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CRTICAL EVALUATION OF INSTITUTIONAL QUALITY ON STANDARD OF
LIVING IN MIDDLE-INCOME SUB-SAHARA AFRICAN COUNTRIES (SSA)
BY
Stephen Akpo Ejuvbekpokpo (PhD)
Department of Economics, Delta State University
Abraka Nigeria.
stephen.akpo@delsu.edu.ng; steveuum@gmail.com
+2347065888235
Abstract
The write up of this article is about Critical evaluation of institutional quality on standard of
living in middle-income sub-Sahara African (SSA) countries. To my knowledge little has been done
to critically evaluate institutional quality on standard of living in middle-income sub-Sahara
African (SSA) countries.The challenges facing SSA especially the middle-income SSA countries
are enormous. These include weak institutions in terms of good governance, accountability and
transparency which are addressed in this paper. The objective of this paper is to address the role
of institutional quality on standard of living in those countries from 2013 to 2022. The research
used secondary data sourced from World Bank governance indicators and transparency
international. The method of analysis adopted is panel data using the panel corrected standard
error (PCSE) and generalized method of moments (GMM). The analysis produced apriori
expectation. The findings are in line with theory. Both static and dynamic methods on institutional
quality and standard of living indicates that most of the countries examined shows inconclusive
result in terms of rule of law, corruption, bureaucratic quality and property rights. As a result the
study recommends policies to address these critical issues to improve economic activities in the
middle-income SSA countries. In addition, rule of law need to be implemented to the later and
educational sector given utmost priority to upgrades standard of living in middle-income sub-
Sahara African (SSA).
Keywords: Institutional Quality, Standard of living, Corruption, Rule of law, Property
rights, Panel data, GMM, SSA countries.
JEL Classification: O15, O43, O5
INTRODUCTION
Standard of living (PCY) is theoretically the amount of money that each individual gets in that
particular country. It is a measure that results from GDP divided by the size of the nation’s
overall population or GDP per capita. Income per capita is used as a means of evaluating the
living conditions and quality of life in different areas. The GDP per capita is especially useful
when comparing one country to another because it shows the relative performance of the
countries. A rise in GDP per capita signals growth in the economy (Todaro, 2011). This concept
Contents lists available at Science Direct
Journal of Development Economics
Journal home page:https://www.sciencedirect.com/journal/journal-of-development-economics
Volume No. 172
2
is published by the World Bank governance indicator. Previous studies on institutional quality
and economic growth, which represents standard of living was carried out by Prochniak (2013);
Efendic and Pugh (2015); Lobsiger and Zahner (2012); Green and Moser (2013) and Neugarten
(2015).
Specifically institutional quality as a concept in economics has been particularly influenced by the
work of Douglass North, a Nobel Laureate in economics. According to North (1990) and others.
Institutions are manmade rules that are imposed to guide and evaluate the attitude and behavior
of people and also to determine the level of their interaction to ascertain the degree of
commitment to the growth and development of the society. Furthermore, they are made up of
formal constraints such as laws, regulation and constitutions and informal constraints such as
nooms, taboos, values, customs, and traditions of any given cultural background.
In other words, institutions are structured within which human interactions take place either
positively or otherwise. It is important to note that macroeconomic performance is influenced
by institutional quality variables such as rule of law, property rights, corruption, and bureaucratic
quality (Barro & Lee, 2013). Institutional failure occurs when the structure of state apparatus
itself causes rather than reduce uncertainty (Acemoglu, Gallego & Robinson, 2014). In the African
context, institutional quality is not well organized or entrenched, in terms of implementing
proper rule of law, control of inflation and bureaucratic quality. All these affect the standard of
human development in the region to the extent that, there is poor allocation of fund to human
capital development. Also, due to high level of corruption, funds being allocated to educational
sector are not judiciously utilized to develop the human resources as proposed. This is a common
practice in SSA countries, which negates the ideal socio-political and economic environment
where economic activities could strive (Barro & Lee, 2013).
On the other hand, stable and strong institutions are the reverse of the weak. This means that
strong institutions entail an economic development, an environment with formidable and
reliable institutional indices that bring about human development, doing business free from
government renege process (Acemoglu & Robinson, 2012). In a broad sense, institutions are
expected to facilitate the generation of ideas, define property rights and contracts, stimulate
innovation, lower transaction costs, correct government failure, reduce uncertainty, foster
efficiency and enhance economic performance (Acemoglu, Gallego & Robinson, 2014; Barro &
Lee, 2013)
EMPERICAL STUDIES ON STANDARD OF LIVING
Theoretical and Empirical studies on Institutional Quality and Standard of Living
It is important to note that Neugarten (2015) opined that there are six indicators to measure the
standard of living of the people in the country: GDP per capita (in PPP USD), telephone lines,
television sets, radios, electric power consumption per capita, and energy use per capita. Over
the years, there seems to be a consensus that these indicators are paramount to the goals and
aspirations of countries. Gyimah-Brempong (2002), using a sample of African countries and
corruption to proxy for institutional quality, finds that corruption affects economic growth
3
indirectly through decreased investment in physical capital and in education. He also finds
corruption to be positively correlated with income inequality.
For instance, Kurtz and Schrank (2007), demonstrate that countries receive high score in World
Governance Indicator (WGI) for having high standard of living and not necessarily for improving
the quality of institutions. They find that the bureaucratic quality indicator in the WGI is
significantly related to two year average growth rates prior to the date of the institutional quality.
However, their finding is disputed by Kaufmann et al., (2007) who show that minor changes to
Kurtz and Schrank’s empirical specification completely invalidate their results. Kaufmann et al.
point out that after controlling for long-run economic performance of countries; the short-term
growth that Kurtz and Schrank claim is driving a corona effect which is no longer significant.
In another scenario, widespread and rather outcomes oriented measures of institutional quality
are the indicators of political instability that Alesina, Ozlar, Roubini and Swagel (1996), and Barro
and Sala-I-Martin (1994) employed in their seminal growth studies. Investigated the relationship
between indicators of political instability and economic growth where political instability is
interpreted as adverse influences on property rights. For a sample of 78 countries in the period
1960-1985, they used the objective measure which involves counting the number of civil wars,
coups, strikes and political assassination and found that these variables are negatively and
significantly associated with growth rates.
Also, Alesina, Ozler, Roubini, and Swagel (1996) analysed the relationship between political
instability (defined as the propensity of government collapse and per capita GDP growth. For a
sample of 113 countries in the period 1950-1982, using the number of assassinations, death from
mass violence and coups as the basis for their indicator, they found that their political instability
variable represents a negative and statistically coefficient in their growth model.
Furthermore, Mauro (1995) used data for 67 countries and tested three variables constructed
from business international indicators based on perceptions drawn from business international
overseas correspondents: corruption, a bureaucratic efficiency index and, a political stability
index. He focused on the effect of corruption on growth and found it to be negatively related to
growth over the period of 1960-1985. He also analysed the effects of a perception-based index
of bureaucratic efficiency as well as that of political stability and found them to be positively and
significantly related to growth.
Most prominent among these researchers on composite indicators are Campos and Nugent
(1999), Kaufmann et al. (1999) These researchers basically suggest the results of earlier studies
on the effect of governance on economic growth. For example, Campos (2000) uses OLS from
data covering 25 Central and Eastern European and former Soviet Union countries from 1989 to
1997. He found that governance, especially the rule of law is positively related to growth in the
transitional countries. This study has been supported by a considerable number of other studies
using data sets (Dallor & Kraay, 2003; Naude, 2004; Fayissa & Nshiah, 2013).
Fayissa and Nshiah (2013) employ quartile regression to investigate whether the impact of good
institutional quality on economic growth depends on the conditional economic income
distribution of countries. This study employs panel data for 28 SSA countries for the years 1990-
4
2004. The results of the alternative models suggest that institutional quality has a positive and
significant impact on growth, regardless of the proxy for institutional quality. A common
characteristic of the conclusions reached by all of these studies is that, institutional quality
variables such as rule of law corruption, bureaucratic quality, the stability of property rights and
democracy are directly correlated with economic growth.
Nevertheless, Green and Moser (2013) investigated the role of property rights institutions on
economic growth at a local level with two rounds of a unique dataset covering almost all the
Madagascar at a level akin to countries in the USA. It was discovered that growth in enterprises
developed strengthens formal property rights, supporting the notion that the causality between
institutions and growth runs both ways even at a low administrative level.
