The Impact of stock Market and Bank Developments on Economic Growth in
Selected MENA Countries
Shereen Abdul-AL and Dr. Mohammad Alawin
University of Jordan, Economics department
Abstract
In the last decade, Middle East and North African (MENA) countries
achieved significant progress in stock market and financial sector reforms,
recognizing that economic growth is often associated with increasing financial
deepening. In light of these reforms and developments, it is important to
investigate the relationship between financial and stock market developments
and economic growth; which will enhance decision maker's ability in taking the
appropriate restructuring procedures.
This study aims to examine the impact of stock market and bank
development on economic growth in six countries in MENA (Jordan, Morocco,
Oman, Tunisia, Egypt and Turkey), during the period 1987-2007. The main
purpose of this study is to provide an in-depth analysis of financial sector
development and its relationship with economic growth through analyzing the
following variables: The Market Capitalization Ratio (MCR), the Value Traded
Ratio (VTR), Turnover Ratio (TR), and Bank Credit Ratio (BCR). The goal of
the study will be achieved through applying the Generalized Method of Moments
(GMM).
Empirical results showed that all financial indicators are significant and
affect economic growth. However, one of the models applied in this study showed
that Bank Credit Ratio has a significant negative effect on economic growth,
indicating that the financial sectors are still underdevelopment and need more
efforts to be able to exert its functions effectively in most of MENA countries.
Key words: Financial System Development, Economic Growth, GMM model,
MENA
1. Introduction
This study examines the recent banking and stock market trends in the
Middle East and North African (MENA) countries; it also tries to explain the
major determinants of their overall economic performance. This study will
provide an in-depth analysis of financial sector development in selected MENA
member countries over the last two decades, with the focus on the stock Market
role.
The endogenous growth literature provides sample evidence that financial
development is a major determinant of economic growth. Theory links these two
factors based on the argument that a well-developed financial system performs
several critical functions to enhance intermediation efficiency. Ultimately,
enhanced financial intermediation efficiency causes economic growth (Pagano,
1993). It thus follows that economic growth rarely occurs without a wellfunctioning financial system. In other words, if the financial system distorts the
allocation of funds in the presence of financial repression, economic growth
cannot be sustained (see Levine et al. 2000; Beck et al. 2000). However, the above
theoretical predictions do not match the empirical facts about the financegrowth relation in transition economies, especially those undergoing acceptable
structural change, such as MENA countries.
Much of the theoretical literature suggests that the functioning of stock
Markets and financial intermediaries can alter the rate of Economic growth.
One way stock markets may affect economic activity is through their liquidity;
more liquid stock markets ease investment in the long run, potentially more
profitable projects, thereby improving the allocation of capital and enhancing
prospects for long- term growth (Levine, 1991). Regarding, however, the growth
effects of greater liquidity, some research show that by reducing uncertainty,
greater liquidity may reduce saving rates enough to slow growth (Bencivenga &
Smith 1991). Besides stock Markets, theoretical literature suggests that the
functioning of financial intermediaries can alter the rate of economic growth by
eliminating liquidity risk, banks can increase investment in the high-return,
illiquid asset and accelerate growth (Bencivenga & Smith, 1991). In addition to
reducing liquidity risk, banks provide vehicles for trading, pooling, and
diversifying risk. The financial intermediary provides risk diversification
services, therefore can accelerate technological change and economic growth
(King and Levine, 1993a).
From this point of view, this paper examines the dynamic relationship
between stock market and bank development on economic growth in MENA
countries. We address this issue using the Generalized Method of Moments
(GMM) through analyzing the relationship between the continuous growth rates
of real GDP and the indicators of stock market and bank development. Stock,
banks and economic growth relationship had taken three trends in this study; we
first examine the relationship between stock market development and economic
growth, the second trend investigates the relationship between bank
development and economic growth, and the third trend combines both stock
market and banks development to show their effect on economic growth. This
study takes into consideration five control variables; inflation, government
consumption, number of population, the degree of openness of an economy, and
the lag of real per capita GDP growth rate.
This paper uses average values and uses instrumental variables to extract
the exogenous component of bank and stock market development, it controls for
biases induced by simultaneity. Furthermore, this research suggests that it is
important to use alternative specifications of the system panel estimator in
drawing results.
The rest of this paper is structured as follows: Section 2 reviews the
related literature on stock markets, banks and economic performance. Section 3
highlights the major developments of economic and banking sector in the
selected MENA countries. Section 4 presents both data and methodology. Section
5 reports the empirical results. Conclusions and recommendations are presented
in Section 6.
2. Related Literature on stock Markets, Banks and Economic performance
This section explains how particular financial system can motivate the
emergence of economic growth. Many researches have found that financial
intermediation promotes economic growth because it allows a higher rate of
return to be earned on capital, and therefore financial markets can help in
attracting foreign investments, which may help in transferring technology and
knowledge to the country (Alfaro, 2006). Thus, financial intermediation and
economic growth are linked in accord with the Gold Smith-McKinnon (1991) on
economic development.1
The financial system facilities trade by extending credit and guaranteeing
payments. In addition, it allocates resources, monitors managers, and can be
used for hedging, diversifying, and pooling of risk, and exerts corporate control
and mobililizing savings, and therefore enhances the local economy (Levine,
1997). Levine, Zervos (1998) have found that both the initial level of stock
market liquidity (measured by the turnover ratio) and the initial level of banking
development (measured by bank credit to the private sector as a share of GDP)
were robustly correlated with future economic growth. They have found that the
stock market size (measured by market capitalization divided by GDP), in
contrast, showed no significant correlation with growth. Their results did not
deal explicitly with the issue of causality. In order to fill this gap, Levine, Loayza
and Beck (2000) found evidence of a strong link between financial development
(measured by private credit) and economic growth.
