Munich Personal RePEc Archive

Financial Inclusion and Economic

Growth: The Role of Governance in
Selected MENA Countries

Emara, Noha and El Said, Ayah

Rutgers University, City University London

17 October 2019

Online at https://mpra.ub.uni-muenchen.de/99257/
MPRA Paper No. 99257, posted 27 Mar 2020 07:51 UTC

Electronic copy available at: https://ssrn.com/abstract=3812832

Financial Inclusion and Economic Growth: The Role
of Governance in Selected MENA Countries

Noha Emara, Ph.D. (Corresponding Author)

Department of Economics
Rutgers University, the State University of New Jersey
311 North 5th Street
Camden, NJ 08102, USA
Tel: 856/225-6765
E-mail: nemara@camden.rutgers.edu

Ayah El Said, Ph.D.

Department of Economics
City University of London
E-mail: ayah.el-said.1@city.ac.uk

JEL Classification Numbers: C23; G21; O43

Keywords: Financial Inclusion; Governance; Economic Growth; MENA;
Financial Development

Electronic copy available at: https://ssrn.com/abstract=3812832

 Abstract

Financial inclusion, whether in terms of adoption or usage, is one of the main, but
challenging priorities in the MENA region. The paper empirically investigates the
relationship between financial inclusion and economic growth in selected MENA countries.
A system GMM dynamic panel model technique is employed on yearly data for the period
1965-2016, using a number of measures of financial inclusion covering the households and
the firms access to finance. Particularly, the study uses indicators such as the number of bank
accounts (per 1000 adult population), bank accounts for corporates/enterprises, and the
number of bank branches and ATMS (per 100,000 people), percentage of firms using banks
to finance investments, the percentage of firms using bank loans to finance working capital,
and the percentage of firms using banks to finance investments. The results of the study
indicate that financial inclusion positively impacts GDP per capita growth in the selected
countries. Financial inclusion measured by the household’s financial access index has a
positive and statistically significant impact on economic growth in the MENA region, but
requires supervisory and regulatory regimes with backing of the rule of law, judicial
independence, contract enforcement, control of corruption, and political stability. The effect
firms’ access to finance is only significant in the presence of strong institutions. The results
were insignificant for the general financial inclusion measure.

Electronic copy available at: https://ssrn.com/abstract=3812832

Introduction

In a world where information is far from perfect, information and transaction costs become
the rule. If such costs become sufficiently expensive, some transactions may not wholly take
place (Khan and Senhadji, 2003). Consequently, the rise of financial intermediaries was
inevitable to make such transactions plausible, loosen financial frictions, in addition to
ameliorating any associated costs and market imperfections.

Simply put, financial intermediaries are institutions that channel savings to investors,
thereby, increasing access to capital to concerned stakeholders. The rise of the
aforementioned intermediaries has been a cornerstone in the process of financial development
for any economy. As Levine (2005) put it, financial development broadly takes place when
financial instruments, markets, and intermediaries improve the impact of information,
enforcement, and transactions costs. Such improvements allow financial intermediaries to
efficiently allocate resources, aid the process of exchanging, hedging, diversifying, and
pooling of risk; mobilize and pool savings, evaluate investments, exercise corporate control
and governance, as well as assist in the process of exchanging goods and services.

Financial development is important in terms of its impact on economic growth. The link
between financial development and economic growth can be traced as far as Schumpeter
(1912) more recently McKinnon (1973) and Shaw (1973), and is well established by now in
1

terms of empirical evidence . 2

In addition, given the different pillars of the financial development that range from
banking, to equity, to bonds, to insurance, only a handful of studies attempted to investigate
whether they affected economic growth differently . Hence, breaking up the different types of
3

financial development permits the investigation of how economic growth is affected by the
different types of financial development.

Thus, the purpose of this study is to examine the effects of financial development, and
more specifically financial access, for a group of Emerging Markets (EMs) and Middle East

1
Schumpeter held that financial intermediaries select the firms that utilize an economy’s savings. More formally, his view
stipulated that financial intermediaries tend to adjust the process of savings allocation rather than alter the savings rate itself.
Thus, Schumpeter’s notion of finance and development focuses on the effect of financial
intermediaries on productivity growth and the rates of technological change. Beck at al. (2000). Finance and the sources of
growth.
2
For a detailed review of the literature on finance and growth, see Levine (2005).
3
Chin and Ito (2007) attempted a similar examination of the impact of different types of financial development on the
current account rather than on savings, acknowledging the ambiguity of the relation with regards to savings.

Electronic copy available at: https://ssrn.com/abstract=3812832

and Africa (MENA) Region, where the latter is a region characterized by low financial
access.

Financial inclusion - access to, and use of, financial products and services by households or
firms - is one of the main, albeit challenging priorities in Emerging Markets (EMs), and a
key factor for financial development 4 . Regional blocs 5 and international financial
organizations, including the World Bank, the International Monetary Fund, the Asian
Development Bank, and the African Development Bank, are among the many entities
currently prioritizing access to finance. Financial inclusion units, both within Central Banks,
and Finance Ministries, have been on the rise, and bolstering access to finance has become an
issue that has been repeatedly addressed in various G-20 statements (see Beck, 2016)).6 Over
the last decade, the global average of ATMs per 100,000 adults has increased by at least two
thirds,7 while the global average of holders - especially for depositing purposes - has more
than doubled (IMF, 2018), as shown in Figure (1).

Figure (1): Evolution in Financial Inclusion Trends Over the Last Decade

Source: IMF Financial Access Survey (via IMF, 2018)

4
The literature on financial inclusion over the last decade established that financial development goes well beyond economic
growth (see for example Beck, 2016), Levine, 2005, and Beck, 2009), with financial development contributing to improved
income distribution, and reduced poverty (Beck, 2016), even if financial inclusion was lagging
5
G20, APEC, ASEAN, and GCC.
6
Yet, still over half of the central banks globally have no financial inclusion mandate, but rather objectives related to
financial inclusion (Tissot and Gadanecz, 2017).
7
From 30 in 2004, to almost 50 in 2015.

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Financial inclusion is of key importance, particularly to EMs and frontier markets whose
levels of financial development, as well as access to finance, are well below those of
advanced economies. Financial inclusion can thus help consumption smoothing with
significant welfare gains (see, for example, Jappelli and Pagano, 1989; Bacchetta and
Gerlach, 1997; Ludvigson, 1999), and help in lowering income inequality by increasing the
income of the poorest quintile (Beck et al., 2007), thus boosting savings (Dupas and
Robinson, 2013). Moreover, it can act as a lever to reduce the significant rise in extreme
global inequality (IMF, 2018), while playing a crucial part in risk diversification and building
trust in the financial system, (Cihak et Al., 2016), something that EM and frontier economies
lack. Its contribution, therefore, when it comes to growth (IMF, 2016), as well as in terms of
alleviating poverty and inequality, cannot be ignored. Ideally, financial inclusion should
ensure the sufficient provision of financial services to households, corporates, and
governments, in order to improve individual (and overall) welfare (Beck, 2016), without
jeopardizing financial stability.

Access to finance in the MENA region has been limited. Specifically, the MENA
region is one that can be characterized by the following; 1) it lacks financial deepening; 2) its
financial markets are underdeveloped; 3) its financial markets are bank based rather than
market based; 3) it has insufficient collateral; 4) has limited secured transactions; 4) and has
limited access to finance. This is especially the case among the region’s oil importance. In
fact, financial inclusion has been rising as a priority across the MENA region, and has
significant growth opportunities. The regional turmoil across the MENA region has hit the oil
importers the most, leading to more risk aversion, subdued credit growth, lower liquidity,
whereby external support acting as a buffer against such uncertainty, with significant stock
market volatilities in some countries. However, the region’s banks generally are well
capitalized.

As previously mentioned, bank-based financial institutions dominate the MENA

region’s financial sector, while public banks dominate, once again among oil importers. The
relative inefficiencies in state-owned enterprises have been linked to poorer bank credit, and
lower banking sector profitability. Overall, private sector credit is low relative to other
Emerging Markets, once again, especially among the region’s oil importers.

Electronic copy available at: https://ssrn.com/abstract=3812832

 Figures (1 & 2): Bank Credit Lower Among the MENA Region’s Oil Importers

Source: World Bank Global Financial Development Database (2016; both charts)

On the non-bank side, there is significant scope for non-bank financial development
especially as the stock market capitalization significantly improved. This has been due to
reforms, incentives to list in stock exchanges, and opening up to foreign investor. This has led
to a larger stock market size. Yet stock market liquidity (value traded), remains low,
exacerbated by regional turmoil

Figures (3 &4): Low Stock and Bond Market Development in Selected MENA Countries

Source: World Bank Global Financial Development Database (2016; both charts)

Overall, the MENA region suffers from a small presence of non-bank financial institutions;
small insurance sector, limited private equity, hedge fund, pension funds activity, perhaps
with the exception of Morocco, whereby insurance is mandatory and is used by 24% of the
adult population in Morocco.

Electronic copy available at: https://ssrn.com/abstract=3812832

 Figure (5): Low Insurance in Selected MENA Countries

Source: World Bank Global Financial Development Database (2016; both charts)

As to access to finance, the MENA region has a low financial penetration whereby Egypt and
Morocco have the least access to finance/bank financing, and small firms are more
constrained in their ability to access financing via formal means. Access to finance is
recognized as a major constraint relative to neighbouring Turkey and other Emerging
Markets. Almost 50% of adult population in among the bigger oil importers (Jordan,
Morocco, Tunisia and Egypt) are underserved by the banking system, leaving scope to resort
to informal means of credit/saving.

Figures (6,7 &8): Low Financial Penetration Across Selected MENA (oil importing) countries

Source: World Bank Global Financial Development Database (2016)

The region also grapples with a high concentration ratio, which contributes to the limited
access to finance. In fact, the MENA region is home to some of the world’s highest bank/loan

Electronic copy available at: https://ssrn.com/abstract=3812832

concentration ratios, which leads to a bias towards lending to large firms and excluding
young/small firms.

Figure (9): Bank Concentration Ratios in Selected Oil Importers: Among the World’s Highest

Source: World Bank Global Financial Development Database (2016)

There is also a low share of adults with an account at a formal financial Institution; Morocco
stands out above the 28% average of lower middle-income countries There is also an even
lower share of women with an account at a formal financial institution.

Figure (10): Share of Adults and Women at a Formal Financial Institution

Source: World Bank Global Financial Development Database (2016)

Despite the regional turmoil, and the underdevelopment of some of the MENA region’s
countries, the region’s financial sector continues to be sound. The region’s banks are
generally well capitalized, with NPLs relatively contained despite some increases in Morocco
and Tunisia. Reforms are in place to bring them back to a “tolerable” level in Tunisia.

Electronic copy available at: https://ssrn.com/abstract=3812832

However, higher provisions across the region’s oil importers (97% in Egypt vs. 60% in
Tunisia) imply subdued credit growth. Given Egypt’s weak macroeconomic environment,
there is a higher level of dollarization, in addition to Jordan, but an improvement is expected.
There is also scope for macroprudential policies to support financial stability.

Given the importance of financial access on economic growth, this study will attempt
to answer several questions; do different types of financial access indicators affect economic
growth? Is the effect the same across the two samples, EMs and MENA? How does the level
of institutional quality influence the effectiveness of financial access measures on economic
growth? The rest of this paper will be divided as follows. Section II will briefly review the
literature, Section III describes the data used, Section IV will highlight the methodology
employed and the model specification, Section V will highlight our results, and Section VI
will conclude. The appendix is by the end of the paper.

II Literature Review

There is a vast amount of literature on the determinants and impact of financial development,
the link between financial development and growth.8 However, the literature that examines
the role of financial access in the MENA region and the possible impact of institutional
quality on financial access link to growth is not as vast. Hence, we briefly outline the most
commonly cited literature on the above strands, followed by a detailed account of the studies
that combines them.

Gerschenkron (1962) in addition to others, assert that banks finance growth in a more
effective and efficient way relative to market-based systems, particularly in under-developed
economies. Levine (2002) added that advocates of bank-based systems argue that banks that
are unimpeded by regulatory restrictions tend to benefit from economies of scale in the
process of collecting information, and can, thus, enhance industrial growth. The difficulty of
capturing financial development by one variable, or even in a single broad category was
ascertained by Ito and Chinn (2007). Consequently, the existence of different types of
financial development ranging from banks, bonds, equity, and insurance markets9 must be
accounted for.

8
For a detailed survey on the literature on the relation between financial development and growth, see Levine (1997, 1999a).
9
Comprising the market-based system.

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 Empirical studies testing the impact of financial development generally involved the
use of cross-country studies to understand the relation between financial development and
growth. The main findings of those papers held that cross-country differences in the levels of
financial development explained a considerable fraction of the cross-country differences in
growth rates (Khan and Senhadji, 2003). For a cross-section of 159 countries averaged over
the period 1960-1999, the authors find that financial development has a positive impact on
economic growth. King and Levine (1993) employed four measures of financial
development10 reflecting the size and depth of the financial sector in a cross section of 80
countries averaged over the period 1960-1989. And authors found that the proxies employed
were strongly linked to real per capita GDP growth, and the rate of capital accumulation11.

Many papers have studied the determinants of economic growth in the MENA region,
for instance the study by Makdisi, Fattah, and Lima (2005) found that economic growth in
the MENA region is statistically significantly affected by investment and the initial level of
income. Nabli (2007) concludes that human capital and physical infrastructure are vital
determinants of economic growth for MENA, as well as macroeconomic and external
stability. More specifically the study found that better primary education, improved
infrastructure networks, as well as health status of the people are the most important factors
affecting economic growth in MENA. The study by Duncan, and Denaux (2013) found that
initial income and openness, have a negative impact on economic growth, while being an oil
producer has a positive impact on growth.

To examine the link between financial sector development and economic growth,
using a Generalized Method of Moments (GMM) approach, Ayadi et. Al. (2013) used a
sample of northern and southern Mediterranean countries over the period 1985-2009. They
found that credit to the private sector and bank deposits are inversely linked to growth. The
authors found that stock market size and liquidity is important for growth, especially
institutional quality is taken into consideration.

Also using GMM, Hamdi and Hakimi (2015) study the effect of bank and stock
markets developments on economic growth for eleven MENA countries over the period 1995
to 2010. The authors find a positive relationship between banking and financial developments
10
The ratio of liquid liabilities of banks and non-bank institutions to GDP,10 bank credit as a share of the sum of bank and
central bank credit, the ratio of private credit to domestic credit, and private credit to GDP.
11
A similar conclusion was made by Beck et. al (2000) upon employing a cross-country instrumental variable estimator to
extort the exogenous constituent of financial intermediary development. Using data for 63 countries averaged over the period
1960-1995, a strong, positive connection was found between financial intermediary development and real per capita GDP
growth. Such a connection translates into higher GDP growth as well as long-run links between financial intermediary
development and physical capital growth.

10

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and economic growth. They highlighted the fact that stock markets in MENA countries are
still underdevelopment, with a significant need for reforms to attract investors.

Using GMM estimation methodology for a panel sample of 74 countries over the
period 1960 to 1995, Rioja and Valev (2003) found a statistically significant positive impact
of financial development on economic growth. But, the relationship between finance and
growth maybe uncertain in countries with low financial inclusion- and low financial
development such as the case of the MENA region. Similarly, using panel data for a sample
of 144 countries over the period 1985 to 2009, Abdmoulah and Jelili (2013) found a non-
linear relationship between economic growth and financial development as defined by the
access to finance and density of commercial bank branches.

In terms of the role of institutional quality, among the first studies to address the
question of financial inclusion beyond the greater scope of financial development was that of
Beck et al. (2007b). Using data for banking sector outreach12 for 99 countries over the period
2003-2004, they found that institutional quality affects financial inclusion positively, while
the degree of government ownership of banks has a negative effect.13 Other determinants of
financial inclusion include GDP per capita, governance, and the institutional quality and the
regulatory environment. (Rojas-Suarez, 2010, Park and Mercado, 2015, and Allen et al.,
2016,).

Honohan (2008) uses financial access data for 160 countries within an OLS context
and finds that increased mobile phone penetration14 and better institutional quality (as well as
governance) are positively correlated with their access variables - the number of bank
accounts per 100,000 adults - even when per capita income is controlled for. Similarily,
Honohan and King (2009) finds that the availability of mobile phone increases household
financial penetration ratios. On a more general context, the study of Sarma and Pais (2011)
finds a strong correlation between economic development and financial inclusion are highly
correlated. This result implies that the higher the level of development the fewer unbanked
households15 are to be expected.

12
Covering both access and use of financial services indicators.
13
However, Demirguc-Kunt et al. (2015) highlight the importance of governments in encouraging financial inclusion, by
transforming government payments from cash into bank (and ever more recently into mobile) accounts.
14
Related to this is the rising literature on the role of digital payments in raising income and promoting financial inclusion.
For more information, see Beck (2016).
15
Or more financial inclusion, and less financial exclusion.

11

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 The study by Cherif and Dreger (2014) analyzed the institutional determinants for
financial development in the MENA. Corruption was the most important institutional factor
for banking sector, while the impact of corruption and law and order appear to be relevant for
the stock market. The authors concluded that more prompt economic integration is crucial for
financial development, and is a pre-requisite for higher GDP growth.

Using data for 15 MENA countries over the period 1996-2010, Abouzayed and
Fayoumi (2016) examined the relationship between economic growth and banking sector
concentration with a particular focus on the role of institutional quality. They find a positive
and significant relationship between economic growth and banking concentration as well as
institutional quality. The authors concluded that banking concentration and institutional
quality mattered for growth in MENA countries, while the interaction between concentration
and institutional quality yielded a negative and significant result.

Additionally, Hall and Jones (1999) found a statistically significant effect of the
improvement in institutions and effective government policies on capital accumulation,
productivity, and, output per worker. Banerji and Humphreys (2003) concluded that good
governance in the MENA region, is crucial to boosting growth. Using cross sectional sample
of 150 countries, Kaufmann, Kraay and Zoido-Lobaton (1999) show a statistically significant
correlation between governance and development. Similarly, Honohan (2008), Rojas-Suarez
and Gonzales (2010), and Park and Mercado (2015) found a positive link between
improvement in institutions and financial inclusion.

The study by Banerji and Humphreys (2003) on the MENA region shows that good
governance - responsive, transparent, and accountable public institutions- is key to boosting
growth and lowering poverty. Within the same lines, Kandil (2009) concluded that an
improvement in institutional quality- corruption, regulatory quality, government
effectiveness, and the rule of law) all have positive impact on GDP growth. Additionally, the
study found that export growth is positively affected by political stability and rule of law,
while worsening institutional quality may helped in the increase in loan financing and private
investment in the MENA region.

Emara and Jhonsa (2014) concluded that the improvement in governance; lower
corruption levels, better rule of law, increased political stability, lower internal violence, and
more accountable governments are important for economic growth. Similarly, Emara and

12

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Chiu, (2016) found that an improvement in a composite governance indicator improves per
capita GDP growth in the MENA region.

Against the above background it can be noticed that the literature on the link between
financial inclusion and governance is very thin. Most research focuses on financial
development, but financial inclusion has not been barely looked at. The study by Rajan and
Zingales (2003) showed that changes in political structure are prerequisite for financial, and
that inadequate financial competition is a consequence of political instability. Similarly, the
study by Demetriades and Hook Law (2006) concluded strong institutional framework in
which the financial system operates increases the positive impact of financial development on
GDP per capita.

Chauvet and Jacolin (2017) showed that lack of financial inclusion coupled with low
institutional quality and information asymmetries has a negative impact on financial
development (that is, economic growth). More specifically, the study shows that low
financial inclusion leads to a crowding out effect in favour of the government of a small
number of firms or a reversal of the expected positive impact of financial development on
economic growth.

Law and Habibullah (2006), Balach and Law (2015) concluded that strong
institutional quality improves financial development and economic growth. Within the same
lines, Law and Habibullah (2009) found that income and the quality of a country’s
institutions are the most important factors affecting the banking sector and capital markets.
Similarly, the study by Law and Kutan (2018) concluded that the quality of institutions is
crucial in mediating the positive relationship between banking sector development and
economic growth.

III. DATA

The data set is constructed as a panel of country observations from the World Development
Indicators of the World Bank’s database. The data set includes 44 EMs and MENA countries
over the period 1960-2015. The list of countries included in the sample is reported in Tables
1 and 2 of the appendix.

The dependent variable in the model is the real per capital GDP growth rate and the
set of independent variables consist of inflation rate, growth rate of gross capital formation,

13

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government spending (as a percent of GDP), openness, population growth, and different
financial access16 indicators covering different dimensions such as general financial access,
households’ financial access, and firms’ financial access. The list of economic, financial, and
governance variables used in the study is reported in Tables 3 through 6 of the appendix.

IV. MODEL SPECIFICATION & METHODOLOGY

To perform such an analysis, the following dynamic panel regression methodology is used:

!"#,% = α + *!"#,%+, + -.#,%+, + /01#,%+, + ε3,4 (1)

i = 1, 2,…N, t = 1960,…T

Where Grit denotes the growth of per capital real GDP, of country i, at time t. Next, Grit-1 is
the lagged endogenous variable17, Xit-1 is the vector of explanatory variables, FIit-1 represents
financial inclusion indicators that covers different areas namely financial access of the
financial system in country i at time t, and εit is the error term.
To avoid the correlation problems, following Yafee (2003) Equation (1) is estimated
using the General Method of Moments estimator (GMM) which consistently estimates the
dynamic panel data model (Kitazawa (2003)). It is known in the literature that economic
growth models are best estimated by dynamic panel system GMM (Caselli, Equivel and
Lefort (1996) and Holtz-Eakin, Newey and Rosen (1988)) which is a methodology proposed
by Arellano and Bover (1995), Blundell and Bond (1998), and Blundell, Bond, and
Windmeijer (2000) to overcome the bias problems of the difference GMM methodology.
The system GMM combines together Equation (1) with Equation (2), which is simply
the first difference of Equation (1) to eliminate the country specific or unobserved effect as
suggested by Arellano and Bond (1991):

8!"#,% − !"#,%+, : = α + ρ8!"#,%+, − !"#,%+< : + β8X3,4+, − X3,4+< : + δ(FI3,4+, − δFI3,4+< )

+(ε3,4 − ε3,4+, ) (2)

As explained in details in Emara and El Said (2015), The System GMM assumes two extra
assumptions over the Difference GMM. To ensure a zero correlation between the right hand
16
Financial access and inclusion will be used interchangeably.
17
Lagged values are included to account for causality.

14

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side variable and the list of regressors with the unobserved countries’ fixed effects, two
additional assumptions are added as follows,
CD△ !"#,% F#,% G = 0, 0I" J = 2, … , L
CD△ M#,% F#,% G = 0, 0I" J = 2, … , L (3)

where M i,t is the set of all the explanatory variables of Equation (1) or Xi,t and FIi,t.

Next, a dummy variable for the countries of the MENA is added to the model in order
to estimate the impact of financial inclusion in the MENA region. The model explores how
the changes in access to finance affect the changes in the growth of per capita real GDP in the
MENA region v.s. other countries. To do so a dummy for MENA countries along with an
interaction term is added to the model as follows,

!"#,% = O + *!"#,%+, + -.#,%+, + /01#,%+, + PMCQR#,% + S (MCQR# ∗ 01#,%+, ) + F#,% (4)

where MCQR# represents the dummy variable, which takes 1 if country i is a MENA country
and zero if not. The total effect of the impact of the different areas of financial inclusion is
estimated by adding the coefficient P to the coefficient S and the statistical significance of the
effect is estimated using the standard errors of these two coefficients.
Finally, to analyze if the availability of well-established and credible institutions can fully
achieve the benefits of financial inclusion, an interaction term of the governance index is
added to our model as follows.

!"#,% = O + *!"#,%+, + -.#,%+, + /01#,%+, + PMCQR#,% + S (MCQR# ∗ 01#,%+, ∗ !IV#,% )

+ F#,% (5)

Where Gov3,4 is the governance indicator index which is computed using the principal
component analysis of six main areas including control of corruption, government
effectiveness, political stability, regulatory quality, rule of law, and voice and accountability.

V. ESTIMATION RESULTS
In this section, we report the impact of the various financial inclusion measures – using
different measures of access that can be grouped into general access measures, households’
access measures, and firms’ access measures - for our full sample, and for the MENA region

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to see how the levels of financial inclusion affect economic growth in this region as
compared to the full sample. In addition, we interact governance with financial inclusion
measures, to access the impact of regulatory and institutional quality on the effectiveness of
financial inclusion measures as highlighted in several studies, including Beck et al. (2007b)
and Honohan (2008) who found that the improvement in institutional quality increases
financial inclusion.

To estimate the impact of financial access on economic growth we begin by

highlighting our baseline regressions for the full sample, then we outline our results for the
MENA region, and then we proceed to discuss the role of institutional quality, proxied by
governance indicators in affecting the role of financial access on economic growth.

We start the analysis by using measures that capture access using variables that
combine access to financial markets and financial institutions, as calculated by the IMF’s
Financial Development Database (Svirydzenka, 2016), as a broad measure of financial access
reflecting access to bond and equity markets. The IMF’s Financial Development Database
includes bank branches and ATMs as their proxy for financial institutions access, while
financial markets access is proxied by the percentage of market capitalization outside of the
top-10 largest companies and the total number of issuers of debt.

Table (8) presents our baseline regression with economic growth as the dependent
variable measured as the change in the log of real per capita GDP. It is regressed on its lag
and different macroeconomic variables and the financial access indicators which capture the
ability of both individuals and enterprises to access financial services. The results show that
the main variables of the regression come with the expected sign and statistical significance
with the exception of the government spending variable. Column 1 shows our baseline
regression where economic growth is regressed on its lag, which as expected is positive and
significant at the 1% level. The inflation rate displays a negative relationship, whereby a 1%
increase in inflation rates lowers economic growth by 0.2%. The investment rate shows a
positive expected impact on economic growth where a 1% increase in fixed capital formation
increases economic growth by about 0.1%. The openness index displays a positive impact on
economic growth with a magnitude of 0.01%. Similarly, a 1% increase in population growth
increases economic growth by 0.6%. The index of Financial Institutions Acess (fia) is
positive as expected and statistically significant, where a one unit increase in the fia index
results in 0.032% increase in economic growth.

