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General Equilibrium Effects of Cash Transfers in Kenya
Last registered on February 12, 2017

Pre-Trial

Trial Information
General Information
Title
General Equilibrium Effects of Cash Transfers in Kenya
RCT ID
AEARCTR-0000505
Initial registration date
November 03, 2014
Last updated
February 12, 2017 8:22 PM EST
Location(s)

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Primary Investigator
Affiliation
University of California, Berkeley
Other Primary Investigator(s)
PI Affiliation
UC San Diego
PI Affiliation
UC Berkeley
PI Affiliation
Princeton University
Additional Trial Information
Status
On going
Start date
2014-08-18
End date
2017-12-31
Secondary IDs
Abstract
How redistribution affects the real economy is one of the central, unanswered questions in development economics. The effect of redistribution on the welfare of non-beneficiary households is theoretically ambiguous: there could be positive spillover effects through increased aggregate demand (a multiplier effect), or negative spillovers from price inflation or crowd-out by business expansion for non-beneficiaries. The NGO GiveDirectly provides large cash transfers to rural households in Kenya. We utilize an RCT to study the spillover effects of cash transfers on household welfare, prices, enterprise creation and local public finance and will make use of spatial variation in treatment density in order to estimate these effects.
External Link(s)
Registration Citation
Citation
Haushofer, Johannes et al. 2017. "General Equilibrium Effects of Cash Transfers in Kenya." AEA RCT Registry. February 12. https://www.socialscienceregistry.org/trials/505/history/13953
Experimental Details
Interventions
Intervention(s)
The NGO GiveDirectly is responsible for the intervention; GiveDirectly provides large, unconditional cash transfers to poor households in rural Kenya. GiveDirectly identifies villages in which they are willing to work, and in order to facilitate research on cash transfers, these villages are randomly assigned to treatment or control status. Within treatment villages, GiveDirectly then identifies all households that meet their eligibility criteria, enrolls and verifies the eligibility of eligible households, and sends cash transfers to all eligible households via the mobile money system M-Pesa. Eligible households receive a one-time of around USD 1,000 made in a series of three payments.

This intervention will serve as the basis for the current study on general equilibrium effects, as well as a future study investigating long-term effects of cash transfers.
Intervention Start Date
2014-09-15
Intervention End Date
2016-07-15
Primary Outcomes
Primary Outcomes (end points)
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The study will take place across 653 villages in Western Kenya. Villages are randomly allocated to treatment or control status. In treatment villages, GiveDirectly enrolls and distributes cash transfers to households that meet its eligibility criteria. In order to generate additional spatial variation in treatment density, groups of villages are assigned to high or low saturation. In high saturation zones, 2/3 of villages are targeted for treatment, while in low saturation zones, 1/3 of villages are targeted for treatment. The randomized assignment to treatment status and the spatial variation in treatment intensity will be used to identify direct and spillover effects of cash transfers.

The research team undertakes independent household censuses of treatment and control villages and makes their own judgment on whether households are eligible based on GiveDirectly's criteria. Households are then randomly selected to be surveyed by eligibility status (roughly 8 eligible households per village and 4 ineligible households). The research team also conducts a census of enterprises, enterprise surveys, market surveys and surveys with local leaders (including school principals) to collect data on prices, enterprise creation and local public finance.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Randomization to treatment status is conducted at the village level. High versus low saturation is randomly assigned to groups of villages based on their sublocation, an administrative unit above the village.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
653 villages
Sample size: planned number of observations
7,836 households (12 per village), 6,530 enterprises (this assumes an average of 10 enterprises per village; the exact number will depend on the number of enterprises in the study area).
Sample size (or number of clusters) by treatment arms
328 treatment, 325 control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
University of California, Berkeley Committee for the Protection of Human Subjects
IRB Approval Date
2014-06-18
IRB Approval Number
2014-05-6354
IRB Name
Maseno University Ethics Review Committee
IRB Approval Date
2014-07-24
IRB Approval Number
MSU/DRPC/MUERC/000090/14