In a panel study that included both developed and developing countries,
Rioja and Valve (2004) found a non-linear impact of financial development on
growth; poor countries with underdeveloped financial markets gained very little
from small improvements in financial intermediation. For middle-income
countries that had reached a certain threshold of financial development, the
effect was much larger. In addition to cross-country and panel studies, a
1
The essential tent of the Gold Smith–McKinnon hypothesis (1991) is that a low or negative real interest rate will discourage
saving .This will reduce the availability of loans that are able to fund investment, which in turn, will lower the rate of
economic growth.
substantial amount of literature has employed time-series techniques to
investigate the finance growth relationship. Using basically Granger-type
causality tests and vector autoregressive procedures, the majority of these
studies provided support for the hypothesis that causality runs from financial
development to growth (Christopoulos and Tsionas, 2004). Overall, recent
empirical evidence from cross-country, panel and time-series studies suggest
that financial development is an important determinant of economic growth.
A substantive body of research has examined the relative strengths and
weaknesses of bank-based and market-based financial systems in the process of
economic development. Proponents of bank-based systems generally emphasize
the weaknesses of markets in providing the basic functions of financial
intermediation (Stiglitz, 1985). In addition, the other literature on corporate
governance has highlighted the problems of financial markets to monitor and
control managers effectively (see, for example, Shleifer and Vishny, 1996). This
may also have a negative impact on the economic performance in a country.
Advocates of a market-based system, in contrast, claim that powerful banks are
able to extract rents from firms. This reduces the efforts of firms to seek the
most profitable investment opportunities (Rajan, 1992).
John Krainer (2007) suggests that a bank's performance will depend on
the nature of the economic shocks and on its business strategy. Even then, a
bank's risk management and general business practices, as well as its customer
base, may end up being more important than general economic conditions in
accounting for the variability of its performance.
Furthermore, close ties
between banks (bank managers) and firms may impede the functioning of
corporate control mechanisms and may thus exert a negative impact on the
overall resource allocation in an economy.2
3. The Major Developments of Economic and Banking Sector in MENA
Countries
This section briefly describes the financial reforms implemented in
selected MENA member countries during the past few decades, and assesses the
current state of freedom in the financial sector. We present below an overview of
the financial systems in the six selected countries, namely; Amman Stock
Exchange (ASE) in Jordan, Casablanca Stock Exchange (CSE) in Morocco,
Muscat Securities Market (MSM) in Oman, Tunisian Stock Exchange in Tunisia
(TSE), Cairo and Alexandria Stock Exchange (CASE) in Egypt, and Istanbul
Stock Exchange (ISE) in Turkey.
Stock Exchanges ensure the proper operation of its members and protect
the interests of both the public and the investing community. The oldest Stock
Exchange among the selected MENA countries is CASE which was established
in 1883. ASE is known as one of the largest stock exchanges in the region that
permits foreign investment, followed by CSE; which started in the year 1929 and
considered as the third oldest Stock Exchange in Africa. ISE started in 1986. In
the year 1989, both MSM and TSE were established in Oman and Tunisia,
2
For a more extensive review of the arguments for and against a bank-based financial system, see R. Levine, 2004.
respectively. Most countries enjoy a high degree of self-regulation of the stock
exchange markets and include electronic quotation system.
A review of the bank history of liberalization in the MENA countries
reveals that a comprehensive liberalization process did not start before the
1980s. Actually, the liberalization process in the financial sector started, when
authorities took several steps in response to the IMF and World Bank economic
adjustment program. In the early 1990s restrictions on interest rates were
removed, government direct lending was reduced, product deregulation was
expanded, and restrictions on foreign transactions decreased; allowing a higher
degree of foreign investment.
The structure of the banking system countries is introduced in Table 1.
Several empirical studies found that the liberalization reforms implemented in
MENA countries were followed by higher degrees of efficiency and better
management (Lee, 2002). This development in the Banking system led to an
increase in number of loans among banks which can be measured using the
Bank Credit Indicator (BCR), Figure 1 (according to the annual data for the
markets of Jordan, Morocco, Oman, Tunisia, Egypt and Turkey) shows that
BCR had witnessed an increase through the last ten years.
Table (1) Structure of the Banking System in Selected MENA Countries,
2005*
Morocc
Tunisi
Turke
Jordan
Oman
Egypt
o
a
y
Commercial banks
15
16
12
12
34
33
Of which foreign banks
3
9
9
9
15
10
Investment banks
5
8
3
6
15
4
Specialized banks
3
4
2
3
5
6
Islamic banks
2
1
3
2
3
3
Total
25
29
20
23
57
46
Source: Directory of Arab Banks and Financial Institutions.
* Figures are from Central Bank of Jordan, www.cbj.gov.jo
Figure (1) Bank Credit ratios in the six countries over the period 1987-2007*
Source: Directory of Arab Banks and Financial Institutions.
* % BCR = (BC/GDP)*100, Where BCR is the Bank Credit ratio, and BC
is the value of loans made by deposit money bank to the private sector.
4. Data and Methodology
4.1 Data
Our data set includes information about six of MENA countries, and
covers the period from 1978 to 2007. After a tedious selection process by
checking data from different databases for the last twenty years, we have only 6
emerging markets left in our data set: Jordan, Morocco, Oman, Tunisia, Egypt
and Turkey. In order to provide a comprehensive assessment of the role of
market development in the six MENA countries profiled over the past two
decades, three different indicators were considered; market capitalization
(MCR); the value traded (VTR); and turnover (TR). On the other hand bank
credit ratio (BCR) was used as a measure of financial development. Variables
are calculated as a share of GDP. 3
Bank credit ratio was extracted from International Financial Statistics
(IFS) published by International Monetary Fund. Other yearly data are
extracted from DataStream International Financial and Statistical Service
Published
at
Princeton
University
(www.princeton.edu/econlib/econdatabasescompare).
The study uses also the real per capita GDP growth rate (Growth), the
yearly population series, inflation, government consumption, and the degree of
3
See the Appendix (Table A-1) for more details about data description.
openness of an economy; all are taken from International Financial Statistics
published by International Monetary Fund. Summary descriptive statistics are
presented in Table 2.
Table (2) Summary descriptive statistics of bank stock indicators & economic
growth rates
Growth MCR
VTR
TR
BCR
Descriptive statistics
Mean
17.3
721.9
123.5
43.7
6536.2
Median
9.9
34.4
9.3
17.0
51.7
Maximum
143.5
4850.4
1360.2
399.3
80259.5
Minimum
-11.1
1.9
0.1
1.0
14.5
Std. Dev.
24.7
1440.3
233.3
63.7
16986.0
No. of observations
126
126
126
126
126
Growth
1
0.00
0.34
0.41
-0.19
MCR
0.00
1
0.60
-0.21
0.52
VTR
0.34
0.60
1
0.06
0.54
TR
0.41
-0.21
0.06
1
-0.10
BCR
-0.19
0.52
0.54
-0.10
1
Correlations
Growth is the real per capita GDP growth rate, MCR is the market
capitalization ratio, VTR is the value traded ratio, TR Turnover ratio and BCR is
the Bank Credit Ratio. Where all are variables are calculated as a ratio to GDP.
The construction of variables refers to Table A-1. Statistics for all variables are
based on annual data for the markets of Jordan, Morocco, Oman, Tunisia, Egypt
and Turkey (countries in MENA region).
The maximum and minimum values of Growth are 143.5% and -11.1%,
respectively, with a standard deviation of 24.7%. Going back to the original
data, the study shows that Turkey had the maximum Growth of 143.5% among
all MENA countries, and Oman had the minimum Growth of -11.1%. The
turnover ratio ranges from 1% to 399.3% with a standard deviation of 63.7%.
Data shows that Tunisia and Turkey had a TR of 1% and 399%, respectively.
On the other hand, the maximum value for VTR is 123.5% and the maximum
value of bank credit ratio BCR is 80259.5% with a minimum of 14.5%.4
4.2. Methodology
This study will employ the system panel estimator developed by Arrellano
and Bover (1995). As discussed in Arellano and Bond (1998), the one-step system
estimator assumes homoskedastic errors, while the two-step estimator uses the
first-step errors to construct heteroskedasticity-consistent standard errors (e.g.,
White, 1982). Due to the large number of instruments that are employed in the
4
See the Appendix (Table A-2) for more details about data.
system estimator, however, the asymptotic standard errors from the two-step
panel estimator may be a poor guide for hypothesis testing in small samples
where over-fitting becomes a problem. This is not a problem in the one-step
estimator.
To assess the relationship between stock market development, bank
development and economic growth in a panel, we use the Generalized Method of
Moments (GMM) estimators developed for dynamic panel models by Arrellano
and Bond (1991) and Arrellano and Bover (1995). We can write the traditional
cross-country growth regression as follows:
(yi
t
–
yi
t-1)
=α
yi,t–1
+
β'
Xi,t
+
εi,t
(1)
where y is the logarithm of real per capita GDP, X represents the set of
explanatory variables, other than lagged per capita GDP and including our
indicators of stock market and bank development, ε is the error term, and the
subscripts i and t represent country and time period, respectively.
Arrellano and Bond (1991) proposed to difference equation (1) as follows:
(yi,t ‫ ــ‬yi,t–1) – (yi,t–1 ‫ ــ‬yi,t-2) = α (yi,
t–1
‫ ــ‬yi,
t–2)
y + β' (Xi,t ‫ ــ‬Xi,t–1) + (εi,t ‫ ــ‬εi,t–1)
(2)
Differencing introduces a new bias; by constructing the new error term,
εi,t ‫ ــ‬εi,t−1 that is correlated with the lagged dependent variable, yi,t−1 ‫ ــ‬yi,t−2. Under
the assumptions that: (a) the error term ε, is not serially correlated, and (b) the
explanatory variables X, are weakly exogenous (i.e., the explanatory variables
are assumed to be uncorrelated with future realizations of the error term).
Arrellano and Bond proposed the following moment conditions.
E[yi, t–1 ,(εi,t ‫ ــ‬εi,t–1)]=0
(3)
E[Xi, t–1 ,(εi,t ‫ ــ‬εi,t–1)]=0
(4)
Using these moment conditions, Arellano and Bond (1991) proposed a
two-step GMM estimator. In the first step the error terms are assumed to be
independent and homoskedastic across countries and over time. In the second
step, the residuals obtained in the first step are used to construct a consistent
estimate of the variance-covariance matrix, thus relaxing the assumptions of
independence and homoskedasticity. The two-step estimator is more efficient
relative to the first step estimator. We refer to the GMM estimator based on
these conditions as the difference estimator. This is the estimator that Rousseau
and Wachtel (2000) used with annual data to examine the relationship between
stock markets, banks, and economic growth.
Then, we use the moment conditions presented in equations (3) and (4) and
employ the system panel estimator to generate consistent and efficient parameter
estimates.
The consistency of the GMM estimator depends on the validity of the
assumption that the error terms do not exhibit serial correlation and on the
validity of the instruments. To address these issues, we use two specification tests
suggested by Arellano and Bond (1991), Arellano and Bover (1995), and Blundell
and Bond (1998). The first is Sargan test of over-identifying restrictions, which
tests the overall validity of the instruments by analyzing the sample analog of the
moment conditions used in the estimation process. The second test examines the
hypothesis that the error term εi,t is not serially correlated. We test whether the
differenced error term is second-order serially correlated (by construction, the
differenced error term is probably first-order serially correlated even if the
original error term is not). Failure to reject the null hypotheses of the test gives
support to our model.
5. The Results
System Estimator: One- and Two-Step Results
This paper uses three alternative panel specifications in order to analyzes
the effect of stock market development and bank development on economic
growth in six countries in MENA region during the period 1987-2007. The
results in Table 3 show that (i) the development of stock markets and of banks
have both a statistically and economically large impact on economic growth, and
(ii) The p-values in parentheses in Panels A are from the one-step estimator,
while in Panels B are from the two-step estimator. Table 3 indicates the
significance of stock market and bank development for both the two-step and
one-step estimators.
Table (3) Statistical Analysis using the GMM in MENA countries
Stock
Market Bank
Stock
Market
and
development
Economic Growth
Panel A
& development & Bank development &
Economic
Economic Growth
Growth
Panel B
Panel A Panel B Panel A
Panel B
Constant 4.321894
(0.001)*
-18.86775
(0.002)*
MCR
0.01057
(0.001)*
-0.06902
(0.009)*
1.02202
(0.000) *
VTR
TR
-0.018845
(0.005)*
0.159231
(0.001)*
0.150654
(0.103)
15.94788 8.44933
(0.001)* (0.000)*
BCR
0.003829 -7.03005
(0.2)
(0.007)*
*, ** Significant at 0.05 and 0.10 respectively
7.2015
(0.001)*
3.72601
(0.000)*
0.02102
(0.000)*
0.13052
(0.000)*
0.03175
(0.000)*
0.00216
(0.000)*
-0.00518
(0.116)
0.12487
(0.000)*
0.13375
(0.100)* *
-0.00093
(0.000)*
The Turnover Ratio and Bank Credit Ratio both enter significantly (at
the one-percent level) and positively in all regressions using the one-step
estimator. The one-step estimator, however, indicates that Turnover ratio does
not always enter with a p-value below 0.10. Specifically, it does not enter
significantly when controlling for either trade openness or inflation.
However, even with the one-step estimator, the financial indicators always
enter jointly significantly. Our specification tests indicate that we cannot reject
the null-hypothesis of no second-order serial correlation in the differenced errorterm and that our instruments are adequate.
The two-step results in Table 3 shows a significant negative relationship
between BCR and growth. This result is consistent with previous studies for
empirical evidence of the negative impact of financial development according to
King and Levine (1993). Specifically, this result indicates, in some cases,
improvements in resource allocation would not necessarily lead to higher
economic growth. In fact, under certain conditions, higher returns on savings
that result from financial sector development can reduce savings rates to such an
extent that overall growth slows5. Panels B in table 3, shows also a significant
and positive relationship between TR and growth. This result is consistent with
different studies (Levine and Zervos 1998, Levine and Beck 2002).
The two-step results in Table 3 are not only statistically, but also
economically significant. These results focus on economic growth; for example, if
Jordan’s turnover ratio had been at the average of the MENA countries 42%
instead of the actual 16% during the period 1987-2007, it would have grown 0.6
percentage points faster per year. These results suggest that both bank and stock
market development have an economically large impact on economic growth.
Both bank development and stock market development enter individually
significantly. 6
Overall, these results suggest an independent link between growth and
both stock market (Turnover, Value Traded) and bank development (Bank
5
The overall impact of higher returns on the savings rate depends on the relative strength of the implied income and
substitution effects that work in different directions.
6
These results are not fully consistent with Rousseau and Wachtel’s (2001) findings because they find that both bank and
stock market development enter individually significantly, not just jointly significantly. Their empirical model differs from
ours along several dimensions. First, they use different financial development indicators: M3/GDP to measure financial
intermediary development, and stock market capitalization and trading relative to GDP (deflated by market price indices) to
proxy for stock market development. This study uses credit to the private sector as a share of GDP to measure bank
development, and we use trading relative to market size to measure stock market activity while simultaneously controlling for
market price changes. Second, our sample period is different. Rousseau and Wachtel (2001) estimate their model over the
1980-1995 period, this research beside selecting the MENA markets, it was able to extend the sample period back to 1987 and
forward to 2007.
Credit). Therefore, two-step system estimator seems to offer a particularly useful
assessment of the stock market, bank and growth relationship.
6. Conclusions and Recommendations
This study analyzes the effect of stock market development and bank
development on economic growth in six countries in MENA region during the
period 1987-2007. The study uses GMM method. In sum, the results strongly
reject the notion that overall financial development is unimportant for economic
growth. Using three alternative panel specifications, the data reject the
hypothesis that financial development is unrelated to growth. Stock market
development and bank development jointly enter all of the system panel growth
regressions significantly using alternative conditioning information sets and
alternative panel estimators. The data are consistent with theories that
emphasize an important positive role for financial development in the process of
economic growth.
This study also assessed the independent impact of both stock market
development and bank development on economic growth. In general, we find
across estimation procedure and across different control variables that both
stock markets and banks enter the growth regression significantly. For instance,
with the traditional two-step system estimator, both stock market liquidity and
bank development each enter the growth regressions significantly regardless of
the control variables. Similarly, with the Calderon, Chong and Loayza (2000)
two-step alternative estimator that reduces the over-fitting problem of the twostep estimator but obtains heteroskedasticity consistent standard errors, we find
that both stock market liquidity and bank development enter all of the growth
regressions significantly except for one.
The findings results suggest that banks provide different financial services
from those provided by stock markets in the selected MENA countries, which
provides an evidence of the complementary relationship between stock markets
and banks. The result is consistent with results in previous research (Levine and
Zervos 1998, and Levine and Beck 2002).
The negative association between financial development and economic
growth (using the one-step estimator) can be explained by the threshold effects,
which indicates that most of the MENA countries are still in the transition
period and need to reach a certain level of financial development (a threshold)
before there is a significant effect on economic growth and this is the case in
most of Arab countries.
Further research on this topic is important. Researchers could extend the
sample by using sufficiently low-frequency data; despite that the two-step system
estimator seems to offer a particularly useful assessment of the stock market,
bank and growth relationship; two-step's results can break down the relation
between bank credit and growth when moving to annual data. Given recent
work, however, this conclusion is not surprising. Loayza and Ranciere (2002)
find that short-run dynamics in bank credit are good predictors of banking
crises and slow growth, while high levels of bank credit over the long-run are
associated with economic growth.
In addition to extending research, excessive efforts should concentrate on
activating the credits for private sector in MENA region, by setting policies
encourages private sector to involve and participate in economic development
for these countries. That is, to decrease the interest rates on loans to allow and
encourage the private sector to involve in the economic development process that
will be reflected on the economic growth in these countries.
References
Achy, L. 2003. "Financial liberalization, saving, investment, and growth in
MENA countries". Institut National".
de Statistique et d’Economie Appliquée (INSEA) Morocco. Paper downloaded
on 6 July 2005.
Available at: http://econwpa.wustl.edu/eps/fin/papers/0411/0411004.pdf
Allen, D., and L. Ndikumana. 2000. "Financial intermediation and economic growth
in Southern Africa".
Journal of African Economies, vol. 9, number 2, pp.132-160.
Arestis, P. 2003." Financial sector reforms in developing countries with special
reference to Egypt".
Levy Economics Institute of Bard College, Working Paper No. 383.
Arestis, P., and P. Demetriades. 1997." Financial development and economic
growth: assessing the evidence".
The Economic Journal, 107 (May): 783-799.
Barth, J. R., D. E. Nolle, H. L. Root, and G. Yago. 2000. "Choosing the Right
Financial System for Growth".
Beck, T., and R. Levine. 2004. "Stock markets, banks, and growth: panel evidence".
Journal of Banking & Finance, 28, 423-442.
Ben Naceur, S., and S. Ghazouani. 2003. "Stock markets, banks, and growth in
some MENA region countries".
Laboratoire d’Econométrie Appliquée, Faculty of Economics and Business
Administration, Université Libre de
Tunis; Laboratoire d’Econométrie Appliquée and Institut Supérieur de
Comptabilité & d’Administration des
Entreprises, Campus Universitaire de Manouba. Paper downloaded on 6 July
2005.
Available
at:
http://www.erf.org.eg/tenthconf/Financial_Markets_background/Bennaceur_Ghazo
uani.pdf.
Berger, A., I. Hasan, and L. Klapper. 1999. "Further Evidence on the Link between
Finance and Growth:
An International Analysis of Community Banking and Economic Performance".
Wharton Financial Institutions
Center, Berkley Research Center, Stern School of Business, and development
Research Group.
Boulila, G., and M. Trabelsi. 2004. "The causality issue in the finance and growth
nexus: empirical evidence from
Middle East and North African countries". Faculté des Sciences Economiques et
de Gestion de Tunis, Institut
des Hautes Etudes Commerciales de Carthage. Paper downloaded on 5 July 2005.
Available at: http://gremars.univ-lille3.fr/seminaires/S0405/trabelsi.pdf
Brownbridge, M., and C. Kirkpatrick. 2000." Financial Regulation in Developing
Countries. Institute for
Development Policy and Management", University of Manchester, Working
Paper Series No.12.
Caprio, G., P. Honohan, O. Bandiera, and F. Schiantarelli. 1999." Does Financial
Reform Increase or Reduce
Savings?" World Bank Policy Research Working Paper No. 2062.Central Bank of
Oman. 2004. Annual Report.
Available at: http://www.cbo-oman.org/annual/2004/ENAnnualReport2004.pdf
Christopoulos, D., and E. Tsionas. 2004. "Financial development and economic
growth: evidence from panel unit
root and cointegration tests". Journal of Development Economics, 73, 55-74.
Creane, S., R. Goyal, A Mobarak, and R. Sab. 2004. "Financial Sector Development
in the Middle East and North
Africa". International Monetary Fund, Middle East and Central Asia
Department, IMF Working Paper
WP/04/201.
Darrat, A., and M. Haj. 2002. Economic Fluctuations in MENA: Does Financial
Market Development Matter?
Department of Economics and Finance, College of Administration and Business,
Louisiana Tech University.
De Gregorio, J., and P.E. Guidotti. 1995. "Financial development and economic
growth". World Development,
23(Mar.): 433-438.
Demirgüc-Kunt, A., and R. Levine. 1999. "Bank-based and Market-based Financial
Systems: Cross-country
Comparisons". The World Bank, Policy Research Working Paper 2143.
