Why are Politicians More Likely to Learn From Neighbors? Behavioral Evidence From Three Advanced Democracies

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Abstract Empirical work on policy diffusion has established that policymakers are more likely to learn from the experiences of neighbors. Yet, the underlying mechanism behind spatially clustered policy learning remains unclear. Proximity may signal contextual similarity, leading officials to expect a better policy fit from nearby constituencies. However, proximity may impact policy learning simply due to information exposure. We adjudicate between these mechanisms by repurposing data from two field experiments that delivered information on new policy innovations to local politicians in Germany, the United Kingdom and the United States while varying the constituency of the early adopters. Across studies, issues, and countries, we find no reliable evidence that geographic proximity to early adopters predicts interest in policy learning. The results reveal that proximity effects in studies of policy diffusion likely arise from differential exposure rather than contextual fit and contribute more broadly to our understanding of bounded rationality and elite behavior.
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Why are Politicians More Likely to Learn From Neighbors? Behavioral Evidence From Three Advanced Democracies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Why are Politicians More Likely to Learn From Neighbors? Behavioral Evidence From Three Advanced Democracies Daniel Cruz, Miguel M. Pereira This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8252699/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Empirical work on policy diffusion has established that policymakers are more likely to learn from the experiences of neighbors. Yet, the underlying mechanism behind spatially clustered policy learning remains unclear. Proximity may signal contextual similarity, leading officials to expect a better policy fit from nearby constituencies. However, proximity may impact policy learning simply due to information exposure. We adjudicate between these mechanisms by repurposing data from two field experiments that delivered information on new policy innovations to local politicians in Germany, the United Kingdom and the United States while varying the constituency of the early adopters. Across studies, issues, and countries, we find no reliable evidence that geographic proximity to early adopters predicts interest in policy learning. The results reveal that proximity effects in studies of policy diffusion likely arise from differential exposure rather than contextual fit and contribute more broadly to our understanding of bounded rationality and elite behavior. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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