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Microfinance programs and domestic violence in northern Cameroon; the case of the Familial Rural Income Improvement Program

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Abstract

The aim of this paper is to examine the relationship between female participation to the familial rural income improvement program (PARFAR) and domestic violence in the rural northern Cameroon. To achieve this, two hypothesis based respectively on the theory of marital bargaining and the theory of men’s backslash are tested applying propensity score matching to survey data from a sample of households in the area, to consider the possibility of sampling bias. A battery of test and estimation methods is used to check the robustness of findings. The results support the backslash theory. PARFAR participation leads to an improvement in the contribution of women in decision-making within the targeted households. This effect is associated with a reduction in violence acceptability but an increase in violence prevalence. This double result which embedded household dynamics in an adversarial logic then raises the question of prior cultural adjustment program for targeted households. Among actions to undertake for such attitudinal change about gender considerations in Cameroon, besides those mobilizing local government, non-governmental organizations and community based organizations, an additional challenge for policymakers could be improving policies facilitating access to legal institutions for victims of domestic violence.

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Notes

  1. For Bates et al. (2004), Schuler et al. (1996), women’s participation in microfinance programs has a beneficial effect on domestic violence while Ahmed (2011), Koenig et al. (2003) reject such a conclusion. Ferrari and Iyengar (2010) report no impact on domestic violence.

  2. At the exclusion of an attempt by Eze and al (2015) using a game theory approach.

  3. Goetz and Sen Gupta (1996).

  4. For Schuler et al. (1996) and Hashemi et al. (1996), this positive effect of reducing domestic violence is even more pronounced when the woman is a member of a credit group. Indeed, in such a context, it is not only the fear of public exposure that will push the man to restraint, but also that women are less likely to bring credit to household.

  5. in addition to the prime ministerial decree moving the granting of licenses, the supervision and the control of microfinance institutions under the ministry of finance,

  6. The peculiar colonial history of Cameroon introduced a plurality of laws. Primarily English common law and French civil law with vestiges of Germanic law. Customary laws that were in place prior to the reception of foreign laws are still in place.

  7. In case the woman were to remarry, the husband to whom she owes a refund of the dowry has possessory rights on the woman’s corpse over the current husband.

  8. This is common is most African countries. As noted for instance by Bishai and Grossbard (2010) in Uganda, by paying non refundable bride price, men acquire rights to a woman’s fidelity.

  9. In French ECAM stands for “Enquete Camerounaise sur les Ménages” which is a national household survey.

  10. These matrimonial rules determine the securities that a married woman can present for loan and its ability to save reinvest or distribute the wealth generated by the induced investment in the family.

  11. Or separate spheres in the marriage. For more on this concept, see Lundberg and Pollak (1993).

  12. The matching methods are used to identify the causal effect of the measure under the assumption that the observable differences between treated and untreated households capture all the determinants of selection of beneficiaries. This is the assumption of conditional independence. The assumption of common support ensures that for each household member, there are households in the control group with the same variables observed.

  13. Propensity scores are generally com puted from a logit or a probit mode to predict the probability of program participation

  14. This method involves estimating the density distribution of the two groups and retains the values of P that have a positive density for treated and untreated households.

  15. The nul hypothesis of the balancing test is that the mean difference of treated and control units is equal to zero.

  16. Selection on unobservable (Hidden bias) are driven by unobservable variables that influence treatment decisions as well as potential outcomes (Becker and Caliendo 2007)

  17. Gamma reflects the assumption about unmeasured heterogeneity in treatment assignment expressed in terms of the odds ratio of differential treatment assignment due to unobserved covariate.

  18. Following Steele et al. (2001), we use the concept of membership in the broadest sense of simply participating to the PARFAR program regardless of the amount of the loan taken. This is in contrast to the approach in some studies examining program participation that have defined membership based on amount of loan taken (e.g., Pitt et al. 1999). As Steele et al. (2001) noted, a drawback of such a measure can be that it is likely to account only for economic pathways, which could confound the analysis in this study that addresses a non-economic outcome.

  19. As such women are also generally younger co-wives in polygamous marriages; this may also mean that young co-wives are less likely to participate. We do not have data on the seniority of women in polygamous marriage to further investigate this issue.

  20. The same approach is used to measure empowerment. We consider principal components of the answer of the question of whether or not the woman should first ask permission for her small purchases, to visit parents, to visit friends etc.

  21. The reader should report to Appendix (Table 10) for the result of the balancing check and common support discussion.

  22. We use the R bounds Stata Command on the generated difference between the outcome and the estimated outcome.

  23. For an analysis of the impact of such policies see Beleche (2017).

References

  • Aizer, A. (2010). The gender gap and domestic violence. American Economic Review, 100(4), 1847–1859.

    Article  Google Scholar 

  • Ahmed, S. M. (2011). Intimate partner violence against women: Experiences from a woman development program in Matlab Bangladesh. Journal of Health, Population and Nutrition, 23(1), 95–101.

    Google Scholar 

  • Bang, H., & Robins, J. M. (2005). Doubly robust estimation in missing data and causal inference models. Biometrics, 61, 962–973.

    Article  Google Scholar 

  • Bates, L. M., Schuler, S. R., Islam I., & Islam, M. K. (2004). Socioeconomic factors and processes associated with domestic violence in rural Bangladesh. International Family Planning Perspectives 190–199.

  • Becker, G. (1981). A treatise on the family. Cambridge MA: Harvard Press.

    Google Scholar 

  • Beleche, T. (2017). Domestic violence laws and suicide in Mexico. Review of Economics of the Household, 1–20. https://doi.org/10.1007/S11150-017-9362-4.

  • Becker, S., & Caliendo, M. (2007). Sensitivity analysis for average treatments effects. Stata Journal, 7(1), 71–83.

  • Bishai, D., & Grossbard, S. (2010). Far above rubies: The association between bride price and extramarital sexual relations in Uganda. Journal of Population Economics, 23(4), 1177–1188.

    Article  Google Scholar 

  • Cochran, W. G., & Rubin, D. B. (1973). Controlling bias in observational studies: A review. Sankya: The Indian Journal of Statistics, 35(4), 417–446.

    Google Scholar 

  • Dehejia, R., & Wahba, S. (2002). Propensity score-matching methods for nonexperimental causal studies. The Review of Economics and Statistics, 84(1), 151–161.

    Article  Google Scholar 

  • Eze Eze, D., & Zedou, A. (2015). ‘Microfinance inegalités de genre et conflits intrafamiliaux dans la zone rurale de savane au Cameroun » Communication aux journées de d’économie sociale Bobigny.

  • Eswaran, M., & Malhotra, N. (2011). Domestic violence and women’s autonomy in developing countries, theory and evidence. Canadian Journal of Economics, 44(4), 1222–1263.

    Article  Google Scholar 

  • Farmer, A., & Tiefenthaler (1997). An economic analysis of domestic violence. Review of Social Economy, 55(3), 337–358.

    Article  Google Scholar 

  • Ferrari G., & Iyengar, R. (2010). Discussion sessions coupled with finance may enhance the role of women in household decision making in Burundi. CEP discussion paper.

  • Goetz, A. M., & Gupta, R. S. (1996). Who takes the credit? gender, power, and control over loan use in rural credit programs in Bangladesh. World Development, 24(1), 45–63.

    Article  Google Scholar 

  • Guyer, J., & Peters, P. (1987). Conceptualising the household; Issues of theory and policy in Africa. Introduction. Development and Change, 9, 29–41.

    Google Scholar 

  • Hashemi, S., Schuler, S. R., & Riley, A. (1996). Rural credit programs and women’s empowerment in Bangladesh. World Development, 24(1), 45–64.

    Article  Google Scholar 

  • Jalan, J., & Ravallion, M. (2003). Estimating the benefit incidence of an antipoverty program by propensity score matching. Journal of Business and Economic Statistics, 21(1), 19–30.

    Article  Google Scholar 

  • Jewkes, R. (2002). Intimate partner violence: Causes and prevention. Lancet, 359, 1423–1429.

    Article  Google Scholar 

  • Johnson, S. (2004). Gender norms in financial markets: Evidence from kenya. World Development, 32(8), 1355–1374.

    Article  Google Scholar 

  • Kabeer, N. (2001). Conflicts over credit: Re-evaluating the empowerment potential of loans to women in rural Bangladesh. World Development, 29, 63–84.

    Article  Google Scholar 

  • Khandker, S. R. (2005). Microfinance and poverty: Evidence using panel data from bangladesh. World Bank Economic Review, 19(2), 263–286.

    Article  Google Scholar 

  • Kim, G. G., Ferrari, T., Abramsky, C., Watts, J., Hargreaves, H., Mouson, G., Phetla, J., Porter, & Pronyk, P. (2009). Assessing the incremental effects combining economic and health interventions: Image study in South Africa. Bulletin of World Health Organization, 875(11), 824–832.

    Article  Google Scholar 

  • Kishor, S. (2005). Domestic violence measurement in the demographic and health surveys: The history and the challenges. Geneva: Expert Paper prepared for The UN Division for the Advancement of Women.

    Google Scholar 

  • Koenig, M. A., Ahmed, S., Hossain, M. B., & Mozumder, A. (2003). Women’s status and domestic violence in rural Bangladesh: Individual- and community- level effects. Demography, 40(2), 269–288.

