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THE COMPUTATIONAL SOCIAL SCIENCE WORKSHOP PRESENTS</h3>
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BEN GOLUB</h1>
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ASSISTANT PROFESSOR, DEPARTMENT OF ECONOMICS</h3>
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HARVARD UNIVERSITY</h3>
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The<span class="Apple-converted-space"> </span><a href="https://macss.uchicago.edu/content/computation-workshop" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">Computational
Social Science Workshop<span class="Apple-converted-space"> </span></a>at the University of Chicago cordially invites you to attend this week’s talk:</p>
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<a href="https://github.com/uchicago-computation-workshop/ben_golub/blob/master/2018__golub__when_less_is_more.pdf" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">WHEN
LESS IS MORE: EXPERIMENTAL EVIDENCE ON INFORMATION DELIVERY DURING INDIA’S DEMONETIZATION</a></h2>
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<span style="box-sizing: border-box; font-weight: 700;">Abstract:</span><span class="Apple-converted-space"> </span>How should policymakers disseminate information: by broadcasting it widely (e.g., via mass media), or letting word spread from a small number
of initially informed “seed” individuals? While conventional wisdom suggests delivering information more widely is better, we show theoretically and experimentally that this may not hold when people may need to ask questions to fully comprehend the information
they were given. In a field experiment during the chaotic 2016 Indian demonetization, we varied how information about demonetization rules was delivered to villages on two dimensions: how many were initially informed (broadcasting versus seeding) and whether
the identity of the initially informed was publicly disclosed. The quality of information aggregation is measured in three ways: the volume of conversations about demonetization, level of knowledge about demonetization rules, and choice quality in a strongly
incentivized decision dependent on understanding the rules. Our results are consistent with four predictions of a model in which people need others’ help to make the best use of announced information, but worry about signaling inability or unwillingness to
correctly process information they have access to. First, if who is informed is not publicized, broadcasting improves all three outcomes relative to seeding. Second, under seeding, publicizing who is informed improves all three outcomes. Third, when broadcasting,
publicizing who is informed hurts along all three dimensions. Finally, when who is informed is made public, broadcasting is worse along all three dimensions relative to seeding.</p>
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THURSDAY, 4/12/2018</h4>
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11:00AM-12:20PM</h4>
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KENT 120</h4>
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A light lunch will be provided by Cedars Mediterranean Kitchen.</p>
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<span style="box-sizing: border-box; font-weight: 700;">Benjamin Golub’s</span><span class="Apple-converted-space"> </span>research in economic theory focuses on social and economic networks. His work has examined:</p>
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<li style="box-sizing: border-box;">Learning and gossip: what are the dynamics of information in networks? Who is particularly influential? When do agents learn correctly? When are their beliefs polarized?</li><li style="box-sizing: border-box;">Coordination in organizations: how do strategic agents in complex organizations coordinate, and how do the networks that connect them matter?</li><li style="box-sizing: border-box;">Financial contagion: which financial networks are particularly sensitive to sudden breakdowns?</li><li style="box-sizing: border-box;">Public goods and externalities: in complex favor-trading problems such as pollution reduction, we can use a network perspective to understand how much scope for cooperation there is, who is particularly essential to it, and
how to organize negotiations.</li></ul>
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Since 2015, he has been an Assistant Professor at the Harvard Department of Economics, and prior to that he spent two years as a Junior Fellow at the Harvard Society of Fellows. He was educated at Stanford (Ph.D. in economics) and Caltech (B.S., mathematics).</p>
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The 2017-2018<span class="Apple-converted-space"> </span><a href="https://macss.uchicago.edu/content/computation-workshop" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">Computational
Social Science Workshop<span class="Apple-converted-space"> </span></a>meets each Thursday from 11 a.m. to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.</p>
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Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the<span class="Apple-converted-space"> </span><a href="https://github.com/uchicago-computation-workshop/ben_golub/issues" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">issues
page<span class="Apple-converted-space"> </span></a>of the<span class="Apple-converted-space"> </span><a href="https://github.com/uchicago-computation-workshop/ben_golub" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">workshop’s
public repository on GitHub.</a><span class="Apple-converted-space"> </span>Further instructions are documented in the Computational Social Science Workshop’s<span class="Apple-converted-space"> </span><a href="https://github.com/uchicago-computation-workshop/README" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">README
on Github.</a></p>
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