Likelihood of Insurance Coverage on Damages Due to Level of Insecurity in Nigeria: Logistic Modeling Approach

Orumie Ukamaka Cynthia (), Desmond Chekwube Bartholomew (), Chukwudi Paul Obite () and Kiwu Chizoba Lawrence ()

Financial Risk and Management Reviews, 2021, vol. 7, issue 1, 50-59

Abstract: Insurance serves as a protection against the unexpected and it is one of the most effective risk management tools that protect individuals from being bankrupt due to various contingencies. The binary logistic regression model approach was used to model the described dataset; the model so obtained was statistically significant. All the levels of education were statistically significant in predicting the odds of having insurance cover except for primary education level. Also, employment status and age were statistically significant in predicting the likelihood for insurance cover in Nigeria. The results showed that individuals who move from no formal education to obtain Higher education level are 21.66 times more likely to obtain insurance cover and individuals who move from no formal education to obtain Secondary education level are 2.63 times more likely to obtain insurance cover. The odd ratio is not significant for moving from no formal education to Primary education and therefore should not be interpreted. Further, individuals who move from being unemployed to being employed are more likely to obtain insurance cover. Education has the highest impact in predicting the likelihood for one to have insurance cover in Nigeria. This paper recommends overhauling of the educational system in order to revamp this sector.

Keywords: Insurance; Risk management; Binary logistic regression; Model; Likelihood test; Employment; Education (search for similar items in EconPapers)
Date: 2021
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