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Vol. 4, No. 1/2014 (7th Issue) Print ISSN : 2304-2613; Online ISSN: 2305- 8730

1

Relationship between Ownership Structure and the Modes of Dividend Payment: A Study on Dhaka Stock Exchange

Page No.

07-11

Mohammad Ruhul Amin; Md. Abdullahel Kafi; & Md. Mahabbat Hossain 2

Credit Characteristics and Business Performance: A Survey of Women owned Microenterprises in Tanzania

12-18

Paul J. Salia & Jonathan S. Mbwambo 3

The Dimensions of Industrial Growth in Tamil Nadu, India: Three Decades of Experience

19-23

Dr. A. Sankaran & Dr. P.Rajkumar 4

Foreign Direct Investment (FDI) in Bangladesh: Prospects and Challenges and Its Impact on Economy

24-36

K. M. Anwarul Islam 5

Investment Performance of Islamic Bank: An Empirical Study

37-40

Evana Nusrat Dooty & Mohammed Syedul Islam 6

Volatility Estimation in the Dhaka Stock Exchange (DSE) returns by Garch Models

41-49

Md. Shawkatul Islam Aziz & Md. Nezum Uddin

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Relationship between Ownership Structure and the Modes of Dividend Payment: A Study on Dhaka Stock Exchange Mohammad Ruhul Amin1; Md. Abdullahel Kafi2; & Md. Mahabbat Hossain3 1

Assistant Professor of Finance, Southeast University, Bangladesh Assistant Professor of Accounting, Northern University Bangladesh, Bangladesh 3 Faculty Member, Bangladesh Institute of Bank Management (BIBM), Bangladesh 2

ABSTRACT This paper investigates whether percentage of ownership controlled by the directors of companies has any association with types of dividend declared by them. Based on the data for the years 2006 to 2009 from the Dhaka Stock Exchange, this paper found that most of the companies provided stock dividends rather than cash dividends. Using Yate’s Continuity Correction Chi-square Test, this study has found existence of a significant relationship between the percentage control of ownership and types of dividend declared. Furthermore, the study indicates that the companies having ≥50% share controlled by the directors are 3 times more likely to offer stock dividends than companies having <50% control of the shares by the directors. Whereas, the companies having ≥50% control of ownership by the directors are less likely to offer cash dividends compared with <50% control of the shares by the directors. Key Words: Dhaka Stock Exchange, Ownership Structure, Dividend Policy JEL Classification Code: G32; D78

INTRODUCTION

S

hareholders are the owners of every corporation. However, every share holder is not concerned to voice out their opinion regarding the policies passed in AGM. They feel that their voices are insignificant related to the voting power of the directors who mostly hold a significant portion of the stocks. Thus, the corporate decision regarding to pay stock dividend or cash dividend is primarily made by the Board of Directors (BoD) in their board meeting and most of the time the other small share holders unanimously agreed upon the decision in the annual general meeting (AGM). The question then arises whether cash or stock dividend benefits more to the majority shareholders, namely the BoDs of the corporation. This issue is important to the investors in general for making their investment decision so as to maximize their wealth. Furthermore, it is also relevant with the problem of agency cost involved for the firms, as the directors are not only the decision makers whether or not to provide any dividend by the firms but also are direct beneficiary of the applied dividend strategy. A stock dividend implies an increase in nominal share capital and hence a decrease in retained earnings. Firms announcing stock dividends finance growth entirely by debt (explaining the need for an increase in nominal share capital) and retained earnings. The shareholder can keep the shares and hope that the company will be able to use the money not paid out in as cash dividend to earn

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a better rate of return, or the shareholder could also sell some of the new shares to create his or her own cash dividend. The biggest benefit of a stock dividend is that shareholders do not generally have to pay taxes on the value. Taxes do need to be paid, however, if a stock dividend has a cash-dividend option, even if the shares are kept instead of the cash. The idea about the relevance of dividend on the value creation of a company goes back to Modigliani and Miller‟s (1961) dividend irrelevancy hypothesis, who argued that dividend policy has no effect on either the price of a firm‟s stock or its cost of capital. In a perfect world, the dividend policy is irrelevant to shareholders wealth. This proposition has laid solid theoretical foundation for the dividend policy, which at later stage, the economists have offered explanations in different ways about dividend payment, such as effect of taxes, dividend signaling, agency cost issues and transaction cost. The idea that ownership structures whether or not affect the modes of dividend payment is one of the important fields of study in capital market around the globe. Studies done by various researchers on both the developed and developing capital market found interesting results. Louis T. W. Cheng, Hung-Gay Fung & T. Y. Leung (2006), found that in many emerging financial markets, firms typically pay stock dividends rather than cash dividends. Since the opening up of Chinese capital markets during the early 90‟s, it has been

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found that Chinese investors appear to favor stock dividend over cash dividends. There are many hypotheses explaining why firms pay out stock dividends. The signaling and retained earnings hypotheses, which are closely linked and relate stock dividends to a firm‟s good growth or investment potential, appear to be the leading contenders in explaining stock dividend policies of firms in the U.S. (Baker et al, 1995). Thus, it is important to analyze correlation between the directors‟ control of the shares and the modes of dividend payment by the firms. It may suggest trading strategy that can be devised based on the nature of the relationship. For this, we have chosen an emerging market in Asia, namely the Dhaka Stock Exchange (DSE). An extensive search of literatures also justifies the need to do because there is a dearth study on this market on the subject matter.

RESEARCH OBJECTIVES The objective of this paper is to examine existing relationship between ownership structure and modes of dividend payment, while it will also try to find out industrywise dividend payment for the years 2006-2009. Specifically, the paper is going to examine whether the percentage of directors‟ ownership has an impact on the dividend declaration of companies under different industries. If any, what types of dividend (equity or cash) is relevant with the majority (or minority) ownership shareholders.

LITERATURE REVIEW Qiao, Y. and Chen, Y. (2001) found evidence of positive statistical relationship between dividends and mix dividend policies of firms in Chinese stock markets. Their study showed that the market was not sensitive with cash dividends but was reactive to stock dividends. On the other hand, Chen, Wei et al (1999) Empirically analyzed the dividend policy of different companies listed in Shanghai Stock Exchange by method of Cumulated Abnormal Return (CAR) and studied the existence and character of the signaling effect of dividend policy. The study found different degrees of CARs resulted from different dividend policies. The CARs of right issues were higher than that of cash dividend but lower than that of the bonus issues. Kalay and Loewenstein (1985) found a strong positive relation between dividend changes and a firm‟s ability to generate future earnings and cash. Authors showed that dividend loses its information content in explaining firm‟s future performance when earning and earning related variables (such as earnings forecast) are released simultaneously. A new view is the tunneling perspective, which argues that cash dividends may be used as a tool to re-direct firm resources to benefit large shareholders and top management at the expense of minority shareholders. A number of studies explore the reason for and the impact of issuing stock dividends.

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0

Proposals to explain stock dividends include the signaling, trading range, liquidity, cash substitution, and retained earnings hypotheses. Foster and Vickrey (1978) reported that stock dividend generates positive abnormal returns on the declaration date rather than on the ex-date and that size is not a determinant of market reaction, supporting a signaling function of stock dividends. Authors report significant abnormal returns around the announcement of stock dividends, suggesting that stock dividend issue is a signal for future cash dividends, cash flows, and earnings. In an examination of responses from chief financial officers, Eisemann and Moses (1978) found them supporting for signaling, liquidity, cash substitution, or retained earnings hypotheses. Whereas, Baker and Philips (1995) reported evidence from a managers‟ survey supporting signaling and retained earning hypotheses. Cash dividends and stock dividends have been argued substitutes for one another. As discounting a dividend payment would likely produce a negative market reaction, firms usually issue stock dividends rather than paying out cash dividends that might lead to a cash shortage for internal use. Ghosh and Woolridge (1985) found that issue of stock dividends can mitigate the negative market reaction due to reduction or omission of cash dividends, which provides evidence for the cash substitution hypothesis. Fung and Leung (2001) proved that reinvestment by plowing back earnings should be viewed positively; as it indicates profitable opportunities in firms. If firms indeed have good investment prospects, shareholders prefer stock dividends in order to preserve cash for investments; seasoned equity financing is not readily available for future funding needs because of regulatory constraints in China. Thus, the underdevelopment of China‟s financial market implies that rational Chinese stockholders would generally prefer stock dividends to cash dividends, supporting the retained earning hypothesis. Huang and Fung (2004) found that if dividend policy serves as a signal to the market, firms‟ values (prices) will change as a result. Price appreciation will not translate into financial gains for the controlling stockholders whose shares cannot be traded through the stock exchanges. Thus, they would prefer cash dividend to realize an immediate financial gain. Mitton (2002) found no significant association between insider ownership and stock price performance for a sample of East-Asian companies. Furthermore, studies regarding the association between insider ownership and managerial misbehavior are found to have mixed results. Recent studies on the relationship between dividend policy and level of ownership by the directors include Wang (2006), Lee J. (2006) and Andres, C. (2008). Wang provided evidence that family ownership is associated with higher earning quality, a finding consistent with the alignment effect of family ownership. Jim Lee (2006) studied on S&P and fortune 500 companies where a comparison based on net profit margin, employment, revenue and gross income growth

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were made between 1992-2000 and found that average profit margin for family firms was 10%, two points higher than non-family owned firms. German researcher Andres, C. (2008), analyzed on 275 German public companies and found that companies with significant family ownership are more positively and outperform their peers with other type of shareholders.

METHODOLOGY To investigate the relationship between the ownership structure and the types of dividend payment by various companies, study years have been considered from 2006 to 2009. For this paper we have selected data on dividend payout by firms under different industries listed on Dhaka Stock Exchange (DSE). Survey years 2006 to 2009 have been selected because during these years many companies offered both cash and stock dividends for their shareholders and the related data have been collected from the official website of DSE (www.dsebd.org). A total of 193 samples have been selected from four different industries, namely, banks, insurance, cement, and pharmaceutical. Purpose sampling technique has been followed in this regard. The companies which declared either stock or cash dividends only are selected and companies which declared both stock and cash dividends are excluded from the sample of this study. The paper divided the firms into two main categories based on the control of the ownership by the directors of the companies. On one segment, there are companies with greater than or equal to 50% ownership controlled by the directors and on the other are the companies with less than 50% control of shares by the directors. Seventy one companies have been included in the survey having greater than or equal to 50% ownership by the directors whereas, 122 companies with ownership control of less than 50% by the directors. The study begins with descriptive analysis of dividend payments by the four different types of industries for the study periods. Besides, the paper will also analyze whether the types of dividend declared has any association with the amount of control by the director shareholders for the selected sample. To analyze it the following hypotheses have been proposed: H0: There is no significant association between ownership structure and types of dividend payment. H1: There is a significant association between ownership structure and types of dividend payment. Chi-square (

x

2

) test will be used to determine the

significance of the association, if there is any. The greater the value of

x

2

, the greater would be the discrepancy

between observed and expected frequencies. formula for computing chi-square is:

x

2



The

O  E 2 E

Where, O = observed frequency. E = expected or theoretical frequency.

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The calculated value of tabulated value of

x

2

x

2

is compared with the

for given degrees of freedom at

specified level of significance. If the calculated value of

x

2

is greater than the tabulated value, the difference

between theory and observation is considered to be significant, i.e., it could not have arisen due to fluctuations of simple sampling. On the other hand, if the calculated value of

x

2

is less than the table value, the

difference between theory and observation is not considered significant, i.e., it could have arisen due to fluctuations of sampling. Logistic regression has also been used where ownership structure is considered as the independent variable and modes of dividend payment as the dependent variable.

FINDINGS Table 1 describes the weighted average returns classified under the stock and cash dividends for the years 2006-2009 for the four selected industries. It shows that except for the year 2006, all the banks either provided stock dividends or a combination of both cash and stock since the firms which provided both types of dividends are excluded from our sample. During the year 2006 most of the banks provided stock dividends rather than cash dividends. With the exception of the year 2009, insurance companies provided mostly stock dividends where as cement and pharmaceutical industries provided mostly cash dividends. The reason for this could be primarily attributed to implementation of BASEL II, which made it obligatory that every commercial bank, insurance companies and other non-bank financial institutions have to increase the equity participation by issuing right/bonus shares for its shareholders and not primarily relying on the debt capital. Table 1: Average Dividends of the Sample Companies for the Years 2006-2009 (%)

Source: Study result Table 2 and 3 explain the average returns for both directors controlled firms (50% or more controlled by the directors) and the general investors controlled firms (less than 50% controlled by the directors) and associated average dividends as stock and cash dividend. They show an interesting result. We find that higher percentage of stock dividends were declared for banks where the majority shares are controlled by the directors for the year 2007. But, for the year 2006, 2008 and 2009 companies with directors holding minority shares provided higher percentage of dividend. For insurance

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companies we find very similar dividend rates irrespective of the percentage control by the directors of the firms. For cement industry, cash dividends were mainly declared and the higher percentage of dividends went to the companies with primarily under the directors‟ control. However, pharmaceutical industry declares mainly cash dividends, where companies with less than 50% controlled by the shareholders during the years 2006, 2007 and 2009. Nevertheless, it has been changed during 2008 when a little larger dividend was declared for the favor of directors‟ controlled shares. Table 2: Comparison of Average Dividends for ≥50% & <50% Control of Ownership by Directors in 2006 & 2007.

0

Furthermore, to analyze the relationship between types of dividend declared and the ownership structure; a Yate‟s Continuity Correction chi square test was carried out since the number of degree of freedom is 1 and SPSS software has been used. The results of the Yate‟s Continuity Correction chi square test are shown in Table 5. It shows a significant relationship between types of dividend payment and the ownership structure at ρ = 10% level. Therefore, it can be concluded that the directors‟ control of ownership has significant association with the types of dividend paid, whether stock or cash. Table 5: Results of Yate‟s Continuity Correction ChiSquare Test Value df Continuity Correction No. of Valid Cases

2.826

1

193

Source: Study result Source: Study result Table 3: Comparison of Average Dividends for ≥50% & <50% Control of Ownership by Directors in 2008 & 2009

Source: Study result Table 4 shows that out of the 193 sample companies for the four years a total of 135 companies provided only stock dividends where as 58 companies provided only cash dividends. Whereas, a total of 91 companies having <50% ownership control by the directors offered stock dividend and 31 companies offered cash dividends. The same tendency has been observed in case of ≥50% control of ownership. In such case 44 companies declared stock dividend and 27 companies declared cash dividend. Table 4: Four years average ownership structure and dividend category Ownership Structure <50%

Stock Cash Dividend Dividend

Total

91

31

≥50%

44

27

71

Total

135

58

193

For a better understanding of the relationship a logistic regression has been run. The results of the logistic regression have been presented in Tables 6 & 7. Where, <50% ownership controlled by directors is indicated as 0 (zero) and ≥50% ownership controlled by directors is indicated as 1 (one). Table 6 indicates that companies having ≥50% control of ownership by directors are less likely to offer cash dividends than stock dividends compared with <50 ownership controlled by the directors. Table 7 indicates that companies having ≥50% share controlled by the directors are about 3 times more likely to offer stock dividends than companies having <50% control of the shares by the directors. Table 6: Results of Logistic Regression Ownership Controlled by Directors <50% ≥50%

B

Sig.

Exp(B)/Odd s ratio 1.000 0.341

-1.077 .000

Source: Study result Table 7: Results of Logistic Regression Ownership Controlled by the Directors <50% ≥50%

B

Sig. Exp(B)

1.077 .000

1.000 2.935

Source: Study result

122

Source: Study result

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CONCLUSION This paper has tried to investigate the relationship between director‟s control of ownership and modes of dividend payment. It found that, in general, most of the industries would like to provide stock dividend rather than cash dividend. Using Yate‟s Continuity Correction Chi-Square, this study has found existence of a significant relationship between the percentage control of ownership and types of dividend declared. Furthermore, the study indicates that companies having ≥50% control of ownership by directors are less likely to offer cash dividends than stock dividends compared with <50 ownership controlled by the directors. Whereas, the companies having ≥50% share controlled by the directors are about 3 times more likely to offer stock dividends than companies having <50% control of the shares by the directors. This provides an intriguing thought on the matter of agency relationship. Whether or not the interests of the general investors are protected by the types of dividend declared is a matter of further study using longer time series data.

[3]

REFERENCES

[12]

[1]

[2]

Andres, C. (2008), “Large Shareholders and firm Performance: An empirical examination of founding-family ownership”, Journal of Corporate Finance, 14 (4), 431-445. Baker, H.K. and A.L.Philips, and G.E. Powell, (1995), “The Stock distribution puzzle: A Synthesis of the literature on

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stock splits and stock dividends”, Financial Practice & Education, Spring/ Summer, 24-27. Chen, W; Liu, X; Yang, Y; (1999), “An empirical study on the signaling effect of dividend policy in shanghais stock market”, Chinese Journal of Management Science; 7(3). Eisemann, P.C. and E. A. Moses, (1978), “Stock dividends: Management‟s view.” Financial Analysts Journal 31, 77-80. Foster, T. W. III and D. Vickrey, (1978), “The information content of stock dividend announcements,” The Accounting Review 53, 360-370. Fung, H G. and W.K. Leung, (2001) “Financial liberalization and corporate governance in china.”, International Journal of Business, 2 (2), 3-31. Ghosh, C. and J. R. Woolridge, (1988), “An analysis of shareholder reaction to dividend cuts and omission”, Journal of Financial Research 11, 281-294. Huang, A.G. and H.G. fung, (2004), “Stock ownership segmentation, floatability, and constraints on investment banking in china.” China and world Economy, 12 (2), 66-78. Kalay, A. and U. Loewenstein, (1985), “Predictable events and excess returns: the case of dividend announcements,” Journal of Financial Economics 14, 149-175. Lee, J. (2006), “Family Firm Performance: Further Evidence” Family Business Review. 19 (2), 103-114. Merton H Miller, Franco Modiglian. (1961), “Dividend policy, growth, and the valuation of shares.”, Journal of Business, 34:411-33. Mitton, T. (2002). “A cross-firm analysis of the impact of corporate governance on the East Asian financial crisis”. Journal of Financial Economics. 64: 215–241. Qiao, Y; Chen Y; ( 2001), “Dividend policy and fluctuation of stock market in Chinese companies”, Economic Research; 4 (in Chinese) Wang, D (2006), “Founding Ownership and Earnings Quality”, Journal of Accounting Research, Vol. 44, No. 3.

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Credit Characteristics and Business Performance: A Survey of Women owned Microenterprises in Tanzania Paul J. Salia1 & Jonathan S. Mbwambo2 1

Assistant Lecturer, Institute of Accountancy Arusha, Tanzania Sokoine University of Agriculture, Development Studies Institute, Tanzania

2

ABSTRACT This article provides assessment of the effects of four credit characteristics including size, interest rate, repayment period and borrowing experience on business performance. The article makes use of survey data collected from 217 women microcredit clients from Arusha, Dar es Salaam and Mwanza regions in Tanzania. Bivariate correlation analysis was used to find out specific effect of each of those four credit characteristics on three business performance measures namely total sales revenue, net profit and business net worth. The combined effect of all four credit characteristics on business performance was estimated by a multiple linear regression model. The findings revealed that size of credit was positively correlated with total sales revenue and business net worth at significant level. Interest rate was negatively correlated with all three measures of business performance at significant level. It was also found out that repayment period was positively correlated with all three business performance indicators at significant level. Furthermore, the study established that borrowing experience was positively correlated with total sales revenue at significant level but not with other two indicators. The model accounted for 25% of sales revenue, 9% of net profit and 28% of business net worth. Key words: Size of credit, interest rate, repayment period, borrowing experience and business performance JEL Classification Code: E51, E43

1 INTRODUCTION

C

redit is an important source of capital to finance women owned microenterprises in Tanzania. This is particularly so given that most of those enterprises are capital constrained (Martijn and Daan, 2012). Evidences from a study by International Labour Organization (ILO, 2003) show that 67% of women enterprises in Tanzania use their meagre savings to start up their businesses. Amidst this situation, women owners of microenterprises can hardly secure loan from the commercial banks which offer relatively low interest rates because have no control over the conventional collaterals like land or houses. This view is supported by Nchimbi (2002) and Olomi (2001) when they observe that microenterprises owners, especially women, cannot easily borrow from commercial banks due to lack of collaterals which are demanded in the process of asking for financial supports. Since women owners of microcredit cannot access credit from the mainstream financial system, their only remedy are the Microfinance Institutions (MFIS) and money lenders, who unfortunately attach their loan products with stringent conditions including high interest rate, short repayment period and limited amount to borrow. This paper therefore is set to assess how those stringent lending conditions affect business performance in terms of total sales revenue, net profit and business net worth.