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 Column 3 uses the other measure of financial inclusion, Financial Markets Access
Index (fma), where again this index is calculated as the percent of market capitalization
outside of top 10 largest companies and the total number of issuers of debt (as shown in
Table (6)). The results suggest that a one unit increase in the fma index results in 0.011%
increase in economic growth.

To combine the effects of both types of financial access, Column 5 shows the impact
of a general financial access indicator (accgen), proxied by the principal component analysis
of the two indices fia and fma. The results show that a one unit increase in the accgen index
results in 0.023% increase in economic growth. Our results are in line with Gerschenkron
(1962), King and Levine (1993), Levine (2001), Khan et. al (2013), and others who
confirmed that financial development boosts economic growth.

In Columns 2, 4, and 6 the dummy variable for the MENA region is interacted with
fma, fia, and accgen, respectively. The interaction terms are statically insignificant, however
what matters is the total effect which are measured in Table (9) by adding the coefficient of
the financial access indicator under consideration to its interaction term with the MENA
dummy, as explained in Equation (4). Table (9) shows that the total effect of the impact of
the fma, fia, and their combination represented by accgen are all statistically insignificant.
This result confirms the fact that the MENA region suffers from financial underdevelopment,
as evident by limited presence of non-bank financial institutions including a small insurance
sector, limited private equity, hedge fund, and pension funds activity.

Table (10) shows the estimation results of Equation (5) where the effects of the
different measures of financial inclusion on economic growth in the MENA region are
estimated in the presence of improved institutional quality. In Columns 1, 2, and 3 the
dummy variable for the MENA region is interacted with the governance index and with fma,
fia, and accgen, respectively, and once again, the results are insignificant, highlighting the
limited impact of financial inclusion on economic growth in the MENA region. Table (11)
shows that the total effect of the impact of the fma, fia, and accgen, in the presence of good
institutions are all statistically insignificant. This result implies that the improvement in the
institutional quality in the MENA region does not affect the role of financial inclusion on
economic growth, where inclusion is measured by the ability of both individuals and
enterprises to access financial services.

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 Table (12) introduces an alternative financial inclusion measure that reflects the
households’s access to financial services. This is comprised of ATMs per 100,000 adults
(atm), bank branches per 100,000 adults (bb), and the number of depositors with commercial
banks per 1,000 adults (ba). Column 1 shows the results of the full sample for the first access
indicator, ATMs machines, which has a statistically significant positive impact on economic
growth, where a one unit increase in ATMs leads to an increase in economic growth by about
0.021%. (how can we link the physical presence of ATM machines to economic growth?)
Similarly, Column 3 shows that a one unit increase in bank accounts per 1000 adults leads to
a statistically significant increase in economic growth by about 0.02%. Column 5 shows that
a one unit increase in bank branches per 1000 adults leads to a statistically significant
increase in economic growth by about 0.003%.

Next, to analyze the impact of household’s access to finance on economic in the

twenty-one MENA countries of our sample an interaction term of the dummy variable
MENA is added to the regression. In Columns 2, 4, and 6 the dummy variable for the MENA
region is interacted with atm, ba, and bb, respectively. The interaction terms are statically
insignificant, with the exception of the interaction term of bb. Next, Column 1 of Table (13)
shows that the variable “acc”, a linear combination using the principal component analysis of
the three access to finance indicators, ATM machines, bank branches, and accounts, is
positive and statistically significant where a one unit increase in acc leads to an increase in
economic growth by about 0.007%. Column 2 shows that the interaction term of the dummy
for the MENA region with the acc indicator has positive statistically significant impact on
economic growth.

Table (14) provides the calculations of the at the total effect of the availability of
ATM machines, bank branches, accounts, and their linear combination on economic growth.
The results show a positive statistically significant impact where a one unit increase in ATMs
leads to about 0.015% increase in economic growth in the MENA region. The results also
show that the total effect of the availability of bank branches in the MENA countries is
positive and statistically significant where a one unit increase in bank branches leads to about
0.04% increase in economic growth. Similarly, the total effect of the availability of bank
accounts is positive and statistically significant where a one unit increase in bank accounts
leads to about 0.002% increase in economic growth. Finally, the total effect of the variable
acc is statistically significant for the group of MENA countries, where a one unit increase in
that variable results in about 0.004% increase in economic growth.

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 To analyze how improved institutions can affect the role of households’ access to
finance on economic growth, Table (15) shows the dummy variable for the MENA region is
interacted with the governance index and with atm, bb, ba, and acc, respectively whereby
most of the results are insignificant. In contrast, Table (16) shows that the total effect of the
impact of the atm, bb, ba, and acc, in the presence of good institutions are all statistically
significant, with the exception of the bank branches (bb) variable. This result implies
financial inclusion – conditional on improved institutional quality – positively affects
economic growth in the MENA region, when inclusion is measured by the ability ATM
machines and bank accounts. To dig deeper into how improved institutions can affect the role
of households’ access to finance on economic growth, Table (17) shows the results when the
dummy variable for the MENA region is interacted with the six measures of the governance
index with the acc indicator. More specifically, the results show a positive and statistically
significant impact of the households’ access to finance on economic growth conditional
onimproved control of corruption, government effectiveness, political stability, regulatory
quality, rule of law, and voice and accountability, where economic growth increases by
0.0076%, 0.0074%, 0.013%, 0.0079%, 0.0076%, and 0.0070% respectively. These results are
in line with Beck et al. (2007b), Honohan (2008), Cherif and Dreger (2016), and Park and
Mercado (2015) who found that institutional quality increases financial inclusion. The results
also support the findings of Banerji and Humphreys (2003), Emara and Johnsa (2014), and
Emara and Chiu (2016) who found that an improvement in institutional quality improves
economic growth in the MENA region.

Next, Table (18) introduces another financial inclusion measure that reflects the
firms’ access to financial services, comprised of the percentage of firms using banks to
finance investments (finv), the percentage of firms using bank loans to finance working
capital (fwork), and the percentage of firms identifying access to finance as a major constraint
(fc). Column (1) shows the results of the full sample for the first firm’s access indicator, finv,
which has a statistically significant positive impact on economic growth, where a one unit
increase in finv leads to an increase in economic growth by about 0.073%. Similarly, Column
3 shows that a one unit increase in fwork leads to a statistically significant increase in
economic growth by about 0.069%. However, Column 5 shows that a one unit increase in fc
is statistically insignificantly affecting economic growth of the full sample.

Columns 2, 4, and 6 show the impact of firms’s access to finance on economic growth
in the MENA region where an interaction term of the dummy variable MENA is added to the

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regression. Again, the dummy variable for the MENA region is interacted with finv, fwork,
and fc, respectively, where results show that the three interaction terms are negative and
statically significant. Column 1 of Table (19) shows the results for the full sample, where the
variable “firmacc”, which is computed as the principal component analysis of the three firms’
access to finance indicators with finv, fwork, and fc, is positive and statistically significant
where a one unit increase in firmacc leads to an increase in economic growth by about 0.08%.
Column 2 shows that the interaction term of the dummy for the MENA region with the
firmacc indicator has a negative statistically significant impact on economic growth.

Table (20) provides the calculations of the at the total effect of the availability of with
finv, fwork, and fc, and their linear combination, firmacc, on economic growth. The results
show insignificant results with the exception of the variable the total effect of the variable fc
which shows an expected statistically significant negative impact on economic growth in the
MENA region, where a one percent increase in the percentage of firms identifying access to
finance as a major constraint results in about 0.08% drop in economic growth. This result
goes well with the fact that despite bank-based financial institutions dominate the MENA
region’s financial sector, the dominance of inefficient public banks led to poorer bank credit.
This is in addition to the fact that many small firms in the MENA region are constrained in
their ability to access financing via formal means reinforces the fact that limited access to
finance lowers economic growth.

Table (21) adds the interaction terms of the governance indicator with the three
measures of firms’ access to finance finv, fwork, and fc, and their linear combination, firmacc,
in order to analyze how improved institutions can affect the role of firms’ access to finance
on economic growth. Table (22) computes their total effects in the presence of good
institutions, where the results show that the improvement in the institutional quality in the
MENA region improves firms’ access to finance and thereby increases economic growth,
where firms’ access measure is dominated by the positive statistically significant impact of
the percentage of firms using bank loans to finance working capital. The results show that a
one unit increase in the firmacc variable in the presence of improved institutions increases
economic growth by 0.12%.

VI. CONCLUSION

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 The study analyzes the effect of access to finance to households and firms on economic
growth for a sample of 23 EMs and 21 MENA countries over the period 1960-2015. Using
Arellano-Bover/Blundell-Bond Dynamic Panel System GMM methodology, the studyfinds
financial access, measured either by the IMF access indicators, households access measures,
or firms access measures, are positive and statistically significantly in affecting economic
growth across the full sample. The results of the MENA region indicate that households’
measures of financial inclusion positively impact GDP per capita growth however this impact
requires supervisory and regulatory regimes with backing of the rule of law, judicial
independence, contract enforcement, control of corruption, and political stability. The results
for the impact of the firms’ access to finance are only statistically significant when
complemented by strong institutions with the strongest impact stemming from the availability
of firms’ bank loans to finance working capital. The results reinforce the importance of
private sector development, improved institutional quality, and increasing firm access to
credit as a means to increase per capita growth.

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APPENDIX

Table 1 –List of EMs included in the Sample

1 Argentina 15 Philippines
2 Bangladesh 16 Poland
3 Brazil 17 Romania
4 Bulgaria 18 Russia
5 Chile 19 South Africa
6 China 20 Thailand
7 Columbia 21 Turkey
8 Hungary 22 Ukraine
9 India 23 Venezuela
10 Indonesia
11 Malaysia
12 Mexico
13 Pakistan
14 Peru

Table 2 –List of MENA included in the Sample

1 Algeria 15 Qatar
2 Bahrain 16 Saudi Arabia
3 Djibouti 17 Syria
4 Egypt 18 Tunisia
5 Iran 19 United Arab Emirates
6 Iraq 20 West Bank & Gaza
7 Israel 21 Yemen
8 Jordan
9 Kuwait
10 Lebanon
11 Libya
12 Malta
13 Morocco
14 Oman

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 Table 3 - Definitions of Economic Variables
Unit of
WDI Definition Data Source
Variable Name Measurement Abbreviation
Growth Computed as the change in the log GDP per capita (constant World Development
2010 US$) (Author computation). GDP per capita is gross Percent Indicators. gr
domestic product divided by midyear population. GDP is the
sum of gross value added by all resident producers in the
economy plus any product taxes and minus any subsidies not
included in the value of the products. It is calculated without
making deductions for depreciation of fabricated assets or for
depletion and degradation of natural resources. Data are in
constant 2010 U.S. dollars.
Change in the log of Consumer price index (2010 = 100) World Development
Inflation (Authors computation). Percent Indicators. inf
Investment Change in the log of Gross capital formation (constant 2010 World Development
US$). Percent Indicators. govexp
Government General government final consumption expenditure (formerly World Development
expenditure (% of general government consumption) includes all government Percent Indicators. govexp
GDP) current expenditures for purchases of goods and services
(including compensation of employees). It also includes most
expenditures on national defense and security, but excludes
government military expenditures that are part of government
capital formation.
Openness Exports of goods and services (constant 2010 US$) Imports of World Development op
goods and services (constant 2010 US$) Percent Indicators.
GDP (constant 2010 US$)

Population Change in the log of Population (Total). World Development popgr

Growth Percent Indicators.

Table 4 - Definitions of Households’ Financial Inclusion Variables

Indicator Definition Periodicity Abbreviation
Bank accounts per 1,000 adults Number of depositors with commercial banks per 1,000 adults. 2001-2015 ba
ATMs per 100,000 adults Number of ATMs per 100,000 adults. 2001-2015 atm
Bank branches per 100,000 adults Bank branches per 100,000 adults 2001-2015 bb
The principal component of the last three indicators (Author acc
acc computation) 2001-2015
Source: World Development Indicators

Table 5 - Definitions of Firms’ Financial Inclusion Variables

Indicator Definition Periodicity Abbreviation
Firms using banks to finance The percentage of firms using fiv
investments (% of firms) banks to finance investments. 2007-2015
The percentage of firms using fwork
Firms using banks to finance bank loans to finance working
working capital (% of firms) capital. 2007-2015
Firms identifying access to Firms identifying access to fc
finance as a major constraint (% finance as a major constraint
of firms) (% of firms) 2007-2015
The principal component of firmacc
the last three indicators
firmacc (Author computation) 2007-2015
Source: World Development Indicators.

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 Table 6 - Definitions of General Access Variables
Indicator Definition Periodicity Abbreviation
Financial Institutions Access Index Number of ATMs per 100,000 adults. 1980-2014 fia
Bank branches per 100,000 adults
The percent of market capitalization outside of top 10 largest 1980-2014 fma
Financial Markets Access Index companies
Total number of issuers of debt (domestic and external, nonfinancial
and financial corporations)
Financial Access General Index Principal component analysis of fia and fma 1980-2014 accgen
Source: Katsiaryna Svirydzenka Introducing a New Broad-based Index of Financial Development, IMF Working Paper No. 16/5, January 12, 2016

Table 7 - Definitions of Governance Indicators

Indicator Periodicity Abbreviation
Control of Corruption 1996-2015 corrup
Government Effectiveness 1996-2015 goveff
Political Stability and Absence of 1996-2015 pols
Violence/Terrorism
Regulatory Quality 1996-2015 regq
Rule of Law 1996-2015 rl
Voice and Accountability 1996-2015 vacc
Governance 1996-2015 gov
Source: World Development Indicators

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Table 8: General Access to Finance & Economic Growth
Dependent variable: Economic Growth
Estimation Method: Dynamic Panel System GMM
Regressors (1) (2) (3) (4) (5) (6)

L.gr 0.240*** 0.263*** 0.250*** 0.249*** 0.245*** 0.244***

(0.0457) (0.0548) (0.0488) (0.0485) (0.0475) (0.0473)
inf -0.0228* -0.0222 -0.0198 -0.0198 -0.0212* -0.0213*
(0.0130) (0.0138) (0.0122) (0.0122) (0.0127) (0.0128)
inv 0.0770** 0.0766** 0.0778** 0.0778** 0.0774** 0.0774**
(0.0349) (0.0355) (0.0350) (0.0349) (0.0349) (0.0349)
govexp -0.0726 -0.0024 -0.0357 -0.000352 -0.0619 -0.0607
(0.0612) (0.0379) (0.0513) (0.000513) (0.0572) (0.0579)
op 0.0059** 0.0054** 0.0057** 0.0056** 0.0058** 0.0058**
(0.0029) (0.0025) (0.0025) (0.0026) (0.0027) (0.0028)
popgr 0.593** 0.524** 0.523** 0.566** 0.565**
(0.241) (0.213) (0.213) (0.228) (0.229)
fia 0.0324** 0.0266***
(0.0126) (0.0102)
fiaMENA -0.00284
(0.0182)
fma 0.0111** 0.0123*
(0.00517) (0.00647)
fmaMENA -0.00520
(0.0131)
accgen 0.0287** 0.0299**
(0.0116) (0.0128)
accgenMENA -0.00695
(0.0167)

Observations 746 746 746 746 746 746

Countries 34 34 34 34 34 34
Chi-Sq. Stat. 375.3 334.97 395.90 334.91 335.92 362.97
Sargan Pvalue [0.091] [0.065] [0.029] [0.032] [0.031] [0.066]
Note: Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

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 Table 9: MENA Total Effects of
Access to Finance
Regressors Total Effect
fia 0.024
(0.019)
fma 0.007
(0.011)
accgen 0.023
(0.015)

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Table 10: General Access To Finance & Economic Growth With Governance
Dependent variable: Economic Growth
Estimation Method: Dynamic Panel System GMM
Regressors (1) (2) (3)

L.gr 0.148** 0.159*** 0.151**

(0.0629) (0.0577) (0.0608)
inf -0.110*** -0.108*** -0.110***
(0.0365) (0.0386) (0.0374)
inv 0.0827** 0.0838** 0.0831**
(0.0381) (0.0392) (0.0384)
govexp -0.0625 -0.0436 -0.0638
(0.0669) (0.0565) (0.0652)
op 0.0193 0.0193 0.0192
(0.0142) (0.0149) (0.0148)
popgr 0.262 0.199 0.236
(0.226) (0.270) (0.244)
fia 0.0414***
(0.0120)
fiagovMENA -0.0100
(0.106)
fma 0.0522***
(0.0188)
fmagovMENA -0.000396
(0.101)
accgen 0.0567***
(0.0154)
accgengovMENA 0.00418
(0.115)

Observations 331 331 331

Countries 32 32 32
Chi-Sq. Stat. Sargan 395.90 335.92 362.97
Pvalue [0.029] [0.031] [0.066]

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Note: Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

Table 11: MENA Total Effects of General

Access to Finance With Governance
Regressors Total Effect
fia*gov 0.031
(0.110)
fma*gov 0.052
(0.102)
accgen*gov 0.061
(0.117)

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 Table 12: HH’s Access to Finance & Economic Growth
Dependent variable: Economic Growth
Estimation Method: Dynamic Panel System GMM
Regressors (1) (2) (3) (4) (5) (6)

L.gr 0.0487 0.0450 0.0470 0.0462 0.0827 0.0775

(0.0634) (0.0636) (0.0615) (0.0622) (0.120) (0.120)
inf -0.0498*** -0.0455*** -0.0436*** -0.0432*** -0.0466*** -0.0488***
(0.00629) (0.00670) (0.00612) (0.00625) (0.00371) (0.00402)
inv 0.168*** 0.169*** 0.168*** 0.168*** 0.191*** 0.189***
(0.0166) (0.0168) (0.0164) (0.0164) (0.0167) (0.0166)
govexp -0.0714** -0.0333 -0.0228 -0.0234 -0.0610 -0.0351
(0.0361) (0.0380) (0.0440) (0.0443) (0.0513) (0.0467)
op 0.0258*** 0.0266*** 0.0238** 0.0230** 0.005 0.004
(0.0001) (0.0001) (0.0111) (0.0111) (0.008) (0.007)
popgr 0.496** 0.416* 0.375 0.332 0.343
(0.207) (0.228) (0.241) (0.429) (0.403)
atm 0.0208*** 0.0180***
(0.007) (0.007)
atmMENA -0.003
(0.0008)
bb 0.0161* 0.0158*
(0.001) (0.0001)
bbMENA 0.0207
(0.0197)
ba 0.003*** 0.003***
(0.001) (0.001)
baMENA -0.001**
(0.0007)

Observations 223 223 226 226 115 115

Countries 19 19 19 19 13 13
Chi-Sq. Stat. 358.3 362.97 377.30 374.92 232.99 227.38
Sargan Pvalue [0.09] [0.066] [0.028] [0.031] [0.026] [0.041]
Note: Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

32

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Table 13: HH’s Access to Finance & Economic Growth
Dependent variable: Economic Growth
Estimation Method: Dynamic Panel System GMM
Regressors (1) (2)

L.gr 0.0805 0.0737

(0.125) (0.126)
inf -0.0471*** -0.0493***
(0.00401) (0.00439)
inv 0.191*** 0.190***
(0.0170) (0.0168)
govexp -0.0717 -0.0450
(0.0547) (0.0519)
op 0.007 0.006
(0.008) (0.008)
popgr 0.390 0.404
(0.470) (0.450)
acc 0.007*** 0.007***
(0.002) (0.002)
accMENA -0.003**
(0.0016)

Observations 113 113

Countries 13 13
Chi-Sq. Stat. 229.93 224.57
Sargan P-value [0.022] [0.0351]
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

33

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 Table 14: MENA Total Effects
of HH’s Access to Finance
Regressors Total Effect
atm 0.015*
(0.009)
bb 0.037*
(0.02)
ba 0.0017**
(0.001)
acc 0.0036**
(0.002)

