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Moral Hazard, Networks and Risk Sharing: Evidence from a Lab Experiment in the Field
Last registered on March 18, 2015

Pre-Trial

Trial Information
General Information
Title
Moral Hazard, Networks and Risk Sharing: Evidence from a Lab Experiment in the Field
RCT ID
AEARCTR-0000605
Initial registration date
March 18, 2015
Last updated
March 18, 2015 3:24 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
University of Michigan
Other Primary Investigator(s)
Additional Trial Information
Status
On going
Start date
2015-01-28
End date
2015-08-15
Secondary IDs
Abstract
Risk sharing, in which individuals and households make both monetary and non-monetary transfers to each other, is an important mechanism through which households can cope with idiosyncratic risk in settings with little or no access to insurance. Moral hazard, in which individuals cannot observe the actions of others, may exist in these settings and limit the potential for risk sharing. The purpose of my research project is to investigate the extent to which moral hazard limits risk sharing and whether social proximity can help overcome the problems of the moral hazard. I use a laboratory experiment in Nairobi, Kenya with residents of the Kibera slum to address these questions.
External Link(s)
Registration Citation
Citation
Jain, Prachi. 2015. "Moral Hazard, Networks and Risk Sharing: Evidence from a Lab Experiment in the Field." AEA RCT Registry. March 18. https://doi.org/10.1257/rct.605-1.0.
Former Citation
Jain, Prachi. 2015. "Moral Hazard, Networks and Risk Sharing: Evidence from a Lab Experiment in the Field." AEA RCT Registry. March 18. https://www.socialscienceregistry.org/trials/605/history/3801.
Experimental Details
Interventions
Intervention(s)
We have participants will play three risk sharing games with partners. We vary how income is generated (luck only, luck and effort) and, in the games with effort, whether effort is observable to partners.
Intervention Start Date
2015-03-19
Intervention End Date
2015-05-15
Primary Outcomes
Primary Outcomes (end points)
Transfers promised, for each possible set of income (and, in effort observable game, efforts).
Effort, defined as whether or not the participant completes the task and the number of correct answers in the task.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Participants will play three risk sharing games with partners. Individuals will play a luck only game, a game with luck and observable completion of a task and a game with luck and unobservable completion of a task. Subjects will play all three games and game order will be randomized. Participants are randomly assigned to play each game with a partner. Partnerships are non-anonymous - meaning that participants will know their partner's name and may know their partner outside of the laboratory.
Experimental Design Details
Randomization Method
Game order is randomized (by a computer in advance of the session). Due to the fact that the number of participants per session varies and thus the number of experiment sessions cannot be known in advance, I use "block" randomization. There are 6 possible game orders of the 3 risk sharing games. I ensure that in every block of 6 sessions, each possible game order is used exactly once. I randomize order separately for each block of 6 sessions.
Randomization Unit
The design is within-subject as participants play all game. Due to concerns about game order effects, I randomize order of the 3 games resulting in 6 combinations of game orders. The game orders are randomized at the experimental session level.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
500 individuals
Sample size: planned number of observations
500 individuals
Sample size (or number of clusters) by treatment arms
If there are substantial game order effects, we might use only the data from the first game played, effectively changing the design into between subject design. In this case, there would be 3 arms and so effectively approximately 166 subjects by treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
University of Michigan Health Sciences and Behavioral Sciences Institutional Review Board
IRB Approval Date
2014-12-18
IRB Approval Number
HUM00095117
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers