Go for It while You Can: Insurance Panel Experiment

Last registered on June 13, 2021
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Pre-Trial

Trial Information

General Information

Title
Go for It while You Can: Insurance Panel Experiment
RCT ID
AEARCTR-0007084
Initial registration date
January 27, 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
January 27, 2021, 5:10 PM EST

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

Last updated
June 13, 2021, 9:43 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

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
Mohammed Abdellaoui
PI Affiliation
HEC Paris
Contact Investigator
PI Name
Emmanuel Kemel
PI Affiliation
HEC Paris
Contact Investigator

Additional Trial Information

Status
In development
Start date
2021-01-27
End date
2022-12-31
Keywords
Behavior, Finance & Microfinance, Firms & Productivity
Additional Keywords
risk preferences; time preferences; time discounting; insurance; index insurance
JEL code(s)
D01, D81, D91, O12
Secondary IDs
Abstract
We seek to investigate how the provision of insurance influences decisions under risk and time in a panel setting. Our study will be implemented in a homogenous area in rural Uganda over the course of the next two years.
External Link(s)

Registration Citation

Citation
Vieider, Ferdinand et al. 2021. "Go for It while You Can: Insurance Panel Experiment." AEA RCT Registry. June 13. https://doi.org/10.1257/rct.7084-1.2000000000000002
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)
Measures of risk and time preferences (see design document for details)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our research aims to investigate how the provision of insurance influences decisions under risk and time. 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 inferences on the effect of background risk on preferences and behaviour. In order to carry out these tests, we will be measuring the risk and time preferences of maize farmers in a panel structure within a homogeneous maize-growing region in Uganda, with two measurements a year between the two rainy seasons.
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 0.05 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