Discussion of Miranda Ghana Project: Coupling Insurance and Credit

The project focuses on the demand for credit with and without the requirement to purchase insurance. Research suggests that the requirement to purchase insurance may affect demand for credit, with some studies indicating a decrease in demand when insurance is not required. The project's unique feature is its use of a strong pre-existing index insurance product, known as the Ghana Agricultural Insurance Product (G-AIP). This product provides weather-based insurance to farmers, protecting them against crop losses due to adverse weather conditions. The project also takes into account the lenders' exposure to weather-related risks, which may be mitigated by the linking of insurance and credit. The project's design involves several key interventions. Firstly, the project aims to link insurance and credit, providing a risk management tool for lenders. This may help to increase credit supply and reduce the risk of default. Secondly, the project plans to use the insurance product as a management tool for lenders, rather than pushing it all the way to the borrower. This approach may help to reduce the complexity of the loan product and make it more appealing to borrowers. The project's product design raises several questions. For instance, whether lenders want to insure 100% of their loan portfolio, and what borrowers should know about the nature of their loan contingencies. Additionally, the project faces challenges in covering part but not all of the loan, and in estimating the combined cost of commercial index insurance and commercial index insurance. The project's evaluation plan is also a subject of discussion. While the project aims to work without subsidies, it is unclear how many clusters will be needed to make this design work entirely cross-cluster. The project's proposal is also vague about identifying a sample of farmers interested in loans, which is a critical aspect of the study. Furthermore, the project faces challenges in estimating the longer-run average treatment effect (ATE) due to the rarity of default events in any given year.