Management
p-ISSN: 2162-9374 e-ISSN: 2162-8416
2012; 2(4): 80-86
doi: 10.5923/j.mm.20120204.01
Dadson Awunyo-Vitor
Department of Agricultural Economics, Agribusiness and Extension, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Correspondence to: Dadson Awunyo-Vitor , Department of Agricultural Economics, Agribusiness and Extension, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
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Copyright © 2012 Scientific & Academic Publishing. All Rights Reserved.
This study examines the determinants of comprehensive motor insurance demand in Ghana. Data was collected from private car owners who were registering their vehicle at Driver and Vehicle Licensing Authority (DVLA) regional office in Kumasi. The study used logit model to assess factors influencing demand for comprehensive motor insurance. The results revealed that, demand for comprehensive motor insurance is significantly influenced by income, value of the vehicle, age of the vehicle, perception of the premium and claim procedure. The price of comprehensive motor insurance negatively affected the demand. Generally, wealthy people and individuals who used bank loan to purchase vehicle are more likely to purchase comprehensive motor insurance. In addition, claim procedures and the premium if perceived satisfactory would improve demand for comprehensive motor insurance. Hence to encourage demand for comprehensive motor insurance, insurance companies should target wealthy car owners and individual who use bank loan to purchase their vehicles. In addition insurance companies should reduce the time taken to process claims. Finally policy makers should place emphasis on designing comprehensive insurance with attractive premium. Results of this study will be useful to insurance companies in improving demand for comprehensive motor insurance.. The information would also benefit stakeholders in the insurance industry in Ghana especially policy makers as how to improve demand for comprehensive insurance in a sustainable manner.
Keywords: Insurance Demand, Comprehensive Motor Insurance, Driver And Vehicle Licensing Authority (DVLA) Kumasi Ghana
was assumed to be dependent on his assessment of the marginal cost and benefits associated with the use and non-use of comprehensive motor insurance respectively. Based on his assessment he may decide to purchase or not to purchase comprehensive motor insurance. In reality we do not observe this marginal cost and benefit hence dependent variable
. One can only observe whether respondent purchase comprehensive motor insurance or not through responses to question in the survey questionnaire. Hence another variable
is defined such that:
Thus vehicle owners’ decision to demand comprehensive motor insurance is dichotomous, involving two mutually exclusive alternatives. The car owner may either purchase comprehensive motor insurance or may not This yields a binary dependent variable
which takes on the value of 1 if car owner demand comprehensive motor insurance and 0 if he does not demand/ purchase comprehensive motor insurance which is influenced by a set of factors (
.
Comprises individual and household characteristics as well as institutional factors, the relationship between
and
can be presented as: ![]() | (1) |
and
are defined as above and
is a parameter of interest and
the disturbance term. Linear Probability Model (LPM), probit and logit models can be used to analyse qualitative response or binary choice models such as equation 1.The Linear Probability Model (LPM) can be used to analyse equation 1. However,[17],[7],[13] have noted that though LPM can be used to analyse binary models the estimated probability values can lie outside the normal 0-1 range. Hence probit and logit models are advantageous over LPM in that the probabilities are bound between 0 and 1. Moreover, these model best fits the non-linear relationship between the probability and explanatory variables. Due to the above shortcomings of the LPM, logit model was adopted for this study. ![]() | (2) |
is the probability that a car owner will make a particular choice or probability that a car owner would purchase comprehensive motor insurance
is the dependent variable (demand for comprehensive motor insurance)
is the threshold value of the dependent variable. The above equation
yields
where
is cumulative distribution function (cdf) assuming logistic distribution we have[17] .![]() | (3) |
of the logit model do not provide direct information about the effect of the changes in the explanatory variable and the probability of demand for comprehensive motor insurance. The relative effect of each explanatory variable on the likelihood that a car owner will demand comprehensive motor insurance is given by: ![]() | (4) |
is the mean dependent variable whose value is given in the logit result as ![]() | (5) |
Where
take value of 1 if a respondent purchase comprehensive motor insurance and zero if otherwise.
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