Modelling Road Traffic Accident Costs in Developing Countries
Keywords:Mathematical Model, Road Traffic Accident Costs, Developing Countries, Gross National Income Loss, Extreme Risk, Road Safety
Researchers have been yearning for a mathematical model of costing road traffic accidents due to the shortcomings of the existing methods. This research is aimed at developing the mathematical model for road traffic accident costs in developing countries. To achieve the aim, basic road traffic accident cost determinants (death rate, interest rate, Gross National Income, life expectancy, average age at first marriage, literacy and population) were sourced from the websites of World Bank, World Health Organization (WHO), International Statistical Institute (ISI), International Monetary Fund (IMF), United Nations (UN), Central Intelligence Agency (CIA), Google, Yahoo and Ask. Then, some of the basic accident cost determinants were used to drive Gross National Income loss, cost of casualty by life insurance approach, amount of road safety and accident severity number using a developed program written in FORTRAN 77 language. With the derived parameters and the remaining basic parameters, goodness of fit was carried out using Easyfit 5.5 professional to choose the relevant explanatory variables for the response variable and to obtain the appropriate regression analysis for developing the model. Log – logistic regression analysis was used to develop the model which expresses transformed Gross National Income loss (logit) in terms of life expectancy (years), amount of road safety and accident severity number (with no unit). When tested, the model was not able to predict the Gross National Income loss of some developing countries through logit transformation formula of its response variable and therefore a complementary model was developed using Graph 220.127.116.114 to obtain unlimited logit transformation of the response variable. The complementary model gives the Gross National Income loss in dollars per year and it was checked against the existing methods for accuracy. Thereby, it was found out that the model is only statistically the same as the other methods of costing road traffic accident at no risk. However, the model is statistically the same as the human capital approach of costing road traffic accident even at an extreme risk of 42.5%. Therefore, the model could be used for decision making to invest in road safety of developing countries.
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