Moral Hazard, Networks and Risk Sharing: Evidence from a Lab Experiment in the Field

Last registered on March 18, 2015


Trial Information

General Information

Moral Hazard, Networks and Risk Sharing: Evidence from a Lab Experiment in the Field
Initial registration date
March 18, 2015

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
March 18, 2015, 3:24 PM EDT

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



Primary Investigator

University of Michigan

Other Primary Investigator(s)

Additional Trial Information

On going
Start date
End date
Secondary IDs
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

Jain, Prachi. 2015. "Moral Hazard, Networks and Risk Sharing: Evidence from a Lab Experiment in the Field." AEA RCT Registry. March 18.
Former Citation
Jain, Prachi. 2015. "Moral Hazard, Networks and Risk Sharing: Evidence from a Lab Experiment in the Field." AEA RCT Registry. March 18.
Experimental Details


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
Intervention End Date

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?

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)

Institutional Review Boards (IRBs)

IRB Name
University of Michigan Health Sciences and Behavioral Sciences Institutional Review Board
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials