Heterogeneous Analysis of Institutional Quality on Economic Growth in SubSaharan Africa
Ojapinwa, Taiwo Victor
Department of Economics, University of Lagos, Lagos-Nigeria
ojapinwataiwo@gmail.com/+2348034172740
Abstract
The hierarchy of institutions hypothesis suggests that, various institutions exert different effects
on growth. Based on this argument, this study first disaggregates institutions into three economic, political and governance and analyzes their individual effects on growth. The study
further unbundles institutions into nine - rule of law, control of corruption, governance
effectiveness, voice and accountability, political stability/absence of terrorism, regulatory
quality, business freedom, private property right and economic freedom to separate their
individual effect and determine which of the institutions is most fundamental to growth. This
study employ a panel data set of 25 African countries over the period 1996-2015 based on
availability of data on the variables. Based on system Generalised Method of Moments (GMM),
the study reveals that economic institution is crucial to growth and rule of law is the most
fundamental to other institutions. Thus, rule of law is foundational to every other institution
especially as a good strategy in fighting corruption. This provides empirical support for
hierarchy of institution hypothesis in SSA with the lesson that, a one-size-fits-all institutional
reform strategy to promote growth may likely be counterproductive. Understanding which
institutions that is most fundamental to growth therefore requires studying detailed and welldefined institutions conditional on thorough unbundling. Thus, attaining economic growth in
Sub-Sahara Africa may therefore have a considerable bearing on vigorous judicial reforms
entrenched in speedy hearing and determination of cases with adequate sanctioning.
Keywords: unbundling, institutions, rule of law and economic growth.
JEL Code: O11, E02, O17, O43
1
Introduction
The last decade has recorded a growing acceptance of the idea that institutions are fundamental
to economic growth. Adam Smith (1776) eloquent articulates how society with well-organized
institution can influence investment behaviour, incentives and equilibrium growth rates in the
economy (Acemoglu & Robinson 2013). With quality institutions, people in the society can
secure returns on physical capital, human capital and new ideas which would lead to economic
progress (North 1990). Otherwise, people would invest in rent-seeking and economic stagnation
would ensue (Angeles 2010). Institutions are humanly devised rules that shape human interaction
(Acemoglu et al 2005). Different types of institutions can therefore depends on the domain they
structure (Braunfel 2016). Political institutions, for instance provide structure for the interplay of
political actors. They regulate how elites within the state interact and determine to what extent
the executive branch is subject to checks and balances. An independent judiciary is important for
strong rule of law, economic freedom, but may also act as elite that places certain constraints on
1
the executive branch of government. Of primary importance to economic outcomes are the
economic institutions in society such as the structure of property rights and the presence and
perfection of markets (Adam Smith 1776). Economic institutions are said to be important
because they have direct effect on growth unlike political institutions that have indirect effects
(Flachaire et al 2011). Although several empirical studies (Hall & Jones 1999, Aron 2000,
Rodrik et al. 2004, Nawaz et al 2014, Orayo 2016, Mullings 2018, Arshad 2019 among others)
have reported that institutions are fundamental cause of growth, but most of the studies are
without recourse to Acemoglu et al (2005) argument that different institutions exert different
impact on growth. The lumping of all institutions, despite the distinct role different institutions
play in growth process might have obscured World Bank (2002) question, which institution is
most fundamental for growth.
This study unbundle institutions into different parts based on Acemoglu et al (2005) hierarchy of
institutions hypothesis, which argue that, different institutions exert different impact on growth.
Institutions are first unbundle into three - economic, political and governance institutions and
further into nine (rule of law, control of corruption, governance effectiveness, voice and
accountability, political stability/absence of terrorism, regulatory quality, business freedom,
private property right and economic freedom). The unbundling of institutions addresses the
fundamental problem of lumping all institutions under the same subcategory, thereby answering
the question: which institutions matter most for growth, an issue which is said to be the most
controversial in the institution-growth literature. This study is crucial since it would lay to rest
the question, which institutional reform should SSA government embark upon first, given that
the subgroup is frantically embarking on various institutional reforms at the same time just to
achieve sustainable growth. This study is justified since it separates different effects of
institutions on growth and determines which one is most fundamental.
The rest of the paper is organized as follows: Section 2 reviews empirical literature. Section 3 is
the theoretical framework and 4 describes the methodology. Section 5 presents the results. In
Section 6, we deepen the discussion of the results by determine how closely related are the
institutional variables employed and section 7 concludes with policy implications.
2
Literature Review: From Proximate to Fundamental and to Unbundling
Traditional neoclassical growth models postulate that the main causes of economic growth are
exogenous physical capital accumulation and technological progress. In contrast, new growth
theory links the real cause of growth to knowledge capital, with a prominent role for knowledge
spillovers (Romer 1986, Grossman & Helpman 1991). The case between traditional versus new
growth has not received final judgment when researcher like North & Thomas (1973), Hall and
Jones (1999), Rodrik et al (2004), Acemoglu et al (2005) among others argue that, the
fundamental cause of growth may lie more on the Smith principle of properly-organized markets,
where quality institutions are front and center (Bruinshoofd 2016). Acemoglu et al (2005), for
instance argue that knowledge capital, physical capital and technology are just proximate causes
and that institutions are the fundamental causes of growth.
2
North (1981) defines institutions as the rule that shape incentive structure in the society which
may increase or hamper economic activities. Easterly (2013) builds on the case that, any type of
economic progress that is to be sustainable should be built on respect of the rights of the
individual in the society. Better performing institutions may improve growth by increasing the
volume of investment (Rodrik 2008). Alexiou, Tsaliki, and Osman, (2014) support the findings
that the quality of the institutional environment is highly fundamental in defining economic
prosperity for Sudanese economy. This result is not different from the study of Nguyen, Su, and
Nguyen (2018) that investigated the impacts of institutional quality on economic growth for 29
emerging economies over the 2002-2015 period based on System Generalized Method of
Moments (SGMM) estimators and found positive and significant impacts on economic growth.it
should be noted that many of the results above found positive effects although without focusing
on the channel effect of institutions on growth. This result is similar to that of Góes (2015), who
finds institutional quality to be crucial for real per capita income growth. Other studies like
Rodrik (2004), Hall & Jone (1999), Nawaz et al (2014), among others also favoured institutiongrowth enhancing argument.
Meanwhile studies like Arshad (2019) argues that the impact of institutions on growth might be
overstated and emphasized the importance of measuring their impact in general –rather than
specific effects, which also crucial for policy diagnosis. Arshad (2019) empirically, explores the
role of institutional quality on economic growth while focusing on the channel of foreign direct
investments. Using dataset of 104 countries based on a dynamic panel data analysis, the study
provides evidence that both FDI inflows and institutional quality cause stronger economic
growth. Similarly, Yushi and Borojo (2018) examine the impacts of quality of institutions on
growth through infrastructural channels. Yushi and Borojo (2018) specifically study institutions
in terms of border and transport efficiency, physical and communication infrastructure on overall
and intra-Africa trade. The study covers 44 African countries and their 173 trade partners for the
periods 2000–2014. While the findings disclose that the marginal effect of the quality of
institutions in terms of physical and communication infrastructure on trade flow lead to
increasing growth, the marginal effect of border and transport efficiency on trade decreases
growth. The investigation of Mullings (2018) into the existence and strength of the interaction
between institutional quality and globalization on real economic growth was also channel based.
Based on a panel dataset covering 82 countries and spanning 25 years (1986–2010), the author
employs dimensionality reduction techniques to identify key components of institutional quality:
the rule of law, civil liberties and political rights. The empirical results reveal that while
institutional quality robustly and positively affects growth, the direct effect of economic
globalization was not significant and the interaction effects, perhaps as a consequence, are muted
over the review period. Direct and interaction effects of institutional quality and economic
globalization on growth were, however, observed for the sub-sample of developing countries.
It should be noted that all the empirical studies above reported that institutions are fundamental
cause of growth, without recourse to Acemoglu et al (2005) argument that different institutions
exert different impact on growth. Braunfel (2016) argues that different effects of institutions
depend on the domain they structure. The lumping of all institutions, despite the distinct role
different institutions play in growth process also been queried by World Bank (2002). The world
3
bank have specifically argued that homogenous assumption of possible distinct effects of
institutions on growth might have obscured the different channels through which institutions
operate, an issue that is crucial to a better understanding of the fundamental cause of growth.
Acknowledging the importance of separating measures of institutions, Kormendi and Meguire
(1985), Helliwell (1992), Mauro (1995), Knack and Keefer (1997), Angeles (2011) focus on one
aspect of institutions and economic growth. Kormendi and Meguire (1985) specifically examine
the relationship between civil liberties growth and find positive relationship. The work of
Helliwell (1992) on democracy and growth finds negative relationship. Using ethnolinguistic
fractionalization as instrument to accounting for issue of endogeneity, Mauro (1995) discovers
that bureaucratic efficiency is fundamental to high investment and growth. Murphy et al. (1999),
Svensson (2005), Blattman (2012) all focus on issue related to corruption-growth nexus,
although with different conclusion. While Murphy et al. (1999) considers corruption as a
headwind, Svensson (2005) calls corruption a ‘grease the wheels’ instrument, or Blattman (2012)
‘speed money’. Easton and Walker (1997) on the other hand find that economic freedom is an
important explanatory variable for steady-state levels of income. Knack and Keefer (1997)
provide evidence on the relevance of property rights and economic growth for US. Using
evaluations of contract enforceability and risk of expropriation, the authors found that rates of
convergence to US level of incomes increase notably when property right variable was included
in growth regressions.
Flachaire et al (2011) observe that majority of the above studies either lumped different versions
of institutions into one or just focused on one aspect, hence unable to determine which institution
that is most fundamental. Flachaire et al (2011) focus on the question: which institution is more
important between political and economic. The study asserts that, political institutions set the
stage in which economic institutions and policies were implemented. Other studies that
attempted to distinguish various measures of institutions are Vijayaraghavan and Ward (2007)
and Orayo (2016). Vijayaraghavan and Ward (2007) incorporate three institutional variables
(security of property rights, governance size and political freedom) but concluded that security of
property rights and sizes of government are the most significant institutions that explain
variations growth rates. The work of Orayo (2016) considers six different institutional variables
based on World Bank governance indicators (voice and accountability, political stability and
absence of violence, government effectiveness, regulatory quality, rule of law and control of
corruption). Results from static analysis and ordinary least square (OLS) suggest that voice and
accountability is significant for the growth of Kenya and Uganda, quality of regulation for Kenya
and Tanzania and rule of law for Kenya.
It could be observed that, results from empirical studies either suggest collective classification of
institutions or focus on one aspect without separating different institutional effects on growth
which have left hanging the question; which institution is fundamental for growth? This study
attempts to bridge the literature-gap by unbundle institutions and determining which institutional
quality is most fundamental to growth, an aspect that has not received adequate attention in SSA,
4
where overarching vision and policy framework for accelerating growth are in dire need for
agenda 2030. This study is therefore unique.
3
Theoretical Framework: The Hierarchy of Institutions Hypothesis
The argument that different institutions exert different impact on growth provides a natural
starting point for separating the effects of distinct institutions on economic development. In their
pioneering work, Acemoglu et al (2005) point to the importance of distinguishing types of
institutions. They separate the role of contracting, economic institutions, and political institutions
in growth process. Economic institutions are said to be important because it gives the creator of
an idea certain exclusive rights over its creation; notably the right to benefit from its commercial
exploitation through a legal monopoly (Angele, 2010). These rights take mainly the form of
patents and copyrights. Without property rights, economic agents in the society may not have the
incentive to invest in physical or human capital or adopt more efficient technologies. People who
invest in new capital or in the case of intellectual property rights- new ideas expect to have the
freedom to use and profit from them as they deem it fit. If that condition is not met i.e if people
believe that their capital may be expropriated or their ideas stolen, they will refrain from making
those investments in the first place. The more likely it is that the sovereign will alter property
rights for his or her own benefit, the lower the expected returns from investment and the lower in
turn the incentive to invest (North & Weingast, 1989, p. 803).
