Abstract

PurposeThe purpose of this paper is to analyze the impact of microcredit on per capita income of farm households in Cameroon. It discusses short- and long-term implications of access to microcredit on income poverty.Design/methodology/approachThe authors interviewed rural households with agriculture being either their first or second income-creating activity. All sampled households are clients of a Cameroonian village bank. The authors used a balanced panel with a treatment and a control group, the latter not having had a village bank microcredit yet. The results were reaffirmed using bootstrapping.FindingsThis paper argues that microcredit has had a significant positive impact on per capita income in the short run, but the long-term effect was negative, albeit not significant. In the long run, absolute income poverty had further decreased in the treatment group, however, not as much as in the control group. Because the treatment group had been shifting back to the informal financial sector and had diverted part of the microcredit for consumption, this may have led to lower marginal income effects. Productivity of credit financed inputs by the treatment group remained constant, which also explains why the treatment group fell back over time.Research limitations/implicationsThe balanced panel data set was relatively small due to attrition over time. This was accounted for using bootstrapping. Nevertheless, research results must be interpreted with care. Furthermore, the discussion is not exhaustive.Practical implicationsDespite tremendous methodological advancements regarding the impact analysis of microcredit on income poverty, findings remain controversial and inconsistent. Frequently, fungibility is a confounding issue. Microcredit policy ought to consider more long-term effects.Originality/valueThere is much discourse amongst development economists about the impact of microcredit on poverty. Research based on panel data may clarify some of the controversial issues. This research paper uses a rather unique panel data set from Cameroonian farm households that are clients of a private sector village bank. The issue of sample size limitation is dealt with using bootstrapping. The authors base the empirical analysis on a comprehensive and theoretically founded economic farm household model.

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