Abstract
AbstractThis paper employs a statistical mechanical model as a framework to investigate how socioeconomic factors of individuals such as gender and place of residence influence their decision when deciding between comprehensive and third-party motor insurance policies in Ghana. Data from a general insurance firm was used for this investigation taking five years’ worth of transactions into account. The methods of partial least squares and the ordinary least squares are, respectively, used to estimate the parameters of the interacting and the non-interacting models in the Multipopulation Currie-Weiss model in a discrete choice framework. The findings showed that both location and gender have discernible influences on how people choose their motor insurance. We encourage insurance companies to intensify their campaign on the importance of motor insurance to all vehicle/car owners, especially those in rural areas in order to reduce the risk and associated losses in vehicular accidents on Ghanaian roads.
Publisher
Springer Science and Business Media LLC
Reference44 articles.
1. Abdi H. Partial least squares regression and projection on latent structure regression (PLS regression). Wiley Interdiscip Rev: Comput Stat. 2010;2(1):97–106.
2. Abdikerimova S, Feng R. Peer-to-peer multi-risk insurance and mutual aid. Eur J Oper Res. 2022;299(2):735–49.
3. Aeron-Thomas A. The role of the motor insurance industry in preventing and compensating road casualties. Scoping Study Final Report. 2002.
4. Allen EA, Erhardt EB, Damaraju E, Gruner W, Segall JM, Silva RF, Havlicek M, Rachakonda S, Fries J, Kalyanam R, Michael AM. A baseline for the multivariate comparison of resting-state networks. Front Syst Neurosci. 2011;5:2.
5. Amoo GK. Going the extra mile: the challenge of providing insurance cover for loss of use of motor vehicle in a developing economy. 2002. A dissertation summated to Chartered Insurance Institute.