Adaptation and Personalization, Vol. 2, Issue 1, Mar  2020, Pages 1-20; DOI:

An Application of Logistic Regression Analysis on the Old Pension Scheme and the New Contributory Pension Scheme in Borno State, Nigeria

Adaptation and Personalization, Vol. 2, Issue 1, Mar  2020, Pages 1-20.


Yahaya Abdullahi Musa 1* , Nicholas Pindar Dibal 1 , Ibrahim Adamu Usman 2

1 Department of Mathematical Sciences, University of Maiduguri, Maiduguri, Nigeria

2 Department of Mathematics Education, Umar Suleiman College of Education Gashua, Gashua, Nigeria

Received: 15 November 2019; Accepted: 20 December 2019; Published: 4 January 2020

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This paper determined the socioeconomic effects of contributory pension scheme on the wellbeing of retired federal civil servant in Borno State. The paper employed self-developed questionnaire to collect data from a simple random and a purposive sample of 162 respondents in the study area. One hundred and sixty-two (162) copies of questionnaires were administered but only one hundred and forty-two (142) copies were retrieved, making 88% return rate. The study employed inferential statistics for data analysis (Logistic regression analysis). The results of the study revealed that MPCR, SOR, AOR, NYR, FSR, VRSA and SSR were the determinants of prompt and timely payment of retirement benefits (lumpsum and monthly pension) at retirement and the new pension scheme has significantly contributed in addressing the problems inherent in the old pension schemes in the study area. The study recommended that Federal Government should also increase the pension of retirees from time to time because retirees’ expenses could increase at old age due to health challenges.


Logistic Regression, Odd Ratio, Socioeconomic, Pension, Retirees


© 2017 by the authors. Licensee International Technology and Science Press Limited. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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