Enhancing access to index-based weather agricultural insurance: a new marketing approach in Burkina Faso
Last registered on January 13, 2020

Pre-Trial

Trial Information
General Information
Title
Enhancing access to index-based weather agricultural insurance: a new marketing approach in Burkina Faso
RCT ID
AEARCTR-0005180
Initial registration date
January 12, 2020
Last updated
January 13, 2020 10:23 AM EST
Location(s)

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Primary Investigator
Affiliation
OSU
Other Primary Investigator(s)
PI Affiliation
University of Kent
Additional Trial Information
Status
On going
Start date
2019-04-01
End date
2022-12-31
Secondary IDs
3IE Project ID: TW13.1018; RIDIE-STUDY-ID-5c90b74be830d
Abstract
Large segments of the population in developing countries, especially in rural areas, have a high level of vulnerability to weather-related shocks but have limited means to insure themselves against them. In recent years, microfinance institutions have experimented with insurance products, in particular rainfall index insurance, to address this need in different parts of the world. But the uptake of these products has generally been very low because of liquidity constraints, lack of trust in insurance provider and unfamiliarity with formal financial products. We study how existing ties between urban migrants and rural farmers can be used to provide the latter improved access to formal insurance. The study is motivated by well-established evidence regarding the use of rural-urban migration as a risk-coping and risk-management strategy and that rural households in developing countries often rely upon assistance from close relatives among urban migrants to cope with adverse weather-related shocks.
Registration Citation
Citation
KAZIANGA, HAROUNAN and Zaki Wahhaj. 2020. "Enhancing access to index-based weather agricultural insurance: a new marketing approach in Burkina Faso." AEA RCT Registry. January 13. https://doi.org/10.1257/rct.5180-1.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
Large segments of the population in developing countries, especially in rural areas, have a high level of vulnerability to weather-related shocks but have limited means to insure themselves against them. In recent years, microfinance institutions have experimented with insurance products, in particular rainfall index insurance, to address this need in different parts of the world. But the uptake of these products has generally been very low because of liquidity constraints, lack of trust in insurance provider and unfamiliarity with formal financial products. We study how existing ties between urban migrants and rural farmers can be used to provide the latter improved access to formal insurance. The study is motivated by well-established evidence regarding the use of rural-urban migration as a risk-coping and risk-management strategy and that rural households in developing countries often rely upon assistance from close relatives among urban migrants to cope with adverse weather-related shocks.
Intervention Start Date
2019-06-03
Intervention End Date
2022-03-31
Primary Outcomes
Primary Outcomes (end points)
 Take-up of the rainfall index insurance which is measured as 1 if a paired rural household-urban migrant link purchases insurance and 0 otherwise.
 The value of the capital or acreage insured, measured in CFA insured for the capital, and in hectares for the acreage.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
i. Risk coping and management mechanisms
a. Land area allocated to food crops and cash crops; and to crops with different levels of sensitivity to variations in rainfall;
b. Seasonal migration from rural households and participation in non-farm economic activities;
c. Off-farm activities;
d. Education: measured as enrollment of children between 6 and 15 years old;
e. Livestock (herd size and sales);
ii. Investments in agriculture
a. Cultivated area: measured as hectares of land cultivated;
b. Fertilizer use, measured in kilograms of fertilizers per hectare of cultivated land;
c. Labour input, measured in labour per unit time per hectare of cultivated land, at different stages of the farming cycle;
d. Improved seeds, measured as acreage planted with improved varieties;
e. Agricultural productivity, measured as the value of harvest (net of marketed input costs) per hectare.
iii. Consumption smoothing and income growth
a. Consumption smoothing by rural farmers, measured as changes in consumption. Insurance should shelter consumption from income shocks;
b. Income growth: measured as the change in household total income between the baseline and the endline.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The evaluation exploits the random assignment of rural households and their migrant relatives to treatment and control groups. First, we assign villages into a treatment group (where the standard insurance product will be marketed) and into a control group. Urban migrants from both treatment and control villages will be randomly assigned to two groups. The first migrant group will receive offers to purchase the insurance product to cover their rural relatives, but the second migrant group will not (the control). We denote by V0 and V1 the control and the treated villages, and by U0 and U1, the control and treated migrants. Thus, considering pairs of rural farmers and urban migrants, we obtain four experimental groups: V0U0 (the insurance product is not marketed either to rural households or their migrant relatives); V0U1 (the insurance is marketed to the urban migrants, but not to their rural relatives); V1U0 (the insurance is marketed to rural households, but not to their urban relatives); V1U1 (the insurance is marketed both to rural households and their urban relatives). Randomization will occur at the village-level in the rural areas, and at the migrant-level in urban areas.
Experimental Design Details
Not available
Randomization Method
Randomization was done in the office by a computer.
Randomization Unit
The randomization is the village in the rural area, and the individual migrant for the urban migrants sub-sample.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
88 villages
Sample size: planned number of observations
1770 rural households and 970 urban migrants
Sample size (or number of clusters) by treatment arms
For the rural survey: 44 villages in the control group, and 44 villages in the treatment group (with 20 households per village).
For the urban sample, 466 urban migrants in the control group and 534 in the treatment group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We start with 80 villages, and randomly sample 20 households in each village. We will block villages at the commune level with 8 villages per commune. We then proceed to estimate the minimum detectable effect (MDE) for the economic outcomes of interest: consumption, fertilizers, cultivated area, and education, using data from the Burkina Faso 2010 DHS (for education) and from the Ministry of Agriculture of Burkina Faso for the remaining outcomes (the construction of the latter variables are described in Kazianga and Wahhaj (2017). The data are summarized in Table 02 attached. We calculate the MDE under two scenarios. In the first case, we treat any rural household in a treated link as treated. We also account for the proportion of variance explained by blocking. We assume 20% take-up rate. Under these assumptions and with the figures shown, we can detect a minimum change equivalent to roughly 40% of the standard deviation. This MDE corresponds to CFA 198,802 increase in consumption, 17.6 KG increase in fertilizers, 1.7 ha increase in cultivated area, and 19% increase in current enrollment for education. In the second case, we consider comparing V0U1 with V0U0, and V1U1 with V1U0. In this case, we can again ignore the intra-cluster correlation (as when comparing take-up) and block at the village level. Assuming again a take-up rate of 20%, the MDE is, in this case, about 0.30 for the outcomes we consider.
Supporting Documents and Materials
Documents
Document Name
Questionnaire
Document Type
survey_instrument
Document Description
Baseline survey instrument
File
Questionnaire

MD5: 9500296137756ff37bec797a2b5b70bd

SHA1: d2528f0aa9272236edaaa87959612882a37d9046

Uploaded At: January 12, 2020

IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
INNOVATIONS FOR POVERTY ACTION IRB – USA
IRB Approval Date
2018-11-02
IRB Approval Number
11945
Analysis Plan

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