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Journal ArticleDOI

Education, lifelong learning, inequality and financial access: evidence from African countries

02 Jan 2020-Contemporary social science (Routledge)-Vol. 15, Iss: 1, pp 7-25
TL;DR: In this article, the role of financial access in modulating the effect of education and lifelong learning on inequality in 48 African countries for the period 1996-2014 Lifelong learning is investigated.
Abstract: This study investigates the role of financial access in modulating the effect of education and lifelong learning on inequality in 48 African countries for the period 1996–2014 Lifelong learning is

Summary (1 min read)

Introduction

  • Lifelong learning on inequality in 48 African countries for the period 1996 to 2014.
  • Lifelong learning is conceived and measured as the combined knowledge gained from primary through tertiary education while the three educational indicators are: primary school enrolment; secondary school enrolment and tertiary school enrolment.
  • Inequality is also an important policy syndrome because though Africa has experienced more than 20 years of renewed economic prosperity, the number of extremely poor people has been steadily increasing (Asongu & Le Roux, 2017).
  • The policy relevance of financial development as opposed to educational enrolment builds the fact that financial access has a higher likelihood of being increased (given its current low rate), when compared with educational level which are reaching the maximum limit in some specific education levels like primary school enrolment.
  • Hence, the authors use principal component analysis to reduce these variables to a single composite indicator.

PSE SSE TSE

  • The following results can be established on the nexus between education levels, financial access and inclusive variables.
  • 1) The significance of estimated coefficients and the Wald statistics.
  • Not specifically applicable because the information criteria does not validate the model, also known as nsa.

Asiedu, E., 2014. “Does Foreign Aid in Education Promote Economic Growth? Evidence

  • “The Role of Knowledge in Economic Growth.
  • Department of Economic & Social Affairs, DESA Working Paper No. 143.

Dahlman, C. J., 2007. “The Challenge of the Knowledge Economy for Latin America”,

  • Globalization, Competitiveness and Governability Journal, 1(1): 18-46.
  • “What We Are Learning About Early Education in Sub-Saharan Africa”.the authors.the authors.
  • Principal Component Analysis (2 nd Ed.), New York: Springer.
  • “Financial Development and Dynamic Investment Behaviour: Evidence from Panel VAR” .The Quarterly Review of Economics and Finance, 46:190-210.

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1
Research Africa Network (RAN)
RAN Working Paper
WP/18/003
Education, Lifelong learning, Inequality and Financial access:
Evidence from African countries
Forthcoming: Contemporary Social Science
Vanessa S. Tchamyou
Faculty of Applied Economics,
Stadscampus, Prinsstraat13, 2000 Antwerp,
University of Antwerp, Belgium
E-mails:
simenvanessa@yahoo.com
Vanessa.SimenTchamyou@student.uantwerpen.be

2
2018 Research Africa Network WP/18/003
Research Department
Education, Lifelong learning, Inequality and Financial access: Evidence from African
countries
Vanessa S. Tchamyou
January 2018
Abstract
This study investigates the role of financial access in modulating the effect of education and
lifelong learning on inequality in 48 African countries for the period 1996 to 2014. Lifelong
learning is conceived and measured as the combined knowledge gained from primary through
tertiary education while the three educational indicators are: primary school enrolment;
secondary school enrolment and tertiary school enrolment. Financial development dynamics
are measured with financial system deposits (liquid liabilities), financial system activity
(credit) and financial system efficiency (deposits/credit). Three measures of inequality are
employed notably: the Gini coefficient; the Atkinson index and the Palma ratio. The
estimation strategy is based on Generalised Method of Moments. The following findings are
established. First, primary school enrolment interacts with all financial channels to exert
negative effects on the Gini index. Second, lifelong learning has negative net effects on the
Gini index through financial deposit and efficiency channels. Third, for the most part, the
other educational levels do not significantly influence inequality through financial access
channels. Policy implications are discussed.
JEL Classification: I28; I20; I30; O16; O55.
Keywords: Education; Lifelong Learning; Inequality; Financial development; Africa.

