Abstract
This study was conducted to predict insurance penetration rates in developing countries using discriminant analysis. Sixty (60)
developing countries sampled from four continents of the world were included in the study. The continents from which samples
were taken are Africa, Asia, Europe and the Americas. The dependent (categorical) variable of the research was insurance penetration
rate divided into low and high insurance penetration rates as the grouping variable. The predictor variables were gross premium
written, per capita GDP, literacy and unemployment rates. Research questions were formulated and hypotheses were drawn for the
purpose of determining which factors best discriminate groups in insurance penetration rates in developing countries. The study
made use of secondary data and SPSS version 22 was used for data analysis. Findings from the study indicate that gross premium
written is the most important discriminating variable followed by literacy rate, per capital GDP, and the least, being unemployment
rate
Ehiorobo, Osa Abraham. (2020) Discriminant Analysis of the Socio-Economic variables for predicting insurance penetration rates in developing Countries, Paradigms , Vol 14, Issue 1.
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