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02 Nov 2017

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CHAPTER ONE Introduction

Background of study

One of the key targets an economy sets is the development of its economy through economic growth. It is therefore no surprise that the significance of financial development for economic growth has been the center of the theoretical debate for a long time. In the 1930s, Schumpeter had already brought into focus the gradual assistance of financial sector to economic growth. For sustainable growth and progress, funds must be efficiently mobilized and allocated to enable businesses and the economy exploit their human, material, and management resources for optimal output.

Mauritius is emerging as a major business and financial sector in the region .It has been experiencing a sustained and consistent growth over the years. Real output growth has averaged just below 6% over the past two decades and this had led to a significant rise in per capita income. With the process of economic progress, every country observes a development in its financial sector and Mauritius has not been excluded from that development. As a key financial institution, SEM has been adding new scopes to the financial sector in Mauritius. It promotes effectiveness in capital formation and allocation. It enables the government of Mauritius and industry to raise long-term capital for financing new projects, and expanding and modernising industrial/commercial concerns. In this sense, the SEM has been increasingly representing a distinct aspect of the financial system of the country.

Though SEM is emerging it is however characterized by complications. The complexities arise from developments in globalization and increased variety of new instruments being traded which include equity options, derivatives of various forms and index futures among others. However, the central objectives of the stock exchanges worldwide remain the maintenance of the efficient market with attendant benefit of economic growth (Alile, 1997) and this is also one of the objectives of the SEM.

The determination of the general growth of an economy depends on how efficiently the stock market performs its allocative functions of capital. As the stock market mobilizes savings, alongside it allocates a larger proportion of it to the firms with relatively high prospects as indicated by its rate of returns and level of risk. The importance of this function is that capital resources are channeled by the mechanism of the forces of demand and supply to those firms with relatively high and increasing productivity thus enhancing economic expansion and growth.

Objectives of the study

The main objective of this study is to examine the impact of stock market development in the economic development and growth of the nation in context to Mauritius. The specific objectives of the study are as follows:

  • To conduct the empirical analysis of stock market by investigating the link between stock markets and economic growth.
  • To further analyze the link based on set of different variables of economic indicators and stock market indicators.
  • To examine the importance of liquidity for the economic growth.
  • To examine whether size is a vital determinant for economic development
  • To determine and analyze the co-integration between the variables in the long run and short run.

CHAPTER 2: An overview of the literature

The increasing importance of stock markets in developing as well as developed countries around the world over the last few decades has moved the focus of researchers to investigate the link between stock market development and economic growth.

A stock market, as such, is a mutual organization which provides "trading" facilities for stock brokers and traders, to trade stocks and other securities. Stock exchanges also provide facilities for the issue and redemption of securities as well as other financial instruments and capital events including the payment of income and dividends. The securities traded on a stock exchange include: shares issued by companies, unit trusts, derivatives, pooled investment products and bonds.

On the other hand, economic growth relates the increase of total GDP. It is often measured as the rate of change of gross domestic product (GDP). It is that branch of one, which deals with the study of rate of change of gross domestic product, referring to the quantity of goods and services produced.

Stock market development and economic growth

The liaison between financial growth and economic development is not a new subject in the economics literature. In 19th and 20th century, academics such as Bagehot (1873) and Schumpeter (1911) had focused on the gradual assistance of financial sector to economic growth. They observed that financial markets play a vital role in the growth process by channeling funds to the most efficient investors and by nurturing entrepreneurial innovation. Berthelemy and Varoudakis(1996), Becsi and Wang(1997), Pagano(1993) and especially Levine(1997) give excellent surveys of the functions of financial markets and how they help to improve economic development.

Levine and Zervos (1998) showed a positive and significant correlation between stock market development and long run economic growth in their study of 47 countries. However, their study relies on a cross-sectional approach with well known empirical limitations. Theoretically, the conventional literature on growth was not adequate to explore the relationship between financial markets and economic growth due to the fact that it is primarily focused on the steady-state level of capital stock per worker or productivity, but not on the rate of growth, that is, in fact, endorsed to exogenous technical progress. The growing interest of recent literature in the link between financial development and growth stems from the insights of endogenous growth models, in which growth is self-sustaining and influenced by initial conditions. In this framework, the stock market is shown not only to have level effects but also rate effects.

The "finance-led growth" hypothesis postulates the "supply-leading" relationship between financial and economic developments. It is argued that the existence of financial sector, as well-functioning financial intermediations in channeling the limited resources from surplus units to deficit units, would provide efficient allocation resources thereby leading the other economic sectors in their growth process. Indeed, a number of studies have argued that the development of financial sector has significantly promoted economic development (Schumpeter, 1912; Levine, 1997).

FDI and economic growth

FDI is thought to be growth-enhancing mainly through the capital, technology and know-how that it brings into the recipient country. By transferring knowledge, FDI will increase the existing stock of knowledge in the host country through labour training, transfer of skills, and the transfer of new managerial and organisational practice. FDI will also promote the use of more advanced technologies by domestic firms through capital accumulation in the domestic country (De Mello, 1997, 1999). Finally, FDI is thought to open up export markets and to promote domestic investments through the technological spillovers and the resulting productivity increase. Overall FDI is thought to be more productive than domestic investments. Indeed, as Graham and Krugman (1991) argue, domestic firms have better knowledge and access to markets, so for a MNC to enter it must have some advantages over the domestic firms. Therefore, it is likely that the MNC will have lower costs and be more productive thanks to technology and know-how.

Zhang (2001) has studied the causal relationship between FDI and economic performance in both East Asian and Latin American countries. Zhang's findings suggest that there is considerable cross-country variation and differences between East Asia and Latin America in the causal patterns of FDI-growth links. He further concluded that a key advantage created by FDI to recipient countries is technology transfer and spillover efficiency. This advantage, however, does not automatically occur, but rather depends on recipient countries' absorptive capabilities, such as a liberal trade policy, human capital development, and an export-oriented FDI policy. Investigations of the causal relationship between economic growth and FDI inflows have, therefore, a significant role in economic development. If there is a unidirectional causality from economic growth to FDI, this implies that national income growth can be treated as a catalyst in attracting inflows of FDI. Conversely, if the unidirectional causality runs from FDI to economic performance, this would strongly suggest that FDI not only stimulates the economic growth rate, but also leads to fixed capital formation and employment augmentation (Borensztein, De Gregorio, and Lee 1998; Lim and Maisom 2000; Zhang 2001). If a bi-directional causality exists between these variables, then both FDI and economic growth would have a reinforcing causal relationship.

Furthermore, the hypothesis of FDI-led economic growth is actually based on the endogenous growth model, which states that foreign investment associated with other factors--such as capital, human capital, exports, and technology transfer--have had significant effects in driving economic growth (Borensztein, De Gregorio, and Lee 1998; Lira and Maisom 2000). These growth-driving determinants might be initiated and nurtured, so as to promote economic growth through FDI. To this extent, FDI may have a positive growth impact that is similar to domestic investment, along with alleviating partly balance-of-payment deficits in the current account (Zhang 2001, p. 177). Recent studies have recommended that, via technology transfer and spillover efficiency, the inflow of FDI might be able to stimulate a country's economic performance. The spillover efficiency occurs when domestic firms are able to absorb the tangible and intangible assets of multinational corporations (MNCs) embodied in FDI.

Stock market liquidity and growth

One way stock markets may affect economic activity is through their liquidity. Many high return projects require a long-run commitment of capital. Investors, however, are generally reluctant to relinquish control of their savings for long-periods. Without liquid markets or other financial arrangements that promote liquidity, therefore, less investment may occur in the high return projects. As shown by Levine (1991) and Bencivenga, Smith, Starr (1996), stock markets may arise to provide liquidity: savers have liquid assets - like equities - while firms have permanent use of the capital raised by issuing equities. Specifically, liquid stock markets reduce the downside risk and costs of investing in projects that do not pay off for a long time: with a liquid equity market, the initial investors do not lose access to their savings for the duration of the investment project because they can quickly, cheaply, and confidently sell their stake in the company. Thus, more liquid stock markets ease investment in long-run, potentially more profitable projects, thereby improving the allocation of capital and enhancing prospects for long term growth. Theory is unclear, however about the growth effects of greater liquidity. Bencivenga and Smith (1991) show that by reducing uncertainty, greater liquidity may reduce saving rates enough so that growth slows.

Furthermore, stock markets play an important role in allocation of capital to corporate sector that in turn stimulate real economic activity. Many countries were facing financial constraints particularly developing countries, where bank loans are restricted to some favorable groups of companies and personage investors. This limitation can also reflect constraints in credit markets (Mirakhor & Villanueva, 1990). Due to stagnant bank's return from lending to specific groups of borrowers, this return does not increase as the interest rate to borrowers rises [Stiglitz & Weiss, (1981); and Cho, (1986)]. Efficient stock markets provide guidelines as a mean to keep appropriate monetary policy through the issuance and repurchase of government securities in the liquid market, which is an important step towards financial liberalization. Similarly, well-organized and active stock markets could modify the pattern of demand for money, and would help create liquidity that eventually enhances economic growth (Caporale et al, 2004)

Risk diversification and growth

Risk diversification through internationally integrated stock markets is a second vehicle through which stock market development may influence economic growth. Saint-Paul (1992), Devereux and Smith (1994), and Obstfeld (1994) demonstrate that stock markets provide a vehicle for diversifying risk. These models also show that greater risk diversification can influence growth by shifting investment into higher-return projects. Intuitively, since high expected- return projects also tend to be comparatively risky, better risk diversification through internationally integrated stock markets will foster investment in higher return projects. Again, however, theory suggests circumstances when greater risk sharing slows growth. Devereux and Smith (1994) and Obstfeld (1994) show that reduced risk through internationally integrated stock markets can depress saving rates, slow growth, and reduce economic welfare.

Information aggregation and coordination in stock market

Stock markets may also promote the acquisition of information about firms [Grossman and Stiglitz (1980), Kyle (1984), and Holmstrom and Tirole (1994)]. Specifically, in larger, more liquid markets, it will be easier for an investor who has gotten information to trade at posted prices. This will enable the investor to make money before the information becomes widely available and prices change. The ability to profit from information will stimulate investors to research and monitor firms. Better information about firms will improve resource allocation and spur economic growth. Opinions differ, however, over the importance of stock markets in stimulating information acquisition. Stiglitz (1985, 1993), for example, argues that well functioning stock markets quickly reveal information through price changes. This quick public revelation will reduce - not enhance - incentives for expending private resources to obtain information. Thus, theoretical debate still exists on the importance of stock markets in enhancing information.

Stock market size and economic development

Demirgc - Kunt and Maksimovic, (1996) argue that at initial stages of economic development, the expansion of stock markets increases both the opportunity for risk sharing and the flow of information in the market. These, in turn, allow firms easy and cheap access to bank loans and to increase the level of leverage. However, at the later stage as stock markets develop further, issuing equity becomes more convenient because of the declining costs and firms substitute equity for debt. Pagano et al (1998) conclude that because of trading externalities in the market and the deliberate behavior of listing companies, the size of the stock market is critical in explaining its own development. Indeed, it will increase the risk sharing opportunities through risk portfolio diversification when firm raise capital from equity financing.

In principle a well-developed stock market should increase saving and efficiently allocate capital to productive investments, which leads to an increase in the rate of economic growth. Stock markets contribute to the mobilization of domestic savings by enhancing the set of financial instruments available to savers to diversify their portfolios. In doing so, they provide an important source of investment capital at relatively low cost (Dailami and Aktin (1990)). In a well-developed stock market share ownership provides individuals with a relatively liquid means of sharing risk when investing in promising projects. Stock markets help investors to cope with liquidity risk by allowing those who are hit by a liquidity shock to sell their shares to other investors who do not suffer from a liquidity shock. The result is that capital is not prematurely removed from firms to meet short-term liquidity needs.

North(1991) state that the founding of a new stock market will be expected to accelerate economic growth by increasing liquidity of financial assets, making global risk diversification easier for investors, promoting wiser investment decisions by saving-surplus units based on available information, forcing corporate managers to work harder for shareholders' interests, and channeling more savings to corporations. Furthermore, Bencivenga and Smith (1992) state that a new stock market also can increase economic growth by decreasing holdings of liquid assets and boosting the growth rate of physical capital, at least in the long run. In the short run, however, the equilibrium response of the capital stock to a new stock exchange can be negative because the opening of an exchange can increase households' wealth and raise their contemporaneous consumption enough to temporarily lower the growth rate of capital.

From a monetary growth prospective a well-developed stock market provides a means for the exercise of monetary policy through the issue and repurchase of government securities in a liquid market. A modern financial system promotes investment by identifying and funding good business opportunities, mobilizes savings, monitors the performance of managers, enables the trading, hedging, and diversification of risk, and facilitates the exchange of goods and services. These functions result in a more efficient allocation of resources, in a more rapid accumulation of physical and human capital, and in faster technological progress, which in turn feed economic growth [Creane, and Al. (2004)].

In addition, the "feedback" hypothesis suggests a two-way causal relationship between financial development and economic performance. In this hypothesis, it is asserted that a country with a well-developed financial system could promote high economic expansion through technological changes, product and services innovation (Schumpeter, 1912). This in turn, will create high demand on the financial arrangements and services (Levine, 1997). As the banking institutions effectively response to these demands, then these changes will stimulate a higher economic performance. Therefore, both financial development and economic growth are positively interdependent and their relationship could lead to feedback causality. The work of Luintel and Khan (1999), among others, is supportive of this view.

Inflation and economic development

The negative effects of inflation have been studied in the context of the models of economic growth, in which the continuous increase of per capita income is the outcome of capital accumulation along with technological progress. The uncertainty associated to a high and volatile unanticipated inflation has been found to be one of the main determinants of the rate of capital and investment [Bruno (1993 ), Pindyck and Solimano (1993)]. Besides, inflation undermines the confidence of domestic and foreign investors about the future course of monetary policy. Inflation also affects the accumulation of other determinants of growth such as human capital or investment in research and development and thus slows down economic growth.

But over and above these effects, inflation also worsens the long run macroeconomic performance of the market by reducing total factor productivity. A high level of inflation induces a frequent change in prices which may be costly for firms and reduces the optimal level of cash holdings by consumers. Several authors have found a negative correlation between growth and inflation. Kormendi and Meguire (1985) estimate a growth equation with cross-section data and find that the effect of inflation on growth is negative, although it loses explanatory powers when the rate of investment is included in the regression. This would indicate that the effect of inflation mainly manifests itself in the reduction in investment and not in the productivity of capital.

More recently, the study of the long- run influence of inflation has progressed within the framework of convergence equations developed by Barro and Sala- I-Martin (1991). Fischer (1994, 1993) reports a significant influence of several short term macroeconomic indicators and in particular inflation, on the growth rate.

No relationship between stock market development and growth

However traditional growth theorists believed that there is no correlation between stock market development and economic growth because of the presence of level effect not the rate effect. Similarly, Singh (1997) contended that stock markets are not necessary institutions for achieving high levels of economic development. Many viewed stock market as a agent that harm economic development due to their susceptibility to market failure, which is often manifest in the volatile nature of stock markets in many developing countries (Singh, 1997; Singh & Weis, 1999). So, the traditional assessment model of 'stock prices' and the 'wealth effect' provide hypothetical explanation for stock prices to be proceeded as an indicator of output (Comincioli, 1996). According to wealth effect, however, changes in stock prices cause the variation in the real economy.

In a recent survey of development economics, Nicholas Stern (1989) does not mention the role of the financial system in economic growth. Furthermore, at the end of Professor Stern's review, he lists various issues that he did not have sufficient space to cover. Finance is not even included in the list of omitted topics. Similarly, a recent collection of essays by the 'pioneers of development economics, including three Nobel Laureates, does not describe the role of the financial system in economic growth (Meir and Seers (1984)). Clearly, according to these economists, the financial system plays an inconsequential role in economic development. Furthermore, the most recent Nobel Prize winner, Robert Lucas (1988), argues that economists frequently exaggerate the role of financial factors in economic development. Moreover, Joan Robinson (1952) argues that the financial system does not spur economic growth; financial development simply responds to developments in the real sector. Thus, many influential economists give a very minor, if any, role to the financial system in economic growth.

Empirical Review

In the last two decades, the link between financial development and economic growth is a subject of high interest among academics, policy makers and economists around the world. There have been attempts to empirically assess the role of stock market and economic growth. The link between stock market and growth has varied in methods and results.

The idea that finance matters for growth in the early stages of economic development goes back to Patrick (1966), Cameron (1967) and Goldsmith (1969). In his study, Goldsmith (1969) establishes the important stylized fact that periods of above average rates of economic growth tend to be accompanied by faster financial development. King and Levine (1993) document a robust relationship between initial levels of financial development and subsequent economic growth across 80 countries, after controlling for other growth-inducing factors. Their measures of financial development are based on the degree of monetization and bank development. Rousseau and Sylla (2001) also employ a cross-country regression framework to make the case for finance-led growth. They use a long data set (1850-1997) for the US, the UK, Japan, France, Germany, and the Netherlands. Consistent with our findings, they argue that financial factors had the strongest effect in the 80 years prior to the Great depression.

Hansson and Jonung (1997) investigate the case of Sweden from 1830 to 1991. In a bivariate system, they find that bank development is co integrated with per capita GDP for the entire period 1834-1991, but the relationship is unstable over time. Banking has the strongest influence on the real economy in the interval 1890-1939 and to a lesser extent in the period 1834-1890. Rousseau and Wachtel (1998) compare the US, the UK, Canada, Norway and Sweden for the period 1870-1929. This comparative 5 country study uses the same methodology to study tri-variate systems of GDP, the monetary base and financial intensity, measured by the value of the financial sector's assets. The authors find a single cointegration relationship between the three variables under examination, suggesting persistent co-movements between finance and growth. Demetriades and Hussein (1996) and Van Nieuwerburgh (1998) apply co-integration analysis to a mixed sample of developing and developed countries for the postwar era. Financial development variables, which are bank-based, are cointegrated with economic development. In both studies, the direction of causality varies across countries and depends on the measure of financial development used.

Arestis, Demetriades and Luintel (2001) and Rousseau and Sylla (2005) investigate the role of stock market in a cointegration framework. The former use data for Germany, the US, Japan, France and the UK, but their sample only spans the last 25 years. The evidence for finance-led growth is mixed across countries, maybe due to the short sample. Rousseau and Sylla (2005) focus instead on the early stages of economic growth in the U.S. (1790-1850). They convincingly argue that financial development had a significant impact on business incorporations and investment.

Levine and Zervos (1998) have focused on the relationship between economic growth and financial development using both bank and stock market indicators. They tested this relationship for a sample of 42 countries over the period [1976-1993]. They found that the initial level of stock market development liquidity and the initial level of banking development are positively and significantly associated with long-term economic growth, productivity growth and capital accumulation. They also find that stock market size, as measured by market capitalisation divided by GDP, is not correlated with growth indicators. However, there are number of weakness associated with the Levine and Zervos approach: It does not deal with the issue of causality; it does not control for country fixed effects; it excludes other components of the financial sector e.g., bond markets and the financial services; and it uses initial values of stock market and bank development indicators while theory stresses the contemporaneous level of financial development

To correct for the simultaneity bias, Levine (1999), and Levine et al. (2000) introduce an instrumental variable (the legal origin) that explains cross-country differences in financial development but is uncorrelated with economic growth. They find that the strong link between financial development and growth is not due to simultaneity bias.

Arestis et al. (2001) use quarterly data and apply time series methods to five developed countries and find that both bank and stock market development lead economic growth. They also find that the impact of banking sector development is substantially larger than that of stock market development.

Rousseau and Wachtel (2000), and Beck and Levine (2003) extend the Levine and Zervos approach of stock markets, banks and growth by using panel techniques (GMM estimator). Rousseau and Wachtel (2000) use annual data and the difference estimator. Beck and Levine (2003) use data averaged over five-year periods, use the system estimator to reduce potential biases related to the difference estimator, and extend the sample through 1998. Both studies show that banking and stock market development explain altogether subsequent growth. These studies stressed the benefits of panel data techniques. The first six benefit is the ability to exploit the time-series and cross-sectional variation in the data. The second benefit is that panel estimators solve the country specific problem. The third benefit is that panel permits the use of instrumental variables to consider the potential joint endogeneity of the explanatory variables. Nevertheless, problems remain Alonso-Borego and Arellano (1996) show that the instruments in the difference panel estimator are frequently weak but recent econometric development permit the use of statistical procedures to control for these problems.

Atje and Jovanovic's (1993) studied stock market trading and economic growth in two ways. Conglomerate indexes of stock market development are used that combine information on stock market size, trading, and integration. Second, there is a control on the initial conditions and other factors that may affect economic growth in light of evidence that many cross-country regression results are fragile to changes in the conditioning information set [Levine and Renelt (1992)]. Thus, the robustness of the relationship between overall stock market development and economic growth to changes in the conditioning information set is gauged. A strong correlation between overall stock market development and long-run economic growth is thus found. After controlling for the initial level of GDP per capita, initial investment in human capital, political stability, and measures monetary, fiscal, and exchange rate policy, stock market development remains positively and significantly correlated with long-run economic growth. The results are consistent with theories that imply a positive relationship between stock market development and long-run economic growth. The results are inconsistent with theories that predict no correlation or a negative association between stock market development and economic performance.

Some earlier studies have examined the relationship between growth and stock markets, and the banking sector, using either cross-country or panel methods. However, their empirical approach typically suffers from serious econometric weaknesses. For instance, the OLS regressions estimated by Levine and Zervos (1998) are potentially affected by simultaneity bias, and do not control for country fixed effects. Beck et al (2000) tried to control for simultaneity bias by using instrumental variable procedures, but did not include a measure of stock market development in their analysis, as this was available only for a much smaller group of countries than the ones they considered. Rousseau and Wachtel (2000) improved upon earlier contributions by using the difference panel estimator introduced by Arellano and Bond (1991), which removes both the bias resulting from unobserved country effects and simultaneity bias.

Furthermore, Bekaert et al. (2003) use an instrumental variable estimator which reduces to pooled OLS under simplifying assumptions on the weighting matrix. They focus on financial liberalisation, arguing that this is not just another aspect of more general financial (banking and stock market) development, and conclude that equity market liberalisation leads to a one percent increase in annual real economic growth over a five-year period in a broad cross-section of developed and emerging countries. However, once again there are some econometric difficulties arising from their panel approach. For instance, the results depend to some extent on the weighting matrix, whose appropriate definition is not the same if one assumes heteroscedasticity across countries and time, group-wise heteroscedasticity, overlapping observations etc. Also, the choice of interval, and more generally omitted variable bias (see Mankiw (1995)) can affect their results. Even more importantly, this type of regression, despite being predictive, is informative about association, rather than causality.