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2. LITERATURE REVIEW Lack of enough capital is one of the major constraints against growth of women owned microenterprises. It is on this background Coleman (2001) observes that without sufficient capital, micro and small firms are unable to develop new products and services or grow to meet demand. However, microcredit has always constituted small-size-loans (Mosley and Hulme, 1998; Morduch 2000; Ghatak and Guinnane, 1999) which can hardly suffice the actual business needs to grow or expand. The contribution of optimally large size of loans to the performance of microenterprises cannot be overemphasised. According to Godquin (2004) there is linear relationship between size of loan and profit that a firm can make as a result of borrowing. She underscore the contribution of size of loan particularly focusing on what the same can do increase business returns and investment. She notes “as the net return is an increasing function of the size of the loan, the borrower always prefers bigger loans and therefore asks for the largest loan size she may apply for given the set of projects within her reach as defined by her own characteristics, those of her environment, and those of her lending group” (Godquin, 2004:1911). Vogelsang (2001) studied the impact of loan size on the performance of the clients‟ enterprises in Bolivia using data from one of the microfinance institutions called Caja Los Andes. Basing on the information from 76,000 clients and

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28,000 rejected loan applicants; the author found out that clients with average higher loan size generated higher revenues than those with lower loan size. Accordingly, the study found out that those with average higher loan size has higher level of assets than those with lower average loan size. Coleman (1999, 2001) studied microfinance programs in Thailand and found out that those programs had insignificant or negative impact on the borrowers‟ household wealth. According to him, those loans had negative effect because were too small in size to make investments in business and thus were used for consumption. The borrowers because even poorer because had to turn to money lenders to finance the repayment the fact that lead the borrowers into a vicious cycle of poverty. Otieno et al., (2011) conducted as study in Kisii County in Kenya to assess the effect of provision of micro finance on the performance of microenterprises focusing particularly on microenterprises under Kenya Rural Enterprise Program (KREP). The study, which involved a total of 86 enterprises, found out that the size of loan given to majority of borrowers was inadequately small to facilitate significant investment in businesses. The study also found out that loan amounts disbursed to the majority of applicants (respondents) were less than the amount applied for. The authors concluded that due to inadequately small loans, youth microenterprises were not able to grow to small and medium size enterprises. At this point it is important to note that all of the above studies confirm to the fact that financial constraints, due to limited loan amounts by MFI, prevent firms from making enough investment in their businesses thus leading to depressed growth, productivity and eventually their survival (Carreira & Silva, 2010; Musso & Schiavo 2008; Parker & Van Praag,2006). Cognizant of the contribution of size of credit in business performance, this study establishes the following hypothesis. H1. The performance of microenterprises with large loan size is significantly higher than those with small loan size. Microenterprise operators, especially in the developing countries, have limited access to credit from formal sources. Banks, which offer relatively low rates compared to MFIs and money lenders, continue to favour large-scale business and neglect the poor potential entrepreneurs on the basis that have no the conventional collaterals to guarantee for the loan they request. A study by Banerjee and Duflo (2006) covering a total 13 developing countries revealed that only 6% of the borrowings of poor people came from formal sources. According to them 94% of the borrowed funds by the poor came from money lenders, friends and merchants. Given this situation, it turns out that the only viable sources of credit to women owners of microenterprises are the microfinance institutions (MFIs) and sometimes money lenders. However, it might be important to note that MFI loans have always been attached to high interest rates. Specifically, high interest rates on microcredit are typical in the so called „new wave MFIs‟ where financial services have been commercialized (Huq, 2004). Bateman (2009) found out that women borrowers

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from one of Mexico‟s MFI called Compartamosbanco were paying a high interest of around 90-100%.

Literature suggests that MFIs associate their loan products with high interest rates in order to meet the operating costs and to achieve financial sustainability. In order to achieve financial sustainability and, arguably be able to reach more poor people with microloans, MFIs have to attach their loan products with high interest rate so as to gain profit (Roodman, 2011; Rosenberg et al., 2009, Ruben, 2007). According to Roodman (2011), the impact of high interest rates has to be judged against the possible harm of poor people having no access to credit at all. Explaining why small loans should be attached to high interest rate; Rosenberg, Gonzalez and Narain (2009:1) note “lending $100,000 in 1,000 loans of $100 each will obviously require a lot more in staff salaries than making a single loan of $100,000”. Ruben (2007) in his work titled “The Promise of Microfinance for Poverty Relief in the Developing World” explains the reason why MFIs have to attach their loan with high interest rates. He argues that MFIs have to hinge the credit products with high interests so as to be able to meet the high administrative costs associated with small loans. According to him, the interest rates of 30 to 50% or more offered by MFIs are low compared to that which is offered by local money lenders. While this is classic explanation around high interest rate offered by MFIs, the argument I put forward here is that those rates are too high to really make it possible for borrowers to expand their business through increased volume of tradable goods and services, investment on productive assets and eventually earn profit. High interest rates can prevent the poor from borrowing. This may happen when those interest rates prevent investment on activities that produce high returns (Fernando, 2006). This is clear when he notes that „only those who can generate a sufficiently high surplus of funds can afford high interest rates on microcredit. More specifically, a borrower's realized rate of return on investment needs to be greater than the interest rate to service the loan‟ (Ferdinando, 2006:7). In fact, loans with high interest rates can have devastating impact on the borrowers when the same are used to facilitate consumption than business investment (Stewart et al. 2010). For instance, women owners of microenterprises are likely to be unable repay loans with high interest rates given that they are tend to invest the borrowed money in other activities like health, education and basic needs than in business. Further empirical evidences suggest that high interest rates offered by MFIs have been reason why microfinance services have not been able to improve the clients‟ wellbeing particularly in Sub-Saharan region (Stewart et al, 2010). The authors observe that the poor borrowers are made poorer not richer and because their businesses do not produce enough profit to compensate for the high interest rates and that due to high interest rate, the poor do fail to repay loan and may fall into a debt trap (Stewart et al., 2010: 49). Higher interest rates were one of the causes of indebtedness among MFI borrowers. In a study conducted in Ghana by the Centre for European Research in Microfinance, Schicks (2011) found out that high

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interest rates were one among highly mentioned reasons for borrower‟s indebtedness in the interviews. In Tanzania, high interest rate on microloans has been found to constrain financial stability of microenterprises. For instance, Kayunze et al., (2005) list high interest as one of the constraints against borrowing other than lack of collateral by the poor.

However, poor people go on borrowing from MFIs in spite of the high interest rates. Engagement in loans with high interest rates means that women borrowers would have little returns on their businesses the fact that will in turn limit business performance in terms of investment on assets, profit and hired labour force. On the basis of these arguments, the study establishes the following hypothesis. H2. The performance of microenterprises whose owners are servicing loans with low interest rates is significantly higher than those whose owners are servicing loans with high interest rates

Generally, the beneficiaries of microcredit schemes, especially where Grameen banks‟ solidarity group lending applies, experience short repayment time most often one week after loan disbursement. Hulme and Mosley (1996) note that frequent repayment scheme is used by MFIs to reduce repayment insecurity. According to them, advantage of this scheme is that it screens out the undisciplined borrowers, thus giving early warning to loan officers and group members. However, short repayment period means that borrowers have to make returns before making any investment. In the same vein, Armendáriz and Marduch (2005) argue for tight repayment schedule showing that flexible repayment contributed to high default rate among microcredit clients in Bangladesh. Scanty literature available on the role of repayment period and business performance suggests that there is positive correlation between more flexible repayment period and business performance. Field and Pande (2008) conducted a study to evaluate the effect of weekly repayment in a microfinance institution called Village Welfare Society in Calcuta – India. In this study, borrowers were randomly assigned to one of three conditions: usual weekly reimbursement starting immediately after loan disbursement, monthly reimbursement, or weekly reimbursement starting a few weeks after the loan started. The findings revealed that the group which was given a gap of a few weeks was more likely to start a business, and when they started they were more likely to make a bigger investment than one that only started paying after a while. Particularly, women borrowers who started loan repayment after a few weeks were less likely to buy saris for resale and more likely to invest on productive assets like acquire a sewing machine. In another study involving 845 clients of a microfinance institution called “Village Financial Services” in Kolkata India, Field et al., (2011) found out that immediate repayment obligation distorted investment in microenterprises financed through credit. The study further found out that longer grace period had positive effect on profit and investment in business but could increase delinquency.

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The ideal advantage of tightly short repayment schedule is that it may screen out the undisciplined borrowers, thus giving early warning to loan officers and group members (Hulme and Mosley, 1996). However, short repayment period means that borrowers have to make returns before making any investment. Particularly, short repayment time may not favour women borrowers who do so to start up a new business because repayment has to begin before the returns on investment. With due consideration of the importance of reasonably enough grace period and eventually long repayment period in the growth and eventually performance of women owned MEs the study considers the following hypothesis. H3. The performance of microenterprises whose owners are servicing loans with long repayment periods is significantly higher than those whose owners are servicing loans with short repayment periods Literature consistently shows that women operators of MEs have limited experience with credit and other microfinance services. In essence this is closely related to limited access to credit among them (Ibru, 2009; Iganiga, 2008; Iheduru, 2002; Kuzilwa, 2005; Lakwo, 2007; May, 2007; Okpukpara, 2009). Limited experience with credit is likely to lead to limited use of other related microfinance services (Karnani, 2007). This view is reinforced by Shane (2003) arguing that “the ability of women to make use of the opportunities provided by microfinance services to ensure enterprises‟ performance depends on the attitude to risk”. The duration of participation in credit scheme, therefore, is an important factor to consider while assessing the impact of microcredit scheme. However, the available empirical evidences show mixed results with regard to usefulness of credit and duration of participation in credit schemes. A study conducted in Zimbabwe showed that households of clients who had participated for long time were likely to fall into poverty than non-clients (Barnes et al. 2001b). A study in Ghana (Adjei and Arun, 2009) reveled that women clients were more likely to purchase refrigerators and sewing machines but the duration of participation did not matter. A study by Lakwo (2006) on “microfinance, rural livelihood and women‟s empowerment in Uganda” revealed that microcredit did improve the wellbeing of clients relative to that of non-clients but those gains were reducing as time for participation increased. The study observed further that clients who had been involved for more than three years saw very negligible value-addition to their wellbeing (Lakwo, 2006). However, in this study it is assumed that women operators of MEs with repeated borrowing experience (i.e. those with higher frequency of borrowing) are more likely to use credit for effective business performance. This is particularly so since most of the MFIs do not provide enough and relevant business education to their clients; especially on the use of credit for business performance. With due consideration of the importance of credit experience, this study puts forth the following hypothesis.

H4. The performance of microenterprises whose owners have had repeated borrowing experiences is significantly higher than those whose borrowers have had limited experience.

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3. MATERIAL AND METHODS 3.1 Sampling procedures and sample size This article used data from a survey of women owners of microenterprises who had borrowed money from various microcredit schemes from three major cities in Tanzania including Arusha, Dar es Salaam and Mwanza. The study, which was cross-sectional by design, adopted a combination of purposive and simple random sampling techniques. Purposive sampling technique was used to identify the suitable locations (wards) from which women operated their microenterprises. This was done by the help of Business Directors for the three city councils. The researcher consulted the Ward Executive Officers (WEOs) who helped him to identify specific women‟s groups to be visited. Using women‟s groups in the different business locations, the researcher was able to get the list of women owners of microenterprises who had borrowed from various sources. He then used simple random sampling technique to select few women from each group to represent others. To accomplish this task in a manner which was less biased, the researcher used a table of random numbers. In Total, therefore, 217 women borrowers including 59 from Arusha, 102 from Dar es Salaam and 56 from Mwanza were selected. 3.2 Data collection and variable measurements Data collection exercise commenced in February through May 2012. Structured questionnaire was used to collect required information. Three business performance measures namely total sales revenue, net profit and business net worth were used. Total sales were considered to be sum of all revenues obtained from business in specific month of reference. Information on the sales was collected by one question requiring the entrepreneur to state the total sales on specific period of time including the previous day, the previous week or the previous month. These three reporting options were provided with due realization that some of the operators of microenterprises did not keep written business records and therefore would face recall problems if they had to give weekly or monthly reports. The weekly and monthly options were specifically meant for those who kept written records. All of the reported sales were converted to monthly sales by multiplying sales per day or week by total number of days for which the business operated in the reference month. Net profit was defined as sum of sales revenue less total business and operating cost in the previous month plus value of output consumed by the entrepreneur or her household plus value of output given away (Daniels, 1999:4). The operating costs were calculated from a list of costs and the amount spent on each per day/week/month. Information on sales was collected using a single question “what were your sales in the last day/week/month?” This question was obtained from AIMS (Assessing the Impact of Microfinance Services) questionnaire (Cohen, 1999:63). Net profit was calculated using the following formula. Net Profit = Sales – [business costs + other operating costs] + output consumed by entrepreneur or her household + output given away.

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Business net worth was considered to be the sum of fixed and current assents only. Human asset and human and/or social assets were left out because of the difficulties of measuring them among women owners of microenterprises. Thus business net worth was calculated using the following equation. Business net worth = Current asset + Fixed assets Current assets involved inventory of finished goods (for manufacturing businesses), raw materials, cash, deposit/checking accounts, account receivables and loans. The value of loan was given a negative sign (-) because this was something the proprietor had to pay off from her earnings. The fixed assets included the monetary values of utilities, machinery, equipment and tools. All three business performance indicators namely total sales, net profit and business net worth were expressed in Tanzanian Shillings (TZS).

Data on the four credit characteristics namely size, interest rate, repayment period and borrowing experience were collected as follows. Information on the size of credit was collected by use of a single question where respondents were asked to state the amount of their last loan in TZS. This question was followed by two others requiring them to state the interest rate per annum associated with their last loan and repayment period in weeks. Where respondents could not give proper information on the interest rate, the researcher either calculated it or sought the required information from the respective lending institution. Lastly, the information on borrowing experience was collected by compiling information from two questions which required respondents to state: (a) number of cycles for which she had participated in microcredit schemes, and (b) Length of those individual cycles. This information was converted into weeks. 3.3 Data analysis Bivariate correlation analysis was used to assess the relationship between the four credit characteristics namely size of credit, interest rate, repayment period and borrowing experience on the one hand and business performance on the other. The results were presented using Pearson correlation coefficient (r) and p-value. The combined effect of all four credit characteristics on the aforementioned three business performance measures was estimated by a multiple linear regression model. Rationale for using this type of model was based on the study‟s goal of finding out the contribution of each of the individual aforementioned four credit characteristics on business performance. Specifically, this type of model was preferred given that there more than one predictor variables. The model adopted logarithmic form because the variables were not normally distributed. It looked as follows.

LogYn  B0  B1 log X 1  B2 log X 2  B3 log X 3  B4 log X 4   Where B0 was a constant and B1...B4 are beta Coefficients and ɛ was an error term. For operational purposes Y1, Y2 and Y3 represented total business sales (tsales), net profit (nprofit) and business net worth (networth) respectively. Accordingly, X1, X2, X3 and X4 represented Size of credit (size),

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Interest rate (interest), Repayment period (repayment) and borrowing experience (experience) respectively. The interpretation of regression analysis was based on group statistics (Means and Standard Deviation), Pearson Correlations, Beta Coefficients, t-values, adjusted R square values, F statistics and significance (P-values).

4. FINDINGS 4.1 Size of credit and business performance The findings revealed that there was significant positive correlation between loan size (amount borrowed) and total sales (r = 0.300, p < 0.01). There was also significant positive correlation between size of loan and business net worth (r = 0.307, p < 0.001). However, loan size was not significantly correlated with net profit. The implication of these findings is that the businesses borrowers with large loan size (i.e. those who borrow a large amount of money) were likely to perform better in terms of total sales and net business worth than of those who borrow little (limited) amount. The findings therefore concur with the first hypothesis for this study that “the performance of microenterprises with large loan size is significantly higher than those with small loan size”. 4.2 The interest rate per annum and business performance The interest rate per annum varied from 5% for borrowers from VICOBA) to 600% for borrowers from individual money lenders. The average interest rate was 52.19% per year. The results of bivariate correlation analysis revealed that interest rate was negatively correlated with sales (r = 0.l78, p = 0.011) and with business net worth (r = -0.137, p < 0.001) at significant levels. Interest rate was also negatively correlated with net profit when the significance value was adjusted to two decimal places (r = -0.137, p = 0.05). Thus, the findings support the second hypothesis that “The performance of microenterprises whose owners are servicing loans with low interest rates is significantly higher than those whose owners are servicing loans with high interest rates” 4.3 Loan repayment period and business performance The repayment periods ranged from 4 to 52 weeks. The average repayment period was 28.6 weeks. The findings of bivariate correlation analysis revealed that there was positive and statistically significant correlation between loan repayment period and total sales (r = 0.221, p < 0.001), between repayment period and net profit (r = 0.168, p < 0.05) and between repayment period and business net worth (r = 0.429, p < 0.001). These findings imply that longer repayment period may lead to more sales, higher profit and higher business net worth. The findings therefore support the third hypothesis that “the performance of microenterprises whose owners are servicing loans with long repayment periods is significantly higher than those whose owners are servicing loans with short repayment periods”. 4.4 Borrowing experience and business performance

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Out of 217 borrowers, 76 (35%) had repeated borrowing experience while 141 (65%) had not. The borrowing frequency ranged from 1 to 14 times. The average borrowing frequency was 1.92. The borrowing experience was calculated as total number of weeks for which a borrower had been on the loan(s) and it ranged from 4 to 468 weeks, with the average of 55.3 weeks. The findings reveal that there was positive and statistically significant correlation between borrowing experience and total sales (r = 0.237, p < 0.001). The rest of two business performance measures namely net profit and net business worth were not significantly correlated with borrowing experience. The findings reject the fourth hypothesis that “the performance of microenterprises whose owners have had repeated borrowing experiences is significantly higher than those whose borrowers have had limited experience”. 4.5 The model estimation Effect on total sales: Using an enter method, a model emerged (F4, 176 = 16.167, p < 0.01, Adjusted R2 = 0.252). The predictor variables with significant positive effect on the total sales were size of credit (Beta = 0.410, p < 0.001) and borrowing experience (Beta = 0.195, p = 0.04). The remaining two independent variables namely interest rate (Beta = -0.096) and repayment period (Beta = -0.102) were not significant predictors of this model. Effect on net profit: The findings on the model summary, ANOVA results and regression coefficients showed that using an enter method a statistically significant model emerged (F4, 176 = 5.65, p < 0.001, Adjusted R2 = 0.094). The findings revealed that size of credit was the only predictor variable with statistically significant positive effect on the model (Beta = 0.268, p = 0.004). The rest of the three independent variables including interest rate (Beta = -0.020), repayment period (Beta = 0.076) and borrowing experience (Beta = 0.020) were not significant predictors of this model. Effect on business net worth: The results showed that a statistically significant model appeared (F4, 172 = 17.889), p < 0.001, Adjusted R2 = 0.277). However, the results of regression coefficients showed that only size of credit (Beta = 0.308) and repayment period (Beta = 0.399) were significant predictors of this model. Interest rate (Beta = 0.014) and borrowing experience (Beta = -0.135) had negative but statistically insignificant effect on the model.

5. DISCUSSION OF FINDINGS Size of credit (amount borrowed) was positively correlated with total sales and business net worth at significant levels. However, the same was not significantly correlated with net profit. The implication of these findings is that borrowers could quickly spend the borrowed money to restock their businesses or purchase business assets. However, since the borrowed sums were as small as TZS 25,000, their businesses could not fetch enough profit to guarantee sustainable investments and

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expansion. This view is well supported by empirical study by Kuzilwa (2005) where women owners of restaurants in Morogoro regions had failed to expand their businesses due to inadequate credit. The stance is also supported by evidences from Kenya showing that credit clients under Kenya Rural Enterprise Program (K-REP) had failed make significant investment on their businesses because the loans were too small to do so. Interest rate per annum was found to have negative and significant correlation with all three indicators of business performance namely total sales, net profit and business net worth. This implies that annual interest rates associated with microloans were too high to allow firms make profit and investments. The findings conform to a reasonably large body of knowledge that suggests that high interest rates have been the reason why microcredit clients have always remained poor (Stewart et al., 2010). The findings are also in consonance with evidences from the previous studies that high interest rates was one of major causes of borrowers‟ over indebtedness (Schicks, 2011) and that the same is a disincentive to further borrowing (Kayunze et al., 2005), at least, for investment in business. Loan repayment period was positively correlated with all three indicators of business performance including total sales, net profit and business net worth at statistically significant level. The findings imply that borrowers given more flexible repayment option in terms of grace period and loan term were likely to have their businesses perform better than those whose loans are guided by strict and tight repayment schedules. The findings corroborate those of previous studies showing that flexible repayment period coupled with a grace period made it possible for borrowers to get more profit and invest on productive assets (Field and Pande, 2008; Field et al., 2011). Borrowing experience was positive and statistically significant correlation with total sales. The rest of two business performance measures namely net profit and net business worth were not significantly correlated with borrowing experience. The implication of these findings is that long participation in microcredit schemes (long borrowing experience) was unlikely to have positive impact profitability and business investment. In fact, there are empirical evidences showing that households of clients who had participated for long time were likely to fall into poverty than non-clients (Barnes et al. 2001b; Lakwo, 2006).

It is worth noting that whereas women borrowers could repay their loans in the first borrowing cycles, they were likely to fail in the subsequent following cycles. According to SEDA‟s loan manager, in the first rounds new entrants in the loan schemes worked hard to repay their loans so as to empress the lender and thus qualify for another round with more funds. This could even involve borrowing from other sources thus increasing their state of indebtedness. Some of the FGDs also revealed the same scenario and that explains the reason why some women borrowers ended up losing household items when they were auctioned by fellow solidarity group members. This is the idea held by Coleman

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(2001) when he posits that due to small size of loan, borrowers have to occasionally turn to money lenders for more loans to finance loan repayment thus making them even poorer than they were before. Finally, the findings revealed that the combined effect of loan size, interest rate, repayment period and borrowing experience accounted for 25% of total sales revenue, 9% of net profit and 28% of business net worth. The models were weak and this can be explained by two reasons. First, borrowers used part of borrowed money to finance other household requirements than business. This means that little credit went into business and thus its effect on the same would as well be little. Second, the performance of women owned microenterprises is a function of a multitude of factors; some of them known to operators themselves. Credit therefore accounts for just part of those many factors .

6. CONCLUSION AND RECOMMENDATIONS This study has shown that interest rate, which was as high as 600% per annum, had negative effect on all three business performance indicators. Both the model results and specific correlation analysis results indicated that the relationship between net profit and the four credit characteristics was either significantly negative or insignificant. This leads to the conclusion that the businesses of women borrowers were not as profitable as they could be due to, among other things high interest rates and other stringent lending conditions by MFI and individual money lenders.

Based on the above findings and conclusion, this paper recommends for the following measures. The MFIs operating in Tanzania should consider lowering the interest rates attached to their loan products to a level which can guarantee a win-win situation. By lowering the interest rates, women owned microenterprises will be more profitable the fact that will in turn contribute to the improved loan repayment rate. The Government thought the Ministry of Cooperatives and Food Security should wage serious campaigns to expand the outreach of Savings and Credit Cooperative Societies (SACCOS) to help the poor get financial services at relatively low cost. This imitative is likely to curb the penetration of microcredit services provided by individual money lenders whose interest rates are exorbitantly high.

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May, N., (2007). Gender responsive entrepreneurial economy of Nigeria: Enabling women in a disabling environment. Journal of International Women's Studies, 9 (1). Mosley, P. and Hulme, D. (1998), “Micro-enterprise Finance: Is there a Conflict between Growth and Poverty Alleviation?” World Development, Vol. 26, No. 5, pp 783-790. Musso, P., & Schiavo, S. (2008). The Impact of Financial Constraints on Firm Survival and Growth. Journal of Evolutionary Economics, 18(2), 135-149. Nchimbi, M. I. (2002). Gender and Entrepreneurship in Tanzania: A Comparative Analysis of Male- Female‟s Start-up Motivation, Individual Characteristics and Perceptions of Business Success, Thesis submitted for award of PhD at University of Dar es Salaam, Dar es Salaam, Tanzania Olomi, D. R. (2001). Entrepreneurial Motivation in a Developing Country Context-Incidence- Antecedents, and consequences of Growth-seeking Behaviour Among Tanzanian Owner-manager. Thesis submitted for award of PhD at University of Dar es Salaam. Okpukpara, B. (2009). Microfinance paper wrap-up: Strategies for effective loan delivery to small scale enterprises in rural Nigeria. Journal of Development and Agricultural Economics, 1 (2), 41-48. Otieno, S, Lumumba, M, Nyabwanga, R. N, Ojera, P and Alphonce, J. O (2011). Effect of provision of micro finance on the performance of microenterprises: A study of youth microenterprises under Kenya Rural Enterprise Program (K-REP), Kisii County, Kenya. African Journal of Business Management Vol. 5(20), pp. 8290-8300, [Available online at http://www.academicjournals.org/AJBM. Accessed on 2013] Parker, S. C., & Van Praag, M. C. (2006). Schooling, Capital Constraints, and Entrepreneurial Performance. Journal of Business and Economic Statistics, 24(4), 416-431. Roodman, D. (2011). „Due Diligence: An Impertinent Inquiry into Microfinance‟, 19 December 2011, Centre for Global Development http://books.google.co.uk/books/ about/ Due_Diligence.html?id=CxGnCoLkt4QC [Accessed on 2012] Rosenberg, R, Gonzalez, A., and Narain. S. (2009). The New Moneylenders: Are the Poor Being Exploited by High Microcredit Interest Rates? Occasional Paper 15. Washington, DC: CGAP http://papers.ssrn.com/sol3/ papers.cfm?abstract_id=1400291 [Accessed on 2010] Schicks, J., (2011). Over-Indebtedness of Microborrowers in Ghana: An Empirical Study from a Customer Protection Perspective, Centre for Financial Inclusion http://centerforfinancialinclusionblog.files.wordpress.co m/2011/12/111108_cfi_over-indebtedness-inghana_jessica-schicks_en_final.pdf[Accessed on 2013] Stewart R, van Rooyen C, Majoro M, de Wet T. (2010). What is the Impact of Microfinance on Poor People? A systematic review of evidence from sub-Saharan Africa, London: EPPI-Centre, Social Science Research Unit, University of London http://www.dfid.gov.uk/R4D/ PDF/Outputs/SystematicReviews/MicroFinance_FOR+ WEB%5B1%5D.pdf [Accessed in 2013] Vogelgesang, U. (2001). The Impact of Microfinance Loans on the Clients' Enterprises: Evidence from Caja Los Andes, Bolivia. Gk working paper series no. 2001-03, University of Mannheim

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The Dimensions of Industrial Growth in Tamil Nadu, India: Three Decades of Experience Dr. A. Sankaran1 & Dr. P.Rajkumar2 1

Assistant Professor, Department of Economics, Pondicherry Central University, India Assistant Professor, Department of Sociology, Annamalai University, India

2

ABSTRACT Industrial development plays a momentous role in all walks of development. The empirical investigations of world famous works pursued by Simon Kuznets(1966) Chennery(1980), Hoffman(1958), Murray & Bryce(1960) and Kaldor(1978) found that there is a positive and significant association between industrial development and overall development of a nation. In this paper an attempt is made to assess the various dimensions of industrial development of Tamil Nadu, India. To examine the performance of the industrial economy of Tamil Nadu, statistics have been collected from Annual Survey of Industries, published by Central Statistical Organization, Government of India. The variables administered in this work to evaluate the performance of agro based and non agro based manufacturing industries of Tamil Nadu include number of factories, productive capital, employment, value of output and value added. This study covers the period of three decades form 1980-81 to 2010-11, so as to understand the effects of the new economic policy. Further, the entire study period has been classified into two folds as pre reform period (1980-81 to 1990-91) and post reform period as (1991-92 to 2010-11). Collected statistics are deflated using wholesale price index to overcome the price fluctuation. The result obtained using annual compound growth rate reveals that almost all the variables express the same level of growth in both agro and non-agro related industries. But, owing to extraordinary performance of chemical based industries the value added of non- agro related industries reveal a dramatic growth. Mention should be made that the growth of employment has shown a negative sign during the reform period. Hence, it is suggested that the policy makers should frame the effective and suitable policy considering the employment generation. Such kind of strategies will give a new life not only to India but also all the developing countries.

Key words: Manufactures, Manufacturing, India JEL Classification Code: O47; L69

1

I

INTRODUCTION

ndustrial development plays a key role in the economic development of a nation in general and developing courtiers in particular. The World Bank(1995) rightly remarked that the industrialization is viewed as almost synonymous with development. The empirical evidences of Chennery(1960 &1980), Simon Kuznets(1966) Colin Clark(1940), and Taylore(1969) show that industrialization leads to enhance the per capita income and the standard of living through spread effect. In fact, industrial development is an effort in which the underdeveloped countries place a major hope of finding a solution to their problems of poverty, insecurity, and over population and ending their newly realized backwardness in the modern world (Murray & Bryce,1960). In addition to this, industrialization of an economy saves foreign exchange, raises output per head, remarkable reduction in cost and drudgery of production process (Slichter, 1961). Development experience of this world demonstrated that no country has achieved sustained economic growth without developing the secondary sector.

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According to Kaldor(1978), the driving force behind economic development rests upon the growth of manufacturing sector. In his scholarly research he has highlighted that there is a close significant association between growth of manufacturing output and overall economic growth. Further, the development experience of East and Southeast Asian Economies demonstrates that they have been efficiently participating in the global trade, aided by manufacturing products, led initially by Japan, then by the newly industrializing economies (NIEs) of Hong Kong, China, Korea, Singapore, Taipei, and more recently by the Peopleâ&#x20AC;&#x;s Republic of China (PRC). Moreover, in the economy of five members of the Association of Southeast Asian Nations (Indonesia, Malaysia, Philippines, Thailand, and Vietnam), there are some crystal clear spillover effects by industrial development. India has been taking a number of efforts to attain a predominant place in the global manufacturing trade. With the globalization of the economy and implementation of liberal industrial policy reforms, the overall industrial environment at national and state level has become very vibrant due to the spurt in direct

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investment flow, import of high-tech machines, technology and managerial skills. In India, Tamil Nadu is one of the important icons in terms of industrial development.

manufacturing sector consisting of all manufacturing enterprises, which are not registered under the Indian Factory Act and are not included in this study.

2

3

SOCIAL RELEVANCE OF INDUSTRIALIZATION

An American economist, Sullivan(2003) pointed out that industrialization is the process of social and economic change that transforms a human group from an agrarian society into an industrial one. It is rightly mentioned in the text book of world history that between 1700 and 1900, industrialization changed the lives of people in Western Europe and the United States. Industrialization has increased dramatically the economic power of Europe and t revolutionized every facet of society, from daily life to life expectancy. Further history shows that due to rapid industrialization in Britain around the 1800s, people enable to earn higher wages in factories than that of cultivation. With this finance, they could afford to heat their homes with coal from Wales and dine on Scottish beef. Further, they purchased better clothing, in Englandâ&#x20AC;&#x;s industrial cities. In fact, industrialization has a direct and positive impact on the human life. These aspects are well documented in the globally recognized literature that there is a perceptible shift in economic life from village to town, social life becomes dependent upon one another, men are free to utilize their human capital, and a very comfortable life is ensured by better transportation, communication, and mechanized environment. Among these contributions Nettl & Roland Robertson(1966), and Igor VriĹĄer(1992), underlined the role of industrialization in social change, Treiman (1986) discussed the effect of industrialization on social stratification. Sickle(1949), Murphy, Shleifer and Vishny(1989) highlighted that underdeveloped countries around the globe considered the industrialization as the solution for all their social and economic ills. Further, the increase in industrial productivity resulting from the use of sophisticated equipments rapidly gained momentum and transformed into a higher standard of living. Greenfield(1961) reported that as a result of urban industrial revolution the modern, small and nuclear families are established in Western Europe and the United States over the course of development. Park(2001) found that in Korea there was an upward mobility in the society, which is entirely different from the experience of European countries of England, France, and Sweden. Further, there was a dramatic change in occupational structure due to industrialization. The purpose of the present study is to examine the industrial growth that has taken place in Tamil Nadu. This study covers only the registered manufacturing sector the manufacturing sub-sector with a value added share of about 80 per cent in the industrial sector. It has two broad sub-folds viz., factory sector and non-factory sector. The factory sector referred to as registered under the Indian Factory Act 1948. The non-factory sector or unregistered

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STUDIES ON INDUSTRIAL GROWTH

There are copious literatures available on industrial growth, expansion, sophistication, and structural transformation in dealing with the theory, policy, practices and its social relevance in both developed and developing countries. A bulk of the analytical literature on industrial sector using stylized analytical tools is available in the form of articles written by eminent scholars and published in the academic journals. The quintessence of the national level studies are presented here. Previous studies in India were done by Ahluwalia(1985), Shetty(1987) Rangarajan(1994), Sandesar(1987), Nagaraj(2003), Balakrishnan & Suresh Babu(2003), Chaudhuri(2002), and Uma Rani & Unni(2004), they concentrated on the growth, performance and structural changes of the industrial economy of India and various states. In addition to these, some other studies have concentrated on various dimensions such as special differences with regard to industrial development, impact of competition and FDI flow of industrial economy. However, studies on agro and non-agro based industries were undertaken by Venkataramaiah & Burange(2003). They have underlined that the non-agricultural related industries grew at a rate of nearly 11 per cent of output, but the agro based industries undergone 8 per cent of growth during the study period of 1980-81 to 1997-98 in Andhra Pradesh. The non-agro based industries recorded higher rate of growth during the post reform period. Similar study was conducted by Burange(1999) on the industrial economy of Maharashtra covering the period from1979-80 to 1994-95. He revealed that the nonagro based industries show higher rate of growth of 6.6 per cent in respect of value added, while the agro-based industries experienced 4.2 per cent of growth under the period of study. From the sharp of the above studies, the present paper tries to scrutinize the growth of agro and non-agro based industries in the industrial economy of Tamil Nadu during the pre and post reform periods.

4

MATERIALS AND METHODS

The present research has attempted to ascertain the growth of industrial economy of Tamil Nadu. The study period has been classified in to two folds as pre reform (1980-81 to 1990-91) and post reform periods (1991-92 to 2010-11) similar classification was made by Golder(2004), Nagaraj(2003), Venkataramaiah and Burange(2003), Balakrishnan ans Suresh Babu(2003), and Uma Rani & Jeemol Unni(2004) at all India level. The authentic date on the industrial economy of Tamil Nadu are available only upto 2010-11 in the Annual Survey of Industries (published by CSO, Government of India) which is the principal source for this study,. The factors such as Number of Factories, Productive Capital, Number of Persons Employed, Value of

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Output and Value Added have been used to assess the growth of industrial economy of Tamil Nadu. The values are duly weighted and normalized against price fluctuation by using the appropriate wholesale price index. The index of wholesale price for Tamil Nadu is available at 1970-71 base, hence this study used all India whole sale price index of 1993-94 base, for deflating the two digit group data. Manufacturing industries at two digit level have been classified by Thomas(2002) Venkataramaiah and Burange(2003) Jayasree De(1993), Sudhakar Reddy(1994), Rajeswari(1989), and Thangamuthu(1983) as agro and nonagro related industries. The agro related industries covered from 20-21 to 29 where as the non-agro related industries are embodied remaining all industries (30 to 38), the same procedure is followed in the present study. The annual compound growth rate has been advocated to understand the growth of these industries for the pre and post reform periods. The formula to compute the ACGR is-

ACGR (t 0, t n )  (V (t n ) / V (t 0 ))

1

t n t0

1

Where, V(t0)- stands for start value, V(tn)- denotes the final value and tn-to - is number of years.

5

ANALYSIS AND DISCUSSION

The quality of industrial sector has been indicated by its forward and backward linkages. The forward linkages of an industry capture its output that feeds into another industry. For instance, the output of semi-conductor manufacturing unit may serve as an input to computer and photographic equipment manufacturing unit. At the same time, the backward linkage creates demand for suppliers who provide input to industrial units such as automobile manufacturing unit creates demand for tyres, steels, and microprocessors (Alamar & Murali, 2007). According to various issues of Tamil Nadu An Economic Appraisal the contribution of the manufacturing industries to Tamil Nadu‟s industrial economy- in 198081 the agro-related industrial group registered 46.5 per cent of value added, the modern industries accounted for 53.5 per cent of value added. In 2002-03, the proportion of agro-related industries declined to 43.7 per cent and the proportion of modern groups improved to 56.3 per cent with respect of value added. In terms of employment generation, the agro-related industries accounted 59 per cent and modern industries provided 40.9 per cent in 1980-81. It should be mentioned that in 2002-03 also the employment generation of agro related and non-agro related industries are more or less gripped in the same place. Similarly, the study conducted by Burange(1999) at all India level concluded that the share of agriculture related industries with regard to fixed capital, employment, value of output and value added had decreased substantially over the study period of 1979-80 to 1994-95, ironically, the non-agro related industries went up.