In addition, Efendic and Pugh (2015) used dynamic panel analysis to investigate the relationship
between institutional improvement and economic performance in 29 transition countries and
the analysis covers the period 1992–2007. They found that per capita GDP is determined by the
entire history of institutional reform under transition and that, conditional on this history, per
capita GDP adjusts to recent institutional changes.
Knowles and Owen (2008) opine that people in most developing countries suffer from poorer
health and live shorter lives, on average, than people in rich countries. Accordingly, in 2005,
average life expectancy at birth in Japan was 82 years compared to 35 years in Botswana and
Lesotho (Knowles & Owen, 2008). It is important to note that, in the health development quality
dimension, there are five indicators. The indicators are the following: Life expectancy at birth,
Infant mortality rate, Physicians, Immunization of children, and CO2 emissions per capita. The CO2
indicator shows an environmental aspect, which may lead to degradation of health conditions.
A few existing studies do consider a role for informal institutions or social capital in explaining
cross-country differences in income or health status. Tabellini (2007) analyses the effect of
culture on per capita output across regions in European countries, but his paper also includes
some cross-country regressions examining relationships between different indicators of culture
and governance, that is formal institutions. Tabellini’s measure of culture includes survey-based
information on the extent of trust, whether people believe children should be taught to respect
others, whether they should be taught to be obedient. Tabellini’s paper makes a strong case for
the relevance of values and behavioural norms in explaining different experiences of economic
development, but it does not adopt a deep determinants perspective, as neither formal
institutions nor geographical characteristics are included as regressors explaining regional per
capita income.
However, the approach adopted Efendic and Pugh (2015) is the most closely related to Knowles
and Owen (2008), in that the explanatory variables in their model include a measure of formal
institutions (covering bureaucratic quality, law and order, and corruption), social capital
(measured as generalized trust) and their multiplicative interaction. Nevertheless, the focus of
their cross-country empirical analysis is on explaining the growth of GDP per capita (from 1995-
2005) or the rate of investment, not health status.
5
Also, rather than using a deep determinants approach; they fit a Barro-type growth regression
that includes base-period income, investment prices and human capital proxied by life
expectancy (Zak & Knack, 2001). Their results imply that formal institutions and trust are
substitutes in terms of enhancing growth; consequently, social capital has a stronger positive
effect on growth for countries with lower quality formal institutions. There is also a more
extensive literature, reviewed in Islam, Merlo, Kawachi, Lindstrom and Gerdtham (2006), that
examines the effect of social capital across countries on health indicators, including life
expectancy. These studies normally do not control for formal institutions and geography; instead,
proximate determinants, such as immunization rates, the number of doctors and income per
capita, are often included as control variables. Also, Lazarova and Mosca (2006) used a sample of
112 countries (which is representative of a wide range of absolute income governance indicators
from World Bank governance indicator for the years 1996, 1998 and, 2000. Using OLS, Lazarova
and Mosca found that institutional quality has an effect on life expectancy.
In accordance with the previous studies, Eyyup (2013) examines the impact of institutional
quality on life expectancy at birth that will bring about economic growth for 21 OECD countries
using panel data for the period of 1970-2010 in the context of panel cointegration and causality
tests. Two different model specifications are considered for this purpose. The variable of life
expectancy which serve as an indicator of health and real per capita gross domestic product as
an indicator of standard of living. While the independent variables are, real exports, real fixed
capital and energy use per capita. Using Maddala-Wu (1999) cointegration tests, it indicates that
there is a long-run relationship between the variables.
In order to deal with panel OLS, Pedroni dynamic OLS (DOLS) and fully modified OLS (FMOLS)
techniques, employed by Maddala-Wu (1999) the estimated coefficient for life expectancy is
found positive and statistically significant. Also, the results of panel Granger causality tests based
on panel vector autoregressive (VAR) models indicates that there is a unidirectional causality
running from life expectancy to real per capita GDP. Thus, income per capita, education, and
public access to health care improve life expectancy at birth, whereas income inequality has an
adverse effect on this measure of health. According to Eyyup (2013), the failed national and
international programs of economic and structural adjustment policies that have not addressed
the crucial issue of political structure are testimony to the importance of freedom and democracy
for human well-being and health status.
Eyyup (2013; Ejuvbekpokpo,2022)) asserted that healthcare and standard of living
administration explains cross-country differences in levels and growth rates of income. In this
paper, panel data analysis in the content of cointegration and causality relationship was provided
for 21 OECD countries ranging from 1990-2010. The data was derived from World Bank’s World
development indicators, 2012. Also, panel cointegration test developed by Maddala and Wu
(1999) was used. The results show that life expectancy has a positive and statically significant
effect on real per capita GDP. Also the works of Ejedegba, (2022) confirm this assertion.
METHODOLOGY AND MODEL SPECIFICATION
6
In terms of methodology and to avoid the potential difficulties of endogeneity and serial
correlation are controlled by adopting both the static and dynamic panel data analysis. In other
words, unlike previous studies that used fixed and random effect panel analysis only. Here the
study used both fixed and random with generalised method of moments (GMM). All these serve
as my contribution to the existing body of knowledge.
Based on the explanation above, this paper adapted the equation used by Klomp and Haan (2013)
with modification by introducing other variables such as standard of living. In their work, they
estimated the relationship between political factors and human capital. In this work, institutional
quality and standard of living served as both the independent and dependent variables.xxx
Additionally, instrumental variable are inclusive in the models to burst the efficiency of the
results and they are; government expenditure, school expenditure, health expenditure,
infrastructural facilities and labour force. Accordingly, structural equations are used as a
statistical technique to analyse the dimensions of a latent construct and analyse the dependence
structure (Dreher, Kotsogiannis & McCorriston, 2007). Structural equation model is characterized
by two basic components; the measurement model, which allows using several variables (or
indicators) for a single latent independent to dependent variable and the structural model, which
relates independent to dependent variables.
Based on the information and explanation, Klomp and Haan (2013) and to come up with better
measures that include more information and to determine whether human capital and political
institutions have a multidimensional character stated in their model as thus,
[1.0]
iiiiijjli XHC
Political
0
where, HC1i is a measure for human capital (advanced or basic) of country j. As far as this work is
concerned is replaced with standard of living the dependent variable in the paper. While political
variable is replaced with institutional variables like rule of law, corruption, bureaucratic quality
and property rights which also formed the independent variables with control variables.
Nevertheless, this study used both static and dynamic panel data analysis. These include random
and fixed effects and the generalized method of moments. The GMM estimator is developed by
Anderson and Hsiao (1981), Griliches and Hausman (1986), Hsiao (2003), Holtz-Eakin et al. (1988),
Arellano and Bond (1991), Arellano and Bover (1995) and Blundell and Bond (1988) all for
dynamic models of panel data.
The models are formally stated in conjunction with the objectives of the research as shown in
Equation [1.1] for static models and Equation [1.2] Equation [1.3] for dynamic models
respectively. This is consistent with Hsiao (2006) and Poveda, (2012). However both the static
and dynamic structured equations are stated as follows. The structured equations for the static
panel data can be specified as follows
[1.1]
itittitititit INFRGEPRIBQCIRLIPCY 7654321
itit
LAB
8
7
While the dynamic equations are also stated as follows;
[1.2]
itititit
itititititiit
LABINFRGE
PRIBQCIRLIPCYPCY
876
5432111
Where,
PCY = Per Capita Income (Per Capita GDP USD)
RLI = Rule of Law (%)
CI = Corruption (%)
BQ = Bureaucratic Quality (%)
PRI = Property Right (%)
GE = Government Expenditure (Percentage of GDP)
LAB = Labour Force (working age population over total population)
INFR = Infrastructural Facilities (Percentage of GDP)
Discussion on Institutional Quality and Standard of Living in Lower Middle - Income
Countries
The result reveals that RLI, is statistically significant with negative coefficient at five percent level
of significance. In other words, a one percent increases in the regulation of the rule of law index
in the society on average leads to 42.88 percent decrease on the standard of living of the people in
the selected lower middle-income SSA countries. This finding disagrees with human development
theory and supported by previous studies such as Efendic and Pugh (2015) and Carlos (2016).
They opined that improvements in institutions can lead to higher income per capita, which is also
observed in the contemporaneous correlation among the institutional variables. However, CI is
statistically insignificant and is negatively related to PCY in the selected countries of the region.
Table 1.10
Institutional Quality and Standard of Living in Lower Middle-Income Countries: Fixed
Effect
Variable
Coefficient
Standard Error
t-value
Prob>| t |
Constant
83.881
121.321
6.86
0.000*
RLI
-42.882
11.846
3.62
0.000*
CI
-27.851
20.910
-1.33
0.184
BQI
11.550
23.576
4.86
0.000*
PRI
9. 420
34.550
-2.74
0.007*
GE
7.485
11.592
0.65
0.519
LAB
-21.123
16.936
-1.28
0.202
INFR
0.751
0.110
6.84
0.000*
8
Table 1.10 Continuation
Diagnostic statistics:
R2: Within
0.401
Between
0.047
Overall
0.017
Wald
2
7
= 15.390
Prob (
2
)
0.000
Multicollinearity
1.30
Heteroskedasticity
30910.62
Serial Correlation
95.33
F–statistics F(20, 161) = 242.32
GMM Results on Institutional Quality and Standard of Living in Lower Middle-Income
Variable
Coefficient
Standard Error
z-value
Prob>| z |
Constant
26.349
98.291
2.68
0.007*
RLI
-5.416
1.827
1.33
0.018*
CI
-30.315
60.973
2.25
0.025*
BQI
-23.291
44.782
-5.33
0.000*
PRI
-18.452
111.538
-1.07
0.053**
GE
-16.381
11.568
-1.99
0.046*
LAB
-291.571
13.848
-22.44
0.000*
INFR
0.216
0.020
11.35
0.000*
Diagnostic Statistics:
Wald
2
8
= 10847.070
Prob (
2
)
0.000
Sargan test
2
34
= 13.702
Prob>
2
=
0.984
Arellano-Bond
Order
Z
P>Z
1. -1.437 0.151
2. -0.602 0.547
9
Note: * and ** indicates significance at 5 and 10 percent level of significance
However, BQI is statistically significant with positive coefficient at five percent level of
significance. This implies that one percent increase in BQI implementation on average leads to
11.55 percent increase on standard of living of the people in the region generally. This finding is
in line with human development theory and is supported by previous studies among who is Fayissa
and Nshiah (2013), uses OLS from data covering 25 central and Eastern European and former
Soviet Union countries from 1989 to 1997. He found that institutional qualities especially rule of
law and bureaucratic qualities are positively related to growth in the transitional countries.
In addition, property right is statistically significant at five percent with positive coefficient. In
other words, a one percent increases in proper implementation of property right in the selected
countries on average leads to 9.42 percent increase on standard of living of the people. This finding
is consistent with theory and is supported by previous research such as Hansen (2013), using a
cross-country panel data analysis, found that a one percent rise in life expectancy at birth increases
the years of schooling by 3.5 percent, which can influence income positively. Similarly, the
instrumental variables such as GE and LAB are statistically insignificant, is only INFR that is
statistically significant at one percent. This shows that these variables are related to standard of
living in one way or the other in lower middle-income SSA countries.
In another scenario, after obtaining an appropriate model through Hausman test which is FEM as
shown from the computation, then various diagnostic checks were performed and the results are
also shown on Table 1.10. As usual these include the results of multicollinearity, heteroscedasticity
and autocorrelation. However, the post estimation has shown that the model has no issue of
heteroscedasticity and autocorrelation.
This study further proceeded to apply GMM for robustness check as shown in Table 1.10 and the
interpretation follows thus, RLI is statistically significant at five percent level of significance but
with negative coefficient.. It means that one percent increase in RLI, on average leads to 5.42
percent decrease on standard of living within the area of this study. Therefore the non-
implementation of rule of law policy influences the standard of living of the people negatively.
This result disagrees with human development theory. Apart from that, the result is in line with
previous studies Prochniak (2013). He investigated the extent to which the institutional
environment is responsible for worldwide differences in economic development. The analysis
covers 153 countries and the period 1994 to 2009. The empirical analysis confirms a large positive
impact of the quality of the institutional environment on the level of economic development by
laying much emphasis on rule of law.
