Uptake and impact of interlinked index-based insurance with credit and agricultural inputs: Experimental evidence from Ethiopia 2016-2018

DOI

Randomized experiment in Ethiopia that assesses the relevance of bundling index-based insurance with credit and access to inputs. We compare four index-based insurance options in terms of their impact on adoption of modern technologies, consumption and productivity: (1) a standard index-based insurance product; (2) a newly developed index-based insurance product that is promoted via farmer groups and has a delayed premium option; (3) the newly developed index-based insurance product bundled with a credit option and (4) the newly developed index-based insurance product bundled with credit and an input purchasing option. We find that allowing farmers to postpone premium payment improves uptake and consumption expenditures significantly. However, in order to increase investment in modern agricultural technologies and productivity, which is highly important for long run growth in the agricultural sector, bundling insurance with credit and access to inputs is needed. Our analysis shows that only when farmers adopt a package comprised of insurance, credit and inputs, do they significantly increase their investment in modern agricultural technologies and, consequently, farm productivity improves.Farm households in Africa must cope with bad conditions as to soil quality, weather and infrastructure. The variability of rainfall causes yields to vary strongly from one year to the next. With yields already low (due to poor soil condition) these variations can be life threatening. Meanwhile, inadequate infrastructure makes it difficult to help the households with access to financial services, insurance and inputs that could stabilize their access to resources, and enhance yields. Solving a single aspect, say bringing inputs to the farm, will not be sufficient as credit is also needed. But credit can only be provided if sufficient likelihood exists that loans will be repaid. Here, insurance can help. If insurance of the loan makes it attractive enough for the lender, a package can be composed of inputs, with credit and insurance, that solves all these problems with one bundle. Yet, the households will remain exposed to some risks as insuring against all is prohibitively expensive. What is the appropriate degree of insurance in such bundles? That is the core question addressed in this research. It aims at supplying inputs to farmers on credit, with insurance, in such a way that a good balance is found between the benefits and risks to the farmers and the profits and risks to the credit provider. We investigate the possibilities for such a balanced approach in Kenya and Ethiopia in collaboration with a large insurance provider and a farmers organisation. Together with them we collect information on the costs, benefits and risks involved in using the inputs, the alternatives open to them, and the costs and benefits involved in providing credit to finance the purchase of inputs, with and without an insurance against crop failure. With all this information, we go and talk to the stakeholders concerned to find out how they would respond if more or less insurance would be provided. Will credit suppliers lower their prices, if repayment of loan is more likely because the crop is insured? Will households decide to take higher yielding (but more risky) crops if part of the downside risk is insured? We establish this for the parties concerned in Kenya and Ethiopia, but also in other African countries. Having established how these stakeholders respond to changes in insurance, we can proceed to derive what the best degree of insurance might be. And this is then finally tested in a field experiment. With this knowledge we can help other suppliers of insurance and credit, and farm organisations to establish similar packages that are adapted to the local conditions for input supply, and financial services.

We conducted our experiment with a local insurance company, Oromia Insurance Company (OIC), in the Rift Valley zone of Ethiopia. In the Rift Valley zone we randomly selected two kebeles , Desta Abjata and Qamo Garbi. Then, from the two kebeles, we randomly selected 47 farmer groups, called Garees in Ethiopia. The baseline study was undertaken in May 2017; during the following two months, we implemented the training (June) and the experiment (July); while the end-line study was conducted in August 2018. To avoid ethical issues and to mitigate spillover effects, we used a cluster randomization to randomly assign the 47 garees into four groups: T1, T2, T3 and T4 (to be explained below). All household heads from the 47 garees (in total 1661) are part of our experiment; all of them are farmers. Nobody is member of more than one garee. The randomization resulted in three groups with 12 garees (T2, T3 and T4) and one group with 11 Garees (T1). The number of farmers per Garee fluctuates between 15 and 63. The distribution of farmers over Garees differ a little bit per treatment group. However, the median of farmer numbers per Garee for the various treatment groups is similar: it varies between 34 for T3 and 36 for T2.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-853429
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=063b6b8dc7839269d020d2f18b0879840bbd4b037a38fa88dca7050e4c91bb30
Provenance
Creator Belissa, T, Haramaya University; Lensink, R, Wageningen University; Marr, A, University of Greenwich
Publisher UK Data Service
Publication Year 2019
Funding Reference Economic and Social Research Council; Department for International Development
Rights Ana Marr, University of Greenwich; The Data Collection is available for download to users registered with the UK Data Service.
OpenAccess true
Representation
Language English
Resource Type Numeric
Discipline Economics; Social and Behavioural Sciences
Spatial Coverage Rift Valley zone of Ethiopia; Ethiopia