Can climate disasters that require large-scale adaptation measures trigger out-group cooperation? Evidence from small-scale communities in Papua New Guinea

Last registered on April 26, 2023


Trial Information

General Information

Can climate disasters that require large-scale adaptation measures trigger out-group cooperation? Evidence from small-scale communities in Papua New Guinea
Initial registration date
April 19, 2023

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 26, 2023, 4:59 PM EDT

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


Primary Investigator

University of Hamburg

Other Primary Investigator(s)

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
This project studies the willingness to engage in district-wide climate adaptation measures through climate community funds. The setting of the research are small scale coastal communities in Bougainville, Papua New Guinea, that suffer from sea-level rise and more frequent natural disasters such as tsunamis, beach erosion, and coastal floodings while at the same time enjoying a high mangrove abundancy. Through a lab-in-the-field experiment, this project studies the willingness to contribute to district-wide community funds devoted to adaptation measures depending on whether the other player is from one’s own community or from another constituency, i.e. another language and cultural group. I further investigate whether the potential out-group discrimination might be alleviated through observation. I hypothesize that while cooperation with the out-group yields lower contribution levels, the effect of being observed by the community’s chief while taking the decision has the opposite effect.
External Link(s)

Registration Citation

Koch, Juliane. 2023. "Can climate disasters that require large-scale adaptation measures trigger out-group cooperation? Evidence from small-scale communities in Papua New Guinea." AEA RCT Registry. April 26.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
I investigate the treatment effects on cooperation levels through contributions to a climate community fund within and between villages, as well as with and without observation.

Hypothesis 1: Contribution levels are lower when cooperating with people in the out-group compared to the baseline (cooperation with in-group member without observation).

Hypothesis 2: Contribution levels are higher when being observed by the village’s Big Man compared to the baseline (cooperation with in-group member without observation).

Hypothesis 3: The decrease in contribution levels from hypothesis 1 and the increase in contribution levels from hypothesis 2 might level in the combined treatment, i.e. when playing with another player from the out-group while being observed of the village’s Big Man.

First, I intend to compare the effects by using nonparametric tests. Data are collected at the individual level. Between treatments contributions are compared across all subjects as well as by subjects conditional on beliefs’ of other person’s contribution levels (Mann Whitney U). Second, I perform difference-in-differences regression analyses. Third, I look at the heterogeneous treatment effects to see if there are interactions between control variables (see below) and treatment effects. The analysis of possible heterogeneous treatment effects will be explorative.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
• Demographic variables (age, gender, education level)
• Social preferences (risk taking, importance of own compliance, importance of compliance others),
• Climate change and disaster exposure,
• Previous community engagement,
• Task comprehensibility.
Secondary Outcomes (explanation)
I further investigate whether women are generally more cooperative in a sense that they contribute more often to the community fund than men, also whether or not they are expected and believed to contribute more to the community fund than men.

Experimental Design

Experimental Design
To test the willingness to cooperate by averting a potential climate disaster jointly, participants play a one-shot risk game in a two-player setting. Both participants are endowed with 15Kina (approx. 5Euros; additional to 2Kina show-up fee) which they can invest into a climate community fund (disctrict wide) serving as a type of insurance that can protect the players in case of a disaster happening. Communities are used to so-called ‘community funds’ which is why this setting is being used for the framing. To induce the larger necessity of adaptation solutions, the fund is not restricted to the community but to the district level, including people from the same coast but with different cultures and languages. Furthermore, the experiment is framed in a way that participants in the field know what their investment is devoted to. The district community fund is used for local engagement in climate adaptation measures, for example the conservation and reforestation of mangrove trees, or the building of dams. Those adaptation measures have shown to help coastal communities that are affected by sea levels rise and climate change induced disasters such as tsunamis and coastal floodings to detain the water in the short-run. Participants are being told that the experimental game they are engaging in is only a hypothetical situation and their investment in the game’s community does not really lead to the engagement of mangrove conservation and reforestation. Also, the occurrence of a disaster, drawn by a card in the game is only hypothetical and to be imagined only for the game itself.

Once, this is clear to participants, the game is being explained and its understanding is being controlled for through control questions. In the game, the disaster is happening with a 50% probability, which is being determined by a random draw of two cards (‘disaster happening’ vs. ‘disaster not happening’).
In case the card determines that the disaster is not happening, the participants’ payoff is determined by their initial endowment from which their chosen investment level is being deducted. In case the card determines that the disaster is happening, the payoffs of the players depend on the previous investment and thus protection levels. In case both players invest, together they reach full protection and they only ‘lose’ their investment of the community fund. In case only one player invests, they reach a partial protection for both, i.e. some of their endowment is lost and in case no one invests, they both have no protection at all, meaning that nearly all their endowment is lost.
To facilititate high simplicity among the communities in which some people are illiterate, the following simple parameters are chosen: Endowment=15Kina; Payment for Community Fund=5Kina; Destruction no protection=15Kina; Destruction partial protection=10Kina.

Participants chose their investment level without knowing the investment decision of their playing partner, all they know is whether their playing partner is from their own village or from another village of another constituency (but in the same district), i.e. with another culture and language.
The first treatment variation studies the difference of being observed. As we know from the cooperation literature, being observed normally leads to people contributing more (Grimalda et al. 2016). The Big Man serves as observer as he is the person with the highest degree of authority and normally represents the person of a village who represents the village’s social norms and who most people look up to. He will not interact with participants, i.e. not giving any suggestions but merely observing the participants while taking their decision. The second treatment variation refers to the cooperation partner either being within the same village or from another village with a different language. This treatment variation triggers the ingroup-outgroup differentiation.

The experiment will be conducted as a pen and paper lab-in-the-field-experiment in approx. four to six small-scale coastal communities in Bougainville, Papua New Guinea, starting 20 April 2023. I continue the lab-in-the-field-experiment until (i) the maximum sample quota (see below) is reached, (ii) I have used all the available budget, or (iii) 19 May 2023 has been reached.
The experiment is followed by a detailed survey questionnaire which includes various social preference questions, including questions about trust, altruism, fairness perceptions, reciprocity, inequity aversion. Furthermore, questions are directed towards knowledge and beliefs about climate change as well as the willingness to engage in adaptation projects, specific community-based disaster management engagement, the support for national climate policies and one’s own experience with extreme weather events and potential losses thereof.
Experimental Design Details
Randomization Method
Randomization done by a computer
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
In all treatments, subjects interact in groups of 2, however their one-shot decision are independent observations. In the minimum case of 4 villages, I plan with a minimum of 240 subjects. Until time and budget are exhausted, I plan to further continue collecting data in a fifth (or even sixth) village. This way the total amount of observation could go up to a maximum of 400 participants but which only becomes definite during the field phase.
Sample size (or number of clusters) by treatment arms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number


Post Trial Information

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Program Files

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