Viewing all posts with tag: Agriculture  

Borrower Identification vs. Product Design: Does "Who" or "What" Matter More?

Given the mixed results of recent randomized evaluations of microfinance, an open question is whether there are broad limits to the benefits of microloans or whether programs can be tailored in specific ways to maximize impact.  Two features of microfinance programs that may matter are targeting and product design.  A recent working paper by Pushkar Maitra, Sandip Mitra, Dilip Mookherjee, Alberto Motta and Sujata Visaria investigates the role of these features by studying a microfinance program they term TRAIL, or Trader Agent Intermediated Lending.

The paper compares the impacts of a traditional group-based lending microfinance model to a more innovative and targeted model in the context of smallholder farming in West Bengal.  The TRAIL model targets loans by incentivizing local traders to identify high potential borrowers for unsecured individual loans. The loans also have some innovative terms . . . 

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Studying Cash Flow Patterns to Design Better Loans in Myanmar

“If you build it, he will come.” Unfortunately, this line that worked so well in Field of Dreams is less effective in the world of social enterprise.  Simply producing and having the networks to distribute a product does not guarantee its success—to be successful, a product must address a customer need.

What better way to understand customers’ needs, wants, and limitations than to involve them in the design process? This customer-centric philosophy is also known as human-centered design (HCD).  I work with Proximity Designs, a social enterprise that sells locally manufactured solar lanterns and low-cost irrigation products to smallholder farmers in rural Myanmar.  Before we launched these products at scale, our team presented prototypes to farmers in the field. Farmers could see, hold, and operate the products and give us immediate feedback on size, color, weight, price, and wattage.

But when Proximity launched its microfinance services in 2010, we had to come up with a different approach . . . 

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What to Read On Agriculture Microfinance

The majority of the world’s poor share one profession: farming. Most of these farmers cultivate less than 10 acres of land, far away from paved roads and with limited access to the improved seed and fertilizer they need to produce good harvests. Most of these farmers also lack access to financial services that could help them buy that seed and fertilizer. If the global microfinance industry seeks to have a long-term impact on global poverty, it must address the needs of smallholder farmers. Most microfinance institutions are focused in urban and peri-urban areas, but a few are starting to offer products specifically targeted at farmers.

We’ve seen fast-growing interest in the farm microfinance sector in the last few years. The books, videos, and papers discussed below helped us understand the market opportunity in farm microfinance, and what needs to happen for the market to take off . . . 

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Reliability of Self-Reported Data: Deliberate Misreporting

Program evaluations and policy proposals are only as good as the data upon which they are based. Although we all know this to be true, discussions about the reliability of data, especially self-reported data, have only recently emerged in the field of development economics. The other week, I highlighted two papers from the Journal of Development Economics’ Symposium on Measurement and Survey Design which discussed how recall bias might undermine the reliability of self-reported data. Even when recall bias is not at play though, self-reported data might be threatened by respondents’ desire to misreport their activities so as to portray their behaviors in a more positive light.

Sarah Baird and Berk Özler explore this phenomenon as it relates to education in their study, “Examining the Reliability of Self-Reported Data on School Participation.” Many Conditional Cash Transfer (CCT) programs are evaluated based on self-reported data about school enrollment and attendance rates. However, the desire to give socially desirable answers or the belief that program funding is linked to evaluation results might lead survey participants to over-report their level of school participation. Baird and Özler test the extent to which self-reported data of school enrollment rates can be considered reliable in CCT evaluations of this nature . . . 

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Financing Seasonal Migration: A New Use for Microcredit?

In many places, agriculture is highly seasonal. That presents difficulties for subsistence farmers who have to stretch incomes year-round. If farmers (or family members) could migrate during the off-season to areas where wage labor is available, they could substantially smooth their annual income and consumption. Indeed, this is what happens in many places. But even where seasonal migration does happen, many people don't migrate even when it seems it would be advantageous to do so. Why?  

In recent work, Bryan, Chowdhury and Mobarak study the role of risk aversion in preventing households from migrating. You can see a presentation of this work here.

While migrating from poorer areas to wealthier ones, particularly from rural to urban locations, can provide access to more and (much, much) better-paying wage labor, it comes at a significant cost . . . 

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Reliability of Self-Reported Data – Recall Bias

In a recent post, Tim Ogden and I discussed the importance of having solid, reliable data on which to base program evaluations and policy decisions. The Journal of Development Economics explored this theme in last year’s Symposium on Measurement and Survey Design which featured more than a dozen papers on improving data quality in development research (Hat tip to Berk Ozler of the World Bank’s Development Impact blog for pointing us to it).

An important discussion at the symposium was the extent to which self-reported data can be considered accurate and reliable. Because study participants are usually asked to report information after significant time has elapsed, self-reported data are often subject to recall bias and can be inaccurate or misleading. This post is the first in a three-part series that will explore the reliability of self-reported data through a discussion of papers featured at the symposium . . . 

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Fingerprinting Microcredit Borrowers Gets the Spotlight

A very interesting microfinance experiment is in the new issue of the American Economic Review, one of the premier journals in the field (Published, but gated, version here. Ungated version here). The paper is by FAI Affiliate Xavi Giné, Jessica Goldberg (see her recommended reading on savings here), and Dean Yang. It's not often that microfinance makes the pages of AER; it's a testament to the work that Xavi, Jessica and Dean did to set up this experiment and their careful analysis of the data. 

In brief, the experiment tested the effects of fingerprinting borrowers from a microcredit program in rural Malawi. I had the opportunity to interview Xavi and Dean (separately) for my upcoming book on economic field experiments and we talked about this work. I’ll let them explain the project and its implications in their own words . . . 

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What I Learned at the 6th Microinsurance Conference

This is a guest post from Aparna Dalal, independent consultant and former FAI Director of Special Projects.

If you are studying or working in the field of microinsurance, the annual International Microinsurance Conference, jointly hosted by the Munich Re Foundation and theMicroinsurance Network, is the place to be. The 6th installment of the conference was held in Manila last week. This was the third conference I’ve attended, and in many ways, the most interesting one. While challenges remain, various organizations are successfully implementing innovative products and processes. Below are four areas of development that I found particularly interesting . . . .

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