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12 Mar
2020

Determinants of Stock Markets Development | Good Grade Guarantee!

Macroeconomics Determinants of Stock Markets Development in Selected African Countries
by
Catia Castelo Vera Cruz
A research report submitted to the School of Banking and Finance, University of International Business and Economics, Beijing, in partial fulfillment of the requirements of the degree of Bachelor in International Finance and Investments Concentration
China
Professor Chu Yin Xiao
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Table of Contents
Abstract…………………………………………………………………………………………………………………………………. iii
LIST OF TABLES and FIGURES …………………………………………………………………………………………..iv Chapter 1:Introduction ……………………………………………………………………………… 1
1.1Background …………………………………………………………………………………………………………….. 1 1.2Motivation ……………………………………………………………………………………………………………….. 2
1.2. ProblemStatement ………………………………………………………………………………………………. 3 1.3 Objectives and Hypothesis…………………………………………………………………………………… 4 1.4 Outline of the Study……………………………………………………………………………………………….. 5
Chapter 2 Literature Review ……………………………………………………………………………………………… 6 2.1 Introduction ……………………………………………………………………………………………………………. 6 2.2 Does finance cause economic growth? ……………………………………………………………… 7
Chapter 3: The Role of Financial Intermediaries in the Economy………………………..17 3.2 The Role of Financial Intermediaries: Theoretical Background ……………….20 3.3 The Special Role of the Stock Market ……………………………………………………………….24 3.4Equity Markets Development: Opposing Views ……………………………………………..25 3.5 Hurdles to Stock Market Development in Africa ……………………………………………27
Chapter 4 Research Methodology …………………………………………………………………………………… 31 4.1 Data Collection Procedures …………………………………………………………………………………31 4.2 Econometric techniques …………………………………………………………………………………….. 31 4.3 Estimation Techniques………………………………………………………………………………………..33 4.6 Conclusion………………………………………………………………………………………………………………36
Chapter 5: Data Analysis……………………………………………………………………………………………….37 5.1 Descriptive Statistics……………………………………………………………………………………….37 5.2 Unit Root Tests ………………………………………………………………………………………………… 39 5.3 Impulse Responses, Variance Decomposition and Causality Tests………….40
Chapter 6- Discussion of Findings and Policy Recommendations …………………………. 55 6.1 Summary of Results …………………………………………………………………………………………….55 6.2 Policy Recommendations ………………………………………………………………………………. 61 Chapter 7: Conclusion ……………………………………………………………………………………………….63 8. References ……………………………………………………………………………………………………………..64 Appendix: 1 ………………………………………………………………………………………………………………… 67
Abstract
The stock market in African countries is rarely mentioned among the world, which has created a big controversy and a doubt about its impact to the economy growth of the country. Moreover there are frequent questions about the effect of macroeconomics variables on the development of the stock market thus, in this research paper is made an investigation concerning to the effects of macroeconomics variables and their role of stock market in African countries by estimating a dynamic panel data analysis of sixteen years, from 2000 to 2015.
Similar researches were made in other developed countries, for example, Jordan, Ghana, South Africa, Malaysia, Singapore, China, countries in Latin America and European Zone and in MENA regions (Middle East and North African countries) but, none of the has ever covered studies or any type of investigations in the African continent as a whole, which instigate in me the curiosity to investigate the main reasons of the backward position of the African stock markets compared to the rest of the world.
Compiled with previous research papers, it was found that income, monetization ratio, liquidity ratio, saving rate and inflation have some effect on stock market development. Monetization ratio and inflation have negative effects while income, liquidity ratio and saving rate have positive effects on stock market development. Liquidity ratio emphasizes that the stock market liquidity help to improve stock market development. Furthermore, income and saving rate are correlated with stock market growth. Hence if we assume that this correlation is true, does it really applies to most of the countries in general?
In order to respond to this question, and what really drives the stock market development in those areas, I conducted a the research by using a dynamic panel data model using on both macroeconomics and potential institutional determinants that have an impact on the development of the stock markets in African countries.
Key words: Stock market development, macroeconomics determinants and dynamic panel data model
1. Introduction
With the world opening trade on the flows of goods, services and capital among countries, we could notice an accelerated development on the financial and economic globalization. As a result of that, in recent years, the world has been observing an increasing number of stock exchanges in emerging-market and an establishment of dedicated market segments for small and medium sized enterprises by developed economies countries. Global stock market capitalization increased to about 114% of world GDP in 2007 from about 27% world GDP in 1975. Global stock market capitalization was about 94% of world GDP as of 2014, although late financial crises led substantial contractions in global stock market capitalization (Ylmaz Bayar, 2016).
World Stock Market Capitalization (% of the world GDP)
Chart 1
Therefore, this accelerated growth has been beneficial to these developing economies because it helps to expand access to equity finance for relatively small but growing firms with the potential, as a group, to significantly contribute to economic growth and employment (Deniz Şükrüoğlu& Halime Temel Nalin, 2013).
Along with the openings to the world, recent researches have conferred that increases in macroeconomics variables have a compact impact on the development of stock market performance. Multiples studies have been made on this correlation. According to some sources, we could say that, just at the beginning of year 2019, there are around 30 dedicated SME boards in emerging-market and developing economies which majority has been established in the last decade or so.
It is agreed that stock markets have a significant role on the economic growth, which if we look at the financial sector development, we can find a thin and straight relationship of functionality between both. By this, we can claim that the financial system facilitate on processes such as the trading, hedging, diversifying, pooling risk and mobilize saving, and also, the financial system also helps on problems of asset allocation. Well functioning the financial regulation and government management provide financial sector development.
As a proof for this relationship, many researches have made deep analysis on both variables, for example, King and Levine (1993), Atje and Jovanovic (1993), Demirguc-Kunt and Levine (1996), Singh (1997), Levine (1997) and Levine and Zervos (1998) reviewed in their studies that stock market development is deal with economic growth.