10
Also, corruption index exhibits a negative relationship and is statistically significant at five percent
level of significance with standard of living in the selected countries in the region. In other words,
a one percent increase in corruption index (control of corruption) will on average leads to 30.32
percent decrease on standard of living of the people. This result is in disagreement with human
development theory. The results of this research are in line with the study of (Lambsdorff, 2008;
Kuniedia, Okada & Shibata, 2011 and Popsilaghi and Mutu, 2013). They observed from their
findings that pervasive corruption in an economy can reinforce existing economic and social
inequalities as well as intensify the depth of poverty and reduce the access by the vulnerable
segments of society to the basic needs of life.
In addition, bureaucratic quality index is statistically significant at five percent but the coefficient
is negatively related to standard of living. This implies that increase in effective bureaucratic
qualities in these countries on average leads to 23.29 percent decrease on the level of standard of
living in SSA countries. This result is not in line with human development theory. In another
scenario, the issue of property rights in this circumstance, the variable, shows that it is statistically
significant at one percent but with negative sign. In other words, one percent increase in property
right in lower middle-income countries on average leads to -18.45 percent decreases on standard
of living within the research area. That is to say that as the level of the freedom of property rights
increases the standard of living of the people among the countries of this study decreases. This
result is not in consonance with human development theory. Also is in line with previous studies
(Elisa and Peluso, 2011 and Lobsiger and Zahner, 2012). They assert that the ability to accumulate
private property and wealth is fundamental bedrock which motivates investors and workers in a
market economy.
Nevertheless, the control variables are statistically significant but with negative coefficient. In
other words, the instrumental variable contributes little or nothing to the standard of living of the
people. The standard of living model passed the Sargan test of over identifying restrictions after
two step was computed. The χ2 value of the Sargan test is 13.702, and the probability χ2 is 0.984.
This means that the p-value of the test is greater than 0.05, this shows that the instruments are
valid. Also, the Arellano-Bond serial autocorrelation test was also not significant. Here, first order
and second order are -1.437 corresponds to 0.151 and -0.602 and 0.547 respectively. This shows
that there is no autocorrelation in the model as illustrated in Table 1.10
Conclusion and Recommendation
This paper provides empirical evidence between institutional quality and standard of living
characterizing the SSA countries. Using static and dynamic panel data analysis, the researcher
found that institutional variables like rule of law, corruption index, bureaucratic quality index and
property rights index exhibits significant relationship with standard of living in SSA region.
Authors have acknowledged that better institutions tend to be associated with higher rates of
economic growth. It is important to know that institutions play a key role in setting up the path of
standard of living and capital accumulation. This fosters technology and output growth.
Productivity then contributes to increase in returns on human capital accumulation and induces
non-educated workers to invest in education and become educated. This generates a self-
perpetuating accumulation mechanism. This self-perpetuating mechanism can be enhanced by
improving institutions. In addition, the acceleration in the increase in standard of living also
generates further improvements in structural institutions like rule of law, corruption index,
bureaucratic quality and property rights as far as this study reveals.
From the forgoing discussion, it is recommended that as far as standard of living is concerned, it
encompasses good level of literacy, innumeracy; health and income which correlate with standard
11
of living levels in other advanced countries of the world. Therefore, economic growth should be
pursued at every level of human society; individual level, community level, organizational level,
national level, regional level and global level for the fulfillment of standard of living ethics in SSA
countries in particular and the world in general. This can be achieved through efficient and
transparent institutional quality ethics. For future research concerning the topic of the institutional
quality and standard of living, it is necessary to focus on country specific among others. Also
disaggregate the region into lower middle-income and low-income for comprehensive
investigation to assess the extent of poverty in the region.
Stephen Akpo Ejuvbekpokpo is a PhD holder in Economics is currently a Lecturer 1 at
Economics Department, Faculty of the Social Sciences Delta State University, Abraka Nigeria. He
teaches Micro and Macro Economics and Development Economics. His research interests are
focused on Institutional and Development Economics with particular emphasis on institutional
Quality, Human Development analysis and Poverty reduction analysis. He is a member of Nigerian
Economics Society (NES) and a member Institute of Personnel Management of Nigeria(IPMN).
ORCID: http://orcid.org/0000-0001-9611-5627
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