Theme 1: Field Experiments in Rural Finance: An Example from Tamil Nadu, India

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Suppose you’re in charge of the rural finance portfolio at a private bank in a developing country. You’re reviewing the performance of your rural branches, and would like to consider some policy changes. Some staff members propose new products, while others suggest changing interest rates and the borrowing limit. Remembering your old economics courses, you realize that while raising the interest rate increases margins, higher interest rates can also decrease take-up and lead to more default. The effect on profits is ambiguous. You are also aware that increasing the loan to value (LTV) ratio on collateralized products could increase your portfolio size but might also have adverse effects on default. Again, it is not clear whether an increase in the LTV ratio will have a positive impact on profits. So what should you do?

Given the challenges involved in these decisions, it is perhaps not surprising that most managers choose to rely on instinct and gut feelings. Gut decisions are not made from complete ignorance. Rather they are informed by thousands of historical data points and anecdotes from the individual’s past. But this begs the question of whether people are good mental statisticians. This paper suggests that there is an infrequently used option in the analytical toolbox: randomized controlled trials (RCT), which offer greater precision. The author's argue that by spending some resources, and avoiding the traditional guess and implement strategy, an organization can dramatically improve the quality of choices it makes. However they also acknowledge that not all questions can be answered through RCTs and propose a simple three-tiered framework to help assess whether a particular problem is suitable.

The authors go on to outline the six steps of a successful RCT and then, to give a better sense of what an experiment looks like in the field, they provide details of the design and results of an experiment conducted in several rural branches of one of India’s largest private banks. The experiment was initially setup to help the bank answer the following question: "Is the bank being too cautious in setting the loan-to-value (LTV) ratio for one of its collateralized loan products - jewelry loans?" In addition to this question, they researchers were also interested in testing for the existence and prevalence of credit constraints. Much anecdotal suggests extremely high levels of credit constraints in rural areas, yet there has been relatively little academic work in the area.

While the experiment is still running and the results not yet conclusive, the authors can already point to several interesting findings. For example, the low rates of credit constraints and minimal refinancing is surprising. It seems the literature has been placing too much emphasis on credit constraints. The researchers suggest that mental accounting, a behavioral economics theory, explains such unexpected borrowing patterns. In conclusion they suggest that RCTs can be applied to many areas of rural finance and agriculture. They could be used for anything from understanding the impact of subsidized fertilizer on local market outcomes to the impact of relaxing the traditionally rigid microfinance contracts. They provide the most scientifically founded answers to many of the most difficult policy questions and should be taken very seriously in policy discussions. In the experiment described in the paper, they will not only able to inform the bank whether they can safely increase credit limits without much concern for increased default, but can also say something about the prevalence of credit constraints and the importance of mental accounting in understanding borrowing patterns.

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