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Table: 1 Annual Average Growth Rate from 1980-81 to 2010-11. Characteristics Agro-Based Non-Agro Based Factories 3.25 3.62 Productive Capital 10.07 10.90 Employment 1.98 1.85 Value of Output 8.14 7.95 Value Added 7.96 23.57 Source: Computed from ASI data. Note: Productive Capital, Output and Value Added are monetary terms and Factories and Number of Persons Employed are in Numbers. Considering the result of annual compound growth rate, the criterion viz., number of factories, productive capital and employment are nearly same for both agro and non-agro related industries. Surprisingly, the growth rate of output of agro-related industry is slightly higher than that of non- agro related industries. But, with respect to value added, the nonagro related industries revealed a dramatic growth. This appreciable trend is aided by the hasten growth of chemical and chemical producing industries, transport equipment and parts and metal producing industries. While comparing prereform period with the post-reform period, the productive capital and employment are increased in agro based group. Its growth of output is at a stagnant position. All the other characteristics have declined in the reform regime. The leading economists like Ahluwalia and Rangarajan(1994) have stressed that the poor performance of agricultural sector is the causative factor for the sluggish trend of industrial sector in the reform period. Table: 2 Annual Average Growth Rate of Tamil Nadu Manufacturing Non-Agro Based Agro-Based Pre-Reform Post-Reform Pre-Reform Post-Reform Characteristics (1980-81 to (1991-92 to (1980-81 to (1991-92 to 1990-91) 2010-11) 1990-91) 2010-11) Factories 3.97 2.45 5.38 1.67 Productive 9.21 11.03 10.69 11.13 Capital Employment 1.70 2.29 3.66 -0.17 Value of Output 8.08 8.20 7.70 8.22 Value Added 9.82 5.90 21.92 25.40

Source: Computed from ASI data. Note: Productive Capital, Output and Value Added are monetary terms, and Factories and Number of Persons Employed are in Numbers. Based on the non-agro based industries, productive capital and value of output had increased at a snail‟s phase and the value added had revealed nearly 4 per cent growth from pre to post reform period. It is obvious that the usage of chemicals in all the production process, particularly in agriculture, medicine, textile, matches and photo processing has increased steadily. Mention should be made that the cosmetic industries (by using chemicals) have increased tremendously in the recent periods, which boost up the value added of chemical industries in the industrial economy of Tamil Nadu.

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Conversely, the number of factories revealed a sharp decline and the growth of employment has shown a negative sign during the reform period, the same trend is observed at all India level also Nagaraj(2000). Hence, the down turn trend in the employment generation of overall industrial economy of Tamil Nadu during the reform regime is a matter for serious concern and there is an urgent need to arrest this trend.

6

0

[4]

[5] [6]

CONCLUSION

The foregoing analysis of growth of agro and non-agro based industries for the period of three decades starting from 1980-81 to 2010-11 has yielded the following conclusions. Number of factories, productive capital and employment are nearly same for both agro and non-agro related industries in terms of growth. But, owing to extraordinary performance of chemical based industries the value added of the non-agro related industries revealed dramatic growth for the entire study period. In the agro-based industries, the growth of productive capital and employment were increased from pre to post reform period, while, all other characteristics are decreased (except output) for the above said periods. In the non-agro based industries, productive capital and value of output had increased at a snail‟s phase and the value added had revealed a healthy growth from pre to post reform period. Ironically, the number of factories revealed a sharp decline. More importantly, the growth of employment has shown a negative sign during the reform period. The same jobless growth was observed by Ahluwalis(1985), Nagaraj(2000), Chaudhuri (2002) and Venkataramaiah & Burange(2003) at all India level too. Hence, it is to be suggested that the policy makers should frame effective and suitable policies considering the employment generation. Such kind of strategies will give a new life not only for India but also for all the developing countries.

ACKNOWLEDGEMENT We express our heartfelt gratitude to Prof. C. Thangamuthu, Former Vice-Chancellor of Bharathidasan University, Tiruchirappalli, Tamil Nadu, and Dr. Amaresh Samantaraya, Associate Professor, Department of Economics, Pondicherry Central University, Pondicherry, India, for their valuable guidance and suggestions towards the preparation of this research article.

[7]

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Economic and Political Weekly, vol. XXXVIII, no: 38, pp. 3997-4005, Sep.2003. L.G.Burange, “Industrial Growth and StructureManufacturing sector in Maharashtra”, Economic and Political Weekly, vol: XXXIV, no.9, pp. 39-48, Feb.1999. M.D. Bryce, Industrial developed A guide for accelerating economic growth”, The McGraw, London, p. 3, 1960. S. Chaudhuri, “Structural Changes and Fluctuations in Manufacturing Factory Secto- A Disaggregative Analysis: 1959-1984-85”, Working paper series –121 (89), Indian Institute of Management, Calcutta, pp 152. Nov. 1989. S. Chaudhri, “Economic Reforms and Industrial Structure in India”, Economic and Political Weekly, vol. XXXVI, no. 2, pp.155-162, Jan.2002. H.B. Chenery, “Patterns of Industrial Growth”, American Economic Review, vol .50, no. 4. pp. 624-654, Sep.1960. H.B. Chenery, “Interaction Between Industrialization and Export”, American Economic Review, vol .10, no. 2. Pp. 281–287, Sep.1980. C. Clark, The Conditions of Economic Progress, Macmillan, London, pp. 123-135. 1940. D. J. Treiman, “Industrialization and social Stratification”, Sociological Inquiry, vol.40, no.9, pp. 207-234, Jan.2007. S. M. Greenfield, “Industrialization and the Family in Sociological Theory”, American Journal of Sociology, vol. 67, no. 3, pp. 312-322, Nov. 1961. B.Goldar, “Indian Manufacturing: Productivity Trends in Pre- and Post- Reform Periods”, Economic and Political Weekly, vol: XXXIX, no.46, pp. 5033-5043. Nov. 2004. H. Park, “Industrialization and Social Mobility in Korea”, CDE Working Paper, No. 99-32, University of Wisconsin-Madison, pp. 1-58. Nov. 2001. Igor Vrišer, “Industrialization of Slovenia”, GeoJournal, vol. 27, no. 4, pp. 365-370. Aug. 1992. D. Jayasree, “Industrial Pattern of Gujarat”, Perspectives on Industrial Development in India, N.K.P. Sinha and M.B. Singh, eds, Deep & Deep Pub, New Delhi, pp. 61-74, 1993. N.Kaldor, Further Essays in Economic Theory, Duckworth, London. pp. 156-170,1978. M. Kevin, Murphy.K, Andrei Shleifer and R. W. Vishny, “ Industrialization and the Big Push”, Journal of Political Economy, vol. 97, no.5, pp. 1003-1026, Oct. 1989. S. Kuznets, Modem Economic Growth: Rate, Structure, and Spread, New Haven: Yale University Press, pp. 132. 1966. R. Nagaraj, “Industrial Policy and Performances Since 1980: Which Way Now?”, Economic and Political Weekly, vol. XXXVIII, no.35, pp. 3707-3715, Sep.2003. R. Nagaraj, “Organized Manufacturing Employment”, Economic and Political Weekly, vol. XXXV, no. 38, pp. 3445-48, Oct. 2000. J.P. Nettl. and Roland Robertson, “Industrialization, Development or Modernization”, The British Journal of Sociology, vol. 17, no. 3, pp. 274-291, Sep. 1966.

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[23] L.J. Perry, “Singapore‟s Rapid Industrialization: A Reassessment”, An Interdisciplinary Journal of Southeast Asian Studies, vol. 10, no. 1, pp. 67-76. Dec. 1996. [24] V.Rajeswari, “Growth and Diversification of Industries, Industrial Development of Andhra Pradesh, J.Manender Reddy, eds, Streling Pub, Bangalore, pp. 122-135, 1989. [25] C.Rangarajan “Industrial Growth: Another Look”, Industrial Growth and Stagnation- The Debate in India, Deepake Nayyar, eds, OUP, Bombay, pp 289-317, 1994. [26] J.C Sandesare, “Industrial Growth in IndiaPerformance and Prospects”, Studies n Industrial Economy of India, V.S Mahajan, eds, Deep & Deep, New Delhi, pp. 19-81, 1987. [27] J. V. V. Sickle, “Industrialization and the South”, Southern Economic Journal, vol. 15, no. 4, pp. 412-424, Apr. 1949. [28] A. Sullivan, “Economics: Principles in action- Upper Saddle River”. New Jersey, Prentice Hall. P.472, 2003. [29] Sudhakar Reddy, “Industrial Performance of Andhra Pradesh”, Political Economy of Rural Development, K.

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Asian Business Review, Volume 3, Number 4/2013 (Issue 6) ISSN 2304-2613 (Print); ISSN 2305-8730 (Online)

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Foreign Direct Investment (FDI) in Bangladesh: Prospects and Challenges and Its Impact on Economy K. M. Anwarul Islam Senior Lecturer, Department of Business Administration, The Millennium University, Bangladesh

ABSTRACT This research will try to examine the FDI plays a dominant role in the economy of Bangladesh through accelerating Gross Domestic Product (GDP), export and domestic investment followed by overall economic growth. So it is vital for a developing country like Bangladesh to carry out effective measures in protecting the prospective foreign investors so that they can get a congenial atmosphere to invest their capital. They should feel that their role in the business arena of Bangladesh is respectfully valued. In this connection, friendly regulations, simplifying regulatory practices, investment incentives and removal of inefficient bureaucratic procedures should be ensured. Keywords: Foreign Direct Investment, Economic Growth, Prospects & Problems of FDI, Impact of FDI. JEL Classification Code: A10, E20, E22, E62

1

INTRODUCTION

F

oreign Direct Investment (FDI) is considered as one of the vital ingredients for overall development process of a developing country like Bangladesh. Industrial development is an important prerequisite for economic growth of a developing country. Bangladesh is basically a country of agrarian economy. For her economic development, industrial economy is imperative. So Bangladesh is gradually moving from agrarian economy to industrial economy. In the age of globalization, it has become a burning issue to exchange views, ideas, capital and human resources. Government of Bangladesh is trying to create a favorable investment environment through introducing economic policies, incentives for investors, promoting privatization and so on. Therefore, the contribution of FDI is necessary in the enhancement of a country‟s economic growth. Researchers have marked FDI as an important factor in accelerating economic success and wealth of a country as well as a door in creating jobs, facilitating economy, and creating more competitive environment and contributing productivity to the host country. In Bangladesh, FDI plays a significant role in GDP acceleration and economic growth (Mottaleb 2007). FDI has an unmentionable role in the modernization of the Bangladesh economy for last two decades. It helps the country in building up infrastructure, creating more employment, developing capacity, enhancing skills of the labor force of the host country through transferring technological knowledge and managerial capability, and helping in integrating domestic economy and the global economy. Various positive attributes of Bangladesh is now drawing the attention of the investors from both developed and developing countries. In Bangladesh, it is

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available to get skilled labor at relatively low wages. Moreover, there is reasonably stable macroeconomic environment. These two important factors can make Bangladesh an alluring destination for foreign investors. Lowest wage rates among the Asian countries, tolerable inflation rate, reasonably stable (except previous year) exchange rate, investment friendly custom regulations and attractive incentive packages make Bangladesh a favorable investment destination. Bangladesh became more open toward FDI policies over the last decades. These above features will certainly maintain the recent advancement in FDI investment in Bangladesh by the foreign investors. During 1980s, FDI to Bangladesh was very little and mostly focused in banking and a few other sectors. Bangladesh started attracting FDI since 1996 in energy and power sector because of favorable and supportive policies for foreign investment, economic reform as well as unexplored gas and oil resources. In 1972, annual FDI inflow was 0.09 million USD and in 1996, it became 231.61 million USD which rose significantly in 2008 to 1086 million USD which declined to 913.32 million USD in 2010 (source: Bangladesh Board of Investment). The objectives of this project paper are as follows:  To evaluate the FDI status in Bangladesh.  To find out the prospects & problems of FDI in Bangladesh.  To analyze the impact of FDI inflow on GDP, Export and private investment of Bangladesh.

2 METHODOLOGY The methodology includes an econometric model as well as simple statistical tools such as mean, standard

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deviation and percentage. This paper is fully based on secondary information. The relevant secondary data are collected from Statistics Department and Research Department of Bangladesh Bank (Central Bank of Bangladesh), Board of Investment, Bangladesh, Bangladesh Bank Bulletin, Economic Trend, Bangladesh Economic Review, World Investment Report 2010 published by UNCTAD, etc. Time Reference The time reference of the study will be 1996-2010. Data Analysis The statistical tools that have been used in the study areTrend analysis: For trend analysis, time series analysis has been used. Standard deviation has been used for measuring dispersion from the mean result. Regression is used to identify the relationship among the variables.

3 KEY DEFINITIONS Foreign Direct Investment (FDI) FDI is an important category of international investment that shows a long-term relationship between the direct investor and the enterprise. It indicates the influence of the investor on the management of the enterprise. Direct investment relates the initial transaction between the investor and the enterprise. It also shows the transactions between them and among affiliated enterprises, both incorporated and unincorporated. The components of FDI are a) Equity capital, b) Reinvested earnings and c) Intra-company loans. Equity Capital states the ownership as well as the share purchasing of an enterprise by a foreign investor. Reinvested earnings demonstrate that portion of earning of an investor which is not distributed back to him. This means the profits that are not given out as dividends. It is kept within the firm. Intra-company loans include debt transactions and these transactions are regarding lending by the foreign parent company to its affiliates in the form of both short and long-term. Economic Growth Economic growth is a rise in national or per capita income of an economy. If a country increases its production of goods and services, by whatever ways and becomes able to increase its average income, it can be mentioned that the country has achieved “economic growth”. Economic growth can be measured in nominal terms. This includes inflation, or in real terms that is adjusted for inflation. GDP or GNP per capita is used in comparing the economic growth of one country‟s to another. FDI and Growth It is revealed in review of various literatures available on FDI that foreign investment is still viewed as a matter of debate. Opinions are still divided in deciding that whether FDI is boom or bane for host countries economic growth and development. FDI has its own merits and demerits.

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Many scholars argue that developed nations may try to invade the sovereignty of host country through FDI. In order to earn quick profit they may exploit the natural resources at the faster rate and thus leave the host country deprived in the long run. It have been feared that FDI is a big threat to survival of domestic players. Again, many are of the opinion that basic objective of foreign investments is to earn profits by ignoring the overall social & economic development of the host nation.

4 LITERATURE REVIEW There is the global race for attracting FDI, but how much it can contribute to host country's economic development is a matter of assessment. Aitken and Harrison (1999) have evaluated the contribution of FDI to domestic productivity and found positive impacts of FDI on economic development. Again, Levine et al. (2000) found negative results on economic development. Rothgeb (1984) found an immediate troublesome effect of FDI flows on developing countries. This effect would overcome after a short period of time, with positive impacts on growth. Rothgeb (1984) used his model to explore the impact of foreign investment on the growth of Bangladesh and found that FDI has a positive impact on growth. He also found a strong positive effect of the change in the level of domestic investment on growth. V.N. Balasubramanyam, M. Salisu, and D. Sapsford (1996) did an examination about the impact of FDI on economic growth in developing economies using ordinary least squares. Applying the export promotion strategy, they found positive and significant impact of FDI on economic growth in developing countries. Simultaneously, it also showed that such relations do not exist in developing countries applying the import substitution strategy. Bengoa and Sanchez-Robles (1997) showed the positive correlation between FDI and economic growth. In this connection, with a view to getting benefit from long term FDI inflows, human capital, stable economic condition and liberalized markets are required in host countries. Borenszteina et al (1998) examined the data on FDI inflows of sixty nine developing countries by regression framework and found the importance of FDI as a means of transferring technology that contributes more to growth than domestic investment. Pattama (1999) analyzed the long run relationship between FDI and domestic investment in case of Thailand. He found that FDI has a significant and positive long term effect on domestic investment in Thailand. Despite this positive link between FDI and economic growth, empirical evidence also reveals negative association between them. This view goes to the dependency theorists who are in the opinion that dependence on foreign investment tends to create a negative impact on economic growth and income distribution. The dependency theories argue that foreign gigantic players may create negative effect on the growth and development of domestic firms' of a host country in the

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long-run as they have large volume of capital, superior technologies, higher market access, advanced marketing networks and better managerial and human relation skills (Marksun & Venables 1997, Agosin & Mayer 2000, Kumar & Pradhan 2002). According to the dependency theories, FDI may have an adverse impact on income distribution, employment, national sovereignty and autonomy of a country (Musila and Sigue 2006). Bogahawatte (2004) examined the relationship between FDI and economic growth of Sri Lanka for the period of 1977 to 2003 by analyzing the relationship between real GDP, FDI Inflow, domestic investment and openness of the trade policy regime. The examination revealed a strong influence of FDI on economic growth. Mottaleb (2007) studied the determinants of FDI and its effect on economic growth in developing countries. He studied panel data of FDI flows of sixty low income and lower-middle income countries and found that FDI has an important effect on economic growth of third world countries by creating bridge between the gap of domestic savings and investment and familiarizing the up to date technology and management skill from developed countries. Jung Wan Lee, Gulzada S Baimukhamedova, Sharzada Akhmetova (2008) analyzed the correlation between FDI inflows, exchange rate, and economic growth of Kazakhstan by a multivariate regression model with weighted least squares estimates. The results revealed the minimum significant impact of FDI on GDP growth of Kazakhstan. Abdul Rehman, Orangzab, Ali Raza (2009) conducted an analysis by using the data collected over the period of 1975-2008 and identified the determinants of FDI and its impact on GDP growth in Pakistan through different statistical tests and found positively significant impact of FDI on GDP growth of Pakistan. Furthermore, these results indicate that market size, trade openness / access to international market and quality of labor are the major determinants that have significant effect on the FDI inflow. The study also found no effect of market potential and communication facility on the attraction of FDI inflow in Pakistan. Quader, Syed Manzur (2009) applied extreme bounds analysis to the data of the various catalyst variables of FDI inflows in Bangladesh. They found FDI and domestic investment have a positive effect on economic growth. Piotr Misztal (2010) examined the influence of FDI on the economic growth in the Romania in period of 2000-2009 using the Vector Autoregression Model (VAR) and found linear relationship between FDI and economic growth. Muhammad Azam (2010) examined the impacts of exports and FDI on economic growth of South Asian countries namely Bangladesh, India, Pakistan and Sri Lanka with simple log linear regression model using secondary data ranging from 1980 to 2009 and found that due to promotion of exports, economic growth of each country would increase. He also found FDI as positively significant at 1% level of significance for Bangladesh and

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Pakistan, while for India it's insignificant and in case of Sri Lanka though it is significant but with unexpected negative sign.

5 AN OVERVIEW OF FDI IN BANGLADESH 5.1 Present FDI Status Bangladesh has attracted USD 913 million foreign direct investments (FDI) in 2010 calendar year, a leap by 30 per cent. This upgrades the country's position to 114 from 119 out of 141 nations in the World Investment Report (WIR). During this period the telecom sector received USD 360 million FDI, the manufacturing sector received USD 238 million in investment from abroad, USD 145 million in the textile and clothing sector, while leather and leather products got USD 46 million. (The financial Express, 27 July, 2011) As a developing country, Bangladesh needs Foreign Direct Investment (FDI) for its ongoing development process. Since independence, Bangladesh is trying to be a suitable country for FDI. In order to accelerate economic growth, Bangladesh opened her economy in the late 1980s to reap the benefits of FDI. In 1989 the government set up Board of Investment (BOI). The primary objective of which is aimed at attracting and facilitating investment from abroad (Mondal 2003). The government also lifted restrictions on capital and profit repatriation gradually and opened up almost all industrial sectors for foreigners to invest either independently or jointly with the local partners. Further, the government also introduced various financial and non-financial incentives like tax exemptions for power generations, import duty exemptions for export processing industries, tax holiday schemes for undertaking investment in priority sectors and low development areas, zero duty rate for the import of capital machinery and spare parts for 100 percent export oriented industries, almost no restrictions on the entry and exit mode, and reduction of bureaucratic hassles in getting faster approvals of foreign projects. Together with all these incentives followed by a low labor cost structure, Bangladesh has been an attractive destination for FDI in the South Asian region since the late 1980s. The trend of Inflow of FDI in Bangladesh has increased over the 1980s as compared to earlier periods and this same momentum continues in 1990s as well. The total inflow of FDI has been increasing over the years. During the period of 1977-2010, total inflows of FDI were USD 8927.9 million, among which the total inflows of FDI during 2006-2010 was USD 4158.63 million. In 1977, this inflow was USD 7 million and in 2008, annual FDI reached to USD 1086.31 million. Unfortunately, there was a declination in inflows of FDI in 2010 which was USD 913.32 million (Source: Survey Report, Statistics Department, Bangladesh Bank).

