3 and 6, the intercept does not have a meaningful interpretation.

  11. The OLS estimates, which for brevity are not reported, are available upon request from the authors.

  12. The full results are available upon request.

  13. The full results, omitted for brevity, are available upon request. We also note that the results for Amhara should be interpreted with caution because the Kleibergen-Paap tests indicate that the null of underidentification is not rejected at standard levels.

References

  • 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 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Bang, S. (1971). KOREA: The relationship between IUD retention and check-up visits. Studies in Family Planning, 2, 110–112.

    Article  Google Scholar 

  • 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 

  • Bauman, K. E. (1997). The effectiveness of family planning programs evaluated with true experimental designs. American Journal of Public Health, 87, 666–669.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Binka, F. N., Nazzar, A., & Phillips, J. F. (1995). The Navrongo community health and family planning project. Studies in Family Planning, 26, 121–139.

    Article  Google Scholar 

  • Bongaarts, J. (1994). The impact of population policies: Comment. Population and Development Review, 20, 616–620.

    Article  Google Scholar 

  • 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 

  • Chan, K. C. (1971). Hong Kong: Report of the IUD reassurance project. Studies in Family Planning, 2, 225–233.

    Article  Google Scholar 

  • Deaton, A. (2010). Instruments, randomization, and learning about development. Journal of Economic Literature, 48, 424–455.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

  • 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 

  • Freedman, R. (1997). Do family planning programs affect fertility preferences? A literature review. Studies in Family Planning, 28, 1–13.

    Article  Google Scholar 

  • Freedman, D. (2008). On regression adjustments to experimental data. Advances in Applied Mathematics, 40, 180–193.

    Article  Google Scholar 

  • Freedman, R., & Takeshita, J. Y. (1969). Family planning in Taiwan: An experiment in social change. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Gertler, P., & Molyneaux, J. (1994). How economic development and family planning programs combined to reduce Indonesian fertility. Demography, 31, 33–63.

    Article  Google Scholar 

  • Hashemi, S. M., Schuler, S. R., & Riley, A. P. (1996). Rural credit programs and women’s empowerment in Bangladesh. World Development, 24, 635–653.

    Article  Google Scholar 

  • Hayashi, F. (2000). Econometrics (1st ed.). Princeton, NJ: Princeton University Press.

    Google Scholar 

  • 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 

  • 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 

  • 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.

    Article  Google Scholar 

  • Kleibergen, F., & Paap, R. (2006). Generalized reduced rank tests using the singular value decomposition. Journal of Econometrics, 127, 97–126.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Macro International Inc. (2007). Trends in demographic and reproductive health indicators in Ethiopia. Calverton, MD: Macro International Inc.

    Google Scholar 

  • Mayoux, L. (1999). Questioning virtuous spirals: Microfinance and women’s empowerment in Africa. Journal of International Development, 11, 957–984.

    Article  Google Scholar 

  • Miller, G. (2010). Contraception as development? New evidence from family planning in Colombia. The Economic Journal, 120, 709–736.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Pritchett, L. (1994). Desired fertility and the impact of population policies. Population and Development Review, 20, 1–55.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • Schultz, T. P. (2005). Fertility and income (Center Discussion Paper No. 925). New Haven, CT: Economic Growth Center, Yale University.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Steele, F., Amin, S., & Naved, R. T. (2001). Savings/credit group formation and change in contraception. Demography, 38, 267–282.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • Thomas, D., & Maluccio, J. (2001). Fertility, contraceptive choice, and public policy in Zimbabwe. The World Bank Economic Review, 10, 189–222.

    Google Scholar 

  • Yang, J. M., Bang, S., Kim, M. H., & Lee, M. G. (1965). Fertility and family planning in rural Korea. Population Studies, 18, 237–250.

    Article  Google Scholar 

Download references

Acknowledgements

Jaikishan Desai was employed by Family Health International during the course of this study. We thank the David and Lucile Packard Foundation for financial support and encouragement for the study, the Packard Foundation in Ethiopia for assistance with coordinating all aspects of the study, Birhan Research and Development Consultancy and Miz Hasab Research Center for conducting the two household surveys, and the four subgrantee organizations―ACSI, ADA, OCSSCO, and ODA―who, despite several pressures, extended their cooperation in implementing their interventions according to the study design. Last but not least, we are grateful to Laura Chioda, Jed Friedman, Jonathan Robinson, seminar participants at the World Bank and NEUDC (Boston), the Editor, and especially two anonymous referees for valuable comments and suggestions. The authors remain solely responsible for all remaining errors and omissions as well as for all the views and interpretations expressed throughout the paper.

Author information

Authors and Affiliations

  1. Health Services Research Centre, School of Government, Victoria University of Wellington, PO Box 600, Wellington, New Zealand

    Jaikishan Desai

  2. Department of Economics, Duke University, PO Box 90097, Durham, NC, 27708, USA

    Alessandro Tarozzi

Authors
  1. Jaikishan Desai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alessandro Tarozzi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jaikishan Desai.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Desai, J., Tarozzi, A. Microcredit, Family Planning Programs, and Contraceptive Behavior: Evidence From a Field Experiment in Ethiopia. Demography 48, 749–782 (2011). https://doi.org/10.1007/s13524-011-0029-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13524-011-0029-0

Keywords

Search

Navigation