A nonlinear logit regression model for determining drivers’ accident probability in Algeria

The aim of the study is to estimate a nonlinear regression logit model to calculate the probability of a road accident occurring in Algeria. Referring to the literature, this probability depends on several variables related to the driver, the vehicle and the road environment. Thus, the objective is...

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Bibliographic Details
Main Authors: Houria Bencherif, Lounansa Ramdhane
Format: Article
Language:English
Published: Coimbra University Press 2022-10-01
Series:Territorium: Revista Portuguesa de riscos, prevenção e segurança
Subjects:
Online Access:https://impactum-journals.uc.pt/territorium/article/view/10558
Description
Summary:The aim of the study is to estimate a nonlinear regression logit model to calculate the probability of a road accident occurring in Algeria. Referring to the literature, this probability depends on several variables related to the driver, the vehicle and the road environment. Thus, the objective is to show which explanatory variables favour the occurrence of a traffic accident and to what extent. In addition, we seek to estimate the probability that a driver with given characteristics, driving a vehicle with given characteristics, and having a driving licence for a given length of time may have an accident. The structure of the estimation is based on disaggregated data collected following the analysis of files proposed by an Algerian insurance company. The results obtained make it possible to determine the category of variables that has a significance and an important role in explaining the probability of accidents occurring.
ISSN:0872-8941
1647-7723