Count Models Analysis of Factors Associated with Road Accidents in Nigeria
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Date
2022-08-19
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Publisher
IIETA
Abstract
The current state of all Nigerian roads is in poor condition, and reports of accidents have
been recorded across the federation. The larger mission of the sustainable development
goal is to promote sustainable cities and communities. This research study aims to
examine factors responsible for road accidents in Nigeria through the quantitative tool of
higher extensions of the Poisson regression model (ZTNPRM). A cross-sectional study
design was adopted and secondary data was used within a sample period from the 1st
quarter of 2006 to the 2nd quarter of 2020. Due to overdispersion, ZTNPRM indicates
human errors contribute to a large proportion (41.4%) of road accidents. Vehicle factors
are also statistically and positively related to road accidents. All the factors this model
identified that lead to road accidents predicted low road accidents. Hence, the study
recommends that Nigerian car users follow all rules and regulations associated with safe
driving and make the environment safer for people as the sustainable development goal
(SDGs). This study recommends more attention to the area of accident and injury
prevention as a strategic objective of the SDGs.
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Keywords
overdispersion, count models, road accident, zero truncated Poisson model, zero truncated negative Binomial