3
1. Introduction
The positioning of this inquiry is motivated by four important trends in academic and policy
circles, notably: increasing interest in knowledge economy for development; growing
inequality; limited financial access in Africa and gaps in the literature. These points are
chronologically discussed.
First, over the past decades, the economies of developed countries which have increasingly
moved towards the knowledge-based economies have relied less on traditional resources for
wealth creation like labour and capital (Dahlman, 2007; Chavula, 2010; Chandra &
Yokoyama, 2011; Asongu, 2017). Moreover, these attractive economies have heavily relied
on essential factors such as highly skilled labour; high technology industries and investment
in new technologies, which are essential components of the development of a knowledge-
based economy (AfDB, 2007). In addition to investing in high-end technologies, the creation
and dissemination of knowledge are also essential via universities (and research institutes) in
various fields and disciplines. Knowledge economy can be understood as a policy syndrome
in Africa because, compared to other regions of the world, the overall knowledge index of the
continent has been decreasing since the year 2000 (Anyanwu, 2012; Tchamyou, 2017a).
Second, despite two decades of economic prosperity, the number of people living in extreme
poverty has increased by more than 100 million between 1990 and 2012 in Africa. This is
why exclusive development remains a growing concern in Africa (Beegle et al., 2015).
According to the authors, it is projected that the concentration of the world's poorest people
will be in Africa. In addition, the Sustainable Development Goals (SDGs) or the post-2015
development program is in line with the thesis that a region with a good understanding of
inequalities will best articulate the policy agenda. Inequality is also an important policy
syndrome because though Africa has experienced more than 20 years of renewed economic
prosperity, the number of extremely poor people has been steadily increasing (Asongu & Le
Roux, 2017).
Third, when Africa is compared with other regions of the world, the continent is considerably
lagging behind in terms of financial development (World Bank, 2016). This is despite the
consensus that an expansion of financial access could provide investment opportunities for
companies and households which in the long run result in concrete development externalities
(Odhiambo, 2010, 2013). However, financial services can be facilitated by the improvement
of institutional infrastructure, market liberalization, and encouragement of innovation and
usage of technology (Claessens, 2006; Amavilah et al., 2017; Asongu et al., 2017).

4
Fourth, as far as we have reviewed, a study closest to our line of investigation is Asongu and
Tchamyou (2017) who have examined the impact of foreign aid on education and lifelong
learning in Africa. The authors have derived lifelong learning from a principal component
analysis of primary school enrolment, secondary school enrolment and tertiary school
enrolment. In addition, after exploring the existing literature on lifelong learning, we notice
that a comprehensive measure of lifelong learning in the African context is missing.
Moreover, To date only two macro level studies, i.e. the European Lifelong Learning
Indicators (ELLI) instrument developed by the EU (2010) and the Composite Learning Index
(CLI) instrument developed by the Canadian Council on Learning (undated.), have dealt with
this issue(Luo, 2015, p.19). The drawbacks of these two indicators in relation to the African
context are that: (i) the CLI is a Canadian indicator for progress in lifelong learning and the
ELLI refers exclusively to European countries. Hence, consistent with Asongu and Tchamyou
(2017), we use principal component analysis in order to measure of lifelong learning as the
combined knowledge acquired during the three stages of education.
The positioning of the study complements the existing literature which for the most part has
largely focused on the relationship between knowledge economy for development (Dahlman,
2007; Suh & Chen, 2007; World Bank, 2007; Chavula, 2010; Weber, 2011; Tchamyou,
2017a) and the finance-development nexus (for instance: Claessens, 2006; Beck et al., 2007;
Odhiambo, 2010, 2013).
In the light of the above, this inquiry contributes to the sparse literature on lifelong learning
(see fourth strand) by assessing how financial access (covered in the third strand) can
modulate the effect of education and lifelong learning (discussed in the first strand) in order to
reduce inequality (engaged in the second strand). To make this assessment, we use interactive
Generalized Method of Moments in which financial development is considered as a policy or
complementary variable. The policy relevance of financial development as opposed to
educational enrolment builds the fact that financial access has a higher likelihood of being
increased (given its current low rate), when compared with educational level which are
reaching the maximum limit in some specific education levels like primary school enrolment.
The remaining of the study is structured as follows. Section 2 covers data and methodology.
The empirical results and corresponding discussion are presented in Section 3 whereas
Section 4 concludes with implications and future research directions.

