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Financial Risk and Management Reviews

March 2021, Volume 7, 1, pp 50-59

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


Kiwu Chizoba Lawrence

Orumie Ukamaka Cynthia 1

Desmond Chekwube Bartholomew 2 ,

Chukwudi Paul Obite 2 Kiwu Chizoba Lawrence 2 
  1. Department of Mathematics and Statistics, University of Port Harcourt, Port Harcourt, Rivers State, Nigeria. 1

  2. Department of Statistics, Federal University of Technology Owerri, Owerri, Nigeria. 2

Pages: 50-59

DOI: 10.18488/journal.89.2021.71.50.59

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Article History:

Received: 12 July, 2021
Revised: 16 August, 2021
Accepted: 03 September, 2021
Published: 23 September, 2021


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.
Contribution/ Originality
The paper's primary contribution is finding that it assessed the impact of each level of the categorical predictor variables in predicting likelihood of insurance in Nigeria.


Insurance, Risk management, Binary logistic regression, Model, Likelihood test, Employment, Education.


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This study received no specific financial support.

Competing Interests:

The authors declare that they have no competing interests.


All authors contributed equally to the conception and design of the study.

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