African countries compared to any other country in other continents have been subject through a lot. Colonialism traumas could be one of the principal reasons for the stagnation of African countries economies. Throughout the year a lot of effort have been made in order to overcome such problems. Although we have observed some positive changes, the position in which we are located at the moment is still far from our goals.
The stock market exchange in African countries still very “unpopular” due to its dimension compared to other developed economies. Thus there are still quite a few aspects that must be adjusted. Hence, I conducted a study on the African Stock market using a dynamic panel data method to do an empirical analysis of relationship between stock market development and its determinants in selected African countries over the period 2000-2015, 16 years of observation change.
1.1 Outline of the Study
This project will be divided into 5 sections, on the first part I will give a brief introduction about this thesis project and my motivations; along with detailed explanation about the background of the problem, statement of the problem and hypothesis, as well as definitions of terms along with my assumption. On the second part, it will be provided a literature review of previous studies on macroeconomic and institutional driving forces for stock market development and the Evolution of the stock market in African countries. On the third section of this work, I will present the data collected and econometrics methodology adopted. On the following section, it will be given the results, empirical interpretation and analysis and presents major findings, final analysis of all the results obtained. Section 5, conclusion of the study and sources’ references.
2. Literature review
The main factors that affect the development of the stock market have always been a point of discussion for many. Many studies have definitely showed the impacts of the varied macroeconomics variables on stock market development in different countries and areas.
On researches made by Demirguc-Kunt and Levine (1996), it was made an examination of the relationship between stock market development and financial intermediary in developing countries and find that most stock market indicators are highly correlated with financial intermediary development. Two years late, Levine and Zervos (1998), concluded that the stock market development has positively impact long-run economic growth. Also, through the use of panel data model, Mohtadi and Agarwal (2004) examined the relationship between stock market development and some variables like: turnover ratio, economic growth, foreign direct investment, investment, secondary school registering for 21 emerging countries over a period of twenty years (1977–1997), and they found that these macroeconomics variables have thin line of relationship with the development of the stock market.
Furthermore, more studies were engaged on the same field to prove the facts. , Garcia and Liu (1999) investigated empirically the macroeconomic determinants (real income, saving, financial intermediary efficiency, stock market liquidity and inflation of stock market development on fifteen industrial and developing countries (Argentina, Brazil, Chile, Colombia, Indonesia, Japan, Korea, Malaysia, Mexico, Peru, Philippines, Taiwan, Thailand, United States and Venezuela) from 1980 to 1995. They showed that real income level, saving rate, financial intermediary efficiency and stock market liquidity are important effective indicators of market capitalization, while macroeconomic stability does not have any explaining power. It was also concluded that there is a complimentary relationship between the banks and the markets and not of substitution.
In addition, using a cross sectional regressions and a dynamic- panel generalized-method of moments (GMM) of annual data from the periods of 1980 to 1995, Rousseau and Wachtel (2000), examined the impact of the 47 capital markets on its economic growth. They showed that liquid stock markets had a significant and subsequent impact on economic growth.
Besides to the financial indicators framework, economists started to put attention to other variables, such as the legal system, corporate trust among former colonies. As an example, we have the research of Beck et al. (2003), where he used a cross-country regression on a sample of 70 former colonies to study the empirical relation of legal system and endowment theories to explain their importance to the financial development. Plus studies made by Calderon et al. (2001), where he analyze the correlation link between trust and both the structure and development of financial system over a sample of 48 countries during 1980-1995. And it is founded that, there is, in fact, a positive correlation between trust and financial development and efficient financial structure.
Billmeier and Massa (2009) assessed the macroeconomic determinants (institutions, remittances, income, investment, inflation change, domestic credit, stocks traded value, oil price index, U.S. federal funds rate) of stock market development in 17 emerging stock markets in the Middle East and Central Asia by using fixed-effect panel regression. After examining the relationship on 17 countries using annual data from 1995– 2005, their results indicate that remittance, income, investment, oil price, Heritage Foundation’s index, stocks traded value effect on stock market development. Cherif and Gazdar (2010) studied the impacts of macroeconomics indicators over covered data of 18 years of fourteen MENA countries. They found a substantial impact of income, saving, stock market liquidity and interest rate on equity market development.
In 2013, Pradhan et al. used panel vector auto regression (VAR) to investigate the causal relationship among stock market development, inflation and economic development in 16 Asian countries (Hong Kong, China, India, Israel, Jordan, Korea, Pakistan, Sri Lanka, Bangladesh, Indonesia, Japan, Kuwait, Malaysia, Philippines, Singapore, Thailand and Turkey) for the period 1988–2012. Their findings showed that existence of a multitude of causal relationship among stock market development, inflation and economic growth.
In 2007 Naceur et al. covered studies in 12 MENA region countries and he found that saving, financial institutions, stock market liquidity and inflation are important determinants of stock market development on that region. Furthermore on the same year, along with Ghazouani, an investigation was done in order to discover a link of connection between stock market banks and the economic development. This investigation was also done on the MENA region over the period (1979-2003), and as conclusion, they couldn’t find any solid results what concerns to these two variables. Sahu (2011) also investigated the causal relationship in India from 1981 and 2006 but it was found that there was no relationship between the stock market development and the economic growth.
