Abstract
This paper includes macroeconomic conditions in an econometric framework to understand urban crash injury severity (CIS) in a developing country, and identify its distinctive socioeconomic conditions. The work combines classic variables from a unique data set of crashes in Medellín, Colombia, with macroeconomic indicators. A multinomial logit (MNL) model with random parameters mines valuable information from the data. Numerical results support the following CIS mitigation policies: upgrading intersections with traffic signals; incorporating forgiving roadway designs; providing better conditions for motorcyclists and non-motorized users; prioritizing education, outreach, and enforcement campaigns during periods of good macroeconomic conditions (for some segments of the population), high motorization rates, and regarding specific periods, that is, times within the day, the week, and the year.
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Schedule a callMore From: Transportation Research Record: Journal of the Transportation Research Board
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