DEMOGRAPHIC FACTORS AS DETERMINANTS OF PRIVATE RETURNS TO INVESTMENT IN EDUCATION AMONG NIGERIAN WORKERS

ABSTRACT

Earlier studies on private returns to education in Nigeria neither gave adequate attention to the demographic factors nor covered the whole country. Some of them investigated the relationship among years of schooling, experience and earnings that covered one state, while others investigated some of the demographic factors that covered a few states. This study, therefore investigated the contributions of demographic factors to private returns to investment in education across the six geo-political zones in Nigeria. The study adopted the descriptive survey research design. Data were collected using the 2005 Labour Market Survey of the National Manpower Board covering 19,888 Nigerian workers: 7,032 with no formal education; 4,910 with primary school certificate; 4,873 with secondary school certificate; and 3,073 with first degree. Occupations were categorised into agriculture, information management, commerce and industry, education, health and safety, science and technology, legal and security, and others. Sectors of employment were grouped into private and public across the six national geopolitical zones. Nine research questions were answered and four hypotheses tested at 0.05 level of significance. Data were analysed using multiple regression and modified Mincerian earnings function. There was a significant difference in workers’ earnings across the geo-political zones (R=0.03, F (5, 19,882) =4.693, p< 0.05). These accounted for 3.4% of the variance in workers’ earnings. The Scheffe post-hoc analysis showed two homogeneous subsets, revealing that North-East, South-South, and South-West salary structures were almost the same, while South-South, South-West, North-Central, North-West, and South-East belonged to the second homogenous group. These results indicated that workers in the North East zone were the least paid, while South East zone workers received the highest earnings. All the independent variables significantly correlated with workers’ earnings (R=0.64, F (7, 8,021) =774.80, p< 0.05) and accounted for 40.3% of the variance in workers’ earnings. Each demographic factor correlated with workers’ earnings as follows: level of education (r=0.034); geo-political zone (r=0.034); occupation (r=0.018); and sector of employment (r=0.07). The following variables also predicted earning differentials: work iii experience (β =0.61); level of education (β = 0.37); and sector of employment (β = 0.02). Earning equations explained 82.9% of the variations in log earnings for all workers, implying that the higher the level of education of workers within the same sector, the higher the earnings. The model for female workers in the public sector explained 85.5% while that of male explained 84.8% of such variations. The slight difference in the male and female coefficients indicated little difference in earnings based on gender. The coefficients for the private sector workers showed that the model for the female explained 83.5% of the variations in log earnings, while that of the male explained 83.3% of the variations. Work experience, level of education and sector of employment are important determinants of private returns to investment in education. Private returns differed across the six geo-political zones in Nigeria. Employers of labour, particularly in the North-East zone should ensure that workers’ remunerations are commensurate with their level of education so as to minimise earning differentials.

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