Aldrich presented with APSA Best Paper Award
June 21, 2012
Despite the tremendous destruction wrought by catastrophes, social science holds few quantitative assessments of explanations for the rate of recovery. This article illuminates four factors—damage, population density, human capital, and economic capital—that are thought to explain the variation in the pace of population recovery following disaster; it also explores the popular but relatively untested factor of social capital. Using time-series, cross-sectional models and propensity score matching, it tests these approaches using new data from the rebuilding of 39 neighborhoods in Tokyo after its
1923 earthquake. Social capital, more than earthquake damage, population density, human capital, or economic capital, best predicts population recovery in post-earthquake Tokyo. These findings suggest new approaches for research on social capital and disasters as well as public policy avenues for handling catastrophes.
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Purdue's Jeff Trapp part of month-long field research campaign to improve severe storm prediction
May 16, 2013
As a principal investigator in the NSF-funded Mesoscale Predictability Experiment (MPEX), Jeff will be collecting data with three radiosonde launch units operated by Purdue and NSSL in vehicles that will maneuver around late-day thunderstorms.
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