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Identifying communication spillovers in lab-in-the-field experiments
1Schulich School of Business, York University, 4700 Keele Street, Toronto, Ontario, Canada M3J 1P3.
Journal of Development Economics
|June 17, 2022
Summary
Communication between participants in field experiments can significantly increase cooperation, potentially biasing results. Researchers must develop protocols to manage these communication spillovers and ensure accurate findings in lab-in-the-field studies.
Area of Science:
- Behavioral Economics
- Development Economics
- Experimental Economics
Background:
- Lab-in-the-field experiments offer ecological validity but face challenges controlling external influences.
- Communication spillovers between participants in sequential field experiments are poorly understood.
- Existing literature shows inconsistent approaches to managing communication effects in field research.
Purpose of the Study:
- To quantify the impact of communication spillovers on participant behavior in public goods games.
- To assess how communication between villages affects cooperation levels in a field setting.
- To provide evidence-based recommendations for mitigating bias from communication spillovers.
Main Methods:
- Utilized existing data from public goods games conducted in 147 villages in Rwanda.
- Leveraged the sequential village visit order to identify villages with and without communication opportunities.
- Employed ex-post matching to compare cooperation levels between villages exposed and unexposed to spillovers.
Main Results:
- Communication spillovers led to substantial increases in cooperation among participants.
- Unanticipated communication between villages significantly biased experimental inference.
- The sequence of village visits created natural variation in exposure to communication.
Conclusions:
- Communication spillovers are a critical factor influencing cooperation in field experiments.
- Researchers must proactively design protocols to address and account for communication effects.
- Careful consideration of experimental design is necessary to avoid biased results in similar settings.
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