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Figure 1 illustrates the trend of FDI inflows in Bangladesh during 1996-2010.

Figure 1: FDI Inflows in USD in Bangladesh during 19962010 Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment. The Figure 1 shows an inconsistent proceeding of FDI inflows during the period. In 1999 there was a sudden decline in the FDI and the falling trend continued for many reasons again in 2001, 2002 and 2003. Serious political unrest during the period discouraged foreign investment and it took quite some time to regain the confidence of foreign investors. There were also some other factors that force this declination in the inflows. After that, there was very good news for Bangladesh. The FDI inflow was on the steady rise from 2003 to 2005. It rose to US$ 1086.3 million in 2008 but slumped to US$ 700.16 in 2009 and again increased to $913.32. 5.2 FDI Inflows by Components

Figure 2: FDI Inflows (in million USD) by components in Bangladesh during 1996-2010 Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment.

Figure 4 FDI Inflows, in million USD by components in 2010 Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment. FDI in Bangladesh consists of three components: Equity capital, Reinvested Earnings and Intra-company loans. These components have fluctuated considerably in the last two decades. In the early year of 1996, the total FDI inflow was only 210 million USD where reinvested earnings were the bigger portion. This trend continued up to 1998. Then there is a sudden decline in terms of total inflow as well as component wise inflow of FDI. Beside a slight increase in 2000, this declining trend continues up to 2003. After then total inflow continues to rise with some ups and downs. The portion of equity capita l continues to have a bigger part in the total FDI inflows. In 2008 the total inflows was 1100 million USD which is the highest ever. The shifting of component wise FDI inflow in Bangladesh is clearly in the Figure 3 and 4. In present years, the major share of FDI inflow in Bangladesh come in equity capital from. In 1996 the share of equity capital in total FDI was 30 percent which increases to 57 percent in 2010. In 1996 share of reinvested earnings was 53 percent which decreased to 40 percent in 2010. On the other hand, share of intra-company loan was 17 percent which then decreased to 3 percent in 2010. This shows that the net transfer of resources from abroad into Bangladesh is fairly negligible. The contribution of FDI is very little in case of transfer of 'hardware' technology. 5.3 FDI Inflows by Areas (EPZ and non EPZ)

Figure 3 FDI Inflows, in million USD by components in 1996

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Figure 5: FDI Inflows (in million USD) by area (EPZ and non EPZ) in Bangladesh during 1996-2010

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Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment. Figure 5 reveals that despite the initial increase and steady continuation, FDI inflows in Non-EPZ areas was in declining trend during the period of 2001-2003. In 2004 it increased to 800 million USD and this trend continued up to 2005.The FDI inflows in Non-EPZ areas in 2010 recorded to USD 795.15 million which is 87 percent of total inflows whereas in the beginning of this period (in 1996) it was USD 189.3 million which is 82 percent of total inflows. In the EPZ areas, the FDI inflows were always in a steady direction. 5.4 FDI Inflows by Sectors Sector-wise analysis of FDI reveals the fact that a shift has been made by the foreign investors in their investment in Bangladesh (Annex Table-3.4). The table shows the trend of FDI towards power and energy, manufacturing and telecommunications, whereas the neglected sectors were agricultural, Services and trade and commerce. In 2005, the main focus of investment was in the manufacturing sector. The success in textiles through the ready-made garments (RMG) industry was a vital part of this investment. The pie chart shows the shift of FDI in the sectors in Bangladesh. The pie chart draws a clear picture how the dimensions of FDI inflows have changed in recent years. The reduction in FDI shares of manufacturing demonstrates that its stronghold position for foreign investment is in declining state. On the other hand, telecom sector is gaining prominence during present years. In 2008 the telecommunications sector overtook manufacturing sector as the leading recipient of FDI. Due to increased privatization efforts by the government, telecom has emerged as one of the fastest growing sectors in the Bangladesh economy. Much of this can be explained by the increased competition between large private corporations that have magnified efforts to attract FDI and attain better and latest technology to optimize the profits. In addition to that, the energy sector draws lower amount of FDI, which is explained by the country‟s natural gas reserves. Another factor is the country‟s difficulty in electricity generation. The lack of production capacity forces the government to frequently „load shedding‟ power. It imposes blackouts in areas of low power usage to meet the needs of areas of higher power usage. The government‟s lacking of the capital and liquidity of building power grids and expanding the country‟s electric capacity opens the door of much scope for foreign investment.

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Figure 6: FDI Inflows (in million USD) by sectors in Bangladesh during 1996-2010. Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment.

Figure 7: FDI Inflows (in million USD) by sectors in Bangladesh during 1996-2000. Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment.

Figure 8: FDI Inflows (in million USD) by sectors in Bangladesh during 2001-2005. Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment.

Figure 9: FDI Inflows (in million USD) by sectors in Bangladesh during 2006-2010. Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment. In the Figure 8 and 3.4.4, it is clearly shown that the percentage of investment in various sectors has changed quite a lot. The percentage of telecommunication investment was 2% in 1996-2000 was only 2%, which increases to 21% during 2001-2005 and finally it topped to 43% during 2006-2010. On the other hand, the portion of investment in the gas & petroleum sector has declined gradually during the year of 1996 to 2010. It was 28% in 1996-2000, 18% in 2001-2005 and only 13% in 2006-2010.

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It is also a matter of great concern that the investment in energy sector has decreased from 12% to only 3%, which is very alarming. The government should take a close look in this matter and take necessary steps to identify the causing factors and to rectify those to improve our present energy sector conditions. 5.5 FDI Inflows by Countries The country wise FDI inflows in Bangladesh from top 10 investing countries during 1996-2010 are presented in Figure 10.

Figure 10: FDI Inflows (in million USD) by countries during 1996-2010. Source: Board of Investment, Bangladesh. The Figure 10 shows that United Kingdom has gained the top most position among the top 10 investing countries in Bangladesh during 1996-2010 in investing in various sectors of economy. Out of total FDI inflows from the top 10 investing countries during this period, 17.4% was from United Kingdom, 13% from USA, 8% from Egypt, 7.7% from South Korea, 6.4% from Netherlands, 6.2% from Singapore, 5.6% from Hong Kong, 5.2% UAE, 4.8% from Japan, 3.5% from Malaysia, 3.2% from Australia, 2.1% from Denmark, 2.1% from Switzerland.

Figure 11: FDI Inflows (in million USD) by countries during 1996-2000. Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment.

Figure 12: FDI Inflows (in million USD) by countries during 2001-2005.

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Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment.

Figure 13: FDI Inflows (in million USD) by countries during 2006-2010. Source: Survey Report, Statistics Department of Bangladesh Bank and Foreign Direct Investment in Bangladesh (1971-2010), Board of Investment. Figures 3.5.3-3.5.5 showed how the ever changing nature of FDI inflows over the year. From the figures, it is clearly seen that developed country was highest investor during 19962005 but during 2006-2010 Middle East stood in the highest position. It revealed that there is a shift in investment regime. It reveals the importance for Bangladesh to maintain a continuous favorable business relation with developed countries for increasing their share of FDI in Bangladesh. The Asian countries should get more attention in terms of creating necessary investment climate. It is also important to continue warm relationship with Middle East countries as their significant share of FDI in recent years. Furthermore, Bangladesh must not lose the faith of ADB and IFC for FDI. They have a remarkable ranking in investing Bangladesh.

6 PROSPECTS & PROBLEMS OF FDI IN BANGLADESH Prospects of FDI Bangladesh has been promoting FDI for decades with the most liberal investment policy and incentive regime in South Asia. The Foreign Private Investment (Promotion and Protection) Act, 1980, ensures equal treatment for local and foreign Investors. This act also provides legal protection to foreign investment in Bangladesh against nationalization and expropriation. It also gives the guarantee of repatriation of capital and dividend. Bangladesh has achieved a consistent GDP growth of over 5% in the last decade and never experienced a negative growth. Even Bangladesh sustained growth of over 5% during the recent global economic crisis. In 2009 Bangladesh achieved a 5.9% GDP growth. Various necessary steps like generation of huge number of SMEs, success in micro credit and NGO activities, rapid spread of telecommunications services, record level of foreign remittances, acceleration of export earnings are taking the economy at a higher level of growth. Its investment friendly climate offers generous and attractive packages of incentives for foreign investors like 100% ownership, tax and duty exemptions and others. Actually, Bangladesh has gained a higher ranking than many

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developing countries in terms of incentive package. A lot of additional fiscal incentives are offered to export oriented industries. The government has created Export processing zones (EPZs) to attract private investment. The government targets foreign investors to invest in EPZ. The vision is that the unique opportunities in energy and power, infrastructures, manufacturing and knowledgebased sectors will attract substantial investment. Bangladesh has become a least cost producer in the world with various positive factors like industrious lowcost workforce, strategic location, regional connectivity and worldwide access, strong local market and growth, low cost of energy, proven export competitiveness, competitive incentives, export and economic zones, positive investment climate. Bangladesh is ranked 119th position globally and 4th in the SAARC region in the Ease of Doing Business Ranking by World Bank and IFC report entitled "Doing Business in 2010". Facilities and incentives for foreign investors FDI has been allowed in all sector of the economy except five industries - defense equipment, nuclear energy, forest plantation, security printing and railways. The investors enjoy the following incentives for investing in Bangladesh – a) 5 to 7 years corporate tax holiday for selected sectors. b) Private power companies enjoy corporate income tax exemption for a period of 15 years. c) Tax exemption on royalties, technical knowhow and technical assistance fees and facilities for their repatriation. d) Tax exemption on foreign loans regarding interest. e) Tax exemptions on capital gains from transfer of shares by the investing company. f) Remittances of up to 50% of salaries of the foreigners employed in Bangladesh and facilities for repatriation of their savings and retirement benefits at the time of their return. g) No restrictions on issuance of work permits to project related foreign nationals and employees. h) Facilities for repatriation of invested capital, profits and dividends. i) Provision of transfer of shares held by foreign shareholders to local investors. j) Reinvestment of remittance dividends would be treated as new investment. k) An investor can wind up on investment either through a decision of the AGM. Once a foreign investor completes the related formalities to exit the country, he or she can repatriate the sales proceeds after securing proper authorization from the Central bank. Bangladesh makes no difference between foreign private investors and domestic investors regarding investment incentives or export and import policies. In Bangladesh foreign investors enjoy the access to domestic capital markets for working capital in the form of loans

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sanctioned from the commercial banks and development financial institutions. The foreign investors have been given the opportunity to have access to the services of the country's stock exchanges. Some export-oriented industries of the thrust sector are provided with the benefit of cash incentives, venture capital, and other investment friendly facilities. The Board of Investment (BOI) of Bangladesh provides registration and other services. They also provide the procedures for FDI those have been simplified to attract FDI. Bangladesh Bank has prepared a sovereign and highly effective credit rating report. This should help to attract FDI as well as boost short-term borrowings for the country's private and public sectors. Country‟s image will be enhanced by this sound and sovereign credit rating report. It will certainly help local financial organizations to tap low-cost borrowings from foreign sources. The dependence on the London inter-bank offer rate will be definitely reduced. It also helps to obtain low-cost funds from foreign sources. Problems of FDI Although Bangladesh is trying to be as friendly as possible to FDI, she is facing some problems regarding investment from foreign sector. The FDI friendly policies of the government and a culture of hospitality to foreigners are very much positive to welcome FDI in Bangladesh. But it is a matter of concern that FDI records in the country in terms of the number of projects implemented as compared to those officially registered is frustrating. Only 72 FDI projects went into production in end of 1999 and 27 were in process of implementation of the 365 FDI projects registered during the year of 1996 - 1998, while the remaining 266 projects languished only as the file-cases. The problems that have restricted FDI potentials in the country are as follows:  Bureaucratic interference  Irregularities in processing papers  Overlapping administrative procedures  Absence of a transparent system of formalities  Continuity and prevent timely implementation of strategic, procedural, and even routine duties  Frequent power failures  Poor infrastructure support  Labor unrest  Political unrest  Lack of professional personnel  lack of commitment on the part of local investors  Unexpected delays in selecting projects in studying feasibility  Frequent changes in policies on import duties for raw materials, machinery, equipment etc.

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7 IMPACT OF FDI INFLOW ON THE ECONOMY OF BANGLADESH 7.1 Impact of FDI inflow Now a daze Bangladesh is trying her best to attract foreign direct investment to boost up her economic condition. Bangladesh has liberalized a number of policies so that she can attract more foreign direct investment into the country. It is usually considered that foreign capital inflows can boost up domestic capital. It is believed that FDI accelerates economic activities and eventually causes economic growth. It increases employment opportunities. FDI brings highly productive resources into the recipient economy. This causes positive effects on the employment creation not only in the sectors that attract FDI inflows but also in the supportive domestic industries. 7.2 Dependent Variables GDP: Gross domestic product (GDP) is the market value of all final goods and services produced within a country within a given period. There are many factors to accelerate GDP. It is assumed that the GDP is influenced by FDI Inflow. If the explanatory power of FDI Inflow, the independent variable is high over Gross domestic product (GDP), the dependent variable, the assumption will be proved. EXPORT: There are many factors that can affect export. It is assumed that FDI Inflow is one of the prominent factors that influence the export. If the explanatory power of FDI inflow, the independent variable is high over export, the dependent variable, the assumption will be proved. DOMESTIC INVESTMENT: There are many factors that can affect domestic investment. It is assumed that FDI Inflow is one of the prominent factors that influence the domestic investment through increasing competitiveness. If the explanatory power of FDI Inflow, the independent variable is high over domestic investment, the dependent variable, the assumption will be proved. 7.3 INDEPENDENT VARIABLE FDI INFLOW FDI Inflow refers to the long-term investment in a foreign country. It consists of three components: equity capital, reinvested earnings and intra-company loans. 7.4 MODEL SPECIFICATION To investigate the impact of FDI on GDP, it is assumed thatY1= a+b1x1 Where, Y1 = Gross Domestic Product in million USD, a= constant term, b1 = Regression coefficients for the independent variable, x1 = FDI Inflow in million USD Here, Y1 (i.e. GDP) is the dependent variable, while the x1 is the independent variable. This test has been used to find out whether there is a relationship between dependent variable and the independent variable. Collected data has been processed and analyzed with the help of SPSS software.

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To investigate the impact of FDI on export, it is assumed thatY2= a+b2x2 Where, Y2 = Export in million USD, a= constant term, b2 = Regression coefficients for the independent variable, x2 = FDI Inflow in million USD Here, Y2 (i.e. Export) is the dependent variable, while the x2 is the independent variable. This test has been used to find out whether there is a relationship between dependent variable and the independent variable. Collected data has been processed and analyzed with the help of SPSS software. To investigate the impact of FDI on Domestic investment, it is assumed that – Y3 = a+b3x3 Where, Y3 = Domestic Investment in million USD, a= constant term, b3 = Regression coefficients for the independent variable, x3 = FDI Inflow in million USD Here, Y3 (i.e. Domestic Investment) is the dependent variable, while the x3 is the independent variable. This test has been used to find out whether there is a relationship between dependent variable and the independent variable. Collected data has been processed and analyzed with the help of SPSS software. 5.5 Hypothesis of the study H1: FDI Inflow has positive and significant impact on GDP. H2: FDI Inflow has positive and significant impact on export. H3: FDI Inflow has positive and significant impact on domestic investment.

8 RESULTS Impact of FDI on GDP The following regression equation is found, Y1 = 56987 + 158.757× FDII Here Y1 = GDP in million USD Table 1 Model Summary and ANOVA (F) Model R R Square

Adjusted R Std. Error of Square the Estimate

F

Sig

17.451 .001(a)

a Predictors: (Constant), FDI Inflow in million USD b Dependent Variable: GDP in million USD The above table reveals that F value is significant at .001 level. This indicates that the variation caused by FDI Inflow in the GDP is significant. The value of Correlation Coefficient (R) and Coefficient of Determination (R square and Adjusted R square) of the model are shown in the Table. The value of correlation coefficient is .757 and R square is .573. These show that the independent variable under reference has high degree of correlation with GDP.

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The above table presents regression coefficients that are obtained from the regression Model. This is observed that the independent variable FDI Inflow has exerted significant influence on GDP. As expected, FDI Inflow is found to have positive and significant relationship with GDP.

0

FDI inflow, the independent variable under reference has high degree of correlation with domestic investment. Table 6 Coefficients (a) Unstandardized Model

Impact of FDI on Export The following regression equation is found, Y2 = 934.8 + 15.7× FDII Here Y2 = Export in million USD Table 3 Model Summary and ANOVA (F)

1

Adjusted R Std. Error of Model R R Square Square the Estimate F Sig. 1 .811(a) .658 .632 2941.73737 25.015 .000(a)

a Predictors: (Constant), FDI Inflow in million USD b Dependent Variable: Export in million USD The above table reveals that F value is significant at .000 levels. This indicates that the variation caused by FDI Inflow in the export is significant. The value of Correlation Coefficient (R) and Coefficient of Determination (R square and Adjusted R square) of the model are shown in the Table. The value of correlation coefficient is .811 and R square is .658. These show that FDI inflow, the independent variable under reference has high degree of correlation with export. Table 4 Coefficients (a) Unstandardized Standardized Coefficients Coefficients B Std. Erro r Beta t 934.807 1988.528 .470

Model 1 (Constant) FDI Inflow in million USD 15.711 3.141 .811 a Dependent Variable: Export in million USD

Sig. .646

Standardized

Coefficients Coefficients B Std. Erro r Beta (Constant) 5266.066 2260.282 FDI Inflow in million USD 14.603 3.571

t

Sig.

2.330 .037 .750

4.090 .001

a Dependent Variable: Domestic Investment in milion USD The above table presents regression coefficients that are obtained from the regression Model. This is observed that the independent variable FDI Inflow has exerted significant influence on domestic investment. As expected, FDI Inflow is found to have positive and significant relationship with domestic investment. Analysis The above regressions were tested for the period 19962010. The regression results suggest that the model is a good fit as indicated by the values of R2 and F statistics. It is observed that FDI Inflow has significant impact on GDP, export and private investment. The coefficients of the independent variable in each case suggest that FDI Inflow has positive and significant impact to accelerate GDP, export and private investment. GDP, GDP Growth, FDII/GDP and FDII/GDP Growth, Export, Export/GDP and Domestic investment over time

5.001 .000

The above table presents regression coefficients that are obtained from the regression Model. This is observed that the independent variable FDI Inflow has exerted significant influence on export. As expected, FDI Inflow is found to have positive and significant relationship with export. Impact of FDI on Private investment The following regression equation is found, Y3 = 934.8 + 15.7× FDII Here Y3 = Domestic investment in million USD Table 5 Model Summary and ANOVA (F) Model R R Square 1 .750(a) .563

Adjusted R Std. Erro r of Square the Estimate F Sig. .529 3343.75800 16.728 .001(a)

a Predictors: (Constant), FDI Inflow in million USD b Dependent Variable: Domestic Investment in million USD The above table reveals that F value is significant at .001 levels. This indicates that the variation caused by FDI Inflow in the Domestic Investment is significant. The value of Correlation Coefficient (R) and Coefficient of Determination (R square and Adjusted R square) of the model are shown in the Table. The value of correlation coefficient is .750 and R square is .563. This shows that

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Figure 14 Trend of GDP, GDP Growth, FDII/GDP and FDII/GDP, Export, Export/GDP, FDI Inflow and Domestic investment over time Source of data: Bangladesh Board of Investment (BOI) The above graphs show that during 1996-2010, GDP has an increasing trend. GDP Growth fluctuates from 6.09% to 10.08% and FDII/GDP ratio lies between 0.003 and 0.006. The mean and (standard deviation) of FDII/GDP ratio have been found 0.005 (0.001), 0.003 (0.001) and 0.004 (0.001) during 1996-2000, 2001-2005 and 2006-2010 respectively. The export/GDP ratio has an increasing trend over the period. This ratio stands between 5.46% and 8.17% during 2001-10. The mean is 6.51% and standard deviation 0.86%. The cumulative average growth rate during this period is 3.75%. Domestic investment is increasing over time keeping pace with FDI inflow. The mean and (standard deviation) of domestic investment in million USD have been found 9,486 (1,077), 12,476 (1,693) and 19,476 (3,671) during 1996-2000, 2001-2005 and 2006-2010 respectively. Though FDI has positive and significant impact on GDP but FDI Inflow/GDP ratio is very small and it has no mentionable increasing trend. In order to accelerate GDP Growth, it is obvious to increase FDI Inflow.

9

CONCLUSION & RECOMMENDATIONS

In Bangladesh FDI plays a very important role in achieving expected economic growth. FDI flows have been successful in increasing GDP. At the same time, FDI has also made a contribution in improving the income level of Bangladesh. FDI can ensure Bangladesh to realize higher growth by having the capabilities of using all the resources to the fullest potential. There is an increasing trend in foreign investment due to positive effect of the incentives provided and changes in our economic policies. FDI has positive correlation with GDP, export and private investment. In order to sustain the economic growth and continue the present status of FDI inflow, Bangladesh needs to maintain some effective steps. The administrative system of the country should be reformed through appropriate and effective measures. The bureaucracy needs to be reorganized. The control of bureaucracy should be minimized. Government should look into the law and order situation to ensure business friendly environment. A social consciousness is much more needed to

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ensure the rule of law and reduce the various effects of corruption. Both the government and private sector should be taken much more priority in this sector. They need to come ahead in investing in developing the infrastructure. Appropriate policy measures are needed to be developed so that private sector can run smoothly. If both public and the private sector work together in the same view of implementing economic reforms, Bangladesh will surely upgrade her position. Similarly, the further simplified custom clearance procedures can be very helpful in improving the present situation. In order to stimulate domestic and foreign investments, the privatization program can be initiated at large scale. It is important for a developing country like Bangladesh to modernize the laws relating to business and investment. It should be done focusing on international practices. The development of new industrial parks can play a very important role in attracting foreign investment in Bangladesh. The government may consider setting up new EPZs to encourage export oriented investors. Necessary steps should be taken to improve the image of the country abroad. An investment promotion agency needs to provide functions such as investment generation and policy advocacy. Bangladesh needs to strengthen economic and commercial diplomacy in attracting FDI in by rapid globalization and increasing competition. Bilateral relations with potential investor countries should be improved. Bangladesh should take effective steps in accelerating reform measures for banks, other financial institutions and capital market. A good governance and political stability should be ensured. Corporate governance will play a key role in enhancing the investment climate of Bangladesh. So we should implement corporate governance strongly in financial sector. The rate of corporate taxes is 40% for non- listed companies. It is one of the highest in Asia. This rate should be favorable for investors. Different ministries and organization needs to work in an integrated manner to successfully address issues regarding sectors. In future, the prospect of the Bangladesh economy would be affirmative if initiatives can be taken to consolidate the proposed reforms. Recently Bangladesh has taken steps to simplify various processes to encourage increased FDI. The government, total financial sector and foreign investors must work together to achieve the goal of making Bangladesh a progressive economy by the end of this decade.

ACKNOWLEDGMENT At the outset, all praise be only to Allah, the Omnipotent to accept this effort and to consider it for His sake only without whose grace this work would have not been accomplished. I would like to acknowledge with thanks all the institutions and individuals who helped me by providing resources, efforts and intellectual capital that resulted in this paper and comments published in this volume. I owe my greatest debts & thanks to my beloved wife Mahbuba Anwar, for her truly extra ordinary patience and emotional support. Last, but not the least, for any sort of error and omission in this research, I hold myself fully responsible.

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APPENDICES Appendices A: Year wise FDI Inflow, GDP, Export, Domestic Investment and Export Year 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

FDI Inflow in million USD 231.61 575.29 576.46 309.12 578.64 354.47 335.47 350.25 460.4 845.26 792.48 666.36 1086.31 700.16 913.32

GDP in million USD 84300 90600 96700 102900 111400 119900 127200 136800 149500 163700 180200 197500 214300 228700 244300

Do mestic Investment in million USD 8130.40 8769.60 9538.10 10140.90 10850.00 10848.00 11011.50 12150.50 13587.60 14784.40 15259.00 16737.30 19258.40 21778.90 24299.40

Expo rt in Million USD 4614.1 5527.2 5865.3 6235.9 7214.2 6836.9 6951 8061.8 9233.7 10551.4 12887.5 14091.1 17497.6 17010.8 19315.85

FDII/ GDP 0.0027 0.0063 0.0060 0.0030 0.0052 0.0030 0.0026 0.0026 0.0031 0.0052 0.0044 0.0034 0.0051 0.0031 0.0037

Export/GDP 0.0547 0.0610 0.0607 0.0606 0.0648 0.0570 0.0546 0.0589 0.0618 0.0645 0.0715 0.0713 0.0817 0.0744 0.0791

Appendices B: FDI Inflows by Components (Figures in million USD) Year 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Equity Capital 69.63 332.06 280.51 137.47 350.18 233.78 133.81 156.14 155.89 425.59 503.65 401.61 809.25 218.55 519.98

Reinvested earnings 121.65 163.45 189.88 76.23 77.77 65.01 116.82 170.13 239.79 247.48 264.74 213.24 245.73 364.94 364.62

Intra- company Loans Total Inflows 40.33 231.61 79.78 575.29 105.07 576.46 95.42 309.12 150.69 578.64 55.68 354.47 84.84 335.47 23.98 350.25 64.72 460.4 172.19 845.26 24.09 792.48 51.51 666.36 31.33 1086.31 116.67 700.16 28.72 913.32

Appendices C: FDI Inflows by Areas (Figures in million USD) Year 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Area EPZ 42.31 69.25 88.31 154.43 81.2 56.06 87.53 59.31 42.68 110.82 71.03 105.44 118.55 141.88 118.17

Non-EPZ 189.3 506.04 488.15 154.69 497.44 298.41 247.94 290.94 417.72 734.44 721.44 560.93 967.76 558.28 795.15

Total 231.61 575.29 576.46 309.12 578.64 354.47 335.47 350.25 460.4 845.26 792.48 666.36 1086.31 700.16 913.32

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Appendices D.1: FDI Inflows by major Sectors (1996-2005) (Figures in million USD) Sectors 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 0.3 1.4 1.4 2.9 15.2 1.1 1.6 4.1 1.7 2.3 Agriculture & Fishing Power 0.0 0.0 78.5 39.3 155.7 119.1 53.5 29.7 30.4 27.2 47.0 242.1 156.7 44.3 145.4 73.4 4.4 58.4 93.7 181.1 Gas & Petroleum 41.3 58.1 87.7 123.4 115.1 56.2 92.5 46.7 37.7 96.5 Textiles & Wearing 2.4 1.7 2.9 4.0 3.9 Chemicals &Pharmaceuticals 29.4 34.2 9.6 14.9 2.6 0.5 1.3 0.6 0.0 0.3 0.1 0.7 0.1 Metal & Machinery Products 0.5 0.8 5.3 3.6 4.3 3.1 0.6 0.2 0.0 1.3 0.4 0.7 Leather & Leather Products 87.6 126.9 157.3 8.3 39.4 18.2 56.0 39.2 61.2 117.8 Banking Insurance 0.0 4.1 5.5 0.0 0.0 0.0 0.0 0.0 0.0 5.8 1.4 5.9 25.3 0.0 5.4 0.9 48.5 45.9 127.5 278.8 Telecommunication 1.5 2.9 0.1 0.4 0.2 0.0 0.0 0.3 0.0 0.0 Computer Software & IT Appendices D.2: FDI Inflows by major Sectors (2006-10) (Figures in million USD) Sectors Agriculture & Fishing

2006 2007 2008 2009 2010 1.3 7.3 14.4 11.8 13.6

Power

21.1 25.8 27.8 30.9 38.5

Gas & Petroleum

187.1 190.2 73.3 20.3 53.6

70.1 102.3 126.4 Textiles & Wearing Chemicals & Pharmaceuticals 5.2 4.2 3.9 0.0 0.0 0.0 Metal & Machinery Products 0.0 1.5 1.6 Leather & Leather Products

134.0 10.4 1.3 7.2

145.2 6.3 3.1 10.5

117.7 80.0 141.8 142.6 163.1

Banking

6.4

Insurance Telecommunication Computer Software & IT

7.3

4.6

10.4 16.7

346.5 201.9 641.4 250.1 359.8 0.2 0.0 0.4 1.8 5.0

Appendices E.1: FDI Inflows by Countries (1996-2005) (Figures in million USD) Country Australia China Den mark Egypt Hong Kong India Japan Malaysia Netherlands Norway Pakistan Saudi Arabia Singapore South Korea SriLanka Switzerland Taiwan UAE U.S.A U.K A.D.B I.F.C Others

1996 55.08 0 2.23 0 5.94 1.01 5.37 0.08 0.41 0 1.29 0 0.03 43.2 0 5.24 0.02 0.15 14.39 86.35 0 0.22 10.6

1997 81.25 0.57 0 0 21.63 1.7 51.31 6.12 1.44 0 2.14 24.32 2.83 34.59 0 3.99 7.27 0.14 67.64 255.9 0 0.29 12.19

1998 128.5 2.67 0.03 0 13.13 1.66 15.64 5.02 0.69 23.71 0.38 0 0.5 70.94 0.82 23.4 0.54 0.18 232.9 40.93 0 0 14.87

1999 0.07 0.35 0.14 0 20.5 0 35 2.92 22.2 3.31 1.87 1.54 1.09 101 0 2.95 3.37 1.58 66.9 35.6 0 1.62 6.68

2000 1.54 0.52 58.96 0 20.46 8.5 28.56 7.96 158.7 0 1 2.49 1.97 61.6 0.07 11.96 2.7 0 29.34 157.3 2.1 0.21 22.66

2001 0 0.11 10.61 0 23.39 2.08 6.85 0.45 126.8 0.84 0.75 2.2 1.67 21.23 0 0.87 0.27 0.86 30.85 71.31 0.32 0.25 52.72

2002 0.01 2.64 21.6 0 23.5 4.3 17.6 13 24.9 30.4 13.2 0 14.3 55.5 0.13 4.57 0.33 0.04 24.5 18.5 0.17 9.72 56.4

2003 0 4.01 14 0 15.9 3.63 29.2 13.4 26.5 22 0.01 0 3.31 26 2.23 1.98 2.03 16.7 32.1 83.6 0.43 0.27 53.1

2004 0 0.37 18.75 19.86 13.89 6.8 30.03 38.99 8.86 59.64 3.81 0 2.35 18.45 3.44 7.15 1.28 12.84 61.76 91.05 29.51 19.92 11.66

2005 0 1.62 18.28 48.4 53.09 2.67 46.42 33.07 15.36 53.48 25.48 0.97 97.5 29.86 4.06 2.26 11.38 55.48 141.8 152.8 12.67 31.68 6.89

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Appendices E.2: FDI Inflows by Countries (2006-10) (Figures in million USD) Country Australia China Den mark Egypt Hong Kong India Japan Malaysia Netherlands Norway Pakistan Saudi Arabia Singapore South Korea SriLanka Switzerland Taiwan UAE U.S.A U.K A.D.B I.F.C Others

2006 0 0.92 15.38 105.36 47.43 6.09 22.79 44.46 13 82.95 5.14 0.52 35.89 53.86 2.63 2.8 2.36 88.02 175.72 70.47 0 0 16.69

2007 0 0.48 8.99 75.17 55.45 1.67 36.61 19.54 18.67 25.68 3.49 1.73 10.68 27.68 3.55 13.39 0.17 83.27 120.36 142.55 0 0 17.23

2008 0 4.5 1.91 373.4 39.85 11.29 57.15 70.72 31.67 33.47 12.51 2.66 32.28 44.64 7.19 69.25 1.96 102.2 40.92 130.57 0 0 18.17

2009 0.22 3.24 9.09 72.71 75.6 7.99 17.47 43.84 49.62 45.63 30.14 2.62 19.12 46 7.37 29.06 11.1 67.08 42.89 88.08 0 0 31.29

2010 13.95 8.66 5.91 3.01 63.84 43.19 21.79 7.45 64.92 39.16 18.88 11.91 317.19 40 8.85 5.89 7.59 24.5 56.95 105.68 0 0 44

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Investment Performance of Islamic Bank: An Empirical Study Evana Nusrat Dooty1 & Mohammed Syedul Islam2 1

Lecturer in Economics, Department of Business Administration, International Islamic University Chittagong Assistant Professor in Economics, Department of Business Administration, International Islamic University Chittagong

2

ABSTRACT The article undertakes an empirical study on investment of Islamic Bank. The aim of the study is to examine and evaluate the performance of investment of Islamic Bank for the time period 2005-2009 in comparison with a conventional Bank. Several financial ratios are applied for this purpose. For the empirical investigation data has been collected from Islami Bank Bangladesh Limited and Mutual Trust Bank Limited. The study found that Islami Bank Bangladesh Limited (IBBL) is relatively less profitable and less risky (more solvent) during 2005-2009 compared to a conventional bank (Mutual Trust Bank Limited), however, it is improving considerably over time indicating convergence with the performance of the conventional banks. Key Words: Islamic bank, conventional bank, profitability, deployment, liquidity, risk

JEL Classification Code: G24; P45

1

I

INTRODUCTION

slamic banking started on a modest scale in the early 1970s and has shown tremendous growth over the last 30 years. What started as a small rural banking experiment in the remote villages of Egypt has now reached a level where many mega-international banks are offering Islamic banking products. The practice of Islamic banking now spreads from East to West, all the way from Indonesia and Malaysia towards Europe and the America. The size of the industry that amounted to a few hundred thousands of dollars in 1975 had reached hundreds of billions of dollars by 2004. Research in the first stage is considered descriptive and focusing on the conceptual issues underlining interest-free financing. In the second stage, several ratio analysis are used to examine the theoretical framework of the Islamic institutions and analyze their behavior Yet, the lack of detailed data on bank behavior and operations impeded any comprehensive empirical analysis of the experience of the last two decades. Very few attempts have so far been made to empirically analyze the investment performance of the Islamic banks (Bashir, Darrat and Suliman, 1993). When Islamic banks were assessed, their financial returns were compared with those of interest-based banks. Their success was measured by their ability to mobilize and efficiently allocate resources to generate comparable returns for their depositors and shareholder. This paper is an attempt to apply recent theories of banking firms to analyze the investment performance of Islami Bank Bangladesh Limited (IBBL). Although the choice of the following bank is dictated primarily by data availability and popularity.

2

LITERATURE REVIEW

Bangladesh Bank has been following the CAMEL rating to rank the banks based on their financial performance. Under this rating, significant issues like capital adequacy,

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asset management, managerial efficiency, earnings quality and liquidity are employed. However, no specific index has been identified to contrast the Islamic bank sector performance with that of the conventional bank sector performance. According to Al-Shamrnari and Salirni (1998) profitability ratio especially return on equity (ROE) signals the earning capability of the organization. They also suggest that higher return on equity (ROE) ratio is appreciable as it is the primary indicator of bank's profitability and functional efficiency. Ahmad and Pandey (2010) analyzed the profitability ratios, efficiency ratios, asset quality ratios, capital adequacy ratios, leverage ratio, liquidity ratios to measure the comparative performance of conventional banks vis-a â&#x20AC;&#x201C; vis Islamic banks in the Gulf co-operation council (GCC) region during the quarters of 2006-2009. The study found that Islamic banks are more volatile than conventional banks Many Islamic bank studies have examined the Shariâ&#x20AC;&#x;ah principles behind offering such finance (ulamas) but historically limited financial analysis was performed, often due to data availability limitations (e.g. Ariff, 1988). Data still remains a problem and so cross sectional studies tend to dominate the literature. One such efficiency performance study by Yudistira (2003) revealed that nonMiddle Eastern Islamic banks were more efficient than Middle Eastern banks which, given the development of Islamic banks in that region, was surprising. Also larger Islamic banks were more efficient than smaller ones. The evidence as to whether Islamic banks are actually more efficient than conventional banks remains quite mixed. Yudistira (2004), for example, with a global sample of 18 Islamic banks, found Islamic banks to be more efficient than conventional banks. In contrast, Hassan (2006) in a larger study of 43 Islamic banks found them

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somewhat less cost efficient than conventional banks. Finally, while not examining efficiency, Cihak and Hesse (2008) found smaller Islamic banks tended to be financial stronger than larger ones. One issue in Islamic banking is the degree to which Shari‟ah law is actually followed.

3

OBJECTIVES

The main objective of the study is to examine the investment performance of Islamic bank. Since the definition of investment is very broad, we would like to focus on the following specific objectives.  To focus on the investment activities in Islamic Banking.  To analyze the investment trend of Islamic Bank  To enlighten on investment performance of interest free Islamic Bank and interest based conventional bank through profitability ratio, deployment ratio, liquidity ratio and risk ratio and to draw comparisons

4

METHODOLOGY

4.1 Data and Information The study is aimed at investment performance of Islamic banking. And also to compare it with conventional banking. Specifically, study makes comparison of Islami Bank Bangladesh Limited (IBBL) and a conventional bank‟s performances year in 2005-2009. Data for each year have been compiled from the income statements and balance sheets of these banks. 4.2 Analytical Framework In order to see how Islamic bank has performed in comparison with the conventional banks over 5 years, the study uses 11 financial ratios for the bank‟s investment performance. These ratios are broadly categorized into four groups: (a) profitability ratio (b) deployment ratio (c) liquidity ratio and (d) risk ratio. For profitability analysis, the following three widely used financial ratios are measured:  Return on Asset (ROA) = Net profit after tax / Total assets  Return on Equity (ROE) = Net profit after tax / Share holder‟s equity  Earnings per Share (EPS) = ( Total Distributable Profit / Average Number of Shares ) × 100 We have calculated two types of deployment ratio.  Deployment Ratio 1 = Total Investment/Total Equity + Total Deposits  Deployment Ratio 2 = Total Investment/Total Liabilities For liquidity analysis, the following four widely used financial ratios are measured:  Loan to Deposit Ratio (LDR) = Total loan/ Total deposit

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 Loan to Asset Ratio (LAR) = Total loan / Total asset  Equity Multiplier (EM) = Total asset / total share holder‟s equity  Current Ratio = Current assets / current liabilities For risk analysis, the following two widely used financial ratios are measured:  Debt-Equity Ratio (DER) = Total debt / Total share holder‟s equity  Bad Debt Ratio (BDR) = (Total Bad Investment / Total investment) × 100

5

FINDINGS

5.1 Profitability Analysis 5.1.1 ROA: our analysis of profitability measures indicates that conventional bank shows better managerial performance and efficient utilization of the assets from Islamic bank in Return on Assets (ROA) . However, it seems that, Islamic bank is getting closer to conventional banks in an upward trend; it is not inconceivable that in the near future that Islamic bank might outperform the conventional banks. 5.1.2 ROE : Further analysis of ROE reveals that Overall, ROE is found rising for Islamic bank and plummeting for the conventional bank during 2005-2009 mainly due to the difference in equity base and profit level of the bank. Net Profits of Islamic bank are found to increase more rapidly than its equity base causing ROE to increase, whereas, the opposite happened for conventional banks causing ROE to fall over time. However, the ROE for conventional found rising from 2008. 5.1.3 EPS: Results indicate that the earnings per share is very much fluctuating. After having drastic decrease, in 2008 both banks recovered their EPS. But EPS of IBBL increased from 30.04 to 43.30 (44.14%) and EPS of MTBL increased from 14.80 to 21.06 (increased 42.36%). In 2009 both banks recovered fully. It was increased from 43.30 to 55.10 for IBBL and increased from 21.07 to 46.46 for MTBL. Finally the average EPS of MTBL is 33.60 and EPS of IBBL is 42.80 which is strongly higher than MTBL. 5.2 Deployment Ratio Further analysis of Deployment Ratio strengthens our finding. Examination of deployment ratio, of the two sets of banks shows that the ratio of Islamic bank is better than conventional bank. For the both ratio, Islamic bank deserves satisfactory condition where as the conventional bank found in fluctuating tendency. 5.3 Liquidity Analysis 5.3.1 LDR: Conventional bank is found to be more liquid than Islamic bank in terms of LDR. Findings also show that while LDR of the conventional bank is higher for sometimes than Islamic bank. This trend is due to increase in its deposits base which can be considered a positive and a good sign for the Islamic bank in that Islamic banking is making inroads into the society.