Economic institutions are also believed to be the outcome of the interpretation, upholding, and
enforcement of laws by the legal system (Angele 2010). Where government decisions concern
the rule of law in the legal system, they can be seen as inputs into the production of property
rights. The rule of law, especially for developing countries, may be the area of economic
freedom that is most important in laying the foundations for economic growth, and in advanced
economies, deviations from the rule of law may be the first signs of serious problems that will
lead to economic decline (Feulner, 2013).
Political institutions are argued to define, for instance, constraints on the executive branch, rights
of political participation, and accountability through forms of election. The key characteristics of
political institutions are accountability, and checks and balances in the political decision-making
process. Stronger constraints improve the representation of different interest groups and
constrain despotic behavior, leading to policies that serve the majority, and induce long-term
stability and development (Acemoglu et al. 2014b). Political institutions regulate accountability
of politicians. While these rules sometimes affect the legal system, they cover a much broader
area (Braunfels, 2016). Where political decisions concern property laws and the organization of
the legal system, they can be seen as an input (into property rights productions). Legal scholars
have associated strong rule of law increased confidences in the judicial system (Feulner, 2013).
Cass (2001) argue that strong rule of law is a critical factor in empowering individuals, ending
discrimination, and enhancing competition that can guarantee sustainable growth.
5
In summary, the distinctive characteristic of institutions is that they regulate relations between
private parties, while economic institutions structure the top down relation by protecting citizens
from elites and powerful individuals. Political institutions define the interaction of elites at the
state level and the bottom up control of the state by citizens. Braunfels (2016) observes that, an
independent judiciary is important for good economic institutions, but may also act as certain
constraints on the executive branch of government. Although there are crucial differences among
different institutions, each of them importantly covers dimensions the other does not.
4
Methodology- Model Specification
To develop more satisfactory answer to question of why some countries are much richer than
others and why some countries grow much faster than others, Acemoglu et al (2005) argue that
differences in human capital, physical capital, and technology are only proximate factors, while
institutional factors are fundamental. In other to determine if the role institutional quality on
growth is fundamentals in SSA, our study follows the model specifications of Acemoglu et al
(2005) thus:
yi ,t   yi ,t 1  Insit    X i ,t   i ,t
1

IID  0. 2  , t
IID  0. 2  ,  i ,t IID  0. 2 
where i
all errors are independent of each other and among themselves.
i indexes countries, t denotes time, yi ,t is the growth rate of GDP per capita measured as
the log GDP growth per capita in year t. yi ,t 1 is the logarithm of GDP growth per capita
lagged one year (a method that helps fix dynamism issues) (Baltagi & Levin 1986). Insi,t
represents institutional quality index, Xi,t represents a matrix of control variables (investment,
growth in population, trade openness, human capital development, government consumption,
landlocked, legal formalization) and  i ,t is an error term.
As mentioned earlier many theoretical models show that institutions are likely endogenous
E ( i ,t / Ins)  0 . Accordingly, Glaeser et al (2004) argue that, it was the subsequent economic
development that allows South Korea to adopt a more inclusive institutional arrangement. This
therefore naturally set the stage for the possibility of endogeneity between institutions and
economic growth (Bruinshoofd, 2016). This is not different from the classical modernization
theories (Moore, 1966) that development positively affects rule of law through the rise of the
middle class and the demand for representation and protection from one another and the state
(Waggonner, 2016). Estimating model (1) directly would generate biased estimators (Arellano &
Bond 1991, Waggonner 2016). We handle this problem by introducing a set of instruments for
Ins . Then we can express (Ins)i,t in terms of these instruments Gi,t as equation (2)
6
 Ins i ,t  g  Gi ,t   i ,t
2
where, for simplicity, g(Gi,t ) is assumed to be parametric, say g (Gi ,t )  bGi ,t .
We choose lagged explanatory variables as instruments (Arellano & Bover 1995). Thus, (2) can
be written as
3
 Ins i,t  bzi,t 1  i,t
where
Z
represents
all
the
explanatory
variables
in
(1).
We
assume
that
E ( i ,t / Zi ,t 1,ui ,t )  E ( i ,t / ui ,t ) . It then follows that E ( i ,t / ui ,t )  0, since E   i ,t / Ins   0 . Hence,
one decomposed  i ,t into i (ui ,t )   i ,t , where i (ui ,t )  E ( i ,t / ui ,t ) and  i ,t   i ,t  E ( i ,t / ui ,t ) .
Equation (1) then becomes (4)
yi ,t   yi ,t 1   Ins i ,t    X i ,t  i  i ,t    i ,t
4
We replace the unobservable i ,t by the observable i ,t   Ins i ,t  Zi ,t 1 . Then equation (4)
becomes equation (5)
y
i ,t
  yi ,t 1   Ins i ,t    X i ,t  i  i ,t    i,t
5
Where the error  i,t   i ,t  i  i ,t   i  i ,t  .
One can use Arellano and Bover (1995) weighting matrix estimator to obtain consistent
estimation of parameters  and  in model (5), say ̂ and ˆ . Then substitute ̂ and ˆ into
the model (6)
y
i ,t
  yi ,t 1   Ins i ,t    X i ,t  i  i ,t    i,t
6
where  i,t denotes the new composite error term that accounts for the estimation of  and  .
One crucial argument of Acemoglu et al (2005) hierarchy of institutions hypothesis is that,
different institutions affect economic growth through different channels (Flachaire et al 2011,
Ivlevs & King 2015). Bettin and Zazzaro (2008) argue that quality and stable political system,
respect for rule of law, effective policy implementations would generally influence motivation to
more investment that could eventually influence equilibrium growth rates; in particular, to the
extent that intermediaries tend to promote capital investment. They also tend to raise rates of
growth.
In order to investigate which institution that is fundamental to growth in SSA, we unbundle
institutional quality based on Braunfels (2016) that separate institutions into three types contracting institutions, economic institutions and political institutions thus:
yi,t   yi ,t 1 1EInsi ,t  2 PInsi ,t  3GIns   X i,t  i (i ,t )   i,t
7
7
Where EIns is economic institutions, Pins is political institutions and Gins is governance
institutions. other definitions are as before.
To estimate the model above, we use the GMM weighting estimators proposed by Arellano and
Bover (1995) and Blundell and Bond (1998) to obtain consistent estimates of f  Ins i ,t and
 i (uˆi , t ), say f  Ins i ,t and ˆí (ui ,t ) . It is of course f  Ins i ,t the estimated function that we are
interested in, since it captures the marginal impact of the separate institutional quality variable on
per capita growth clean of any endogeneity. One can further unbundle equation (8) to
accommodate more number of institutional quality variables as follows:
yi ,t  yi ,t 1  1Geffi ,t  2CoCi ,t  3 PolAvi ,t  4 Roli ,t
 5 Rqi ,t  6VAi ,t  7 Efreei ,t  8 P Ri ,t  9 Bufi ,t
8
   X i ,t  i ( i ,t )   i
,t
(see summary statistics table 1 or correlation table 2 for the definition of the institutional quality
variables in model 8. An important contribution of this study is of course the use of many
institutional quality variables as well as ensuring distinct effects based on average high
correlation value among endogenous variables. Sanderson and Windmeijer (2016) developed a
test that allows evaluating if the effects of multiple endogenous variables can be separately
identified based on average high correlation value. The test is designed for the limit where
the endogenous variables are distinctly correlated such that π1 is close to a linear transformation
of π2 and π3, in which case, such institutional variable is expected to be significantly related with
the other variables.
The inconsistencies observed in the studies above might not be unconnected with the fact that
author assumed away the fundamental issue of dynamism and endogeniety in estimating the
relationship between institution and growth. This jettisoning of the issue of endogeneity call for
worry especially based on its methodological relevance in institutions-growth dynamic. Rodrik
(2004) and Acemoglu, Johnson, Robinson, and Yared (2009) agree that traditional empirical
literature generally carries problems like endogeneity, measurement errors and omitted variables
bias, making it difficult to disentangle the web of cause-effect between prosperity and
institutions.
Acemoglu et al (2009) conclude that the best way to solving endogeneity inherent in institutionsgrowth dynamics may be the use of panel generalized method of moment (GMM). GMM is
efficient in solving endogeneity and other econometric problem since it provides more reliable
and robust inference (Temple, 1999). Another advantage of the estimation techniques is that the
model need not be homoscedastic and serially independent (Nawaz et al, 2014). Although there
are variants of panel GMM, this study in particular, adopt system GMM estimation based on
Arellano and Bover (1995) and Blundell and Bond (1998), to confront issues of endogenity and
8
adjust for dynamism at the same time. The Arellano-Bover/Blundell-Bond estimator augments
Arellano-Bond by making an additional assumption that first differences of instrument variables
are uncorrelated with the fixed effects. It builds a system of two equations – the original equation
in levels and the transformed one in differences – and is known as system GMM. This method
allows more instruments and hence leads to improved efficiency. Although ArellanoBover/Blundell-Bond has one and two step variants, this study makes use of the two-step
because it is more robust and asymptotically more efficient than the one step (Nickel 1981,
Baltagi & Levin 1986, Nawaz et al, 2014).
4.3
Data Sources, Definition of variables and Summary of Statistics
To determine which of the institutions is most important to growth, this study employs a panel
data set of 25 African countries over the period 1996-2015. The choice of the countries and
periods are based on the availability of data on variables. Our outcome variable is growth of
gross domestic product. Other variables include investment, trade openness, population growth,
university education enrolment and institutions. Investment is measured as the gross fixed capital
formation as a percent of GDP. Trade openness is the sum of exports and imports divided by the
GDP. The data employed are from different sources. The dataset are from different sourcesWorld Bank’s World Development Indicators (WDI), heritage foundation (HF), United Nations
Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics and
International Monetary Fund (IMF) Balance of Payments Statistics Yearbook and data files. Out
main outcome variable (growth of gross domestic product) is from the WDI. University
Education (Enrolment) is sourced from United Nations Educational, Scientific, and Cultural
Organization (UNESCO) Institute for Statistics database. Trade-openness is sourced from
International Monetary Fund (IMF), Balance of Payments Statistics Yearbook and data files.
Dummy variables based on legal formalism (UK and French legal origin) and landlocked are part
of our explanatory power. The data on the institutional variables are collected from the
Worldwide Governance Indicators (WGI) published by the World Bank and Heritage
Foundation. The WGI database provides six different measures capturing different dimensions of
the institutional framework. These indicators include: (i) control of corruption, (ii) government
effectiveness, (iii) political stability and absence of violence/terrorism, (iv) regulatory quality, (v)
rule of law, and (vi) voice and accountability. That of HF provides (1) economic freedom, (2)
property right, (3) business freedom. All institutions estimate gives the country's score on the
aggregate indicator in units of a standard normal distribution ranging from -2.5 to +2.5. The low
value indicates bad quality institutions and vice versa. The level of institutional quality across
SSA countries nevertheless remains a missed bag (see figure 1). On average, countries like
Boswana and Mauritius are the best performed while Namibia follows. Sudan got the weakest
scores on average. The same pattern of performance can be observed in term of control of
corruption. (See appendix figure 3 as Sudan, Nigeria, Burundi, Cameron and Congo. Republic
suffer most on control of corruption). Mauritius is the best performed SSA countries in terms of
rule of law followed by Botswana and Namibia and Sudan and Guinea remain the worst hit.
On average, the best performing countries in SSA are Botswana, Namibia and Mauritius. These
countries do not record any negative index in terms of institutional quality variables. Thanks for
9
their significant inclusive institutional reforms. These performances consolidate the World
Economic Forum Global Competitiveness Report 2014-2015 Rankings for Sub-Saharan Africa
where Mauritius, Boswana and Namibia are consistently in leading position. The greatest
strengths of these countries according to the report are their transparent and efficient government
spending, well-protected property rights, strong judicial independence, well organized labour
market, low levels of corruption in regional comparison and a sound macroeconomic
environment (World Economic Forum 2015 & 2017). This phenomenon may let us into
important conclusion that quality institutions are basic requirements for economic success and
long term progress in Mauritius, Boswana and Namibia.
Fig 1: Average levels of institutional qualities across SSA, 1996-2015
1
Mauritius
Botswana
0,5
unit change, -2.5 to 2.5
Namibia
0
-0,5
0
5
Benin
Burkina Faso
-1
10
Ghana
15
Mali
Gambia, The Madagascar
Kenya
Cameroon
Comoros
Cote d'Ivoire
Congo, Rep. Guinea
Burundi
20 Senegal
25
30
INSQ
Tanzania
Swaziland Uganda; Niger Rwanda
0,633153504
Togo
Nigeria
-1,5
Sudan
-2
Sources: Author’s
This study first unbundles institution into three measures: economic, political and governance
institution. Economic institution is a composite average data of economic, business, private
property right and rule of law following Adam Smith well-organized market argument. Political
institution is a measure of degree of stability of democracy following Owen et al. (2009) and
governance institution is based on government consumption expenditure. Institutions are further
unbundled into nine. Economic freedom measures the extent to which property rights are
protected and the freedom that individuals have to engage in voluntary transactions. This
measure takes into account the respect of personal choices, the voluntary exchange coordinated
by markets, freedom to enter and compete in markets, and protection of persons and their
property from aggression by others. A political institution is the degree of stability of democracy.
This measure takes into account the competitiveness of executive recruitment, the openness of
executive recruitment, the constraints on the executive, and the competitiveness of political
participation. Descriptive statistics on the variables use for this study are presented in table 1.
10
Table 1 show that, the annual average GDP per capita growth rate is 1.42 over the period 19962015. The annual average investment as percent of GDP is 24 over the same period. The annual
average inflation across the full sample is 2.92, while annual average openness of trade is
relatively high in SSA (4.13) as compared to population growth rate (2.59).
Table 1: Descriptive statistics
Variable
Min
Std. Dev
Mean
Max
GDP capita growth
1.42
3.51
-2.30
Investment
2.92
3.71
1.02
Govt Consumption
2.60
4.15
1.52
Trade openness
4.13
5.15
2.88
Population growth
2.59
7.98
0.13
Control of corruption
-0.55
1.24
-1.51
Pol stab & Abs of Viol
-0.52
1.18
-2.65
Rule of law
-0.62
1.05
-1.72
Regulatory quality
-0.50
1.12
-1.67
Voice & Accountability
-0.56
1.02
-1.88
University
6.34
39.72
0.55
Education(Enrolment)
Landlock
0.32
1
0
British Legal origin
0.56
1
0
French Legal origin
0.44
1
0
Economic freedom
3.97
4.34
2.30
Property right
3.58
4.31
2.30
Business freedom
3.99
4.44
3.36
Source: author’s
Table 2: Correlation coefficient of different institutions, 1996 to 2015
GEFF COC
PSAVT ROL
RQ
VA
Govt Effectiveness
1
Contr of corruption 0.8155
1
15
11
Pol stab/ Abs of
0.632
0.703
1
Viol
Rule of law
0.8732 0.8364
0.7827
1
1
8
Regulatory quality
0.902
0.781
0.647 0.8673
1
10
13
Voice &
0.726
0.661
0.68812 0.8056 0.7339
1
Accountabil
11
N
0.70
0.39
0.34
0.44
0.79
0.57
0.90
0.62
0.54
0.70
5.77
500
500
500
500
500
500
500
500
500
500
500
0.46
0.49
0.49
0.30
0.40
0.21
500
500
500
500
500
500
LEFREE
LPR
LBUF
Economic freedom
Property right
Business freedom
0.53225
0.58222
0.60419
0.369
0.58621
0.58720
0.155
0.452
0.45626
0.428
0.62616
0.56523
0.56523
0.63614
0.62317
0.265
0.469
0.432
1
0.351
0.376
1
0.61818
Sources: Author’s derivation. Note that the highest correlation coefficient, regulatory quality and government
effectiveness (.902) is dropped in further unbundling model. This is to avoid multi-colinearity problem.
Table 1 depicts correlations for the various institutions employed in this study. As shown in the
table, there general positive correlation between institutions variables. Rule of law shows strong
positive correlation coefficient with 0.873. For instance, the correlation between rule of law
institutions and control of corruption index is 0.836. This is expected based on the theoretical
argument that the two variables are intrinsically related. This high correlation may be a first
indicator that, increase in rule of law may be a good strategy in fighting against corruption.
While correlations between economic freedom and rule of law institutions are 0.626, that of
business freedom and rule of law is not quite different from the same coefficient. These results
indicate that economic and business freedom has something in common. The high correlation
coefficients in most of the institutional variables employed underlines the strong relationship
among the variables. However, regulatory quality and government effectiveness record the
highest correlation coefficient of 0.902, suggesting multi-colinearity problem. To solve the
regression indeterminacy and infinite standard error that this may cause, this study separates
regulatory in the main model.
5
Empirical Results - Proximate and Fundamental Factors impact on Growth restated
Table 3 presents the results based on the impact of proximate, others and fundamental factors.
The results are based on 25 SSA countries over the period 1996-2015. The results pass a battery
of diagnostic tests. The Hansen J 18.5 with 0.67 statistics of over identifying restrictions
confirms that the instruments employed are acceptable and healthy i.e., uncorrelated with the
error term, and that the excluded instruments are correctly excluded from the estimated equation.
Across all estimations, this study finds that initial income as a measure of past realisation of
growth has positive impact on its current levels. We have estimated 3 models in table 3 to
explain the differences in growth models. Model 1 represents the proximate factors that include –
population growth, human capital and domestic investment. This model is also known as humancapital augmented version of the Solow type or conventional model (Easterly & Levine 1997).
As expected, the result indicates that increase in domestic investment leads to growth in SSA. On
average, one point increase in domestic investment increases economic growth by 0.3 point. This
result is in line with economic growth theories - classical, neo-classical and endogenous growth
theories which posit that, domestic capital formation is generally a catalyst for rapid growth and
development of any economy, be it developed, developing or under-developed. It also supports
the idea that rapid domestic investment is capable of increasing the pace of economic growth and
ensuring swift structural transformation of the economy (Romer 1986, Fashola 1998, Easterly
2001, Barro & Sala-i-Martin 2003 & Aghion et al 2005). Accordingly, these results show that
domestic capital formation plays crucial role in economic growth of SSA. Similarly, Population
growth rate is positive and significant, though with very small magnitude on economic growth.
This positive but very small relational impact could be as a result of the rapidly increasing
12
1
population in SSA which adds a substantial number to the total population every year with low
per capita income and employment rates which implies ‘a circular constellation of forces tending
to act and react upon one another in such a way as to keep a poor country in a state of poverty’.
The coefficient of university enrolment that proxy human capital development based on linear
specification is though positive but not significant. The coefficient turns positive and significant
via non- linear dimensions. This results support the argument that the relation between human
capital and growth is not quite simple. One possible explanation is the argument that it takes
some time before increase in enrolment can affect growth. This throws in a sound of warning
that government or any other investor in education should not expect instant impact on growth.
This study is also unaware that a better measure of human capital could be training rather school
enrolment (Temple, 1999).
Model 2 extends Model l, by introducing geographic, historical and trade variables (landlocked,
British and French legal formalism and globalization) which are considered exogenous (Hall &
Jones, 1999). Comparing the results of extended model (2) and baseline model l, the coefficients
of the entire proximate factors only reduce slightly, even with the introduction of the so called
other variables. The coefficient for landlocked is positive and significant in model 2. Trade
openness is also positive and significant, indicating that, countries that are more open to trade
improve more on growth rate. The results for legal origin are similar, positive and significant.
Table 3: Proximate and Fundamental Factors impact on Growth
Variables
GDP capita growth(-1)
Domestic investment
Population growth
University Education(Enrolment)
University Education(Enrolment)2
Proximate factor
Model 1
0.220
(3.376)*
0.334
(10.230)*
0.172
(4.865)*
0.007
(1.467)
0.0026
(0.746)*
Trade openness
Landlock
British Legal origin
French Legal origin
Institutions
13
Trade, Geography
&Legal formalism
Model 3
Fundamental
Model 3
0.193
(3.179)
0.237
(2.395)**
0.116
(3.052)**
0.185
(3.133)*
0.237
(2.396)**
0.031
(3.052)**
0.0028
(3.041)**
0.066*
(0.012)
0.135
(1.649)***
0.800
(2.003)**
0.910
(2.508)**
0.0018
(1.951)***
0.067*
(0.013)
0.125
(1.629)
1.273
(2.395)**
1.378
(2.694)**
0.136
(2.165)**
25
25
Instrument rank
25
23.23(0.67)
26.78(0.78)
Hansen J Stat(Prob J-Sta)
18.5(0.67)
81.33(0.0000)
89.10(0.000)
F statistics
78.17(0.000)
0.66
0.67
Stand Error value
0.67
25
25
Number countries
Observation(panel)
450
480
500
Source: Standard errors in parentheses
***p<0.1, **p<0.05, *p<0.01
The similar in the coefficients of both British (common law 0.8) and French (civil 0.9) support
argument that the differential barrier in the two types of law have rapidly torn, hence suggests
reform convergence (La Porta et al 2008).
Model 3 reveals the results for the inclusion of institutional quality (INSQ). Institutional quality
(though overall) shows a positive and significant effect on growth in SSA countries. On average,
a unit increase in institutional quality suggests around a 0.1 point increase in economic growth.
The results favour the institutional quality – growth enhancing view that, institutions matter for
growth as they shape the incentives in the society, in particular as they influence investments in
physical and human capital and technology, and the organization of production (Adam Smith
1776, North 1990, Acemoglu, Johnson & Robinson 2005, Zouhaier 2012). The findings are
consistent with that of Keefer & Knack (1997), Rodrik et al. (2004), Acemoglu & Robinson
(2013), Iqbal & Daly (2014), Nawaz et al (2014), Bruinshoofd (2016), Mullings (2018), Arshad
(2019). Comparing the significance level of domestic investment (5%) population growth (5%)
and university enrolment (5%), we could safely conclude that both proximate and fundamental
factors are major causes of growth in SSA.
It is although argue that proper understanding of the role of institutions should not be limited on
its overarching definition. This is based on the argument that lumping all institutions would
obscure the separate effects which institution can have on growth. Based on Acemoglu et al.
(2005) hierarchy of institution hypothesis, this study therefore first unbundles institutions into
economic, political and governance in the next session.
5.2
Unbundling Institutions into Economic, Political and Governance
Table 4 shows the result of separate effects of institutions on economic growth. Model 1 shows
the overarching role while model 2 shows the role of political, economic and governance
institutions. As expected, the results show a strong positive relationship between past realization
of economic growth and their current levels. Based on model 2, economic institution exhibits
positive influence on economic growth as before. The result presupposes that economic
institutions matter for growth in SSA. Specifically, a unit increase in economic institutional
quality suggests around a 0.66 point increase in economic growth. This result favour Adam
Smith eloquent description of how economic institution with well-organized market place matter
and matter a lot for growth. It also resonant Acemoglu et al (2005) believe that: ‘of primary
14
importance to economic outcomes are the economic institutions in society such as the structure
of property rights and the presence and perfection of markets’. The results favour the growthenhancing view of economic institutional quality argument by World Bank (2002) and the
empirical works of Flachaire et al (2011). The elasticity of political institution with respect to
growth is positive but not significant. This might be as a result of not trusting political
institutions enough, in particular regarding their commitment enough to a transparent policy
arena, suggesting limited role of political institutions on growth in SSA. The effect of
governance institutions (proxy by governance consumption) is negative and insignificant. This
confirms the argument in the literature that government involvement in everything (spending)
can hardly lead to growth in an environment that is enmeshed with corruption (remember Tony
Blair’s fantastically corrupt euphemism). Specifically, a unit improvement in a country’s
regulatory quality (RQ), lead to 0.27 unit decrease in growth, suggesting that, the more
government regulates, the more economic decline in SSA. This result further unsettled the
argument that too much regulation of government is damaging to growth prospect. This is an
indication that government has been enmeshing itself in unnecessary regulation over the year in
SSA. Government may have to provide unbiased and minimum regulation so as to fairly referee
the business competition. When government abandons its neutrality, either through outright
corruption or through misguided efforts at social engineering that involve picking an economy’s
winners and losers, the predictable results are a loss of efficiency, a reduction in productivity,
and eventual economic stagnation. This resonates Adam Smith government has no business in
business argument, although often misinterpreted.
The results in model 2 provide information regarding distinct effects of institutions - economic,
political and governance on growth. The separation has shown that economic institution is more
important as compared to political institutions in SSA countries. Furthermore, we have found
that different institutions perform differently role on the growth of SSA. These findings have
supported Acemoglu et al (2005) hierarchy of institution hypothesis and Zhuang, et al. (2010)
and Flachaire et al( 2011) view that different institutions perform differently in growth process.
Table 4: unbundling institutions on growth in SSA, 1996-2015
Variables
GDP capita growth(-1)
Institutions
Institutional
qualities(Model 1)
Unbundling
Institutional
qualities(Model 2)
0.106
(9.176)*
0.104
(23.43)*
0.896
(0.013)
Economic Institutions
0.667
(2.955)**
0.116
(3.052)**
Political institutions
15
Further unbundling
Institutional qualities
(Model 3)
0.185
(3.133)*
Govt Consumption
-0.142
(-1.134)
Govt effectiveness
0.024
(0.809)
0.084
(1.142)
0.082
(0.036)***
0.648
(0.787)
Control of corruption
Political stability
Rule of law
Regulatory quality
-0.272
(-3.612)**
Voice & accountability
-0.068
(-1.266)
1.213
(6.088)*
Economic freedom
Private property right
0.111
(0.143)
0.273
(1.886)***
25
19.5(0.68)
0.66
.65
25
Business freedom
Instrument rank
Hansen J Stat(Prob J-Sta)
S.D dependent var
Stand Error value
Number countries
25
18.5(0.67)
0.65
25
20.7(0.69)
0.66
.66
25
Observation(panel)
450
500
500
Source: Standard errors in parentheses
***p<0.1, **p<0.05, *p<0.01 :Our (Hansen J. 18.5(0.67) probability value) of over identifying
restrictions confirms that the instruments used are uncorrelated with the residuals, hence
acceptable and healthy.
In order to give explicit answer to the question: which institution matter most for growth in SSA?
Model 3 further unbundles institutions into nine, measures based on World Bank and Heritage
foundation measures (rule of law, control of corruption, governance effectiveness, voice and
accountability, political stability/absence of terrorism, regulatory quality, business freedom,
Private property right and economic freedom). The coefficient of governance effectiveness is
0.024. This indicates positive but not significant relation with growth. Our coefficient of political
stability (PS) is positive and significant. This result is not very different from the earlier one
since it was positive, but not significant, suggesting limited role of formal institutions on growth
in SSA.
16
Interestingly, the coefficient of economic (1.213) and business (0.273) freedom are positive and
significant. These results show that, the more people the society are freed to pursue their
individual economic/business, the more the growth prospect. On average, a unit point increase in
economic freedom increases growth by 1.2 unit and business freedom by 0.2 unit. The freemarket economy is though conditionally depends on open competitive environment with a level
playing field according to Adam Smith. We find voice and accountability (VA) and government
effectiveness indices (GEI) to be insignificant on growth in SSA. The result for voice and
accountability is not surprising as it reinforces how government in SSA does not take the
voice/demand of their citizen serious (remember the on-going demand for restructuring by
Nigerian).
Unexpectedly, rule of law (ROL) is positive but insignificant. This is not different from the
results from control of corruption. The similarity in the results for rule of law and control of
corruption may be intrinsic. It supports the perspective that a weak rule of law implies high level
of corruption. This is in line with the World Bank idea that strengthening the rule of law is a
fundamental way of controlling corruption. The lack of significance of rule of law index is not
unexpected since it captures the perceptions of the extent to which African do not have
confidence in and abide by the rules of society, and in particular the quality of contract
enforcement, property rights, lack of confidence in the police, and the courts, as well as the
likelihood of crime and violence. The lack of statistical significance of rule of law in SSA should
not be misconstrued as unimportant, rather should be seen as consistent with the poor
performance of rule of law and control of corruption in SSA. This insignificant relationship may
be due to Bratton and Gyimah-Boadi (2016) argument that, on average, citizens express more
trust in informal institutions such as religious and traditional leadership than in formal executive
agencies and the state (AEO 2017). This underscores Dahlberg and Holmberg (2016) position
that, trusts in judicial institutions, electoral process and are among the crucial enablers for a
country’ success with democracy. The legislative institutions and the electoral agencies- key
layers in a democracy- are argued to even have lower levels of trust (AEO 2017). The poor
implementation of rule of law and ineffective control of corruption seems to be undermining all
efforts to growth SSA. Also As opined by Rodick (2002), if the rules of the game were a mess,
corruption would strive (OECD 2017) and no amount of tinkering with macroeconomic policy
would produce the desired results.
It should be noted that, of all the institutional quality variables, rule of law and control of
corruption appear to have insignificant impact in the long term growth in SSA. Should we
conclude that, rule of law and control of corruption do not matter in SSA growth prospects?
Does this mean that increase in rule of law and controls of corruption are intrinsically related as
argued by the traditional argument? See the next session.
7
How Closely Correlated are Institutions in sub-Saharan Africa?
How exactly, institutions measures hang together in SSA can be determined through correlation
and regression coefficient? This is by determining the institution that exhibits the highest average
17
correlation coefficient (Haggard et al 2008). Based on institutions correlation table 2, rule of law
is found to have the highest average correlation coefficient. This is the first indication that, rule
of law is the most central to other institutional measures. What is then the relationship between
rule of law and other institutional quality variables? Regression result (Table 5) suggests that,
every institutional qualities employed in the study is highly sensitive to rule of law. The results
also show that regression of rule of law on each institutional quality variable is a good fit. Rsquared (62%) and adjusted Rw (84%) for control of corruption can be seen to be the highest.
This result resonates the idea that rule of law is intrinsically related to control of corruption
(Mendonca & Fonseca 2012).
