Credit for Climate Change: Water Tanks as a Means of Resilience

Last registered on July 12, 2022


Trial Information

General Information

Credit for Climate Change: Water Tanks as a Means of Resilience
Initial registration date
July 12, 2022

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
July 12, 2022, 1:56 PM EDT

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

Last updated
July 12, 2022, 8:43 PM EDT

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


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Primary Investigator

Precision Development

Other Primary Investigator(s)

PI Affiliation
Development Innovation Lab, University of Chicago
PI Affiliation
University of Chicago

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Climate change induced rainfall and temperature variability pose a substantial economic risk to smallholder dairy farmers in developing countries (Tadesse and Dereje 2018). Rainwater harvesting tanks may help farmers adapt to climate uncertainty. Previous work has found that Asset Collateralized Loans (ACLs) help farmers purchase water tanks in Kenya (Jack et al, 2019). Building on this previous work, this study aims to evaluate the impact of ACLs for water tanks on economic and household outcomes among dairy farmers in Kenya. Specifically, we will use administrative data from dairy cooperatives and survey data to investigate whether improved access to water tanks helps farmers mitigate productivity shocks and domestic water shortages during dry spells. We will also examine how improved water access affects time and water allocation within household members.
External Link(s)

Registration Citation

Deutschmann, Joshua, Tomoko Harigaya and Michael Kremer. 2022. "Credit for Climate Change: Water Tanks as a Means of Resilience." AEA RCT Registry. July 12.
Experimental Details


This study will evaluate the impacts of addressing credit constraints which has the potential to unlock smallholder dairy productivity and income of the farmers. In our interventions, we will (1) conduct sensitization on the asset-collateralized loan (ACL) and register interest with the dairy farmers from two dairy cooperatives in the Rift Valley of Kenya, (2) offer an asset-collateralized loan (ACL) for a water tank to a random sample of the interested and eligible treatment participants, (3) pilot the use of low-cost SMS surveys to gather additional insights and measure time use and milk production immediately during the implementation phase.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Milk production and sales
Health indicators such as incidence of diarrhea
Time use
Water availability and allocation
Subjective well-being
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This experiment will evaluate the impacts of addressing an important constraint that limits agricultural incomes among smallholder dairy farmers: credit. We will partner with two dairy cooperatives in Kenya and their corresponding financial institutions (SACCOs) to implement a randomized control trial among dairy farmers in the Rift Valley of Kenya. We will offer interested, eligible participants an asset-collateralized loan for a water storage tank.

Staff of our partner cooperatives will communicate information to their members about a new lending program for water tank loans. Following this communications campaign, we will call members to conduct a pre-screening for interest in taking an asset-collateralized loan for a water tank. Our primary experimental sample will consist of the first 1,500 eligible, interested members identified by the cooperatives.

Among this sample, we will conduct an in-person baseline survey. We will then randomize this sample at the household level into a treatment group which will be invited to apply for an asset-collateralized loan for a water tank (n = 750) and a control group which will receive no additional loan access (n = 750). We will stratify the randomization on SACCO, agroecological zone and characteristics in the baseline survey and/or administrative data that strongly predict milk production and sales.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Household level
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
1500 farmers
Sample size (or number of clusters) by treatment arms
750 farmers (50:50)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Using administrative data on monthly milk sales with 12 pre-intervention and 18 post-intervention measurements with an expected across-measurement correlation of 0.75 (based on baseline administrative data), we expect to be able to detect an intent-to-treat effect on milk sales of 6 percentage points at 80% power with 617 farmers in each arm. To account for margin of error, we aim to conduct the baseline survey with 1500 households and assign 750 farmers to the treatment group.

Institutional Review Boards (IRBs)

IRB Name
Health Media Lab (HML)
IRB Approval Date
IRB Approval Number
IRB Name
Maseno University Scientific and Ethics Review Board (MUSERC)
IRB Approval Date
IRB Approval Number