Nevertheless, problems remain. First, the goal is to assess the relationship between stock markets, banks, and economic growth. The use of annual data, however, does not abstract from business cycle phenomena. Second, Alonso-Borrego and Arellano (1996) show that the instruments in the difference panel estimator are frequently weak, which induces biases in finite samples and poor precision asymptotically. Recent econometric developments, however, permit the use of statistical procedures that control for these problems.
For causality studies done in this subject area, Kagoshi, Nasser and Kebede (2013) found one-way causality running from economic growth to bank development indicators and a two-way causality test between stock market development indicators and economic growth. Kagoshi et al. (2013) employed panel granger causality tests for seven sub-Saharan African countriesfor the period 1991 to 2007. According to the results, what they founded was that the short-run causality from private credit stimulates the growth and that the banking sector is not developed adequately in those countries in order to support sustained the economic growth.
If I put all the studies together and all the findings from the previous studies, it can be seen that financial growth is the one that has been the most explored and analyzed. Although many economists have been investigating the existent correction between the stick market development and the economic growth, there are still some doubts on the applicability of these results in every country regardless of the size of their economy. Some of evidences have explained the causal relationship and others the financial intermediaries’ impact but it seems that it is not enough to describe the real consensus on how low income countries behave when stock market are develop and if the recent development of their stock market has enhanced economic growth.
3.3 The Special Role of the Stock Market
Before we good deeper into the stock market thematic, I believe that it’s essencial to understand what role it plays on the economy and it’s importance. Stock markets are only just a part of the overall financial system (Naceur et al. 2007). However, some theorists still doubting its position on the market and believe that that stock market development can actually hurt the economy as it is a costly.
On my perspective, stock markets are important, not only for the nation’s economy but also to corporations. Despite the fact the stock market is an alternative source of financing equity as opposed debt, they
they provide corporations with an alternative source of financing equity as opposed debt. One major advantage is that it attracts foreign capital and provides valuation for firms.
This is the primary function of the stock exchange and thus they play the most important role of supporting the growth of the industry and commerce in the country. That is the reason that a rising stock market is the sign of a developing industrial sector and a growing economy of the country.
Levine (1997) points out that those countries with large banks and liquid, developed stock markets have grown quickly in the last decade, after controlling for other growth factors. Industries and firms grow quicker in these economies because of access to a variety of funding. Singh (1999:347) identifies how 3 ways in which stock markets may contribute to economic growth:
a) Increasing savings and investments
b) Improving the productivity and of investments c) Raising the profitability of existing capital
Stock markets expose investors to a wider variety of savings instruments. Another benefit is the stock market pools together the small savings from hundreds of individuals and converts them into large investments.
According to Adjasi and Biekpe (2006) stock markets enable growth in the macro economy in numerous ways. The liquidity of stock enables firms to acquire much needed capital quickly, resulting in capital allocation, investment and growth. They further contribute by reducing investment risk due to the ease in which equities are traded. If foreign investors are involved, they also can also improve the transparency and disclosure in developing countries. This is because they demand accountability of management and clear shareholder rights as a way to protect themselves (Kim and Singal 2000).
Stock markets bring about a takeover mechanism, whereby firms that struggle to utilize their assets efficiently, are acquired by those that do the job better (Singh 1999). Acemoglu and Zilibotti (1997) show that due to availability of portfolio diversification, firms have the opportunity to specialize in production activities thus increasing firm efficiency.
24
Growth can also spur from research and development. This need arises because information about a firm’s performance, financial instruments, prices, profits of listed shares becomes a necessity to the public.
On the other hand, some theorists argue that stock market development can actually hurt the economy as it is a costly, unessential development. This sub-section discusses mainly the works of Ajit Singh who has written extensively on the disadvantages of bourses, particularly for developing countries.
The text book theory, as discussed in the previous sub-section suggests that the stock markets promotes savings rate and also creates a platform for takeovers; that is, larger more resource efficient corporations taking over less efficient, smaller markets. Singh (1999) however opposes this view in relation to developing countries. He puts forward that many firms follow the pecking order hypothesis: that is, the use of internal funds rather than issuing external equity to finance new projects. In this case, this stock market does not act like as saving vehicle, as one would expect.
In cases where the stock market has been able to provide much needed funds to large corporations, thus expanding them, this growth had not been translated to the rest on the economy. Interestingly what actually took place was portfolio substitution; individuals moving from bank savings to the purchase of shares. There was no real increase in an economy’s aggregate savings and investments (Singh and Hamid 1992). A good example of this occurrence was in Mexico, whereby large capital inflows ($91 billion) were injected in the 1980’s. This generated a stock market boom, mainly caused by herd behaviour. The Mexican economy expanded at 3.5% per annum despite a widening current account deficit. Eventually the bubble burst in 1994 and the results were catastrophic for the economy.
Singh (1999) further warns that large capital flows into a developing country increase the vulnerability of that country. Because of the confluence of the currency market
and the stock market, the country is exposed to both external and internal shocks. Moreover, the economy may grow as a result of international funds, and not necessarily local production. The euphoria that the creation of stock markets creates is often short-lived economic boom that eventually ends in calamity, when stock prices and interest rates start to dwindle.
Kim and Singal (2000) concurs that, financial liberalization; the allowance of foreign investors to purchase and own local stocks, is beneficial, but has its drawbacks. ‘Hot money’ is the international flow of funds that is sensitive to differences in interest rates and expected returns from holding securities. Because of this high sensitivity, a small shock in a developing economy can lead to a volatile change in fund flows, which exacerbates the shock and further destabilizes the domestic economy.
