Tuesday, December 5, 2017
4:00 pm

Ulric B. and Evelyn L. Bray Social Sciences Seminar

Learning about The Influence of Spatial and Temporal Proximity using Regression Trees
Ines Levin, Assistant Professor, UC Irvine

Abstract: Learning about the impact of localized events taking place over time is a multi-faceted problem, as it requires taking into account the influence of multiple dimensions, including: geographical location, timing, and attributes of events. In this paper, I argue that traditional regression approaches---which assume the existence of a linear, or otherwise known, relationship between predictors and outcomes---are inappropriate for learning about the impact of spatial and temporal proximity to events. Instead, I propose using regression trees, an approach that allows addressing the problem in a non-parametric and efficient manner. I illustrate the usefulness of the proposed procedure by studying the impact of mass shootings on opinions about gun control and of distance to border crossings on support for immigration reform.

Contact Sabrina De Jaegher sabrina@hss.caltech.edu at 626-395-4228
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