Moreover, McKinnon and Shaw showed that countries that are financially repressed are characterized by credit rationing and artificially low real interest rates and that in the 1960s financial repression and inflation shrunk the deposit base for domestic bank lending in the developing world. In addition, the evidence showed that financial repression leads to lower savings and also created a bias in favor of capital- intensive investment. However, these contributions did not demonstrate that financial development causes economic development rather than the reverse. Indeed, Goldsmith concluded his 1969 study by saying that economists will never be able to settle the question of causation one way or the other. This has not prevented a major research effort since. In papers published in 1993, Robert King and Ross Levine reported results based on a study of 80 countries from 1960-89 using measures of economic and financial development respectively. They found a positive, statistically significant correlation between GDP per head and proxies of financial development.

Rousseau and Wachtel (2000) add a time dimension, and study the link between equity markets and growth for 47 countries between 1980-1995 in a dynamic panel setting. They emphasize the importance of the liquidity of stock markets for economic growth.

There are, however, many studies (published in the well-known journals of mainstream economics) supporting the positive link between stock market development and growth. One such important study was undertaken by Levine and Zervos (1998). Their cross-country study found that the development of banks and stock markets has a positive effect on growth. In another study Levine (2003) argued that although the theory provides an ambiguous relationship between stock market liquidity and economic growth, the cross-country data for 49 countries over the period 1976-93 suggest a strong and positive relationship .Henry (2000) studied a sample of 11 LDCs and observed that stock market liberalisations lead to private investment boom. More recently, Bekaert et al (2005) analysed data of a large number of countries and observed that the stock market liberalisation 'leads to an approximate 1 % increase in annual real per capita GDP growth'.

Arestis et al (2001) analysed time series data for 5 developed countries and found a favorable role of stock market along with bank in economic growth; but they observed that the favorable role of stock market is exaggerated in different cross-country

The studies by King and Levine (1993b) and Levine and Zervos (1998) are noteworthy. King and Levine (1993b) find that financial development, in general and in terms of the development of banks, has a positive and robust impact on economic growth for a group of 80 countries over the 1960-1989 period. Levine and Zervos (1998) provide strong evidence for a positive and robust effect of equity market development on the growth indicators. Levine et al. (2000) and Beck et al. (2000) differ from the other studies in that they more seriously deal with simultaneity and unobserved country-specific effects by using a GMM estimation technique. In addition, they present cross-sectional instrumental variable estimators where legal rights of creditors are used as instruments. These studies are in line with the other studies mentioned above in that they also provide empirical evidence for the growth-enhancing hypothesis of financial development.

Moreover, Johansen's (1988, 1991) method based on vector error-correction mechanisms (ECM) is used to test for long-run cointegration between financial development and economic growth. This methodology allows formal testing of short run and long-run causality between finance and growth. Some well-known examples are Demetriades and Hussein (1996), Arestis and Demitriades (1997), Arestis et al. (2001) and Arestis et al. (2004). By specifying and estimating models for individual countries these studies show that results are country specific. The studies deny that financial sector development in general is a determining fact or for the process of economic development. It appears that in some countries finance affects growth, while in other countries growth determines finance or the causality is twofold. Most importantly, these studies argue that generalizations based on multi-country results may lead to incorrect advices at the country level. Some studies use a similar methodology for heterogeneous panels. A recent example is Christopoulos and Tsionas (2004). They estimate an error correction model for a panel of 10 countries and find that long run causality runs from financial development to growth, which contradicts the single country studies by e.g. Arestis et al. (1997, 2001).

The majority of the panel and cross-country studies on financial development and economic growth find that financial development has a positive effect on economic growth. These studies also provide some empirical evidence for the hypothesis that it is the overall provision of financial services (banks and financial markets taken together) that is important, and not whether a country has a bank-based or a market based financial system. However, the cross-country type of studies is not without problems, since they do not properly account for the time dimension. Moreover, the cross-country estimates can give a wrong impression of the impact of financial development on economic growth since they assume that the different countries in the model are homogeneous entities. Since countries may differ greatly with respect to institutions and economic policies used, results may be country specific. It is also argued that while the cross-country type of studies may give some evidence for a positive correlation between income per capita and the development of the financial sector, the causality between financial sector development and economic growth remains unclear. Most of the multi-country studies do not pay much attention to the direction of causality. They seem to implicitly assume that financial development causes economic growth, in line with the supply-leading view (Patrick, 1966).

CHAPTER THREE Research Methodology

Introduction

The literature presented before gives us a number of contrasting views of the link between stock market development and economic growth. One school of thought is of opinion that stock market development is an essential element for economic growth whilst another attribute finance as being the pillar behind the growth rate. This chapter will attempt to elucidate the validity of whether stock market development is greatly linked to economic growth.

Discussion of the data

This study combines three measures of economic growth and two measures of stock market development namely size and liquidity. For the analysis of relationship between the stock market development and economic growth , the time period of ten years employed over an average of 1989- 2008 is covered. The growth rate of real GDP is regressed on a variety of variables namely FDI, labour, inflation rate and two measures for stock market development, liquidity and size.

Model Specification

Using the independent variables real gross domestic product per capita, foreign direct investment, labour, inflation and stock market development index, the model is thus constructed as shown below.

    RGDPPC = ƒ (FDI, LAB, INFLA, SMD)

Where RGDPPC denotes real GDP per capita; FDI denotes foreign direct investment, LAB denotes the labour force, INFLA refers to Inflation and SMD denotes stock market development. For the analysis purpose, the econometric model will be further broken down to form an equation for SIZE and LIQUIDITY, which will be used as measures of stock market development;

Theoretical justification of the variables

Mauritius has over the past years encountered a sustainable level of growth and this achievement has been possible due to several factors such as trade liberalization, institutional factors, capital, political environment amongst others. However it should be noted that the two factors which have mostly contributed for the growth rise are undoubtedly foreign direct investment and skilled labour.

