Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/181344
Authors: 
Elba, Filippo
Cosci, Fiammetta
Pettini, Anna
Stefanini, Federico M.
Year of Publication: 
2018
Series/Report no.: 
CESifo Working Paper 7144
Abstract: 
The 2016 report of the European Transport Safety Council claims that EU safety progress has come to a standstill. This study aims at deepening the knowledge of factors that influence adolescents’ risky behavior on the road. Bayesian Networks offer a promising new way to looking at the issue. In the analysis of a dataset collected in Tuscany, Italy, called EDIT, we found evidence that the use of alcohol and illegal substances explain only part of the probability of having an accident, and that other observable variables, like the level of distress or the type of school attended are significantly related to the probability of incurring in a road crash. New and close attention should be given to a systemic approach and to a plethora of environmental and individual variables that may rise the probability of road accidents for very young drivers.
Subjects: 
Bayesian Networks
structural learning
road accidents
distress factors
risky behavior
adolescence
youth
novice drivers
JEL: 
C11
D91
I11
Document Type: 
Working Paper

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