Demetriades, P., and K Hussein. 1996. "Does financial development cause economic
growth?" Time-series
evidence from 16 countries. Journal of Development Economics, 51: 387-411
Eltony, M. 2003. "Quantitative Measures of Financial Sector Reform in the Arab
Countries". Arab Planning
Institute (API), Working Paper Series 0303, Kuwait.
Greenwood, J., and B. Smith. 1997. "Financial markets in development, and the
development of financial
markets". Journal of Economic Dynamics and Control, 21, 145-181.
Hakura, D. 2004. "Growth in the Middle East and North Africa". International
Monetary Fund, Research
Department, IMF Working Paper WP/04/56.
Isik, I., and M. K. Hassan. 2003. "Financial deregulation and total factor
productivity change: an empirical study
of Turkish commercial banks". Journal of Banking & Finance, 27 (8): 1455-1485.
International Financial Statistics published by International Monetary Fund - April
2008.
Kar, M, and E. Pentecost. 2000. "Financial Development and Economic Growth in
Turkey: Further Evidence on
The Causality Issue", Loughborough University, Department of Economics,
Economic Research Paper.
King, R., and R. Levine. 1993b. "Finance and growth: Schumpeter might be right".
The Quarterly Journal of
Economics, MIT Press, vol. 108 (3), pp. 717-37.
Levine, R., and S. Zervos. 1996. "Stock Market Development and Long-Run
Growth". World Bank Policy
Research Working Paper 1582.83
Levine, R. 1997. "Financial development and economic growth: views and agenda".
Journal of Economic
Literature 35: 688-726.
Levine, R., and S. Zervos. 1998. "Stock markets, banks, and economic growth". The
American Economic Review,
88, 537-558.
Levine, R., N. Loayza, and T. Beck. 2000. "Financial intermediation and growth:
causality and causes". Journal
of Monetary Economics 46 (August) pp. 31-77.
Levine, R. 2002. Bank-based or Market-based Financial Systems: "Which Is Better?
National Bureau of
Economic Research", NBER Working Paper 9138.
Levine, R. 2004. Finance and Growth: Theory and Evidence. National Bureau of
Economic Research", NBER
Working Paper 10766. Available at: http://www.nber.org/papers/w10766.
Lynch, D. 1996. "Measuring financial sector development: a study of selected
Pacific countries". Developing
Economies, 34 (1), 3-33.
Nashashibi, K., M. El Hage, and A. Fedelino. 2001. "Financial Liberalization in
Arab Countries". Edited by
Zubair Iqbal., Macroeconomic Issues and Policies in the Middle East and North
Africa. International Monetary
Fund, Washington D.C.
Rioja, F., and N. Valev. 2004. "Finance and the sources of growth at various stages
of economic
development".Economic Inquiry, 42, 127-140.
Rivlin, P. 2003. "Egypt’s demographic challenges and economic responses". Middle
East Review of International
Affairs (MERIA), vol. 7, No. 4.
Stulz, R. 2000. "Does Financial Structure Matter for Economic Growth? A
Corporate Finance Perspective". Reese
Chair of Banking and Monetary Economics, Ohio State University, and Research
Associate,National Bureau of
Economic Research (NBER).
Tadesse,
S.
2001.
"Financial
Architecture
and
Economic
Performance:
International Evidence". William
Davidson Working Paper 449.
The Central Bank of Jordan: www.cbj.gov.jo
The Central Bank of Oman: www.cbo-oman.org
The Central Bank of Egypt: www.cbe.org.eg
Xu, Z. 2000. "Financial development, investment, and economic growth". Economic
Inquiry, 38, 331-344.
www.datastream.com
Appendix
Table (A-1) Descriptions and sources of the variables
Variable
Descriptions and data sources
Dependent variable
GDP growth rate (PCGDP) PCGDP = [(GDP t – GDP t-1)/GDP t-1]*100 Subscript
t denotes time period t. Where PCGDP is the real per capita
GDP growth rate, GDP t : is the per capita GDP in current year t-1. And GDP t-1
is the per capita GDP in the (t-1) previous year . The GDP time series are
constant prices and, for the markets of Jordan, Morocco, Oman, Tunisia,Egypt
and Turkey (countries in MENA region), all series are seasonally adjusted. The
yearly GDP series are take from International Financial Statistics (IFS),
DataStream International and from International Finance Corporation
Independent variable
A) Stock Market Indicators
Indicators of market size
Market capitalization ratio (MCR) %MCR = (MCi /GDP) *100 Where
MCi Subscript I denotes country. MC i: is the value of listed domestic shares on
the market. This indicator is expected to be positively correlated with the ability
to mobilize capital, diversify risk. The data are taken from International
Financial Statistics (IFS), Datastream International, and from the IFC.
Indicators of market liquidity:
Turnover Ratio (TR) %TR = (VT/MC)*100 Where TR is Turnover ratio,
VT is the value of trade in domestic shares. MC is the value of listed domestic
shares. This Indicator measures the value of equity transactions relative to the
size of equity
market and it complements the measure of stock market size since markets
could be large and not active.
Turnover also complements the measure of value traded since markets could
be small but liquid. In addition,
High turnover ratio will be used as an
indicator of low
Value traded ratio (VTR) %VTR = (VT/GDP)*100 Where VTR is Turnover
ratio, VT is the value traded ratio, where domestic VT is the
value of trade in domestic shares. And GDP as
mentioned above is VTR. This measures the value of equity
transactions, it
captures trading relative to the size of the economy, turnover measures
complements the measure of value traded, thus, small liquid market will have
higher turnover and smaller value traded.