Kim and Singal (2000) further point out that the high volatility of foreign stocks may cause domestic stock to also fluctuate. This heightened volatility in stock prices makes investors apprehensive. They in turn demand a higher risk premium, which implies a higher cost of capital and fewer investments for firms ultimately deterring economic growth.
Other than the above reasons, stock market development may be perceived negatively by locals. Banks might be fearful of stock market development as they fear that it will reduce the volume of their business, because it provides an alternative source of funding for firms (Demirgὕḉ-Kunt and Maksimovic 1996). Also, policy makers may fear their currency appreciating when there is larger inflow of capital. For export-orientated countries, an appreciation of the local currency would threaten the global competitive position. Furthermore, the ensuing excess capital will fuel inflation.
The above arguments are parallel with Hassan’s findings and views on the equity markets. In poor countries, the economy drives finance and not the other way around. Financial markets may help, but do not suffice in creating a steady economic growth.
Lastly, it appears as though there are crucial elements in an economy that must precede successful stock market development, which leads us to the next section.
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As Perotti and Oijen (2001) found, privatisation of previously state-owned enterprises may encourage bourse development due to the perceived reduced risk in a particular country. Privatisation shows a commitment by political forces to withdraw from governance of economic activity. Privatisation may also require the institutional changes that contribute significantly to the strengthening of the legal framework.
Other than lack of privatisation, there are other issues in the macro-environment that may hinder the success of stock markets in developing countries, particularly Sub- Saharan Africa. This section is important to this research report because the latter’s focus is in an area that is under-researched i.e. newly developed markets of Africa. The issues raised here may surface in the subsequent chapters when reporting the finding. Our attention now turns to factors that hinder stock market development in African economies.
2.2 Stock Market Evolution in Africa
The stock market development has grown in Africa over Egypt in 1883. It was then followed by South Africa in 1832. According to Ntim (2012) the last couple of decades have seen a rapid growth in the development of bourses. It was witnessed, in the periods from 1992-2004 an increased from 9 to 19 (Andrianaivo & Yartney 2010) stock markets exchange in Africa.
Although most of them still small, illiquid, low correlated with larger stock markets and low capitalized, Andrianaivo and Yartey (2010), compared to counter partners in Asia, MENA and America, we can notice that they made significant improvements in they domestic markets. Some countries that can highlight due to it significant improvement are Ghana, Tanzania and Namibia.
Table1. Stock Market Opening in African countries before 2000
*Data to be added
Generarily speaking this is great to the country itself but what why this change can’t be made all over all the Africans countries? We are seen as the poorest continent in the whole world, with an tremendous unbalanced balance of wealth distribution, poor education and lower income, but the richest nation in resources. So I ask all the society and myself what is stopping us from being big, from standing in the top? Some countries find their way to make it shine, as for us, how long are we expecting to be lying on that comfortable hole of ours, relying on others to feed us, while in our backs they are stealing what we have most valuable and precious, our natural resources.
One of the main reasons for things happening the way they are, is due to the lack of education. Uneducated people aren’t aware of the things that are happening around them, they can be easily fooled by the politics who give them a penny, and as for them, that money is an eternal happiness. Uneducated people can’t find for their rights, because they don’t know what are their rights. Uneducated people cant understand the values of certain “rocks”, as they call them, because they didn’t studied them, and as we know, those “rocks” turn out to be valuable diamonds, gold, and unique things. Uneducated people are naïve, innocent people who survive with little and find happiness on that little, we get so used to that way of living that we end up believing that life cant be more than that, our hope gets limited. And that’s what is stopping us from moving, from growing, from fighting, being brave and standing for a cause. We don’t understand the cause.
According to the African Securities Exchange Association, Ghana Ghana appears to have experienced the highest growth overall, with a peak of 15% growth in 2011. And How did they make it?
As another reason for me, I would that the limited range of technological infrastructures and instruments to work. As we can observe, there is a hindrance to development in African exchanges compared to other stock exchanges. Many economists believe that it is influenced by the lack of benchmarks with which to provide pricing and risk measurements and lack of transparency correlated to corruption. Furthermore, its important to be point out that many exchange centers still operate on a manual system, and as a consequence of that is the resulting delay during the transactions, taking days or week until the actions is executed. These clearing and settlement systems coupled with restrictions make African exchanges unattractive and inaccessible to the foreigner investor or even the local, causing feelings of insecurity.
Hearn and Piesse (2010) made a study at thus barrier to development of small African economies. They found that African stock markets offer a very limited range of tradable instruments compared other markets due to limited technological infrastructure. Unlike other exchanges that serve as a useful platform for initial public offering (IPO’s) thus offering an opportunity for companies to raise capital, African exchanges seem to be concentrated with multi nationals and former government entities in their stock exchanges. Hearn and Piesse (2010) further point out that the Jonesburg Stock Exchange is the only one in Africa that serves as a real competitor to the London Stock Exchange for raising capital
3.5 Hurdles to Stock Market Development in Africa
African markets are characterized by illiquidity, low correlation with larger stock markets and low capitalization, Andrianaivo and Yartey (2010) compared to counter partners in Asia, MENA and South America. The turnover ratio stood at 3.7 in Namibia compared to 70.2 in Thailand in 2007.
