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How to make services work for the poor?

Maria Jones's picture

This question is particularly relevant in the context of traditional public agricultural extension services. Expensive and burdened by high rates of under-staffing and low levels of accountability, privatization of extension services may be a way to improve cost-effectiveness. However, private services may lack incentives to tailor their services to the poorest, making them an unsatisfactory substitute for a public system of extension. This issue is particularly salient in sub-Saharan Africa, where markets for agricultural services are typically lean.

Rwanda is a good case study, as ‘progressive disengagement from extension service in favor of private extension delivery’ is part of the government's agricultural strategy.  The Land Husbandry, Water Harvesting, and Hillside Irrigation (LWH) project served as a pilot for privatization: in the LWH project areas, farmers purchase agricultural services (inputs and extension) from One Acre Fund (OAF).

Partnership. We worked with OAF and the Rwandan government to design, introduce, and test innovative farmer feedback tools. Together, we set up a large field experiment, in which we randomly assigned two types of feedback tools to groups of OAF clients. We added a twist to learn more about the underlying mechanisms: to separate out pure monitoring effects from user empowerment effects, we announced to some extension workers that their work is being monitored, in both treatment groups (“true” announcement) and control groups (“false” announcement). We also tested the cost effectiveness of different feedback modalities.

So, what did we learn?

Offering feedback channels is a meaningful way to combat dropouts and increase attendance in extension trainings. First, feedback tools help sustain demand for the service among current clients. Farmer groups offered the opportunity to provide feedback were half as likely to have members leave the service the following year as control groups.

Feedback tools retain farmers but also address constraints to adoption among non-users. Second, and more surprisingly, this demand effect spills over to non-users in the vicinity of the treated groups, who are more likely to sign up in the following season. Farmers groups who have access to feedback tools are 28 percentage points more likely to attract new members, relative to control farmers groups that have a 8 percent chance to attract new members. This implies an increase in group size of up to 3 additional members in the subsequent season (0.69 SD). These effects are robust to multiple hypotheses testing.

This is not a simple monitoring story. Randomly announcing the presence of scorecards to extension workers allows us to rule out a pure monitoring story. Extension workers do not overwhelmingly respond to our intervention by exerting more effort in villages where additional monitoring was announced. We therefore conclude that the large impacts feedback tools have on farmers’ demand for agricultural services are primarily attributable to farmers’ empowerment, or taste for respect.

Offering feedback is particularly effective in getting women to start interacting with a field officer. Given female farmers have access to smaller plots, this is in line with the idea that, in the absence of a strong feedback loop mechanism, private extension services exclude the more modest producers.

What changed after the regressions were run? The most cost-effective feedback mechanism piloted (a hotline) was adopted and scaled up by OAF throughout Rwanda the following season. In addition, the satisfaction data drawn from the feedback tools themselves helped convince MINAGRI to continue its partnership with OAF and scale it up to new LWH sites.  

We see this case study as a good example of a happy marriage between research and operations: an impact evaluation motivated by a direct policy question, but going beyond simple program evaluation (see a great discussion on the importance of moving beyond program evaluation here). As policy makers, we had an opportunity to improve the effectiveness of a policy that touches large numbers of farmers. In addition, useful data were collected in the process, highlighting gender difference in access to services as well as information on quality of service delivery. As researchers, we had an opportunity to learn more about how feedback mechanisms affect demand for services and contribute evidence that advances understanding of behavior change more broadly.