Evaluating Demand for Multi-Season Crop Insurance: Experimental Evidence from Uganda

Last registered on August 05, 2024

Pre-Trial

Trial Information

General Information

Title
Evaluating Demand for Multi-Season Crop Insurance: Experimental Evidence from Uganda
RCT ID
AEARCTR-0013377
Initial registration date
April 16, 2024

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
April 16, 2024, 3:54 PM EDT

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

Last updated
August 05, 2024, 10:02 AM EDT

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

Locations

Primary Investigator

Affiliation
University of Zurich

Other Primary Investigator(s)

PI Affiliation
Columbia University
PI Affiliation
Ludwig Maximilians University of Munich (LMU)

Additional Trial Information

Status
In development
Start date
2024-08-06
End date
2026-01-01
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this project, we collaborate with a crop insurance consortium in Uganda and experimentally study the demand for multi-season insurance contracts among smallholder farmers in Uganda. We focus on insurance products with ex-post premiums (“Pay-at-Harvest Insurance”). We investigate whether farmers demand multi-season insurance, whether they want to have the option to cancel after the first season or a commitment to take up for two seasons, and possible mechanisms for the commitment demand. In addition, we will study the effect on insurance demand of a randomized information intervention that aims to make farmers aware of the state-dependent nature of their farming activities and the possible state-dependency of their demand for insurance.
External Link(s)

Registration Citation

Citation
Casaburi, Lorenzo, Jack Willis and Sili Zhang. 2024. "Evaluating Demand for Multi-Season Crop Insurance: Experimental Evidence from Uganda." AEA RCT Registry. August 05. https://doi.org/10.1257/rct.13377-2.0
Experimental Details

Interventions

Intervention(s)
We partner with the Uganda Agricultural Insurance Consortium (AIC), to study the demand for multi-season insurance contracts among smallholder farmers. AIC will offer Pay-at-Harvest Insurance—farmers subscribe at planting time but pay the premium at the end of each insured season as a deduction from the harvest payments the off-taker makes to the farmers. The crop insurance product will be an area yield index insurance: the insurance payout is disbursed if the average yield across farmers in a certain area (e.g. a district) is below a certain threshold, as measured in a crop-cutting exercise on a sample of farmers.

Farmers can choose to purchase insurance for two seasons (Season B 2024: Sep-Dec 2024 and Season A 2025: Mar-Jun 2025) and can decide whether they want an option to cancel the contract after the first season. They can also choose to have this option to cancel the contract for the second season depending on if they would receive or would not receive payouts in the first season (i.e., a state-dependent option).

In addition, we test the effect of an information intervention on farmers' demand. The treatment group (T1) will receive an information treatment aimed at making farmers aware of the potential state dependency of the crop activities and of their insurance demand---farmers will be guided to think through farming activities and insurance demand in different scenarios when the current season is good or bad and the associated pros and cons of the cancellation option in their insurance plan. The control group (T0) will not receive such an intervention.
Intervention Start Date
2024-08-06
Intervention End Date
2025-09-30

Primary Outcomes

Primary Outcomes (end points)
Insurance demand outcome: no purchase, purchase of two-season insurance with/without cancellation option.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1. Purchase of a two-season insurance product with a state-dependent cancellation option
2. Follow up on whether the chosen cancellation option is used
3. Manipulation checks:
- farmers' ability to imagine circumstances that have not yet happened
- farmers' self-reported tendencies for contingent thinking
- farmers' self-reported likelihood of state dependence in their insurance demand
- farmers’ normative attitude towards state dependence in their insurance demand
- farmers’ judgement about the desirability of different states
- farmers’ trust in insurance
4. Robustness checks and exploration of heterogeneity with respect to the following covariates.
- Comprehension of insurance terms
- Yield of last cycle
- Trust in offtaker
- Other variables concerning household characteristics and farming activities
- Behavioral measurements
- Responses on how they would decide about insurance and related reasoning in good/bad scenarios in the treatment
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The intervention targets a sample of farmers who sell their product to a local offtaker. The offtaker provided a list of farmers at the beginning of the study. The field team conducts confirmation calls to verify that the farmers have a basic relationship or experience with our partner and that they intend to sell their crop to the off-taker. We will specify our exclusion criteria below in more detail.

After the list of farmers is verified, the farmers on the verified list are mobilized to attend group meetings where a general introduction to insurance is provided. Farmers can additionally contact the local offtaker or call a toll-free center to ask any questions they may have. This step ensures that the farmers in our study have a good understanding of insurance terms in general.

During the data collection, each of the farmers will be reached individually to complete a baseline survey and receive a two-season insurance offer that entails paying the insurance premium via deduction from harvest time payments in each season. Specifically, farmers are given the choice to buy insurance (or not) for two seasons, and whether they would like to have the option to cancel the insurance after the first season. They are further asked whether they would like to have the cancellation option regardless of the outcome of the first season, or whether they would like to retain the cancellation option if they receive/ do not receive an insurance payout in the first season. All farmers are told that they will receive another phone call at the end of the first season during the insurance window for the second season.

The intervention consists of two treatment groups randomly assigned at the farmer level. The treatment group (T1) will receive an information treatment that guides farmers to think through farming activities and insurance demand in different scenarios when the current season is good or bad and discusses the associated pros and cons of the cancellation option in the insurance plan. Within the treatment group, we include a battery of manipulation check questions to explore mechanisms through which our treatment may be having an effect, and we randomize the order of treatment and manipulation checks. The control group (T0) will not receive the intervention or manipulation check questions.

Exclusion criteria: As mentioned above, we will only target farmers for the baseline survey if they have been verified. Specifically, in this verification process, we exclude farmer groups in which no farmer intends to sell in the next two seasons. This leaves about 500 farmers with whom we proceed to group meetings and the baseline survey (we do not expect to be able to reach all of them). In the baseline survey, we will again include questions asking whether each individual farmer has basic experience and relationships with their offtakers, and whether they intend to sell. We plan to conduct our main analysis on the full sample and on the subsample that includes only farmers who we expect to sell to offtakers, and those who have attended the group meeting.
Experimental Design Details
Not available
Randomization Method
The randomization of the information treatment is done on SurveyCTO, only with farmers who are reached for the baseline survey.
Randomization Unit
The randomization of T0/T1 is at the farmer level. In addition, the order of some survey sections is randomized at the farmer level. The randomization determines whether scenarios presented to the farmers are first about a positive or a negative shock and whether a manipulation check is presented before or after the information treatment. These order-randomizations only occur for those farmers in the information treatment groups.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Approximately 500 farmers targeted for the baseline survey (we do not expect to reach all of them).
Sample size: planned number of observations
Approximately 500 farmers targeted for the baseline survey.
Sample size (or number of clusters) by treatment arms
50% of the farmers reached in the baseline will be in T1 and 50% in T0.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Research Ethics Committee (MUREC)
IRB Approval Date
2024-07-25
IRB Approval Number
MUREC-2022-179