5
2. Data description and Estimation technique
2.1. Data description
We investigate a sample of 48 African countries for the period 1996 to 2014 in order to assess
the role of financial access in modulating the effect of education and lifelong learning on
income inequality. To fulfil this objective, we merge data from five main sources, namely: (i)
World Development Indicators (WDI) of the World Bank for education variables; (ii) World
Governance Indicators (WGI) of the World Bank for governance variables; (iii) the Financial
Development and Structure Database (FDSD) of the World Bank for financial access
variables; (iv) the Global Consumption and Income Project (GCIP) for inclusive variables and
(v) Principal Component Analysis for the lifelong learning index (Educatex). Governance
indicators are only available from the year 1996 and 2014 is the ending date due to constraints
in data availability.
Building on recent knowledge economy literature (Asongu & Tchamyou, 2017; Tchamyou,
2017a), lifelong learning is conceived and measured as the combined knowledge gained
during three main levels of education, namely: primary education, secondary education and
tertiary education. Hence, we use principal component analysis to reduce these variables to a
single composite indicator. These results in the derivation of a principal component are
(named “Educatex”) based on the underlying levels of formal education. Principal Component
Analysis (PCA) is a statistical method which consists of transforming a large set of correlated
variables into a small set of uncorrelated variables. These new variables account for the most
information contained in the original dataset. The information criteria used to determine the
number of common factors to keep
, are from Jolliffe (2002) and Kaiser (1974). Their
recommendation is to retain factors with an eigen value higher than one. As shown in Table 1,
the retained first principal component meets these criteria. The corresponding lifelong index
(or Educatex) consists of more than 78% of information contained in primary, secondary and
tertiary school enrolment.

Citations
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01 Jan 2002
TL;DR: This article investigated whether income inequality affects subsequent growth in a cross-country sample for 1965-90, using the models of Barro (1997), Bleaney and Nishiyama (2002) and Sachs and Warner (1997) with negative results.
Abstract: We investigate whether income inequality affects subsequent growth in a cross-country sample for 1965-90, using the models of Barro (1997), Bleaney and Nishiyama (2002) and Sachs and Warner (1997), with negative results. We then investigate the evolution of income inequality over the same period and its correlation with growth. The dominating feature is inequality convergence across countries. This convergence has been significantly faster amongst developed countries. Growth does not appear to influence the evolution of inequality over time. Outline

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TL;DR: In this article, the authors investigated the role of information and communication technology (ICT) on income inequality through financial development dynamics of depth (money supply and liquid liabilities), efficiency (at banking and financial system levels), activity (from banking and finance system perspectives) and size, in 48 African countries for the period 1996 to 2014.

447 citations


Cites methods from "Education, lifelong learning, inequ..."

  • ...Data description To investigate how ICT influences inequality through financial access, we are consistent with Tchamyou (2018a, 2018b) in combining four sources of data, namely: (i) the Global Consumption and Income Project (GCIP) for inclusive variables; (ii) the Financial Development and…...

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TL;DR: In this article, the role of information sharing in modulating the effect of financial access on income inequality in 48 African countries for the period 2004-2014 was examined, where information sharing is proxie...
Abstract: This study examines the role of information sharing in modulating the effect of financial access on income inequality in 48 African countries for the period 2004–2014. Information sharing is proxie...