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Source: Author‟s calculation

Moreover, this shows that level of trust and confidence of the people is increasing in Islamic bank with the passage of time and also a manifestation of a positive attitude of the people for considering Islamic financial products as alternate and viable financing options. 5.3.2 LAR: Further analysis of LAR indicated that Bai‟Murabaha has been the most famous and mostly used mode of financing followed by Ijarah, Export refinance under Islamic scheme, and Hire Purchase under Shirkatul Melk is standing second position. Records also shows that, the Islamic bank is potentially more profitable than conventional bank. 5.3.3 EM: Analysis of Equity Multiplier (EM) reveals that, the Islamic bank has used more debt to convert into assets with share capital. However the difference is little in comparison to conventional bank. 5.3.4 CR: Current Ratio for both type of bank almost same. That means, the both banks deserves good capability in case of paying obligations. 5.4 Risk Analysis Analysis of the results of all the risk measures, Debt Equity Ratio (DER), Bad Debt Ratio(BDR), indicates conventional bank to be more risky and less solvent than Islamic bank. We observed in LDR that deposit base of Islamic bank is increasing rapidly over time and since deposits make the largest component of total liabilities of the bank. We also observed Bad Debt Ratio (BDR) of Islamic bank on the decreasing trend. The difference in these performance measures is suggests that these two types of bank do not fall in the same risk class. This confirms that product of Islamic banking is a viable investment class providing unique risk structure for interested investors.

6

CONCLUSION

Our findings on the investment performance measurement of Islamic banking in Bangladesh are different and at times mixed in comparison to the results drawn from the similar studies done in different parts of the world. For example, Kader and Asarpota (2007) found in their study that UAE Islamic banks are relatively more profitable, less liquid, less risky, and more efficient as compared to the UAE conventional banks. Samed & Hassan (2000) revealed in their study that BIMB (Bank Islam Malaysia Berhad) is less profitable, relatively less risky and more solvent as compared to conventional banks of Malaysia. The difference in results is largely due to the fact that Islamic banking has longer history in these countries as compared to Bangladesh where Islamic banking system started merely few years back. Moreover, conventional banking has a longer history, deeper

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roots, vast experience of learning from the financial markets mechanisms, and larger share in the financial sector of Bangladesh. Considering these facts of the matter, we don‟t find the results of our study surprising. However, the way Islamic banking sector is improving and growing in Bangladesh, we expect Islamic banking of Bangladesh to be equally or even better in performance than conventional banking in the foreseeable future. Finally, for future studies, as the time passes, when there will be more Islamic banks to study and longer time period, a similar study would generate better insight on the issue of performance comparison and provide solid evidence one way or another. By then, we would gladly join the discussion again.

REFERENCES [1] Ahmed, Mareyah Mohammad & Pandey, Dayanand, 2010. Are Islamic Banks Better Immunized than Conventional Banks in the Current Economic Crisis?. Paper presented at 10th Global Conference on Business & Economics held at Rome, Italy [2] Al Shammari, M., and Salimi, M. (1998). Modeling the operating efficiency of banks, A parametric methodology. Journal of Logistic Information Management, Vol. 11. [3] Ariff Mohamed, „Research Report on Islamic Banking‟, Asian Pacific Economic Literature,Vol:2, No:2, PP.46-62, University of Malaya. [4] Bashir, A. M., and Darrat, A. F. (1992), "Equity Participation Contracts and Investment," [5] American Journal of lslamic Social Sciences (9) Summer: 219-232. and Suliman, M. O. (1993), "Equity Capital, ProfitSharing Contracts and Investment: Theory and Evidence," Journal of Business Finance and Accounting [6] Cihak, M. and H. Hesse (2008), Islamic Banks and Financial Stability: An empirical analysis, IMF Working Paper No. 08. [7] Hassan, M., (2006), The X Efficiency of Islamic banks, Islamic Economic Studies, 13(2): 49-78. [8] Kader, Janbota M. & Asarpota, Anju K., 2007. Comparative Financial Performance of Islamic vis-à-vis Conventional Banks in the UAE. Paper presented at 2006-2007 Annual Student Research Symposium & First Chancellor‟s Undergraduate Research Award at UAE University [9] Samed Abdus & Hassan, M. Kabir, „The Performance of Malaysian Islamic Bank During 1984-1987: An Exploratory Study”, International Journal of Islamic Financial Services Vol.1, No.3 [10] Yudistira, Donsyah (2003), “Efficiency of Islamic Banks: an Empirical Analysis of 18 Banks,”Finance No. 0406007, EconWPA [11] Yudistira, Donsyah, 2004. Efficiency of Islamic Banks: an Empirical Analysis of 18 Banks. Islamic Economic Studies 12(1), 1-19

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Appendix-A Table 1 : Balance Sheet of IBBL from 2005 to 2009 (Figure in Million tk) Particulars Cash in Hand Cash with BB & Other Banks/FIs Cash with Other Banks/FIs Investment in Shares & Securities Total Investment, Adv. & Bills Fixed Assets Other Assets Total Assets Current A/Cs & Others A/Cs Bills Payable Savings Bank Deposits Term Deposits Other Mudaraba Deposits Deposits & Other A/C Other Liabilities Total Outside Liabilities Paid Up Capital Reserves & Others Shareholders' Equity Total Liab. & Shareholders' Equity

2005 1,285.56 17,135.82 1,775.32 3,534.16 93,644.15 3,067.99 2,437.34 122,880.35 12,411.23 695.43 43,386.77 22,062.21 29,223.78 107,779.42 6,885.19 114,664.61 2,764.80 5,450.94 8,215.74 122,880.35

2006 1,410.15 22,108.80 1,329.13 3,557.76 113,575.07 3,724.69 4,547.22 150,252.82 14,016.13 890.28 52,118.58 25,872.28 39,522.14 132,419.40 7,826.18 140,245.59 3,456.00 6,551.23 10,007.23 150,252.82

2007 2,907.14 14,169.31 4,012.33 20,365.71 144,920.61 3,987.23 1,000.01 191,362.35 19,165.15 1,767.59 62,403.50 31,103.69 51,885.35 166,325.29 13,195.73 179,521.01 3,801.60 8,039.74 11,841.34 191,362.35

2008 3,107.36 28,222.96 5,623.18 7,532.61 180,053.94 4,407.22 1,931.87 230,879.14 18,958.13 2,308.04 77,498.41 36,706.85 64,871.98 200,343.41 16,475.23 216,818.64 4,752.00 9,308.49 14,060.49 230,879.14

2009 2,480.77 35,004.90 7,678.38 11,136.61 214,615.80 6,512.36 874.02 278,302.84 23,794.37 2,545.72 95,081.55 45,268.01 77,602.50 244,292.15 13,905.15 258,197.30 6,177.60 13,927.94 20,105.54 278,302.84

Table 2: Income Statement of IBBL from 2005 to 2009 (Figure in Million tk) Particulars Investment Income Profit Paid on Deposit Net Investment Income Income from Investment in Share & Securities Comm., Exchange & Brokerage Other Non Investment Income Total Operating Income Salary, Allowance & PF Other Operating Expenses Total Operating Expenditure Profit/Loss before Provisions Prov. for Unclassified Investment Prov. for Classified Investment Prov. For others Assets / Off Balance Sheet Items Net P/L before Taxes Provisions for Tax Net P/L after Tax

2005 8,336.03 5,884.73 2,451.30 90.50 2,016.99 143.27 4,702.06 1,170.99 662.21 1,833.19 2,868.86 286.20 420.25 2,162.42 1,036.60 1,125.82

2006 11,158.06 8,019.34 3,138.72 137.38 2,456.73 286.15 6,018.97 1,851.22 852.45 2,703.67 3,315.30 508.79 (107.26) 5.10 2,908.67 1,508.07 1,400.59

2007 14,572.19 9,410.59 5,161.60 284.00 2,579.01 264.32 8,288.94 2,037.23 1,089.35 3,126.58 3,162.36 436.76 653.62 291.16 3,780.82 1,731.77 2,049.05

2008 19,543.84 12,162.10 7,381.74 408.76 3,337.52 940.22 12,068.23 2,837.99 1,277.82 4,115.81 7,952.43 310.02 528.51 766.06 6,347.83 3,673.04 2,674.80

2009 21,370.53 13,076.99 8,293.54 115.16 3,437.20 480.96 12,326.86 3,153.35 1,392.62 4,545.97 7,780.89 384.26 939.60 -60.63 6,517.66 3,114.11 3,403.55

Appendix-B Table 3 Financial Highlights of Mutual Trust Bank Ltd from 2005 to 2009 (figure in million tk) Particulars Paid up Capital Total Capital Surplus in Capital Fund Total Assets Total Deposits Total Loans and Advances Total Contingent Liabilities Classified Loans as % of Total loans and advances Profit after provision and tax Total Classified loans during the year Total provision maintained against classified loans Surplus in provision against classified loans Cost of Fund Earning assets Non-interest earning assets Income from Investments Profit per Share (Figure in Taka) Price-Earning ratio (Times)

2005 864.00 1692.52 478.57 19,306.99 16,098.54 14,373.26 7498.27 Nil 336.17 Nil Nil Nil 8.96% 17,419.05 1887.94 139.97 35.37 11.35

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2006 950.40 311.53 506.00 26,217.99 22,264.05 18,591.52 9,671.39 1.03% 478.28 191.63 30.30 0.03 10.33% 23,575.83 2,642.16 184.40 50.32 6.80

2007 997.92 2,370.95 43.12 32,181.90 24,776.92 22,683.23 10,916.14 2.39% 210.8 541.64 217.43 0.30 9.15% 28,470.97 3,710.93 162.41 21.12 28.24

2008 1,496.88 2,888.33 107.24 38,964.97 33,820.41 28,529.35 11,467.71 4.92% 305.03 1,402.85 829.33 0.09 10.18% 33,944.60 5,020.37 454.84 17.27 18.52

2009 1,766.32 3,969.33 952.56 52,774.77 42,354.07 33,883.92 10,061.04 2.81% 820.61 952.76 663.09 2.26 10.21% 46,075.04 6699.72 857.47 46.46 8.86

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Volatility Estimation in the Dhaka Stock Exchange (DSE) returns by Garch Models Md. Shawkatul Islam Aziz1 & Md. Nezum Uddin2 1

Mphil Research Fellow, Department of Economics, University of Chittagong, Bangladesh Lecturer in Economics, Department of Economics & Banking, International Islamic University Chittagong, Bangladesh

2

ABSTRACT This study aimed at understanding the volatility of Dhaka Stock Exchange (DSE). The daily and monthly average DSE General Index (DGEN), from the period January 1, 2002 to July 31, 2013 has been used. The study has been made by using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models to estimate the presence of volatility. Though volatility is a common phenomenon in the capital market, the study recommends careful monitoring of volatility by the concerned authority if necessary. It is also recommended that activities of corporate insiders should be properly checked and information should become available for all of the interested investors and to ensure adequate supply of stock through active participation of the government and giant national and multinational companies and so forth. Keyword: ARCH, DSE, GARCH, Stock Market, Volatility JEL Classification Code: O16; P34

INTRODUCTION

T

he The capital market of an economy like a thermometer which reflects the health of the economy. The economy of a country largely depends on a strong capital market. Hafer and Hein [1] pointed that growth of new businesses or our economy would not be possible without the availability of stocks and development of financial markets. In an economy with a sizeable private corporate sectors such as security price stability, investor‟s confidence, stable capital market and general economic development etc. are so linked that the state of the economy, specially the „investment climate‟ in the country can easily be guessed by a mere review of the behavior of the stock market. Here investors participate voluntarily to buy ownership of a company in the public market. It is said that stock market is an intermediary institution to adjust a gap between surplus units and deficit units of an economy. In these days for millions of middle class educated people in Bangladesh think that investing in stocks is more popular than investing in any other investment sectors. In case of Bangladesh, capital market investment is very important and significant for the development and the market capitalization of domestic industry, trade and commerce. There are various financial variables in stock market such as stock price, share index etc. These prices may fall in some situation and may constant or rise in another situation. These oscillations are termed as volatility. In view of the rapidly increasing role of the stock market, volatility in stock prices can have significant implications on the performance of the financial sector as well as the entire economy. Volatility

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is simply defined as a measure of dispersion around the mean or average return of a security. It is a measure of the range of an asset price about its mean level over a fixed amount of time as observed by Abken and Nandi [2]. It follows that volatility is linked to the variance of an asset price. If a stock is labeled as volatile the price will vary greatly over time. Conversely, a less volatile stock can have a price that will deviate relatively little over time. Volatility is calculated as the standard deviation from a certain continuously compounded return over a given period of time. According to Karolyl [3] and Mordi [4], volatility is a measure of risk based on the standard deviation of the asset return. It is a one kind of variables that appears in option pricing formulas, where it denotes the clustering of the underlying asset return from now to the expiration of the option. There is an important link between stock market uncertainty and public confidence in the financial market. Excessive volatility and fluctuations in stock prices fail to provide the correct signal on company‟s real worth although stock prices generate useful information to ensure efficiency of markets in the real world. Volatility however, is not an evidence of irrational market behavior of inefficient markets. Before pricing a stock; we require to know the volatility of the underlying asset from now to mature of the stock. In fact, in terms of volatility units the market convention is to list stock prices. The main objective of this study is to compute the volatility of Dhaka Stock Exchange (DSE) returns. In this regard the DSE General Index is used.

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LITERATURE REVIEW A lot of active scholarly studies are being held about the volatility of stock return for developed capital markets. Fama [5] has found that large (small) changes in the stock prices follow by large (small) changes in either signs or stock prices exhibit fatter tails than a normal distribution. Bekaert and Harvey [6] test a variety of sophisticated models of conditional volatility and find that volatility is difficult to model in emerging markets. Haque and Hassan [7], Kim and Singal [8], Choudhury [9], Lee and Ohk [10], Claessens, Dasgupta and Glen [11] examined the return volatility behavior of a number of emerging market economics. Moosa and Al-Loughani [12] used monthly data to examine four Asia stock markets which are Malaysia, Philippines, Singapore and Thailand, while Saatcioglu and Starks [13] scrutinsed six Latin American stock markets that are Argentina, Brazil, Chile, Colombia, Mexico and Venezuela. Poterba and summers [14] conducted an extensive study using various frequencies of data from the New York Stock Exchanges (NYSE) and 17 other equity markets. Their study consistently shows that returns are positively correlated over longer periods. In addition, Poterba and summers [15] found that for the long horizon, a mean reverting component of stock prices could explain a large portion of variations in stock returns. They find evidence, however, that the importance of world factors in emerging market volatility may be increasing, and that volatility tends to decrease following market liberalization. Batra, A. [16] examines the time variation in volatility in the Indian stock market during 1979-2003. Using monthly data and asymmetric GARCH methodology augmented by structural change analysis, the paper reveals that the period around the BOP crisis and the subsequent initiation of economic reforms in India is the most volatile period in the stock market. Stock return volatility in India seems to be influenced more by domestic political and economic events rather than by global events. The analysis in the paper also reveals that stock market cycles in India have not intensified after financial liberalization. A generalized reduction in stock market instability is observed in the post- reform period in India. Raju and Ghosh [17] in attempting to calculate the volatility of stock prices for a number of countries came into conclusion that both in Indian and Chinese stock market volatility is higher compared to other emerging economies. Döpke, [18] Using monthly data of Germany concluded that volatility in the stock market can be explained by the performance of major macroeconomic indicators which have influence on business cycles. Uppal and Mangla [19] empirically concluded that although the Indian regulatory agencies managed to control excessive market volatility to a large extent, the Karachi Stock Exchange demonstrated little success. They argued that market behavior due to regulatory responses depends both on

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the structure of industry and effectiveness of the regulations. In an attempt to find the determinants of stock volatility, Verma and Verma [20] concluded that investor‟s irrational sentiments contribute more strongly to increase the stock volatility than to reduce it. Besides Baklaci and Kasman [21] examined the 25 individual stocks traded in Istanbul stock exchange in this respect. Furthermore, Olowe [22] examines volatility in the Nigerian stock market. In brief, it is generally accepted that there is a relationship between trading volume and price volatility indicated by different models and methods. Alam and Uddin [23] using monthly data for fifteen developed and developing countries found strong relationship between share price and interest rate-one very important macroeconomic variable or change in share price and change in interest rate. Studies on stock market of Bangladesh largely associates volatility with various factors rather than the role of regulators‟ or weaknesses in regulations. In this state, the present study attempts to examine the market volatility in two accounts namely its association with the regulatory measures as well as with relevant macroeconomic factors.