Foreign Direct Investment

FDI is any form of investment that earns interest in enterprises which function outside of the domestic territory of the investor. Consistent economic growth, de-regulation, liberal investment rules, and operational flexibility are all the factors that help increase the inflow of Foreign Direct Investment. FDI is thought to be growth-enhancing mainly through the capital, technology and know-how that it brings into the recipient country. By transferring knowledge, FDI increases the existing stock of knowledge in the host country through labour training, transfer of skills, and the transfer of new managerial and organisational practice. FDI also promotes the use of more advanced technologies by domestic firms through capital accumulation in the domestic country (De Mello, 1997, 1999). Thus FDI is deemed to be having a positive effect on growth and it is due to this that over the years, successive governments have done their level best to attract foreign direct investment in Mauritius.

Labour

It is needless to say that human capital is the most important factor of production in today's economies. According to the early neoclassical model of Robert Solow (1956), economic growth was driven by the improvement of productivity via technological advance. Increases in skilled labour are crucial to achieving increases in GDP. The theoretical models of the impact of a skilled labour on economic activity have become increasingly sophisticated over the past centuries, especially during the last twenty years. As early as 1890, Alfred Marshall noted that "the most valuable of all capital is that invested in human beings." And Benjamin Franklin was aware that "investment in education pays the best interest." Economic policy that raises the rate of growth of human capital will lead to higher growth rates of GDP. So, GDP growth hinges on the accumulation of human capital and it is due to this that a positive sign is expected for the coefficient of labour.

Inflation

"Inflation not only reduces the level of business investment, but also the efficiency with which productive factors are put to use." Inflation can be defined as the erosion in the purchasing power of money that is a loss of real value in the internal medium of exchange and unit of account in the economy. The decrease in the purchasing power entails to a fall in consumption which eventually leads to a fall in standard of living. Lower standard of living implies that there is lower growth rates. Inflation has the bad effect on economic growth since it increases uncertainty n the economy and discourages savings as well. Furthermore inflation discourages investments since nominal interest rates are increased by much, leading to rising unemployment and lower growth rate. To this extent, a negative sign is expected for the coefficient of inflation.

Stock Market Development Index

We need to have a measure of the stock market development. Theory, however, does not offer a single concept of stock market development. Thus, for the purpose of the study, two measures of stock market development is used namely size and liquidity.

Size

As such, size is referred to as the market capitalization ratio. It denotes the market capitalisation as a percentage of GDP at constant prices. Although large markets do not essentially function effectively and taxes may distort incentives to list on the exchange, many observers use capitalisation as an indicator of market development.

Liquidity

Liquidity denotes total value of shares traded as a percentage of GDP at constant price. Value traded measures trading volume as a share in national output and should therefore positively reflect liquidity on an economy wide basis.

Sources of data

For the purpose of analysis, the data pertaining to Mauritius was for the period 1989 to 2008 and it was obtained from various sources.

  • FDI (expressed as a percentage of GDP) was obtained from the Bank of Mauritius.
  • Labour force was proxied by the addition of the Mauritian labour force and foreign workers in Mauritius and it was obtained from the Central Statistics Office of Mauritius.
  • Inflation rate was as well obtained from the Central Statistics Office of Mauritius.
  • Size was calculated by taking the market capitalisation as a percentage on gross domestic product and data for this was obtained from the factbook 2009 of the Stock Exchange of Mauritius.
  • Liquidity was as well obtained from the same source as Size and it was calculated by using the total values of shares traded on the stock market of Mauritius as a percentage on gross domestic product.
The Augmented Dickey-Fuller test

A common assumption in many time series techniques is that the data are stationary. Granger and Newbold (1974) were among the first to argue that macroeconomic data as a rule contained stochastic trends, characterized by unit roots, and that using these series in traditional econometric models may lead to spurious regressions. Therefore, to avoid dealing with spurious result owing to non stationary data, it is important to check for stationarity. The ADF test ensures that a variable follows a unit-root process. The null hypothesis is that the variable contains a unit root, and the alternative is that the variable was generated by a stationary process. The ADF test augments the DF test by adding lagged difference terms of the regressed.

where ?Y is the first difference of the series Y, k is the lag order, and t represents time. Equation (1) is the ADF test with constant, but no time trend, and equation (2) is the test with constant and a time trend. All equations will be estimated with optimal lags, the later being determined by the Akaike Information Criterion (AIC)

Cointegration tests

If it is possible for two or more variables to be I(1) and yet for a certain linear combination of those variables to be I(0) then the variables are said to be cointegrated. Cointegration implies that there is a long run relationship between the variables although they may diverge from equilibrium in the short run. The most popular test for cointegration which is closely related to unit root test was suggested by Engle and Granger (1987).

The usual procedure for testing hypotheses concerning the relationship between non-stationary variables is to run Ordinary Least Squares (OLS) regressions on data which had initially been differenced. Although this method is correct in large samples, cointegration provides more powerful tools when the data sets are of limited length, as most economic time-series are.

Residual-based cointegration

A residual-based cointegration test evaluates whether the residuals from the empirical regression contain a unit root. Now, if the original data are in fact near-integrated, with a root less than unity, the test will over-reject since the residuals will not contain a unit root even if there is no cointegration. But, by instead using critical values based on a conservative estimate of the local-to-unity root in the original data, a valid test is obtained. Intuitively, if one views a residual-based test of cointegration as a test of whether there is less persistence in the residuals than in the original data, then this test is only valid if the persistence of the original data is not overstated. In a spirit similar to the Bonferroni methods proposed by Cavanagh et al. (1995), it is shown how an appropriately conservative estimate of the local-to-unity root is obtained

Testing for Multicollinearity

Multicollinearity is a problem with being able to separate the effects of two (or more) variables on an outcome variable. If two variables are significantly alike, it becomes impossible to determine which of the variables accounts for variance in the dependent variable. As a rule of thumb, the problem primarily occurs when x variables are more highly correlated with each other than they are with the dependent variable. The variance inflation factor( VIF) is used to check for multicollinearity. Normally, a variable whose VIF values are greater than 10 may necessitate more profuse investigation when it comes to multicollinearity.

Testing for Serial Correlation

Autocorrelation violates the OLS assumption that the error terms are uncorrelated. While it does not bias the OLS coefficient estimates, the standard errors tend to be underestimated when the autocorrelations of the errors at low lags are positive. The Durbin Watson test is thus used to test for serial correlation. Normally, serial correlation is detected when the Durbin Watson statistic( original) is near to zero.

Error correction model

An ECM is a dynamical system with the characteristics that the deviation of the current state from its long-run relationship will be fed into its short-run dynamics. A rough long-run relationship can be determined by the cointegration vector, and then this relationship can be utilized to develop a refined dynamic model which can have a focus on long-run or transitory aspect.

OvTest

The omitted variable bias (OVB) is the bias that appears in estimates of parameters in a regression analysis when the assumed specification is incorrect, in that it omits an independent variable that should be in the model. Thus, the Ov test is applied to check for model specification.

Expected results

CHAPTER FOUR Empirical testing and analysis

Introduction

This chapter will deal with the empirical tests which have been discussed in the previous chapter. The results obtained will be presented and thus interpreted. In the first section the unit root properties of the data included in the analysis is presented. The ADF test will be used to check for stationarity. Testing for multicollinearity, serial correlation and model specification will also be carried out. Furthermore, the Engel-Granger test will be used to check whether there exists co integration between the variables and the residuals in the long run. Last but not the least the error correction model will be used to portray the relationship of the variables in the short run.

Testing for stationarity

In this section, the variables will be tested for stationarity using unit root tests namely the Augmented Dicker-Fuller (ADF) test. Non stationarity in a data series may probably lead to spurious result which means that the correlation between the variables might be misleading. In general, a non stationary process requires differencing to bring on stationarity.

It was Granger and Newbold (1974) who were the ones who brought about the term "spurious regression". It meant to describe regression results which involved time series that look good when in fact there cannot be significant relationships between the variables.

Unit root test is carried out using the data analysis and statistical software namely Stata 9 and the stationarity is inferred the test statistics with the critical value at 10 % significance level.

The standard Augmented Dickey-Fuller (ADF) test is performed to assess the degree of integration of the variables. For stationarity to be present, the test statistics needs to be greater than the critical values. Having conducted the level form stationary test, it can be concluded that all the variables, except inflation are non stationary in their level form, since their computed statistic lie well above the 90% critical values. The variable Inflation has a t- statistics of 4.017 with lag 0 and a trend and thus only inflation can be said to be I (0), that is stationary at level form

It is however notorious that unit root tests suffer from low power and tend to under-reject the null hypothesis of a unit root (Maddala and Kim, 1998).

To check whether the other remaining variables are integrated in the first order, the ADF test is applied on the first difference of the variables. The table 4.2.2 presents the findings.

The ADF statistics on the first differenced data reveals that it rejects the null hypothesis of non-stationarity for all the variables at 10% significance level since at first difference because their test statistics are greater than the critical values. Therefore, all the variables are 1(1)

Now that we have tested for stationarity for all the variables, we will now proceed with the long run equation

The Long Run Equation

Foreign Direct Investment Variable Theory Intuition Expected sign Actual sign

FDI Economic growth is expected to be influenced positively by FDI along with spillover effects through employment generating process. positive Negative As theory says, FDI is deemed to positively affect economic development in Mauritius. FDI from Multinational Corporations (MNCs) is thought to be growth-enhancing mainly through the capital, technology and know-how that it brings into the recipient country. By transferring knowledge, FDI will increase the existing stock of knowledge in the host country through labour training, transfer of skills, and the transfer of new managerial and organizational practice. FDI will also promote the use of more advance technologies by domestic firms through capital accumulation in the domestic country (De Mello, 1997, 1999).

However from the above results of -.0036173 from equation (1) and -.0050813 from equation (2), it can be said that FDI is negatively cointegrated with economic growth.

The results obtained can be due to the fact that it is only from the mid-1980s that FDI started entering Mauritius significantly mostly in the EPZ and in tourism sector and thus the proportion of FDI to gross domestic investment (GDI) remained quite low throughout the 1980s. Furthermore, FDI in Mauritius have also been highly concentrated regarding sector as well as in skills and capabilities, therefore limiting the capacity to rapidly upgrade and diversify production which in turn delayed economic growth (UNCTAD, 2001).

Labour Variable Theory Intuition Expected sign Actual sign

Labour An efficient labour force will entail an increase in productivity and thus improves the output of an economy positive positive Many empirical investigations support the view that labour is the most important factor of production in today's economies. The rapid structural change caused by globalisation and technological change has increased the importance of labour over the past years. Skills and income are closely linked. This is true both for individuals and for whole economies. In short, higher skilled labour leads to more output per hour worked, that is productivity is higher. Similar to additional physical capital (machines), additional skills also raise the productivity of labour, which in turn increases output and thus accelerate growth in the economy.

In this sense, there exist a positive relationship between a skilled labour force and growth, as depicted by the positive result .0047378 ( Eqn 1) and .0042878 (Eqn 2). The p-value of 0.000 shows that the result is significant.