One may argue that equity markets were established long before African exchanges in Asia, and that the former are only in their embryonic stages. As mentioned earlier in the text, other political and macro-economic factors maybe at play. The following table shows the issues an investor considers before he or she invests in a country (Laderkarl and Zervos 2004:290).
Ladekarl and Zervos (2004) identify housekeeping and plumbing issues that determine how investasble a country is. These criteria then help investors establish whether a country is a ‘must invest’, ‘may invest’ or ‘cannot invest’.
Housekeeping factors relate to the macro-economic environment and plumbing relates to security and availability of the asset. It mainly deals with the risk, cost and quality of executing sales, registrations and transfer of ownership. These are described in detail below. In addition to housekeeping and plumbing issues, an investor may also consider size, which refers to GDP and population.
3. Methodology and Data
As a way to assess the stock market capitalization, researches use two approaches, the macroeconomics and the institutional way. If we take a deep look into the institutional approach, it refers to internal problems of institutions, taxation problems, and accounting relates. Meanwhile, the macroeconomics approach takes into consideration income level, population growth, saving and investments in the country, inflation and interests rates in the country.
Due to the lack of accurate institutional information for certain countries, and the direct colligation between institutional and macroeconomics factor, I opted to limit the study solely to the use of macroeconomics variables. Although both represent an a relevant effect of the development of stock market, the decision was also compromised in regards of previous studies and results from it by using a more globalized factor since one, the institutional factor, is in the reflect of the other. As a contributor for the decision, Pagano (1993) shows that regulatory and institutional factors could have a direct effect on the functioning of stock markets. For example, mandatory disclosure of reliable information about firms may enhance investor participation, and regulations that instill investor’s confidence in brokers should encourage investment and trading in the stock markets.
This paper focuses on the determinants of stock market capitalization – defined as the total market value of all listed shares divided by GDP- as a proxy for stock market development.
My main goal is to observe and analysis the performance of major emerging markets in selected African countries.
As a way to improve the efficiency of the econometric estimates, a dynamic panel data is used, because it has several advantages when it comes to cross-sectional data. As first reason, panel data gives a broader data points, which in return enlarges the degree of freedom and decrease the colianearity among the variables in cause. The second reason that explains why I used the panel data is because it permits us to construct and test a more complex behavioral model than the simple and pure cross-sectional or time series models. As last, panel data is also mainly focused on heterogeneity across units, which allows a wider mobility in modeling the non-equal behaviors across countries (Greene 2008; Hsiao 2003).
Data set
According to Wikipedia, currently there are about 29 exchange markets in Africa, representing 38 nation’s capital market and they are divided into two regional stock exchange. As I mentioned above, it’s intended to make a study through the periods from 2000 to 2015, so I have excluded the countries in which exchange market were founded after the 2000’s.
My initial intention was to cover all countries in the Africa, but given that some countries have not yet established stock markets (for example Djibouti, Democratic Republic of Congo, Burkina Faso or Sao Tome and Principe) and other countries have established stock markets later than the 2000th (for example, Angola), the sample included are only 17 African countries: Algeria, Botswana, Cote d’Ivoire, Egypt, Ghana, Kenya, Malawi, Mauritius, Morocco, Mozambique, Namibia, Nigeria, South Africa, Tanzania, Uganda, Zambia, Zimbabwe, because their stock exchange market started before, which goes in accordance with our criteria. Swaziland and Tunisia, although they go in accordance with my criteria, they will not be included in the study because of the inaccessibility of data compares to the other countries.
Empirical studies generally have used real GDP, real GDP per capita, growth rate of real GDP per capita, domestic investments, domestic saving rate, inflation, real interest rate, financial crises, trade and financial openness, foreign direct investment inflows, international portfolio investments, remittances, banking sector development and stock market liquidity, political stability and institutional development as major macroeconomic determinants of stock market development in the literature. However, as a conjugation with previous studies with my own, I used stock market capitalization as a proxy for stock market development, GDP as a proxy for economic performance, inflation rate as a proxy for macroeconomic stability, domestic credits provided to private sector by the banks as a proxy for banking sector development, investment rate and saving rate.
Regarding to the data, most of it will be retrieved from the World Bank Indicators, followed by Trading Economics, CEIC and the missing data will be collected from other websites. These indicators rely exclusively on polls of experts. The main advantages of these datasets are that they were available for a considerable time span; thus allowing testing the dynamics and relevance of institutions in affecting stock market development (Daude and Stein 2007).
Data Variables
As dependent variable- represented by Y in the equation:
Stock Market Capitalization: Equals to the total value of listed shares / constant GDP; measures the size of the stock market relative to the size of the economy. It is important because it reflects the significance of the stock markets as a vehicle to mobilize funds & aid in the resource allocation process (El-Wassal 2005). Moreover market capitalization ratio is used as equity market development.
As explanatory variables- represented by X in the equation compromised:
GDP: Log of GDP per capita is described as income level. The main driving force for development of stock market is high income. It is also important that the level of income correlates with the level of education. In addition, more educated people have known about stock market. In addition, GDP is the general power reflected on the economy. It reflects the nice and steady work from the people, company’s growth, which make in propensity the whole country growth steady and continuous. better education, and a better general environment for business, we expect it to have a positive effect on the stock market size
Investment Rate: Investment is considered an important determinant of stock 
market capitalization as stock markets represent one way to intermediate saving to investment projects. We expect it to be the important determinant of stock market capitalization. 

Gross Savings rate: Saving rate is highly related to market capitalization. Liquid equity markets provide profitability and lead to assets investment. Consequently, it provides resource allocation efficiency. Third, consider the savings and investment. Like financial intermediaries, stock markets intermediate savings to investment projects. Usually the larger the savings, the higher the amount of capital flows through stock markets. However, savings may not be highly correlated with income in our sample. In fact in Latin America during the last several years it is negatively correlated, probably due to the sizable capital flows. Thus, we expect savings and investment to be important determinants of stock market capitalization. Again, to avoid the causality problem, we use last year’s saving or investment rate in the regressions.
Inflation rate (CPI): This variable is used as measures of macroeconomic stability. The impact of high inflation makes stocks less attractive than low inflation. A steady inflation is good because it allows us to buy the same products for the same price everyday. Inflation represents the cost of goods/basket of goods over time. Rough inflation is not good because companies would have to spend more to purchase the goods or pay for services. Deflation is not that good too because will make people hold their consumption additions in to it and don’t buy any goods, which could represent a not really good incentive to invest. Sixth, consider macroeconomic stability. General macroeconomic stability may well be an important factor for the development of the stock market. We expect that the higher the volatility of the underlying economic situation the less incentive firms and savers would have to participate in the market. With the high instability found in many developing countries, particularly during the seventies and eighties, stock markets became more opaque. Prices become signals with large standard deviations which make it very difficult to assert whether price changes were temporary or permanent, and markets become more uncertain and prone to attract mostly “gamblers”.
Theoretically both stock market volatility and macroeconomic volatility are hypothesized to have negative effects on stock market capitalization. But, due to data limitations in stock market volatility, we only examine the effects of macroeconomic stability in this paper.13 Even though the effects of macroeconomic volatility on market capitalization might be ambiguous, we expect high volatility to have a negative effect on market capitalization.14
To evaluate the effects of macroeconomic stability on market capitalization, we use three proxies for macroeconomic stability: inflation rate, inflation change, and the standard deviation of inflation rate. First, we use the inflation rate to measure macroeconomic stability. In addition to current inflation rate, we also consider expectation and examine the effect of last year’s inflation rate. Second, we use the difference of inflation rates to measure macroeconomic stability. We calculate the change of this year’s inflation rate from last year. Inflation change is used because we believe that high, stable inflation may not represent much instability, but inflation rates that bounce around a lot probably do represent macroeconomic instability.
Fourth, consider financial intermediary development. Since both the banking sector and stock markets intermediate savings towards investment projects, they can be either complements or substitutes. From the “demand for funds” point of view, the Modigliani-Miller theorem (1958) states that in a perfect market with symmetric information, the market value of all the securities issued by a firm is independent of the firm’s source of finance and consequently firms could go either to the banking sector or to the stock markets to finance their capital. However, asymmetric and imperfect information dominates in the real world. Some countries also distort the financing choices through taxes, subsidies and regulations. Thus, debt or equity financing does matter.
From the “supply of funds” point of view, in the short run the relationship might be negative because of arbitrage between interest rates and stock market returns, but in the medium and longer term investors would probably want to diversify their financial assets and spread their savings between the banking sector and stock markets. The substitutes or complements issue could be country specific due to special incentives to obtain debt or equity financing.
This complements or substitutes issue has been addressed by many researchers. For example, Boyd and Smith (1996) suggest that stock markets and banks may act as complements rather than as substitute sources of capital. Demirguc-Kunt and Levine (1996a) find that across countries the level of stock market development is positively correlated with development of financial intermediaries. Thus, they conclude that stock markets and financial institutions are generally complements and they growth simultaneously.
In contrast, Garcia (1986) finds that many developing countries have had many episodes of intermittent monetary policies with immediate consequences on banking credit. By changing credit in an exogenous way the central bank may create a negative correlation between banking credit and other sources of finance.
To evaluate whether stock market development is significantly correlated with financial intermediary development, we include the measures of financial intermediary development in the regressions. Two empirical indicators are used to measure the financial intermediary development. One is domestic credit to the private sector divided by GDP, and the other is the ratio of broad money supply M3 to GDP.
We use liquid liabilities of the financial system to proxy M3. Liquid liabilities consist of currency held outside the banking system plus demand and interest-bearing liabilities of banks and nonbank financial intermediaries. The M3 to GDP ratio is an indicator of the size of the banking sector in relation to the economy as a whole. This indicator has been used in several studies of the effect of the financial sector on economic growth.11 In contrast, domestic credit to the private sector divided by GDP measures the role of banks in provision of longer-term financing to private corporations.
Domestic Credit: This is a proxy for development of financial intermediaries. It measures the role of banks in the provision of longer term financing to private corporations. This variable his important because it has been found that stock markets perform well economies in which banks are well functioning. (Demirgűς- Kunt and Levine 1996a; Demirgűς- Kunt and Maksimovic 1996)
Interest rate: Low interest rate are preferred for any industry because it means that they can borrow money for a cheaper price and get the manufacture good or service for cheaper. Despite that, it allows businesses to expand their operations. On the other hand, when the banks make borrowing more expensive, companies may not borrow as much and will pay higher rates of interest on their loans, more precisely this high interest rate environment would cost them a lot more money and firms would have to spend more. Hence, generally talking low interest rate would lift the market and the economy in general.
The variables used in the study, their symbols and data sources were presented in Table 2

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Symbol
Sources
Dependent Variable
Stock Market Capitalization Ratio (% of GDP)
SMC
Trading Economics & CEIC
Independent Variable
GDP per capita
GDP
World Bank website
Investment Rate
InvR
World Bank
Gross Saving Rate
GSR
World Bank
Inflation Rate
InfR
World Bank
Domestic Credit
DC
World Bank
Interest Rate
IntR
World Bank & CEIC
Table 2
Method
Method
For this study data set included in the dynamic processes, the dynamic panel data analysis method was used. The dynamic panel data analysis method takes into consideration the dynamic structure between the dependent and independent variables (Baltagi, 1995). In addition, use of panel data in estimating ensures control for missing or unobserved variables and relationships allow identification of country-specific effects (Arellano-Bond, 1991; Matyas and Sevestre, 1996). The dynamic panel allows dynamic effects to be introduced into the model and allows feedback from current or past shocks (Hsiao, 1986). A simple equation of dynamic panel data model is (Hsiao, 2003: 75):
In this study, among dynamic panel data estimation methods the
Generalised Method of Moments (GMM) technique was used. GMM İsmet Göçer, Mehmet Mercan, Osman Peker procedures are more efficient than other estimators (Arellano and Bond, 1991). The resulting GMM estimator is asymptotically efficient (Baltagi, 1995). GMM estimators use all possible lagged values of dependent and independent variables as instrumental variable (Arellano and Bond, 1991). There are three GMM methods; level GMM, difference GMM and system GMM. System GMM was used in this study.
The crucial point here is that variables must be endogenous in order to use GMM. For this reason, before beginning the analysis, a test of endogeneity is required. For this purpose; Durbin’s score (1954) and Wu- Hausman (Wu, 1974; Hausman, 1978) tests can be used. These hypotheses would be expressed as:
If H is rejected, variables are endogenous. In this case, using the GMM is suitable.
The Sargan test used to determine whether instrumental variables of the GMM are suitable (Greene, 2003).These hypotheses would be expressed as:
H0: Moment conditions are valid.
H1: Moment conditions are invalid.
The hypothesis tested with the Sargan-J statistic. This statistic will be
asymptotically chi-squared ( 2 ) with m-k degrees of freedom. m is the
number of instrumental variables and k is the number of the parameter. If the null hypothesis is accepted, instrumental variables are suitable.
Arellano and Bond (1991) developed an autocorrelation test for GMM. The Arellano–Bond test for autocorrelation is actually valid for any GMM regression on panel data (Roodman, 2009). These hypotheses would be expressed as:
H0: No Autocorrelation H1: Autocorrelation
summary stats
3.3 Descriptive statistics
Mean Median S.D. Min Max
SMC 35.24 18.53 53.71 0.05701 311.1
GDP 2291 1334 2269 150.1 10154
GSR 20.60 18.71 16.70 -94.76 100.0
InvR 24.01 22.53 8.586 6.627 58.56
InfR 9.722 7.341 12.03 -11.19 112.7
DC 37.14 27.23 34.01 -70.38 144.3
IntR 18.68 7.151 63.81 -29.22 572.9
l_GDP 7.233 7.196 1.042 5.012 9.226
panel unit root test
Panel unit root testing is more widely accepted for only the time dimension of time series unit root tests, since it covers the data of both time and cross-sectional size (Im, Pesaran and Shin, 1997; Maddala and Wu, 1999; Taylor and Sarno, 1998; Levin and Lin, 1992; Hadri, 2000; Choi, 2001; Levin, Lin and Chu, 2002; Breuer and Wallace, 2002; Carrion-i-Silvestre, 2005; Pesaran, 2006; Beyaert and Camacho, 2008). At the same time, the addition of the cross-sectional size of the analysis increases the variation in the data.
The first problem encountered in the panel unit root tests is whether each cross-section is independent or not. Panel unit root tests are divided into first generation and second generation tests. While Breitung (2000), Hadri (2000) and Levin, Lin and Chu (2002) based their studies on the assumption of a homogeneous model; Im, Pesaran and Shin (2003), Maddala and Wu (1999), Choi (2001) based their studies on the assumption of a heterogeneous model.
In this study; the Im, Pesaran and Shin (2003) (IPS) test will be used, since the countries aren’t homogeneous. The IPS test is based on this model:
Augumented Dickey =Dickey-Fuller test for GDP
test with constant
model: (1-L)y = b0 + (a-1)*y(-1) + e
endogeneity test
The Endogeneity Test
In this study, the Durbin (score) (1954) and Wu (1974)-Hausman (1978) endogeneity test was used. Hypotheses of these tests are as follows:
Endogeneity test was applied by Gretl and obtained results are presented in Table .

