Go for It: Effects of Insurance on Investment

Last registered on June 14, 2021
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Pre-Trial

Trial Information

General Information

Title
Go for It: Effects of Insurance on Investment
RCT ID
AEARCTR-0007639
Initial registration date
June 13, 2021

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
June 14, 2021, 11:36 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country
Uganda
Region
Eastern

Primary Investigator

Name
Borja Pérez-Viana
Affiliation
University of St. Gallen
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Other Primary Investigator(s)

PI Name
Thomas Epper
PI Affiliation
University of St. Gallen
Contact Investigator
PI Name
Ferdinand Vieider
PI Affiliation
Ghent University
Contact Investigator
PI Name
Arjan Verschoor
PI Affiliation
University of East Anglia
Contact Investigator
PI Name
Ben D'Exelle
PI Affiliation
University of East Anglia
Contact Investigator

Additional Trial Information

Status
On going
Start date
2021-01-27
End date
2022-12-31
Keywords
Agriculture, Behavior, Finance & Microfinance, Firms & Productivity
Additional Keywords
agricultural investment; insurance; index insurance
JEL code(s)
D01, D81, O12, O55
Secondary IDs
Abstract
We investigate how the provision of insurance influences investment decisions in a panel setting. Our study will be implemented in a homogenous area in rural Uganda over the course of two years.
External Link(s)

Registration Citation

Citation
Vieider, Ferdinand et al. 2021. "Go for It: Effects of Insurance on Investment." AEA RCT Registry. June 14. https://doi.org/10.1257/rct.7639-1.0
Sponsors & Partners

Sponsors

Partner

Name
The Field Lab
Type
none
URL
https://thefieldlabuganda.com/
Experimental Details

Interventions

Intervention(s)
We plan to randomly provide maize insurance to about 300 maize farmers in our sample, half the total. We will do so for both rainy seasons of the year. The sum insured will depend on the total land (i.e. acreage) each farmer cultivated during the two seasons of the year prior to the start of the treatment; information that will be collected at the baseline. The yield is estimated to be 2,000 kg of maize per acre; towards the upper limit of what farmers achieve with traditional farming techniques, and a reasonable amount for farmers using modern inputs. Each kilogram is insured at 500 USh.
Intervention Start Date
2021-06-15
Intervention End Date
2022-07-01

Primary Outcomes

Primary Outcomes (end points)
Measure of agricultural investment. One of such a measures takes the form of the total amount invested in the growing of maize over a cropping season. The focus on maize is explained by the fact that the insurance product we aim to distribute is tailored-made for maize, taking into account its specific growing conditions.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We investigate how the provision of insurance influences investment decisions in a panel setting. We hypothesise that the impact of insurance depends on mediating factors that are both important for investment and the effectiveness of insurance. In particular, the extent of the informal support received— understood as the size, strength and trust on the network— can determine how much protection insurance effectively provides. Such networks can complement the insurance cover mitigating the effects of basis risk. The more active, reliable and wide the networks beneficiaries participate in are, the less basis risk they may suffer from and the more effective the protection can be, which may prompt a different investment response.

We intend to provide crop insurance to randomly selected subsistence maize farmers in order to shelter them from background risk. Such intervention ought to allow us to draw causal inference on the effect of insurance on investment, and its interaction with risk sharing.
Experimental Design Details
Randomization Method
Computer randomisation.
Randomization Unit
Village
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
34 villages in the area of study.
Sample size: planned number of observations
607 participants. Approximately 18 households per cluster (one cluster is double the size)
Sample size (or number of clusters) by treatment arms
285 in the treatment and 323 in the control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Minimum Detectable Effect is a 20% increase in the outcome variable with a power of 0.8.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
University of St.Gallen (HSG) Ethics Committee
IRB Approval Date
2019-12-02
IRB Approval Number
HSG-EC-2019-08-28-A
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials