Education, Inequality and Earnings in Ghana
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Date
2018-10
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University Of Ghana
Abstract
This thesis uses the fifth and sixth rounds of the Ghana Living Standards Survey (GLSS)
conducted in 2005-2006 and 2012-2013, respectively, to examine the themes of education,
inequality and earnings in Ghana. Three key objectives are pursued. The first objective is to
assess how educational attainment, measured by the average years of schooling, relates to
inequality in education. The second objective is to examine how education influences
inequality in earnings through an assessment of the heterogeneous returns to education. The
final objective is to provide an analysis of the effect of educational mismatch (over- and under
education) on earnings and the return to education. Consistent with these objectives, this thesis
is organised into three empirical chapters.
The first chapter examines the nature of the relationship between educational attainment in the
form of average years of schooling and the various measures of inequality in educational
attainment based on the educational Kuznets hypothesis. By employing a pseudo-panel
estimation approach, the study finds evidence of a non-linear relationship between the mean
years of schooling and educational inequality with a threshold occurring around nine years of
education. The results suggest that advances in educational attainment may not necessarily be
associated with a reduction in educational inequality in Ghana, but may increase it depending
on where the increase occurs. That is, while education expansion from the lowest percentiles
of the educational attainment distribution up to the median is found to be associated with
declines in educational inequality, an expansion in the attainment of persons in the higher
percentiles is associated with a rise in educational inequality. Also, increases in the proportion
of people with secondary, post-secondary and tertiary education were found to be associated
with rising educational inequality in absolute terms over the period covered by the analysis.
Public policy should, therefore, be focused on increasing educational attainment particularly at
the basic education level given the benefits of increasing human capital and making its
distribution more equal, as rising inequality in educational attainment has potentially adverse
consequences for economic growth and income inequality.
The second chapter assesses the heterogeneous returns to education across individual income
groups within the human capital framework, given the implications of such patterns for the
inequality-reducing role of education. The analysis is conducted within the operationalised
sectors of employment: the public, formal private, self-employment and agriculture. Recent
studies on Ghana that have assessed whether there exist variations from the mean returns to
schooling have resulted in mixed outcomes. While some studies have found variations from
the mean to exist with the returns to education being highest at the top decile of the earnings
distribution and declining down the distribution, others have found the returns to education to
be highest at the bottom decile of the earnings distribution and decreasing as one moves up the
earnings distribution.
Quantile regression is used to examine whether there is individual heterogeneity in the returns
to schooling. The results reveal that the impacts of education on earnings are not equal across
the conditional earnings distribution in the pooled employment sectors or the public and formal
private sectors of employment. However, such patterns are not observed for self-employment.
The returns to education are highest in the bottom decile of the earnings distribution and lowest
in the top decile for the public sector, indicative of the fact that within the sector, education has
a more equalising effect on earnings. For the formal private sector, returns are highest in top
earnings decile and significantly lower in the bottom earnings decile, giving credence to the
view that education may widen earnings inequality within the sector.
For the pooled employment sectors, although education appears to potentially widen the
earnings differences between workers with low-quality skills and those with high-quality skills
in the GLSS 5 (2005-06); however, it tends to bridge the earnings gap between the least
advantaged and the most advantaged in the GLSS 6 (2012-13). This change in the effect of
education along the conditional earnings distribution over the period of analysis may be
accounted for by a marked deficiency in the relative demand for highly skilled workers over
the period rather than a significant increase in the demand for low skilled workers in the
Ghanaian economy. Moreover, the observed uneven effects of education along the conditional
earnings profile strengthens the view that public policy must seek to improve upon the quality
of education, especially among the least advantaged.
The final chapter provides empirical evidence on the effect of educational mismatch on
earnings and the returns to education in Ghana. The study utilises a data-based criterion, being
the modal measure, to determine the educational requirements of jobs in the two-digit
classification for the GLSS 5 (2005-06) and the three-digit classification for the GLSS 6 (2012
13) of occupations. The analyses are conducted based on the economic sectors of employment
(i.e. agriculture, industry and service), the employment status (i.e. wage and self-employment)
and the institutional sectors of employment (i.e. public, formal private and informal sectors).
The results suggest that over- and under-education exists in Ghana’s labour markets. While in
the GLSS 5 (2005-06), 34 percent of workers are classified as over-educated and 9 percent
under-educated, in the GLSS 6 (2012-13), 42 percent and 12 percent of workers are classified
as over-and under-educated, respectively. The incidence of over- and under- education also
varies depending on the sector of employment. Furthermore, given other characteristics, over
educated workers tend to earn more while under-educated individuals tend to earn less than
University
their co-workers who possess the job-specific level of education. Nonetheless, the over
educated (under-educated) earn less (more) than workers with the same level of education and
engage in jobs for which they possess the job-specific level of schooling. The occurrence of
penalties associated with being over-educated may be indicative of a waste of resources
perhaps due to government subsidization. Government policy can, however, be directed at
enhancing skills utilization in enterprises. Some best practices include the adoption of
occupational forecasting models to anticipate future skills needs and supplies and the setting
up of sectoral and occupational skills councils to advise on policy.
Description
PhD.
Keywords
Education, Inequality, Earnings, Ghana