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How does recalling experiences of conflict affect behaviour that aids or hinders post-conflict recovery

Last registered on May 21, 2018

Pre-Trial

Trial Information

General Information

Title
How does recalling experiences of conflict affect behaviour that aids or hinders post-conflict recovery
RCT ID
AEARCTR-0003008
Initial registration date
May 21, 2018

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
May 21, 2018, 5:17 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
Durham University

Other Primary Investigator(s)

PI Affiliation
Busara Center for Behavioral Economics
PI Affiliation
Busara Center for Behavioral Economics
PI Affiliation
Busara Center for Behavioral Economics
PI Affiliation
PI Affiliation
Overseas Development Institute (ODI)
PI Affiliation
Overseas Development Institute (ODI)

Additional Trial Information

Status
On going
Start date
2018-05-18
End date
2018-12-31
Secondary IDs
N/A
Abstract
Numerous studies suggest that past experiences of violent conflict can affect deep determinants of behaviour (see (Bauer et al. 2016)). Perhaps contrary to intuition, the consensus among these studies is that past experiences of violent conflict promote pro-social behaviour. Two important questions remain regarding this literature: (1) is the relationship observed causal? As opposed to driven by reversed causality or attrition bias; (2) if so, why does this relationship exist?

We use an experimental set-up using priming to better establish causal relationships (so far only used by (Callen et al. 2014) for economic outcomes). The study design makes use of micro-narratives as a prime, which the respondents classify themselves along various dimensions. This means that respondents are asked to recall a significant experience and analyse it using the Sensemaker framework, providing insight into the analytical frameworks people use. Half of respondents (N=400) are primed to account a micro-narrative of their conflict experiences, half is primed to account a neutral narrative, prior to playing a set of behavioural games to measure deep determinants of behaviour. This will be followed by qualitative interviews.

Qualitative research and the use of self-classified micro-narratives will enable us to unpack the mechanisms behind the relationship between exposure to violence and behaviour. We will consider subsets of respondents for whom this relationship is especially strong or weak, and detect any patterns in the narratives these sub-groups tell.

We also reflect on the methodological lessons we have learned from using this integrated research design, including a consideration of how those at the receiving end of behavioural experiment experienced this type of research. Has this approach given us more rigorous and grounded insights—and can these insights help in developing better policies and programme approaches?
External Link(s)

Registration Citation

Citation
Ayee, Tracy et al. 2018. "How does recalling experiences of conflict affect behaviour that aids or hinders post-conflict recovery." AEA RCT Registry. May 21. https://doi.org/10.1257/rct.3008-1.0
Former Citation
Ayee, Tracy et al. 2018. "How does recalling experiences of conflict affect behaviour that aids or hinders post-conflict recovery." AEA RCT Registry. May 21. https://www.socialscienceregistry.org/trials/3008/history/29876
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention is a priming treatment. EITHER:
a. The participant recounts a narrative of their experience during the Government of Uganda - Lord's Resistance Army conflict (treatment)
b. The participant recounts a neutral narrative (control)
Intervention Start Date
2018-05-18
Intervention End Date
2018-06-30

Primary Outcomes

Primary Outcomes (end points)
Altruism; Fairness; Contribution to Public Goods; Joy of Destruction; Retaliation; Risk preferences; Time preferences.
Primary Outcomes (explanation)
● Altruism
o From the dictator game: Continuous variable on amount given to matched player.
● Fairness
o From the ultimatum game: Continuous variable on amount given to matched player.
o From the ultimatum game: Dummy variable equaling one if offer is rejected for each possible scenario (fairness preference).
● Contribution to public goods
○ From the fragile public goods game: Continuous variable on amount contributed to or taken from the pot.
○ From the fragile public goods game: Dummy variable equaling one if any amount is taken from the pot.
● Joy of destruction
○ From vendettas and retaliation round 1: Dummy variable equaling one if a player decided to reduce the other player’s endowment.
● Retaliation
○ From vendettas and retaliation: Dummy on whether participant reduced outcomes for each subsequent round + dummy on whether participant reduced outcome for each subsequent round if other player matched player reduced their amount in preceding round (retaliation).
○ From vendettas and retaliation round 1: Dummy variable equaling one if a player guesses the other player will reduce their endowment (expectation of retaliation).
○ From vendettas and retaliation all rounds other than round 1: Dummy variable equaling one if a player guesses the other player will reduce their endowment (expectation of retaliation), controlling for a dummy variable equaling one if the player has reduced the other player’s endowment in the previous round and a dummy variable equaling one if the other player has reduced the player’s endowment in the previous round.
● Risk preferences
○ From risk task round 1: Risk measure as per Eckel and Grossman (2008).
○ From risk task round 1 and 2: Transitivity violation measure as per Eckel and Grossman (2008).
● Time preferences:
○ From time preferences task round 1-4: Time inconsistency/present bias (aggregate estimate of beta) (Andreoni, Kuhn, and Sprenger 2015).
○ From time preferences task round 1-4: Discounting (estimate of delta) (Andreoni, Kuhn, and Sprenger 2015).

Secondary Outcomes

Secondary Outcomes (end points)
Effectiveness of prime
Secondary Outcomes (explanation)
● Effectiveness of prime
o From the content question: Dummy variable if the story includes violence or conflict.
o From the time of the story question: Dummy whether the story took place more than 10 years ago or less than 10 years ago.

Experimental Design

Experimental Design
Participants will be asked to participate in a series of consecutive exercises:
1. Priming treatment . EITHER:
a. The participant recounts a narrative of their experience during the GoU/LRA conflict (treatment)
b. The participant recounts a neutral narrative (control)
2. Self-signification. The participant classifies their narrative on a set of multi-dimensional scales which involves a series of questions that show the analytical framework which respondents use to make sense of experiences in their lives.
3. Behavioural games, to elicit preferences and pro- and anti-social behaviours.
4. Closed-ended survey questions, to assess the efficacy of the prime.
5. Qualitative interviews in the area affected by the conflict to establish how people describe the ongoing effect of conflict on their lives. These interviews examine the extent to which NGO programming continues to use a post-conflict lens that uses conflict recall and whether those elements that were largely considered part of the conflict dynamics at the time—such as neglect, exclusion, underdevelopment—still feature in people’s daily experience.

The main analysis will be a comparison of behaviour as measured by the games between treatment and control group.
Experimental Design Details
Randomization Method
Randomization done in lab by computer
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
400-600 individuals
Sample size (or number of clusters) by treatment arms
200-300 control, 200-300 treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
0.281 standard deviations for a sample size of 400 at 5% significance. 0.229 standard deviations for a sample size of 600 at 5% significance.
IRB

Institutional Review Boards (IRBs)

IRB Name
Ugandan Institute of Science and Technology
IRB Approval Date
2018-04-27
IRB Approval Number
SS4529
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials