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Activity Number:
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429
- Frequentist and Bayesian Inference for Complex Social Data
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Type:
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Contributed
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Date/Time:
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Wednesday, August 10, 2022 : 10:30 AM to 12:20 PM
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Sponsor:
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Social Statistics Section
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Abstract #323153
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Title:
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Estimating Causal Spillover Effects in Smallholder Farmer Networks in Western Kenya
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Author(s):
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Medha Uppala* and Bruce Desmarais and David P Hughes
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Companies:
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Center for Social Data Analytics, Penn State University and Center for Social Data Analytics, Penn State University and Huck Institutes of the Life Sciences, Penn State
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Keywords:
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interference;
spillover effects;
causality;
social networks;
randomization test;
direct and indirect effects
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Abstract:
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As farmers share information on practical agricultural techniques with each other, we want to understand what demographic and social network factors lead to greater information sharing and adoption. The goal of this research is to understand and estimate how efficiently information on disease management behaviors (DMB) spread in smallholder farmer networks. In this research, we are concerned with DMBs with respect to plant and crop disease. More formally, the goal is to causally estimate the network spillover effects of specific DMBs in smallholder farmer networks in Western Kenya. We intend to achieve this goal through a cluster randomized trial. Methods employed include re-randomization during design phase, randomization tests to detect interference and estimating direct and indirect effect size via exposure networks.
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Authors who are presenting talks have a * after their name.