34

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Table 15: HH’s Access To Finance & Economic Growth With Governance
Dependent variable: Economic Growth
Estimation Method: Dynamic Panel System GMM
Regressors (1) (2) (3) (4)

L.gr -0.0458 -0.0579 0.0895 0.0764

(0.0808) (0.0743) (0.168) (0.167)
inf -0.0837 -0.0738 0.0399 0.0264
(0.0603) (0.0658) (0.0622) (0.0613)
inv 0.183*** 0.174*** 0.155** 0.144**
(0.0265) (0.0221) (0.0660) (0.0625)
govexp -0.112 -0.0017 -0.0978** -0.136***
(0.0708) (0.0741) (0.0482) (0.0454)
op 0.0352*** 0.0265* 0.0105 0.0159
(0.0105) (0.0144) (0.0136) (0.0122)
popgr 0.470 0.329 -0.0997 -0.238
(0.404) (0.503) (0.165) (0.165)
atm 0.0309***
(0.0075)
atmgovMENA 0.0058
(0.0189)
bb 0.0154*
(0.0079)
bbgovMENA 0.0476
(0.0530)
ba 0.0041*
(0.0021)
bagovMENA -0.0012
(0.0012)
acc 0.0101**
(0.0043)
accgovMENA -0.0031
(0.0025)

Observations 101 102 57 56

35

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Countries 11 11 8 8
Chi-Sq. Stat. 160.42 178.19 88.24 86.47
Sargan P-value [0.07] [0.01] [0.33] [0.32]
Note: Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

Table 16: MENA Total Effects of HH’s Access

to Finance with Governance
Regressors Total Effect
atm*gov 0.037**
(0.018)
bb*gov 0.063
(0.056)
ba*gov 0.003**
(0.001)
acc*gov 0.0070***
(0.002)

Table 17: MENA Total Effects of HH’s Access to Finance

With Components of Governance in MENA Countries
Regressors Total Effect
acc *corr 0.0076***
(0.002)
acc* geff 0.0074***
(0.0021)
acc*pols 0.013**
(0.005)
acc *regq 0.0079**
(0.003)
acc* rl 0.0076***
(0.002)
acc*vac 0.007***
(0.002)

36

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Table 18: Firm's Access to Finance & Economic Growth
Dependent variable: Economic Growth
Estimation Method: Dynamic Panel System GMM
Regressors (1) (2) (3) (4) (5) (6)

L.gr 0.135 0.147 0.112 0.130 0.178 0.162

(0.130) (0.124) (0.145) (0.136) (0.128) (0.121)
inf -0.0846*** -0.0916*** -0.0898*** -0.0970*** -0.0806*** -0.0890***
(0.0219) (0.0216) (0.0220) (0.0220) (0.0169) (0.0143)
inv 0.0656*** 0.0714*** 0.0713*** 0.0766*** 0.0679*** 0.0716***
(0.0175) (0.0175) (0.0168) (0.0170) (0.0159) (0.0149)
govexp -0.0184 0.0437 -0.0348 0.0156 0.117 0.0999
(0.0580) (0.0450) (0.0579) (0.0504) (0.101) (0.101)
op 0.005 -0.002 0.001 -0.002 0.007 0.009
(0.009) (0.009) (0.0103) (0.0111) (0.0106) (0.0102)
popgr 0.663** 0.919*** 0.800** 1.067*** 0.998** 1.233***
(0.336) (0.299) (0.348) (0.290) (0.411) (0.411)
finv 0.0732*** 0.0660***
(0.0231) (0.0219)
finvMENA -0.0935***
(0.0202)
fwork 0.0692*** 0.0634***
(0.0223) (0.0203)
fworkMENA -0.0865***
(0.0170)
fc -0.0241 0.003
(0.0567) (0.0644)
fcMENA -0.0778**
(0.0335)

Observations 54 54 52 52 54 54
Countries 18 18 18 18 18 18
Chi-Sq. Stat. 27.69 19.63 27.52 18.99 18.65 19.79
Sargan P-value [0.998] [0.999] [0.998] [0.999] [0.999] [0.999]
Note: Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

37

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Table 19: Firm's Access To Finance & Economic Growth
Regressors (1) (2)

L.gr 0.112 0.129

(0.139) (0.132)
inf -0.0874*** -0.0943***
(0.0220) (0.0215)
inv 0.0685*** 0.0739***
(0.0170) (0.0170)
govexp -0.0479 0.0136
(0.0621) (0.0565)
op 0.003 -0.002
(0.01) (0.01)
popgr 0.745** 1.016***
(0.355) (0.302)
firmacc 0.0804*** 0.0699***
(0.0234) (0.0223)
firmaccMENA -0.0911***
(0.0220)

Observations 52 52
Countries 18 18
Chi-Sq. Stat. 27.33 19.17
Sargan P-value [0.99] [0.99]
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

38

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 Table 20: MENA Total Effects of
Firm’s Access to Finance
Regressors Total Effect
finv 0.03
(0.03)
fwork -0.02
(0.03)
fc -0.08*
(0.05)
firmacc -0.002
(0.004)

39

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Table 21: Firm’s Access to Finance & Economic Growth With Governance
Dependent variable: Economic Growth
Estimation Method: Dynamic Panel System GMM
Regressors (1) (2) (3) (4)

L.gr -0.115 -0.186 -0.184 -0.150

(0.219) (0.276) (0.129) (0.262)
inf -0.150*** -0.156*** -0.166*** -0.144***
(0.0347) (0.0447) (0.0413) (0.0385)
inv 0.101*** 0.107*** 0.119*** 0.0980***
(0.0231) (0.0309) (0.0357) (0.0261)
govexp -0.168 -0.142 0.0168 -0.153
(0.136) (0.0904) (0.112) (0.105)
op 0.0359** 0.0376*** 0.0587*** 0.0330**
(0.0180) (0.0139) (0.0209) (0.0155)
popgr 0.700** 0.834* 1.733* 0.710
(0.334) (0.483) (0.901) (0.476)
finv 0.149**
(0.0685)
finvgovMENA -0.0785***
(0.0189)
fwork 0.0938**
(0.0376)
fworkgovMENA 0.0469
(0.0527)
fc -0.0230
(0.0807)
fcgovMENA 0.125**
(0.0485)
firmacc 0.121**
(0.0471)
firmaccgovMENA -0.006
(0.0378)

Observations 30 28 30 28
Countries 10 10 10 10

40

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Chi-Sq. Stat. 4.31 15.35 14.55 15.40
Sargan P-value [0.97] [0.34] [0.41] [0.42]
Note: Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

Table 22: MENA Total Effects of Firm’s

Access to Finance with Governance
Regressors Total Effect
finv*gov 0.0701
(0.061)
fwork*gov 0.141*
(0.075)
fc*gov 0.102
(0.109)
firmacc*gov 0.115*
(0.0069)

41

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