358 citations


Cites background or methods from "Education, lifelong learning, inequ..."

  • ...Consistent with Tchamyou (2018) and Tchamyou et al. (2018), the Atkinson index employed in this study ranges from 0 to 1 as the Gini index....

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  • ...…extension of Arellano and Bover (1995) is preferred in this inquiry because it has been acknowledged to take into account crosssectional dependence and restrict instrument proliferation (or over-identification) (see Baltagi, 2008; Boateng, Asongu, Akamavi, & Tchamyou, 2018; Love & Zicchino, 2006)....

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Journal ArticleDOI
TL;DR: In this paper, the role of ICT in modulating the impact of education and lifelong learning on income inequality and economic growth was assessed in 48 African countries from 2004 to 2014.
Abstract: This study assesses the role of ICT in modulating the impact of education and lifelong learning on income inequality and economic growth. It focuses on a sample of 48 African countries from 2004 to 2014. The empirical evidence is based on the generalised method of moments (GMM). The following findings are established. First, mobile phone and internet each interact with primary school education to decrease income inequality. Second, all ICT indicators interact with secondary school education to exert a negative impact on the Gini index. Third, fixed broadband distinctly interacts with primary school education and lifelong learning to have a positive effect on economic growth. Fourth, ICT indicators do not significantly influence inequality and economic growth through tertiary school education and lifelong learning. These main findings are further substantiated. Policy implications are discussed.

211 citations

Posted Content
TL;DR: In this article, the authors investigated if financial development benefits from financial globalisation are questionable until certain thresholds of financial globalization are attained, and provided policy makers with levels of FDI (as percentage of GDP) that are required to start materialising financial development gains from financial globalization.
Abstract: Purpose - We investigate if financial development benefits from financial globalisation are questionable until certain thresholds of financial globalisation are attained. Design/methodology/approach - Financial globalisation is proxied with Net Foreign Direct Investment Inflows as a percentage of GDP (FDIgdp) whereas financial development entails dynamics of depth, efficiency, activity and size. The empirical evidence is based on; (i) data from 53 African countries for the period 2000-2011 and (ii) interactive Generalised Method of Moments with forward orthogonal deviations. Findings- The following findings are established. First, thresholds of FDIgdp from which financial globalisation increases money supply are 20.50 and 16.00 for below- and above-median sub-samples of financial globalisation respectively. Second, FDIgdp thresholds from which financial globalisation increases banking system activity and financial system activity for below-median sub-samples of financial globalisation are 13.81 and 13.29 respectively. Third, for financial size, there is evidence of: (i) a positive threshold of 21.30 in the full sample and (ii) consistent increasing returns without a modifying threshold for the above-median sub-sample. Practical implications- Evidence of a positive threshold implies that while the initial effect of financial globalisation on financial development is negative, there is a positive marginal effect, such that at a certain level of FDIgdp (or threshold), the overall effect of financial globalisation on the given financial development dynamic becomes positive. It follows that financial globalisation is both negative and positive for financial development, with a U-shaped relationship. Therefore the appropriate role of policy should neither be to stem the tide of capital flows nor to encourage them, but to understand what levels or thresholds of capital flows are required to benefit domestic financial development. Originality/value- We have extended the debate on initial or threshold conditions for the financial development benefits from financial globalisation by providing policy makers with levels of FDI (as percentage of GDP) that are required to start materialising financial development benefits from financial globalisation.

210 citations

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"Education, lifelong learning, inequ..." refers methods in this paper

  • ...Estimation technique: Generalised Method of Moments The estimation strategy adopted in this study is the two-step Generalised Method of Moments (GMM); an empirical strategy based on Roodman (2009a, 2009b) which is an extension of Arellano and Bover (1995)....

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Q1. What are the contributions in this paper?

This study investigates the role of financial access in modulating the effect of education and lifelong learning on inequality in 48 African countries for the period 1996 to 2014. The following findings are established. Policy implications are discussed.