Productivity Shocks and Repayment Behavior in Rural Credit Markets: A Framed Field Experiment

Abstract

Improving rural credit markets requires a good understanding of the root causes of market failures and taking necessary steps to address them. This paper investigates the role of productivity shocks in borrowers repayment choices. Using a framed field experiment that simulated a repeated interaction in an input credit market, the analysis finds strong evidence that adverse productivity shocks lead to higher default, even when they do not induce negative returns. This relationship is robust to the presence of an information exchange system enforcing dynamic incentives. The findings suggest that recurrent shocks such as those resulting from the harmful effects of climate change could exacerbate failures in rural credit markets, undermining hard-won progress toward rural financial inclusion.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. While it is not fully realistic to assume non-negative returns from the use of inputs, allowing for negative returns in case of bad outcome, for example would only reinforce our results. If many of the farmers who take loans are likely to default in case of bad outcome even if this does not lead to negative returns, they are probably even more likely to default when they face negative returns.

2. A point worth noting here is that the increased opportunity cost of repaying does not have to come from productivity shocks. It could well be expenditures shocks, or price shocks, or other sources. Our emphasis on productivity shocks is due primarily to our belief that farmers are increasingly exposed to such type of shocks, as a result of climate change. But this does not take away from the possibility that other sources of shocks could also lead to similar behaviour.

3. Additionally, we ignore the possibility of consumption smoothing through savings, credit, or insurance because financial markets are known to fail critically for farmers in a context such as the one in which this study was implemented.

4. This assumption is for pure simplification and does not particularly influence the outcome of the experiment. Conning and Udry (2007) made a similar assumption when modelling moral hazard in rural financial markets.

5. 100 NGN=0.6200 USD at the time of the experiment (https://www.poundsterlinglive.com/best-exchange-rates/us-dollar-to-nigerian-naira-exchange-rate-on-2014-07-14).

6. This base salary was designed simply to incentivise agro brokers in the game to make offers.

7. Please note that we calibrated the game such that the reason for default is unambiguously strategic default. The reason for this is that it allows us to capture the very behaviour we sought to test: default resulting from shocks, even when the investment did not yield negative returns. The main underlying issue is the concavity of the utility function, making repayment more costly after a negative shock than after a positive shock.

8. We thank both anonymous reviewers for pointing this out.

9. Ideally, we would use some covariates to verify that the randomisation process yielded well balanced covariates across treatment groups, if we had access to such covariates. But no other variable was collected during the experiment precluding such test. We are nevertheless confident that the randomisation process was carried out carefully enough to yield such balancedness.

10. Ideally, we would have clustered the standard errors at the village level because the communication treatment is assigned at the village level. But given the small number of village clusters, the asymptotic properties justifying the clustering are no longer valid.

11. The results from the non-linear model is provided in Appendix A.