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Uptake and impact of interlinked index-based insurance with credit and agricultural inputs: Experimental evidence from Ethiopia 2016-2018
Creator
Belissa, T, Haramaya University
Lensink, R, Wageningen University
Marr, A, University of Greenwich
Study number / PID
853429 (UKDA)
10.5255/UKDA-SN-853429 (DOI)
Data access
Restricted
Series
Not available
Abstract
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...
Terminology used is generally based on DDI controlled vocabularies: Time Method, Analysis Unit, Sampling Procedure and Mode of Collection, available at CESSDA Vocabulary Service.
Methodology
Data collection period
01/10/2016 - 30/09/2018
Country
Ethiopia
Time dimension
Not available
Analysis unit
Individual
Universe
Not available
Sampling procedure
Not available
Kind of data
Numeric
Data collection mode
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.
Funding information
Grant number
ES/L012235/1
Access
Publisher
UK Data Service
Publication year
2019
Terms of data access
The Data Collection is available for download to users registered with the UK Data Service.