B) Bank Development Indicators
Bank Credit Ratio (BCR) %BCR = (BC/GDP)*100, Where BCR: Bank Credit
Ratio. BC is the value of loans made by deposit money bank
to the private
sector. And GDP is gross domestic product. Bank credit ratio equals the value of
loans made by
deposit money banks to the private sector divided by GDP.
Bank Credit ratio improves upon traditional financial depth ratio measures of
banking development by isolating credit issued by banks to the private sector as
opposed
to credit issued to governments or other intermediaries, and by
identifying credit to the private sector as opposed
governments.
Control Variables
Macroeconomic Stability Indicators
to the credit issued to the
Inflation
The yearly rate of inflation equals to the change in consumer price
index.
Population Total population over the period of (1987-2007) for each country.
Government Consumption Ratio %GCR= (GC/GDP)*100, Where GCR is the
government consumption ratio. GC is the government consumption.
And GDP is the gross domestic product. So GCR is equal to the government
consumption as a share of GDP.
The Degree of Openness of % OTR = (EX+IM)/GDP * 100, Where OTR is the
openness of trade ratio, EX is exports of goods and service,
an Economy while IM is imports of goods and service. And GDP is gross
domestic product. This measure is used, as a control variable since the study
believes that openness of trade is an important determinant of economic growth.
Table (A-2) Stock Market and Financial indicators over the period (1987-2007)
Total
Market
Capitalization
198
198
199
7
9
1
895
731
651
4
9
1
10.
17.
6
5
Average
Turnover /GDP
9.4
1993
6393
21.4
199
5
489
3
50.6
1997 1999 2001 2003 2005 2007
4961 4260 2539 1464 1209 1941
45.9
30.4
63.3
67.5
78.5
90
Total
Value
Traded
574
752
172
.3
3
774
903
1005 104
1042 1191 1382 1494 1569 1843
3
4
0
0
208
336
6
4
22.
17.
1
8
1599
107
688.
567.
7
0
7
545
556
563
541
Average
Financial
Depth 203
/GDP
7
Average
Bank 180
Credit /GDP
.9
Average Real Per
Capita GDP
Source:
9.4
International
33
4186
18.5
Financial
485
8
24.0
3
8
9
9
7953 8890 9089 9263
20.7
Statistics,
13.4
12.0
DataStream
11.1
6
1028 1342
8
1
11.8
11.0
International
and
International Finance Corporation
Table (A-3) Real Per Capita GDP in the six countries over the period 1987-2007
Year/
Jordan
Morocco
Oman
Tunisia
Egypt
Turkey
Total
Country
1987
1988
1989
1990
1991
1992
growth
rate%
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2.75
16.29
-2.81
7.78
19.55
73.65
117.21
0.00
3.23
6.42
11.76
10.73
24.68
75.92
132.73
50.41
13.83
9.74
24.68
12.78
25.13
72.91
159.08
62.65
7.14
13.88
-2.94
11.22
17.07
60.31
106.67
21.22
22.06
0.69
9.79
13.94
23.64
73.52
143.65
78.13
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
6.87
2.45
0.33
6.98
13.08
81.26
110.98
26.08
10.06
11.82
3.41
7.85
11.25
95.19
139.58
52.55
11.02
1.03
6.84
7.83
16.57
100.66
143.96
34.94
4.18
13.07
10.69
11.81
12.45
90.30
142.50
29.06
4.59
-0.33
3.66
9.61
11.73
95.21
124.46
23.98
9.20
8.06
-11.06
7.96
12.13
143.46
169.74
59.89
3.00
0.46
11.54
9.36
7.03
48.99
80.37
-37.17
3.82
2.49
26.46
8.02
10.57
59.33
110.70
76.78
6.09
8.18
0.41
7.90
5.47
44.14
72.19
11.61
6.76
3.81
1.89
4.06
5.63
45.90
68.04
33.11
6.40
5.46
7.18
7.61
10.19
29.76
66.60
30.42
11.92
5.76
13.61
9.31
16.24
22.92
79.78
75.10
10.52
3.14
24.59
5.68
10.96
16.08
70.97
60.23
11.81
10.11
12.99
7.17
14.71
16.87
73.65
81.12
9.19
4.91
12.99
6.27
18.37
14.43
66.17
66.93
Table (A-4) Value Traded Ratio in the six countries over the period 1987-2007
Year/
Jordan
Morocco Oman
Tunisia
Egypt
Turkey
Total
Country
growth
rate%
1987
18.37
399.26
1.66
0.07
0.46
154.54
574.35
0.00
1988
14.34
369.17
1.40
0.15
0.19
78.16
463.41
-19.32
1989
26.88
373.01
0.97
0.33
0.11
351.05
752.35
62.35
1990
14.74
365.48
2.67
0.18
0.13
1.49
384.69
-48.87
1991
14.60
345.09
3.46
0.25
0.23
1360.22
1723.86
348.12
1992
36.48
368.51
2.28
0.24
0.14
749.15
1156.80
-32.89
1993
35.69
386.77
3.89
0.31
0.11
1172.73
1599.50
38.27
1994
14.74
371.91
4.87
1.87
0.43
560.74
954.57