    Article  Google Scholar 

  • Luke, N., & Munki, K. (2011). Women as agents of change: Female income, social affiliation and household decision in south India. Journal of Development Economics, 94(1), 1–17.

    Article  Google Scholar 

  • Lunceford, J. K., & Davidian (2004). Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study. Statistics in Medicine, 23(19), 2937–2960.

    Article  Google Scholar 

  • Lundberg, S. J., & Pollak, R. (1993). Separate spheres, bargaining and the marriage market. Journal of Political Economy, 101, 988–1011.

    Article  Google Scholar 

  • Mayoux, L. (1999). Questioning virtuous spirals: Microfinance and women’s empowerment in Africa. Journal of International Development, 11(7), 957–984.

  • McElroy, M. B., & Horney, M. J. (1981). Nash bargaining household decisions; towards a generalization of theory of demand. International Economic Review, 22, 333–49.

    Article  Google Scholar 

  • McElroy, M. B. (1990). The empirical content of nash bargained household behavior. Journal of Human resources, 25(4), 559–583.

  • Nannicini, T. (2006). A simulation based sensitivity analysis for matching estimators». The Stata Journal.

  • Osmani (2007). A breakthrough in women’s bargaining power: the impact of micro credit. Journal of International Development, 19, 695–716.

    Article  Google Scholar 

  • Pitt, M. M., Khandker, S. R., McKernan, S., & Latif, M. A. (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 

  • Rahman, A. (1999). Micro-credit initiatives for equitable and sustainable development: who pays? World Development, 27, 67–82. 35.

    Article  Google Scholar 

  • Rosenbaum, P. R., & Rubin, D. B. (1983). The central of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.

    Article  Google Scholar 

  • Ruffing, (2009). Cool head, warm heart: Governance and the mission of microfinance in the case of MC2 micro banks Cameroon ISP collection paper 730.

  • Schuler, S. R., Hashemi, S. M., Riley, A. P., & Akhter, S. (1996). Credit programs, patriarchy and men’s violence against women in rural Bangladesh. Social Science and Medicine, 43, 1729–42.

    Article  Google Scholar 

  • Schuler, S. R., Hashemi, S. M., & Badal, S. H. (1998). Men’s violence against women in rural bangladesh: Undermined or exacerbated by microcredit programs? Development in Practice, 8, 148–156.

    Article  Google Scholar 

  • Sen, A. (1990). Gender and cooperative conflicts in I. Tinker (ed.), Persistent inequalities: Women and world development. New York, Oxford University Press, pp. 123–149.

  • Smith, J., & et Todd, P. (2005). Does matching overcome Lalonde’s critique on non experimental estimators? Journal of Econometrics, 125, 305–353.

    Article  Google Scholar 

  • Steele, F., Amin, S., & Naved, R. T. (2001). Savings/credit group formation and change in contraception. Demography, 38(2), 267–282.

    Article  Google Scholar 

  • Straus, M. A., & Douglass, E. M. (2004). A short form of the revised conflict tactics scales and typologies for severity and mutuality. Violence and Victims, 19, 507–520.

    Article  Google Scholar 

  • Tan, Z. (2010). Bounded, efficient and doubly robust estimation with inverse weighting. Biometrika, 97, 661–682.

    Article  Google Scholar 

  • Tauchen H. V., Witte, A. D., Long S. K. (1991). Violence in the family; a non-random affair. International Economic Review, 32(2), 491–511.

  • Time, V. (2014). Women, law, and human rights in cameroon: Progress or status quo? Journal of Law and Conflict Resolution, 6(1), 1–6.

    Article  Google Scholar 

  • Winship, C., & Morgan, S. (1999). The estimation of causal effects from observational data. Annual Review of Sociology, 25, 659–706.

    Article  Google Scholar 

  • Wooldrigde (2010). Econometric analysis of cross section and panel data. 2nd edition Cambridge MA: MIT Press.

    Google Scholar 

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Correspondence to Donatien Eze Eze.

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Appendix

Appendix

Prior to matching, there were substantial differences in the characteristics of treated and control individuals. After matching any such difference were eliminated.

A visual presentation of the density distribution of estimated propensity score for the two groups is shown in Fig. 1. The histogram illustrate the number of women in the sample who are on microcredit support and those who are off. It can be seen that the common support condition is satisfied. There is a substantial overlap in the distribution of propensity scores of both groups (Table 10).

Table 10 Propensity score and covariate balancing (Radius)
Fig. 1
figure 1

Density distribution of propensity scores using radius

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Eze Eze, D. Microfinance programs and domestic violence in northern Cameroon; the case of the Familial Rural Income Improvement Program. Rev Econ Household 17, 947–967 (2019). https://doi.org/10.1007/s11150-017-9393-x

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