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X-WR-CALNAME;VALUE=TEXT:Guillaume Basse (Workshop in Applied Statistics)
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SUMMARY:Guillaume Basse (Workshop in Applied Statistics)
DESCRIPTION:<p>	You can attend this workshop via this link: https://harvard.zoom.us/j/97787602526?pwd=Uzh3bVVVS0F4TEVYQTJlV3BQNjcydz09</p><p>	If you would like to be added to the email list to receive reminders and information about the series, please send your email address to Soichiro Yamauchi (syamauchi@g.harvard.edu).</p><h3>	<strong>Today's presenter:</strong></h3><p>	Guillaume Basse (Stanford University)<!--break--></p><h3>	<strong>Abstract:</strong></h3><p>	<span><span style="color:#222222"><span style="Helvetica,sans-serif"><span style="background-color:#ffffff">In hot policing, resources are targeted at specific locations predicted to be at high risk of crime; so-called "hot spots." Rather than reduce overall crime, however, there is a concern that these interventions simply displace crime from the targeted locations to nearby non-hot spots. We address this question in the context of a large-scale randomized experiment in Medellin, Colombia, in which police were randomly assigned to increase patrols at a subset of possible hotspots. Estimating the displacement effects on control locations is difficult because the probability that a nearby hotspot is treated is a complex function of the underlying geography. While existing methods developed for this "general interference" setting, especially Horvitz-Thompson (HT) estimators, have attractive theoretical properties, they can perform poorly in practice and mislead practitioners. In this talk, I explore the key pitfalls that practitioners should watch out for when conducting this type of analysis, and propose some ways to partially remedy them.</span></span></span></span></p><p>	The Applied Statistics Workshop (Gov 3009) is a forum for graduate students, faculty, and visiting scholars to present and discuss methodological or empirical work in progress in an interdisciplinary setting. The workshop features a tour of Harvard's statistical innovations and applications with weekly stops in different fields and disciplines and includes occasional presentations by invited speakers. It is co-hosted by Harvard University's Department of Government and Institute for Quantitative Social Science (IQSS).</p><p>	For more information, visit the <a data-url="https://projects.iq.harvard.edu/applied.stats.workshop-gov3009" href="https://projects.iq.harvard.edu/applied.stats.workshop-gov3009" title="">Applied Statistics website</a>.</p>
LOCATION:Zoom - see below
STATUS:CONFIRMED
DTSTART:20210127T170000Z
DTEND:20210127T183000Z
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