-40.32
1995
10.97
395.81
3.98
3.89
0.33
662.06
1077.03
12.83
1996
6.05
376.41
9.28
1.47
1.07
249.33
643.61
-40.24
1997
9.75
406.08
63.72
1.24
2.29
204.97
688.04
6.90
1998
11.64
404.06
54.34
0.83
1.75
97.52
570.14
-17.14
1999
9.48
442.72
33.21
1.70
2.94
77.66
567.71
-0.43
2000
6.93
471.47
22.82
2.35
3.27
56.40
563.24
-0.79
2001
6.22
472.36
21.64
2.89
3.68
39.13
545.93
-3.07
2002
5.53
490.22
20.18
3.47
3.24
26.82
549.46
0.65
2003
4.92
498.22
17.84
3.86
2.72
29.09
556.66
1.31
2004
4.15
502.63
14.83
4.12
2.15
25.95
553.83
-0.51
2005
3.53
517.90
11.20
4.45
1.77
24.32
563.18
1.69
2006
2.96
498.12
9.29
4.67
1.39
22.50
538.94
-4.30
2007
2.53
501.31
7.68
4.88
1.05
21.13
538.58
-0.07
Table (A-5) Bank Credit Ratios in the six countries over the period 1987-2007
Year/
Jordan
Morocco Oman
Tunisia
Egypt
Turkey
Total
growth
Country
rate%
1987
59.03
906.18
20.75
49.99
28.88
20.67
1085.50
0.00
1988
62.21
6948.95
23.72
51.37
28.13
17.33
7131.71
557.00
1989
64.53
12327.13 22.86
58.89
26.60
16.64
12516.64 75.51
1990
62.16
16020.58 20.61
55.08
25.45
16.67
16200.55 29.43
1991
62.24
20011.55 21.44
53.76
22.06
17.17
20188.22 24.61
1992
55.77
23185.13 21.51
54.00
22.27
17.94
23356.63 15.69
1993
60.92
24938.40 22.65
53.93
23.45
18.12
25117.47 7.54
1994
66.02
25183.49 24.71
53.81
27.90
15.94
25371.88 1.01
1995
68.70
28950.69 25.58
54.39
32.73
18.49
29150.57 14.89
1996
69.19
28349.35 26.64
49.16
36.53
22.83
28553.71 -2.05
1997
69.82
47497.33 35.65
50.43
41.18
26.30
47720.72 67.13
1998
68.96
48720.10 47.33
51.16
46.55
17.19
48951.28 2.58
1999
71.19
53106.57 46.09
51.28
52.00
16.63
53343.75 8.97
2000
71.87
56343.98 36.78
58.97
51.95
17.75
56581.30 6.07
2001
75.49
54289.37 39.13
60.59
54.93
15.35
54534.86 -3.62
2002
72.53
54037.16 38.55
61.18
54.66
14.52
54278.59 -0.47
2003
70.59
55343.15 36.53
60.53
53.90
14.55
55579.26 2.40
2004
74.47
55992.07 34.25
60.98
54.04
17.28
56233.09 1.18
2005
87.73
61476.55 30.90
62.49
51.17
21.06
61729.89 9.78
2006
97.81
65143.19 29.34
63.10
49.29
25.94
65408.67 5.96
2007
101.66
80259.47 27.96
63.81
46.36
29.59
80528.86 23.12
Appendix: Shows the results through using the GMM method.
Table (A-6) Regression results for growth per capita GDP on two Market indicators:
Market Capitalization and Value Traded Ratio
Variable
Coefficien Std.
t
t-Statistic Prob.
Error
C
-18.86775 8.421811 -2.240344 0.0269
MCR
0.010577 0.003322 3.183677
VTR
-0.069029 0.026223 -2.632373 0.0096
TR
1.022024 0.251547 4.062946
R-squared
-4.771595
Mean
R- -4.913519
squared
S.D.
0
dependent 24.6872
var
S.E. of regression 60.03377
4
Sum
squared 439694.
resid
Durbin-Watson
0.358864
0.0001
dependent 17.2939
var
Adjusted
0.0018
5
J-statistic
stat
0.01548
0
Table (A-7) Regression results for growth per capita GDP on the financial indicator:
Bank Credit Ratio
Variable
Coefficien Std.
t
t-Statistic Prob.
Error
C
8.449334 0.811493 10.41208
BCR
-7.030051 2.56E-05 -2.740876 0.0070
R-squared
-0.127576
Mean
var
0.0000
dependent 17.2939
0
Adjusted
R- -0.136670
squared
S.D.
dependent 24.6872
var
S.E. of regression 26.32023
4
Sum
squared 85901.5
resid
Durbin-Watson
1.296704
9
J-statistic
0.05676
stat
3
Table (A-8) Regression results for growth per capita GDP on four market and
financial indicators: Market Capitalization, Value Traded Ratio, Turnover Ratio and
Bank Credit Ratio
Variable
Coefficien Std.
t
t-Statistic Prob.
Error
C
3.726015 2.652004 1.404981
MCR
-0.005185 0.003277 -1.581999 0.1163
VTR
0.124873 0.032128 3.886755
0.0002
TR
0.133758 0.085848 1.558073
0.1028
BCR
-0.000934 0.000223 -4.198685 0.0001
R-squared
0.201651
Mean
dependent 17.2939
var
Adjusted
R- 0.175259
squared
S.D.
0
dependent 24.6872
var
S.E. of regression 22.41978
Sum
resid
Durbin-Watson
stat
1.407322
0.0000
J-statistic
4
squared 60820.2
4
0.01546
1
*Where, the dependent variable is PCGDP. The Instrumental variables are: real
per capita GDP growth rate (PCGDP), and (PCGDPt-1), the yearly population series
(POP), inflation (INF), government consumption (GC), and the degree of openness
of an economy (OTR).