The Dynamic Relationship Between Accidents, Drivers' Licensing and Automobile Registrations; A Vector Autoregression Perspective

Kpamma, Henry M. and Bruku, Silverius K. and Imoro, Rafiatu and Awaab, John A. and Okyere, Stella (2020) The Dynamic Relationship Between Accidents, Drivers' Licensing and Automobile Registrations; A Vector Autoregression Perspective. Asian Journal of Probability and Statistics, 7 (2). pp. 44-58. ISSN 2582-0230

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Abstract

Aims/ Objectives: The paper seeks to investigate the dynamic relationship between drivers licensing, vehicle registration, motorbike registration and accidents.
Study Design: Cross-sectional study.
Place and Duration of Study: The secondary data was collated on a monthly basis on Accidents, Driver license, Motor Registration and Vehicle Registration that spanned 9 years from January 2010 to December 2018 from the Upper East Regional Oce of the Drivers Vehicle and License Authority.

Methodology: The data was analyzed using vector autoregression model to establish the dynamic relationship between the variables. The R and Eviews softwares were used in the analysis.
Results: The ndings revealed that in the short-run and long-run neither Driver license, Vehicle Registration, Motor Registration none Accidents cannot in uence much on each other but experienced their own shock. Findings further ascertain that Accidents can granger cause vehicle registration to change but the remaining variable have no much in uence on accidents.Although, accidents can granger cause vehicle registration to change, the remaining variables had no
in uence on accidents. The nding nally concluded that ARCH-LM test indicated that there was no ARCH eect present in the series implying that the Vector Autoregression model was appropriate to establish the dynamic relationship between the variables.

Item Type: Article
Subjects: European Scholar > Mathematical Science
Depositing User: Managing Editor
Date Deposited: 15 Mar 2023 09:54
Last Modified: 26 Jun 2024 06:57
URI: http://article.publish4promo.com/id/eprint/1301

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