RECENT TRENDS OF CAPITAL MARKET Volatile stock market and falling index continued almost the whole year after the initial crash in late 2010. Investors saw their investments almost in the verge of negative as most of them were exposed to high loan margins. Right after the stock market crash the Bangladesh Bank took some policies to overcome the struggling situation of the economy. Market capitalization of DSE remarkably increased during last three years as reflected in the ratios of market capitalization to the country's GDP at current market price. Market capitalization reached at Taka 232701.60crore, Taka 193244.08crore, and Taka197743.01crore at the end of FY10, FY11, andFY12 respectively, Bangladesh Bank [24]. From the analysis on volatile nature of DSE, it has found that market has become more volatile over time which has been captured by the major indices of the market (Table-1 and Figure-1). However, if we look at the volatility for other indicators then we can see that overtime volatility has decreased. During FY12 the market has gone through massive correction in market capitalization and index. At the same time different measures have been taken to bring stability as well as investor‟s confidence in the stock market. The face value of a share of all listed companies and mutual funds of the two Stock exchanges has been reset at Taka 10. It has been made mandatory for the sponsors and directors of a company to hold a portion of share of the paid-up capital. The legal provisions on book-building procedure, mutual fund and paid up capital have been updated. Initiatives have been taken to

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amend the relevant laws to make the activities of Securities and Exchange Commission (SEC) transparent and accountable, to establish special tribunal for completion of capital market related cases rapidly, to set up separate clearing and Settlement Company for completion of transaction within short time and to strengthen the monitoring system through establishing high quality surveillance software. Fifteen companies raised new equity of Taka 16.4 billion in the capital market in FY12. This was lower than Taka 27.9 billion raised by the nineteen companies in FY11. Of the new equity issued, Taka 2.6 billion was raised through private placements and Taka13.8 billion was raised through public placements. In FY11, equity issued through private and public placements were Taka 7.6 billion and Taka 20.3 billion respectively. The volume of public offerings in FY12 was oversubscribed more than three times indicating a shortage of new securities in the primary market. Bonus shares worth of Taka 43.0 billion were issued in FY12 by one hundred and fifty seven companies against retained profits. This was lower than Taka 48.7 billion issued in FY11 by one hundred and fifty companies. In market capitalization excluding treasury bonds and debentures, the financial sector dominated with 43.8 percent share, followed by services and miscellaneous (31.6 percent), manufacturing (24.3 percent) and corporate bonds (0.3 percent) at the end of June FY12. Market capitalization inclusive of new issues decreased remarkably by 12.7 percent to Taka 2491.6 billion or 27.2 percent of GDP at the end of FY12 from Taka 2853.9 billion at the end of FY11 in Dhaka Stock Exchange (DSE). The DSE General Index (DGEN) was 6117.23, 4572.88, and 4385.77 in FY10, FY2011 and FY2012 respectively, (Bangladesh Bank) [25]. Although, the Securities and Exchange Commission (SEC) of Bangladesh has tried to correct the abnormal behavior observed in the market, very often it is argued that lack of proper and firm decisions from the regulatorâ&#x20AC;&#x;s side has contributed to make the market more unstable rather than stabilizing it. At the beginning of recent Bull Run, Bangladesh capital market was fairly underpriced in terms of Price Earnings Ratio (PER). The market weighted PER of DSE was 11 to 18 during FY04FY07. PER became to bigger from beginning of FY 09 as the acceleration of price index. The PER reached to its peak level at 30.6 in February 2010 from 18.4 of end June 2009. On June 30, 2012, the market PER stood at 12.53 points whereas it was at 16.55 points on June 30, 2011(DSE) [26]. At present, the market PER of the stock market of Bangladesh is the lowest level in the last few years. The high PER indicates that the market is highly overpriced and overheated. The strong demand from the retail investors, not matched by a corresponding increase in supply of stocks, has caused the PER to rise beyond rational levels. In terms of any measure, Bangladesh capital market is overheated during last couple of years

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as supply shocks (Bangladesh bank) [27]. The capital market developments and its sustainability depend on market fundamentals at least in the medium term, and the fundamental strength of the market essentially comes from financial strength of the listed companies. Also, strong regulatory environment was created and maintained by the regulatory bodies and participation of institutional investors and professional market analysts to help orderly market operations. The market witnessed that last few years many fundamental companies with strong financial strength were listed in the market. The main regulatory body SEC and the Government of Bangladesh and others related regulatory authorities have kept continuation of their all efforts to develop the Bangladesh capital market that reflected in the market trends. But growth of market demand for stock was more than that of supply that inflated the market in recent years and made the market most volatile one in the region. The recent vibrant nature of the capital market also might be due to the increased interest in the market by a large number of individual investors which has been influenced by the governmentâ&#x20AC;&#x;s decision to reduce the bank interest rates for its different types of savings instrument.

RESEARCH METHODOLOGY The prime object of this paper is to estimate the volatility of the stock market in DSE. For this purpose DSE General Index (DGEN) is used. Daily and monthly average DSE General Index (DGEN) has been used. Data is collected from the research section of DSE and website of DSE. The sample period is from January 1, 2002 to July 31, 2013.In order to estimate the volatility in the DSE General Index (DGEN) the study selected Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Model. In econometrics, Auto Regressive Conditional Heteroskedasticity (ARCH) models are used to characterize and model observed time series. The GARCH approach allows for an empirical assessment of the relationship between risk and returns in a setting that is consistent with the characteristics of volatility clustering observed in emerging stock markets, Hassan, Islam and Basher [28]. The Auto Regressive Conditional Heteroskedasticity (ARCH) model introduced by Engle [29] allows the variance of the error term to vary over time, in contrast to the standard time series regression models which assume a constant variance. The generalized ARCH models, i.e. the GARCH models, have been found to be valuable in modeling the time series behavior of stock returns. Baillie and DeGennaro [30], Akgiray [31], French et al. [32], Koutmos [33], Koutmos et al.[ 34]. The GARCH model has the advantage of incorporating heteroscedasticity into the estimation procedure. All GARCH models are martingale difference implying that all expectations are unbiased. The GARCH models are capable of capturing the tendency for volatility

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clustering in financial data. Volatility clustering in stock returns implies that large (small) price changes follow large (small) price changes of either sign. In particular ARCH models assume the variance of the current error term or innovation to be a function of the actual sizes of the previous time periods' error terms: often the variance is related to the squares of the previous innovations. Let đ?&#x153;&#x2013;đ?&#x2018;Ą denote the error terms (return residuals, with respect to a mean process) i.e. the series terms. These đ?&#x153;&#x2013;đ?&#x2018;Ą are split into a stochastic piece đ?&#x2018;§đ?&#x2018;Ą and a time-dependent standard deviation đ?&#x153;&#x17D;đ?&#x2018;Ą characterizing the typical size of the terms so that, đ?&#x153;&#x2013;đ?&#x2018;Ą = đ?&#x153;&#x17D;đ?&#x2018;Ą đ?&#x2018;§đ?&#x2018;Ą The random variable đ?&#x2018;§đ?&#x2018;Ą is a strong White noise process. The series đ?&#x153;&#x17D;đ?&#x2018;Ą2 is modeled by 2 2 đ?&#x153;&#x17D;đ?&#x2018;Ą2 = đ?&#x203A;žđ?&#x2018;&#x153; + đ?&#x203A;ź1 đ?&#x153;&#x2013;đ?&#x2018;Ąâ&#x2C6;&#x2019;1 + â&#x2039;Ż + đ?&#x203A;źđ?&#x2018;&#x17E; đ?&#x153;&#x2013;đ?&#x2018;Ąâ&#x2C6;&#x2019;đ?&#x2018;&#x17E; = đ?&#x203A;žđ?&#x2018;&#x153; +

đ?&#x2018;&#x17E;

đ?&#x2018;&#x2013;=1

2 đ?&#x203A;źđ?&#x2018;&#x2013; đ?&#x153;&#x2013;đ?&#x2018;Ąâ&#x2C6;&#x2019;đ?&#x2018;&#x2013;

Where đ?&#x203A;ž0 > 0 đ?&#x2018;&#x17D;đ?&#x2018;&#x203A;đ?&#x2018;&#x2018; đ?&#x203A;źđ?&#x2018;&#x2013; â&#x2030;Ľ 0, đ?&#x2018;&#x2013; > đ?&#x2018;&#x153;. An ARCH (p) model can be estimated using ordinary least squares. If an Auto Regressive Moving Average (ARMA model) is assumed for the error variance, the model is a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. In that case, the GARCH (p, q) model, where p is the order of the GARCH terms đ?&#x153;&#x17D; 2 and q is the order of the ARCH terms (đ?&#x153;&#x2013; 2 ) is given by 2 2 2 2 đ?&#x153;&#x17D;đ?&#x2018;Ą2 = đ?&#x203A;žđ?&#x2018;&#x153; + đ?&#x203A;ź1 đ?&#x153;&#x2013;đ?&#x2018;Ąâ&#x2C6;&#x2019;1 + â&#x2039;Ż + đ?&#x203A;źđ?&#x2018;&#x17E; đ?&#x153;&#x2013;đ?&#x2018;Ąâ&#x2C6;&#x2019;đ?&#x2018;&#x17E; + đ?&#x203A;˝1 đ?&#x153;&#x17D;đ?&#x2018;Ąâ&#x2C6;&#x2019;1 + â&#x2039;Ż + đ?&#x203A;˝đ?&#x2018;? đ?&#x153;&#x17D;đ?&#x2018;Ąâ&#x2C6;&#x2019;đ?&#x2018;? đ?&#x2018;&#x17E; đ?&#x2018;? 2 2 =đ?&#x203A;žđ?&#x2018;&#x153; + đ?&#x2018;&#x2013;=1 đ?&#x203A;źđ?&#x2018;&#x2013; đ?&#x153;&#x20AC;đ?&#x2018;Ąâ&#x2C6;&#x2019;đ?&#x2018;&#x2013; + đ?&#x2018;&#x2013;=1 đ?&#x203A;˝đ?&#x2018;&#x2013; đ?&#x153;&#x17D;đ?&#x2018;Ąâ&#x2C6;&#x2019;đ?&#x2018;&#x2013; Where đ?&#x153;&#x20AC;đ?&#x2018;Ą ~đ?&#x2018; 0,1 , đ?&#x203A;žđ?&#x2018;&#x153; > 0 Generally, when testing for heteroskedasticity in econometric models, the best test is the White test. However, when dealing with time series data, this means to test for ARCH errors and GARCH errors. The most commonly used specification in applied financial research is the GARCH (1, 1) model which is given by: 2 2 đ?&#x153;&#x17D;đ?&#x2018;Ą2 = đ?&#x203A;žđ?&#x2018;&#x153; + đ?&#x203A;ź1 đ?&#x153;&#x20AC;đ?&#x2018;Ąâ&#x2C6;&#x2019;1 + đ?&#x203A;˝1 đ?&#x153;&#x17D;đ?&#x2018;Ąâ&#x2C6;&#x2019;1 This is said that the conditional variance of đ?&#x153;&#x20AC; at time t depends not only on the squared error term in the previous time periods [as in ARCH (1)] but also on its conditional variance in the previous time period. The economic interpretation of the ARCH effect in stock markets has been provided within both micro and macro area. The ARCH effect in stocks returns could be due to clustering of trade volume, nominal interest rates, dividend yields, capital gains, money supply and oil price index etc. The significance influence of volatility on stock returns is captured by the coefficient of đ?&#x153;&#x17D;đ?&#x2018;Ą2 . The persistence of shocks to volatility depends on the sum of the đ?&#x203A;ź + đ?&#x203A;˝ perameters. Value of the sum lower than unity implies a tendency for the volatility response to decay over time. In contrast value of the sum equal (or greater) than unity imply indefinite (or increasing) volatility persistence to shocks over time. However a significant impact of volatility on the stock prices can only take place if shocks to volatility persist over a long time.

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DATA ANALYSIS AND FINDINGS Table 2 (in appendix) summarizes the basic statistical characteristics of the DSE General Index. The standard deviation is significantly high and the series is positively skewed. The estimation results of the GARCH (1, 1) for DSE General Index (DGEN) during the sample period are listed in Table 3. According to Bollerslev [36] by the help of LM statistic the parameters of the GARCH (1, 1) model on the daily or monthly returns of Dhaka Stock Exchange (DGEN) is statistically significant. The change in the response function of shocks to volatility per period is represented by the sum of đ?&#x203A;ź + đ?&#x203A;˝. If đ?&#x203A;ź + đ?&#x203A;˝ = 1, then it can be said that a current shock persists indefinitely in conditioning the future variance. If đ?&#x203A;ź + đ?&#x203A;˝ > 1, then it can be said that the response function of volatility increase with time. If đ?&#x203A;ź + đ?&#x203A;˝ < 1, this means that shocks decays with time, the closer to unity value of the persistence measure, the slower is decay rate. We present the results for volatility in Table 3. The measure of GARCH model indicates that Îą+β is less than one. However it is not too far from unity, which means the volatility decrease over time. Hence, the volatility is present in the stock market in Bangladesh and it is decreasing over time. Volatility of yearly average DSE General Index using standard deviation is shown by the Figure 2. Observing the Figure 2 we can verify our GARCH (1, 1) result. In the chart it is found that the volatility of DSE was the highest at 2010 which also prove the present situation of the Bangladesh stock market. After 2010 the volatility of DSE is decreasing, that is the Volatility of DSE is decreasing over time. The volatility of monthly DSE General Index and daily DSE General Index by using variance is shown by Figure 2 and Figure 3. From all the result we can conclude that the volatility of DSE returns is decreasing over time.

RECOMMENDATIONS From the results, it is found that the DSE daily and monthly average General Index is volatile over time. But, for a developing country like Bangladesh, reducing volatility is very important for sound and sustainable development. Although the SEC has been trying to retain a continuous flow in the market, very often its role meets the broad economic objectives. For making the market less volatile, SEC itself should be strengthen both in terms of number of manpower and quality of the professionals involved with special focus on independent research, monitoring mechanism and prompt decision making. However, the following recommendations are hereby suggested for reducing the volatility of DSE: â&#x20AC;˘ When especially high volatility prevails in the market, careful monitoring of volatility by the concerned authority is needed in DSE which is yet to achieve maturity. If it is needed, there should be

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effective intervention when the market confronts excess volatility. Mass awareness and the development of the stock market infrastructure are essential to stock market development. In addition, it is obligatory to ascertain enforceable regulations that would make crystal clear for ensuring financial transparency, stopping financial malpractice, and preventing any form of market manipulation. The decisions taken by the regulatory authority should be made as much as predictable with the provision of sufficient explanation for the investors. In addition, before taking any fundamental regulatory decisions a broad-based discussion among widely representative advisory committees, deliberations with the stock exchanges and intermediary associations, chambers of commerce and investor associations and the public which helped drive market consensus for the reforms could be regarded by the SEC. Coordination is very important for the development of the financial market between SEC and Stock Exchanges. Availability of the relevant information relating to specific securities SEC should monitor strongly and the quality of audited reports which requires transparency and accountability of audit firms in topmost. SEC should make sure the proper risk-return relation because without it educated and professional investors will keep on themselves turning away from capital market. Even if they engaged, they will resort to other sources of profit-making opportunities such as inside information, fixed transactions, behavioral transactions, and other informal ways. Likewise, due to information asymmetry the foreign investors obviously avoid DSE. Good shares should keep at utmost importance to improve the market, because they provide more liquidity to the market. If this occurs, it will reduce irregular trading, attracts investors, and increase general investor's confidence as a whole. Regulators or policy makers should force directly (such as compulsory listing when authorized capital passes certain limit) or persuade (such as tax benefit) to ensure the participation of reputed firms apart from off-loading government shares so that the market depth (liquidity) is increased. Bangladeshi multinational companies (such as Grameen Phone, Robi, Banglalink) whose shares and bonds can be brought to the market. If they enter into the market, Small participation of these reputed firms through IPO (Initial Public Offering) can attract institutional as well as foreign investors by raising the depth (liquidity) of the market that can ultimately change the overall scenario of the capital market. Individual stock prices make unpredictable movements and it would be useful for the authority

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to identify the factors behind such price movements and if this happens the authority will be able to disseminate the information very quickly to interest the stakeholders. • By increasing supply of shares government can also take pro-active significant role in creating a stable market through tapping the growing interest of general people in the market. • Off-loading State Owned Enterprises that belong to the capital market will entail government to sell corporations in a lucrative manner and will also diversify the market. • Educational programs related to capital market needs to be strengthened up to root level. Minimum level of knowledge on capital market is very important to protect the interest of new investors. • For raising a part of debt through issue of marketable bonds, public utilities and infrastructure related projects can also be taken into consideration. • Keeping concerns for the growing interest of mass people, opportunities of share business e.g. brokerage house should be spread across the major points of the country. In this context, expansion of information technology, especially availability of internet facilities at root level can be very helpful. • A separate judiciary mechanism for the settlement of the disputes in the share markets (within a specified time limit) can be set up and the restoration of the investor's confidence can be considered seriously. • For guiding and restoring the confidence of individual investor in capital market, the regulatory authority should take necessary steps to encourage corporate governance rating among listed companies which will enable investors to differentiate the good governance companies from the rest and that can attach higher value to those firms as well. In addition, without improving the governance of the market and eliminating scope of manipulation, it will be difficult to attract good scripts at the desired level. In this context, regulators must adapt continuity to the changes in the economy and the pressures of globalization. Finally, of course, it is difficult to appraise the potentiality for these proposals to reduce volatility without understanding the causes of the volatility in the first place. Something can be said, nevertheless, which may help to clarify the debate and to elucidate the pros and cons of the proposals.

CONCLUSION Volatility is a widely researched area in the finance literature. The main thrust of this study is the empirical investigation of the estimation of volatility of Dhaka Stock Exchange (DSE). In conclusion, risk occurs to some degree in all investment markets, and volatility is one of the reflections of this risk. Contrary to popular opinions,

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volatility should not be feared; it should be recognized as a necessary part of the risk and return relationship. A reasonable amount of volatility in an investment is the trade-off for higher long term returns expectations. Investors should not alter their assets allocation plan in response to short-term changes in volatility but should review the reasonable long term expectations for volatility when creating their strategic assets allocation.

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[16] Batra, A (2004), “Stock return volatility patterns in India”, Working paper No. 124, Indian Council for Research on International Economic Relations. [17] Raju, M. T., & Ghosh, A. (2004). Stock Market Volatility – An International Comparison. Securities and Exchange Board of India, Working Paper Series No. 8. [18] Döpke, J., Hartmann, D., & Pierdzioch, C. (2005). Forecasting stock market volatility with macroeconomic variables in real time. Banking and Financial Studies 2006, 01, Deutsche Bundes bank, Research Centre. Discussion Paper Series 2. [19] Uppal, J. Y., & Mangla, I, U. (2006). Regulatory response to market volatility and manipulation: A case study of Mumbai and Karachi stock exchanges. The Lahore Journal of Economics, pp 79-105, 11:2 (winter). [20] Verma, R., & Verma, P. (2007). Noise trading and stock market volatility. Journal of Multinational Financial Management, pp 231-243, Volume 17, Issue 3, July 2007. [21] Baklaci, H. F. & Kasman, A. (2006). An Empirical Analysis of Trading Volume & Return Volatility Relationship in the Turkish Stock Market, Ege AkademikBakis, 6:.115-126. [22] Olowe, R. A. (2009): Stock Return, Volatility & the Global Financial Crisis in An Emerging Market: The Nigerian Case”, International Review of Business Research Papers, 5. 426-447. [23] Alam, M. M., & Uddin, M. G. S. (2009). Relationship between Interest Rate and Stock Price: Empirical Evidence from Developed and Developing Countries. International Journal of Business and Management, Vol. 4, No. 3. [24] Bangladesh Bank Annual Report: 2011-2012. [25] Bangladesh Bank Annual Report: 2011-2012 [26] DSE Annual Report: 2011-2012 & www.dsebd.com [27] Bangladesh Bank Annual Report: 2011-2012. [28] Hassan,K. A, Islam, M. A and Basher, A. S. (2000) : Market Efficiency, Time-Varying Volatility and Equity Returns in Bangladesh Stock Market [29] Engle, Robert F., (1982): “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation,” Econometrica, 50 (July): 9871007. [30] Baillie, R. and R. Degennaro ( 1990): “Stock Returns and Volatility,” Journal of Financial and Quantitative Analysis, 25(June, 1990): 203-214. [31] Akgiray, Vedat, (1989): "Conditional Heteroskedasticity in Time Series Stock Returns: Evidence and Forecasts," Journal of Business, 62, pp55-80. [32] French, Kenneth, William Schwert, and Robert Stambaugh. (1987):“Expected Returns and Volatility”, Journal of Financial Economics, 19, pp3-29. [33] Koutmos, Gregory. (1992): “Asymmetric Volatility and Risk Trade off in Foreign Stock Markets”, Journal of Multinational Financial Management, 2, pp27-42. [34] Koutmos, G., C. Negakis, and P. Theodossiou (1993) “Stochastic Behavior of the Athens Stock Exchange,” Applied Financial Economics, Vol. 3(1993): 119-26. [35] Bollerslev, T. (1986): Generalized Autoregressive conditional Heteroscedasticity. Journal of Econometrics. 31, 307-327.

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Appendix

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