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Durbin Score
Hausman
Sargan
GDP

0.0017 ***
GSR

0.1881
DC

1.64e-16***
InfR

0.5203
InvR

0.0710 *
IntR

0.0121 **
dynamic panel data analysis
The first empirical exercise consisted in finding the political, institutional, and economic determinants of inflation levels across countries and time. After dealing with annual inflation, we searched for the main determinants of seigniorage, so that our results could be compared more easily with those of Cukierman, Edwards, and Tabellini (1992).
The estimation results of the model described in the previous section using the method system-GMM for linear dynamic panel data models are shown in Table 1. The dependent variable is the first difference (D1) of Log (Inflation) and the explanatory variables are in first differences as well. Each estimated coefficient indicates the percentage change in the inflation rate that results from one unit change in the respective explanatory variable.9
All explanatory variables described in the previous section were included in the estimation reported in Column 1. Considering that the high correlation of the index of economic freedom with the polity scale, agriculture (in percent of GDP), and trade (in percent of GDP),10 may lead to problems of collinearity between independent variables, that index was not included in the model of Column 2.11 Since agriculture (in percent of GDP) was not statistically significant, it was not included in the estimation reported in Column 3. The number of cabinet changes that occur within a year was used in the model of Column 4 instead of government crises. Finally, Column 5 reports the results of the estimation of the model of Column 3 only for developing countries.
The results reported in Table 1 confirm the hypothesis that political instability leads to higher inflation, and show that the effects are sizeable: an additional government crisis increases the
9 Since cabinet changes, government crises, growth of real GDP per capita, and real overvaluation can be affected by inflation, they were treated as endogenous. As done for lagged inflation, their lagged values two and three periods were used as instruments in the first difference equations and their once lagged first differences were used as instruments in the levels equation.
10 These correlations are, respectively, 51 percent, -56 percent, and 40 percent. The complete correlation matrix is available from the authors upon request.
11 Several changes in results occur: government crises becomes more significant; the polity scale changes sign and becomes statistically significant; agriculture (in percent of GDP) changes sign; trade (in percent of GDP) becomes statistically significant; and the U.S. treasury bill rate, becomes more significant.
conclusion
unit root test

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ADF
Liu lin chu
Im-Pesaran-Shin
L_GDP
-3.4038
0.498796
-6.90351
GSR
-5.04414
-3.79573
-8.66476
DC
-3.31703
-2.34329
-6.56536
InvR
-4.09715
-4.18395
-10.447
InfR
-5.88201
-9.41156
-15.4582
IntR
-2.64921
-6.71041
-5.19976
According to the Table 3, all series are stationary in level values. This means that analysis performed in this series is reliable and equation (6) can be used.
Dynamic Panel Data Analysis
Dynamic panel data analysis was made using equation (5) via GMM and long-term relevant coefficient was calculated by equation (6). The results are presented in Table 5.

1
2
3 2 step
4 differenciated 2 step
5 sargan test
AR1
AR2
L_smc (-1)
0.546
0.595
0.465
0.762

L_gdp
−0.034
0.618
0.136
0.499

Dc
−0.003
0.005
−0.002
0.012

Gsr
0.005
0.002
0.002
0.001

invR
0.016
0.011
0.017
0.005

InfR
−0.002
−0.002
−0.002
−0.002

IntR
−0.004
−1.381
−0.005
−0.004

No of observations
211
211
211
277

Final points
According to the results obtained, I could see that there are still parts to be review, and then I will be able to get the data and the results correct. Hopefully with a little bit more investigation, and the addition of more parameters, new findings will be found and the state problem will be solved.
Hence since I started working on this new project 2 weeks ago, this is the progress made so far. About the data, as I mentioned above, it will be reviewed and amended. This is just a draft and I guideline to the upcoming output, I expect to be done with the whole research thesis by the end of January.
Reference
Al-Yousif, K. Y., 2002. Finacial development and economic growth: another look at evidence from developing countries. Review of financial economics , 11, 131-150
Andrianaivo, M. & Yartey, C., 2010. Understanding the growth of African financial markets. African Development review, 22, 394-418
Anon., 2013. www.dataworldbank.org. [Online] Available at: www.data worldbank.org/data-catalog/world-development-indicators [Accessed 1 July 2013].
Beck, T., and Levine, R. (2004). Stock markets, banks and growth: Panel evidence. Journal of Banking and Finance, 28 (3), 423-442.
Beck, T., Demirguc-Kunt, A., and Levine, R. (2003). Law, endowments, and finance. Journal of Financial Economic , 70 (2), 137-181.
Ben Naceur, S., Ghazouani, S., and Omrani, M. (2007). The determinants of stock market development in the MENA region. Managerial Finance, 33 (7), 477-489.
Boyd, J.H., Levine, R., and Smith, B.D. (2001). The impact of inflation on financial sector performance. Journal of Monetary Economics, 47 (2), 221-248.
Daude, C. and Stein. E. (2007). The quality of institutions and foreign direct investment. Economics & Politic , 19 (3), 317-344.
Demirguç-Kunt, A., and Levine, R. (1996). Stock markets, corporate finance, and economic growth: An overview. World Bank Economic Review, 10 (2), 223-239.
Easterly, W., and R. Levine. (1997). Africa’s growth tragedy: Policies and ethnic divisions. Quarterly Journal of Economic , 112 (4), 1203-1250.
Ghauri, P. & Gronhaug, K., 2010. Research Methods in Business Studies. 4th ed. London: Pearson.
Garcia , V.F., and Liu, L. (1999). Macroeconomic determinants of stock market development. Journal of Applied Economics, II (1), 29-59.
Levine, R. (1997). Financial development and economic growth: Views and agenda. Journal of Economic Literature, 35 (2), 688-726.
Levine, R. and Zervos, S. (1998). Stock markets, banks, and economic growth. American Economic Review, 88 (3), 537-558.
Yartey, C. A. (2008). The determinants of stock market development in emerging economies: Is South Africa different? IMF Working Paper No.08/32. Zoli, E. (2007). Financial development in emerging Europe: The unfinished agenda. IMF Working Paper No. 07/245 .

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