Inflation Variable Theory Intuition Expected sign Actual sign

Inflation Rate Inflation measures the monetary instability that affects the economic performance through its detrimental impacts. negative negative Inflation affects the accumulation of other determinants of growth such as human capital or investment in research and development and thus slows down economic growth. Kormendi and Meguire (1985) estimate a growth equation with cross-section data and find that the effect of inflation on growth is negative, although it loses explanatory powers when the rate of investment is included in the regression. This would indicate that the effect of inflation mainly manifests itself in the reduction in investment and not in the productivity of capital.

Several authors have found a negative correlation between growth and inflation and this has been proved by studies made in this context

As expected, the coefficient of inflation is negative both for equation one (-.0289539) and equation two (-.0330224) and the results are also significant due to the p value (0.002).

Size Variable Theory Intuition Expected sign Actual sign

Size The expected sign of increase in credit to private sector spurs the economic activity in the economy through their causal channels. positive positive In principle a well-developed stock market should increase saving and efficiently allocate capital to productive investments, which leads to an increase in the rate of economic growth.

Market capitalisation ratio is often used as measure of size. It is given by the ratio of market capitalisation to GDP. Although large markets do not necessarily function efficiently and taxes may distort incentives to list on the exchange, many observes use capitalisation as an indicator of market development.

The relationship between size and economic growth, as per previous researches made in this context, is said to be positive. This means that the coefficient of the regressed variables Size should be positive. As expected, the coefficient for equation (1) yields a positive result of .0036496. This implies that the size of the stock market is indeed quite significant in influencing the level of growth positively.

Liquidity Variable Theory Intuition Expected sign Actual sign

Liquidity The expected sign of increase in credit to private sector spurs the economic activity in the economy through their causal channels. positive positive One way stock markets may affect economic goings-on is through their liquidity. Many high return projects require a long-run assurance of capital. Investors, however, are generally unwilling to give up control of their reserves for long-periods. Without liquid markets or other financial arrangements that promote liquidity, therefore, less investment may occur in the high return projects. As shown by Levine (1991) and Bencivenga, Smith, Starr (1996), stock markets may arise to provide liquidity, that is, savers have liquid assets while firms have permanent use of the capital raised by issuing equities.

Liquidity is used as the second measure for stock market development and is calculated as total value of shares traded as a percentage of GDP at constant price. A positive coefficient of regressed variable Liquidity will imply that liquidity and economic growth are positively correlated.

Having as results .0598249 as the coefficient of liquidity, it can be concluded that the more liquid a stock market is, the higher will be the rate of economic growth.

Summary of results in the Long Run Equation.

As it can be seen, all variables except the FDI have yielded their expected results. Both measures of stock market development, size and liquidity have been found to be positively correlated with economic growth. However when comparing size with liquidity, it can be deduced that liquidity impacts more on growth rather than size. This can be explained by the use of the computed coefficients. A 10% increase in size leads to a 0.36% increase in RGPPC whereas a 10% increase in liquidity yields a 5.98% increase in RGPPC, thus leading to the conclusion that liquidity matters more than size when it comes to growth.

Testing for Multicollinearity

After having established the long run relationship between the variables and economic growth, we will now test for multicollinearity. Multicollinearity is a problem with being able to separate the effects of two (or more) variables on an outcome variable. If two variables are significantly alike, it becomes impossible to determine which of the variables accounts for variance in the dependent variable. Basically, it is tested using the variance inflation factor (VIF). A variable whose VIF values exceed 10 may merit further investigations.

The results obtained after applying the VIF is 2.38 for equation (1) and 2.82 for equation (2). Thus, there is no multicollinearity in both equations.

Testing for Serial Correlation

Using the Durbin Watson test for serial correlation, both equations were tested for serial correlation. Autocorrelation violates the OLS assumption that the error terms are uncorrelated and thus need to be detected. . Normally, serial correlation is detected when the Durbin Watson statistic( original) is near to zero.

From the computed results, equation (1) yielded a Durbin-Watson statistic (original) of 1.309623 and equation (2) yielded a Durbin-Watson statistic (original) of 1.574520. thus no serial correlation is detected.

Testing for model specification

The Ovtest is applied to check for model specification. Equation (1) produces a p value of 0.0588 and equation (2) a p value of 0.0519. This indicates that the model doesn't suffer from omitted variables bias.

Testing for the presence of cointegration

Cointegration requires that the error term of equation (1) and equation (2) is I(0). It is only by fulfilling this prerequisite that the variables will be known to act as cointegrating series.

Number in parentheses indicate the number of lags included in the ADF test

The unit root test is performed to check for the presence of cointegration. It is to be noted that if X1t ~I(0) and X2t ~ I(1), then Zt = (X1t + X2t) = I(1). All the variables have are either I(0) or I(1) and thus cointegration requires that the error term of equation (1) and (2) to be I(0).

Having calculated the test statistics for the residuals, it can be noted that the residual test for equation (1) produces a value of - 4.541 and that of equation (2) produces a value of -3.135. This indicates that the error terms are I (0). Thus it can be said that the variables act as cointegrating series.

The R-Squared

The R-squared of a regression is the fraction of the variation in the dependent variable that is accounted for the independent variables. The R-squared is generally of secondary importance, unless the main concern is using the regression equation to make accurate predictions. The R- squared adjusted on the other hand is the version of r-squared that has been adjusted for the number of predictors in the model.

Equation one yields a R-squared of 0.9553 and an Adj R- squared of 0.9434 while equation two a R- squared of 0.9596 and an Adj R-squared of 0.9488.

A large r-squared does not necessarily imply that the fitted model is a useful one. One example of this occurs if the observations are taken at a narrow interval and the predictions are wanted outside the region of observations. Furthermore, a large r-squared suggests a spurious regression and the presence of serial correlation. However the ADF test has been conducted earlier to test for stationarity and testing for serial correlation has also been done and the results were stationary regression and no detected serial correlation.

The Short Run Equation

Foreign Direct Investment

Compared to the long run, in the short run FDI has a positive relation



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