Table 5: Impact of Rule of Law on other Institutions in SSA
Variable
Govt
COC
RQ
Efree
Buf
VA
PSAVT
PR
Eff
Rule of law
0.777
16.330
0.808
0.763
9.953
11.11 0.939 1.137
41.58
20.450
40.05
33.9
17.58
16.05 32.2 28.08
R-squared
60
62
61
44
32
57
53
39
Adjust Rw81
84
81
62
38
74
62
53
squared
Sources: Author’s
This supports the argument of Fuelner (2013) that, the better the rule of law, the better the
control of corruption and richer the nation. It is also in line with Rodrik (2008) assertion that
stable, predictable laws encourage investors which is an underlying prerequisite for growth of
other institutions. All these go with the Amartya Sen’s assertions that ‘if you expand people's
capabilities within a true independence of judiciary, they will do things that help countries grow
rich. Freeing people to take advantage of their capabilities usually means lifting the oppressive
burden of the state and guaranteeing certain basic rights (Smith 1776, Rodrik 2008). The results
support Berg and Saie (2013) idea that strong rule of law is not a mere adornment to
development; it is a vital source of progress which creates an environment in which the full
spectrum of human creativity can flourish, and prosperity can be built. These results also clearly
reaffirm United Nations Economic Commission for Africa (2016) position that, though a number
of institutional qualities are important to achieve sustainable growth in African countries, strong
rule of law still holds a central place. This is the part the government of the world's newest
country, Kosovo, seems to be toeing when it say, its priority is to improve the rule of law in
order to reduce corruption and build up the state. Moreover, given the poor performance of rule
of law that exists for African economies, it is not impossible that the poor performances of the
rule of law determine the lack of control of corruption (OECD 2017), and the reason for lack of
sustainable growth in SSA (bearing on fantastically corrupt euphemism). The result implies that
increase in rule of law represents a good strategy in the fight against corruption in SSA.
7
Conclusion and Policy Implications
Several studies in the literature have concluded that institutions are fundamental for growth
enhancement and suggested that government in the less developed countries should vigorously
18
pursue institutional reforms. This has left many less developed countries with no choice than to
continually grasp with trying to strengthen all institutions at the same time, without first
identifying which institutions is most fundamental to growth, as advised by Hirshman (1958:
109-10) in his unbalance growth strategy (implied though). This study attempts to answer the
question, which institution is most fundamental to economic growth by first unbundles
institutions into three - economic, political and governance institutions and further into nine rule of law, control of corruption, governance effectiveness, voice and accountability, political
stability/absence of terrorism, regulatory quality, business freedom, private property right and
economic freedom. The study concludes that economic institution is important to growth than
political institutions in SSA countries. While the study reveals that economic institution is crucial
to growth, rule of law is reported to be a good strategy in fighting corruption, hence the most
fundamental of all the institutional quality indicators.
Attaining economic growth in Sub-Sahara Africa may have a considerable bearing on vigorous
judicial reforms entrenched in effective control of corruption. Government should pay close
attention to detail in the implementation of judicial reform, given that reforms must address the
need for cultural changes in those responsible for making the system work. It is necessary to
understand what current practices need to be changed and then to develop training programs for
judicial workers not only to impart the values and culture of the new system but in order that
they fully understand the new procedures they will be carrying out. Government should ensure
that all institutions affected by judicial reform are included in the reform process. For example,
reform in criminal law procedure will be weakened if it includes only judges and prosecutors but
not public defenders or investigative services.
Proper judicial reform would bread well-organized market where private property rights are
protected
This may be important to growth because it would give creator of an idea certain exclusive right
over its creation, notably the right to benefit from its commercial exploitation through legal
monopoly. It would also lead to just society, where individual can pursue their personal human,
physical investment interest without fear. The police reform must be visibly supported
from the top, especially the investigative arm of law enforcement for more efficient and
effective justice/service delivery.
Successful judicial reform underscores the importance of creating special courts solely for the
purpose of hearing and speedily determining case like complex corruption and financial crimes
with adequate sanctioning. Joining of OECD Anti-Bribery Convention which has an arsenal of
legal instruments to fight international and complex corruption through criminalizing bribery in
international arena would promote justice delivery. Provision of institutional frameworks that
encourage reporting and adequate protection of whistleblower would help in fight against
corruption which guarantees just society. Provision of information technology assisted justice
system would enhance justice system by ensuring that information is adequately captured and
processes speedily, finalized and ready on demand.
This requires, as well, measures to ensure adherence to the principles of supremacy of law,
equality in the eye of the law (following principle of isonomy), accountability to the law, fairness
19
in the application of the law, separation of powers, participation in decision-making, legal
certainty, avoidance of arbitrariness and procedural and legal transparency.
This study provides empirical support for hierarchy of institution hypothesis in SSA with the
lesson that, a one-size-fits-all institutional reform strategy to promote growth and development
may likely be counterproductive. Finally, and just as crucial, researchers should keep in mind
that understanding which institutions that is most fundamental to growth requires studying
detailed and well-defined institutions and is conditional on thorough unbundling.
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Appendices:
Appendix 1 F1gure 1
Average performance of rule of law across SSA, 1996 to 2015
1,5
1
Mauritius
Botswana
unit of change
0,5
Namibia
0
0
-0,5
-1
-1,5
Ghana
10
20 Senegal 25
30
Gambia, The 15
TanzaniaUganda; Mali
Benin
Madagascar
Burkina Faso
Swaziland0,509724721
Niger Rwanda
Togo
Kenya
Comoros
Cameroon
Cote d'Ivoire
Nigeria
Burundi Congo, Rep.Guinea
Sudan
5
-2
Source: Author’s
Appendix 1 F1gure 2:
26
ROL
Fig 3: Regulatory quality acrross SSA,1996 to 2015
1
unit of change
Mauritius
Botswana
0,5
Namibia
0
0
-0,5
-1
Uganda; Ghana
5
10
15
20 Senegal 25 0,056194962
30
Burkina Faso
Kenya
Benin
Tanzania
Gambia, The Mali
Swaziland
Madagascar
Niger Rwanda
Cote d'Ivoire
Togo
Cameroon
Nigeria
Guinea
Burundi Congo, Rep.
Comoros
RQ
Sudan
-1,5
Source: Author’s
Appendix 1 F1gure 3
Fig 4: Control of corruption across SSA, 1996 to 2015
1
Botswana
Mauritius
Namibia
unit change
0,5
0
0
5
Burkina Faso
-0,5
Benin
-1
10 Ghana
15
Madagascar
Gambia, The Mali
Cote d'Ivoire
Comoros
Guinea
Kenya
Cameroon
Congo,
Rep.
Burundi
-1,5
Source: Author’s
27
Rwanda
20
25
Senegal
Swaziland
Niger
Nigeria
30
TanzaniaUganda; Togo
0,868814757
Sudan
COC