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The Impact of Foreign Direct Investment for Economic Growth: A Case Study in Sri Lanka ARTICLE 路 JANUARY 2003

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1 AUTHOR: Wasantha Athukorala University of Peradeniya 19 PUBLICATIONS 60 CITATIONS SEE PROFILE

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9th International Conference on Sri Lanka Studies Full Paper Number 092

The Impact of Foreign Direct Investment for Economic Growth: A Case Study in Sri Lanka

P.P.A Wasantha Athukorala

Address for Correspondence Department of Economics Faculty of Arts University of Peradeniya, Sri Lanka.

Email: wathukorala@yahoo.com

Paper submitted for the 9th International conference on Sri Lanka Studies, 28th – 30th November 2003, Matara, Sri Lanka

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The Impact of Foreign Direct Investment for Economic Growth: A Case Study in Sri Lanka By P.P.A Wasantha Athukorala Abstract: The integration of developing countries with the global economy increased sharply in the 1990s with changing in their economic policies and lowering of barriers to trade and investment. Foreign Direct Investment (FDI) is assumed to benefit a poor country like Sri Lanka, not only by supplementing domestic investment, but also in terms of employment creation, transfer of technology, increased domestic competition and other positive externalities. Sri Lanka offers attractive investment opportunities for foreign companies and has adopted a number of policies to attract foreign direct investment into the country and the country seems to offer perhaps one of the most liberal FDI regimes in South Asia. As a result, during the last decade FDI inflows in Sri Lanka has increased considerably by 8.5 in 1990 to 15.0 in 2000 as a percentage of GDP while Indian experience was 0.5 to 4.1 in the same period However, previous literature suggests that the FDI inflows have a positive impact on economic growth of host countries. Although a large volume of econometric literature comprises on the impacts of FDI on economic growth in developing countries, there is not enough studies on the question of causality linkage between them. This paper focuses on the FDI-led growth hypothesis in the case of Sri Lanka. The study is based on time series data from 1959 to 2002 and the response of civil society and foreign firms.

The econometric framework of cointegration and error correction mechanism were used to capture two way linkages between variables interest. It is evident in the results that the regression analysis do not provide much support for the view of a robust link between FDI and growth in Sri Lanka. It does not imply that FDI is unimportant. Rather, its analysis reduces the confidence in the belief that FDI has exerted an independent growth effect in Sri Lanka. But net attitudes of the civil society on the impact of FDI on opportunities for domestic business and economic activities is positive and net attitudes of foreign firms toward FDI reveals that the investment climate has not improved in Sri Lanka as a result of lack of good governance, corruption, political instability and disturbance, bureaucratic inertia, and poor low and order situation.

1. Introduction

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The growth of international production is driven by economic and technological forces. It is also driven by the ongoing liberalization of Foreign Direct Investment (FDI)1 and trade policies. In this context, globalization offers an unprecedented opportunity for developing countries to achieve faster economic growth through trade and investment. In the period 1970s, international trade grew more rapidly than FDI, and thus international trade was by far than most other important international economic activities. This situation changed dramatically in the middle of the 1980s, when world FDI started to increase sharply. In this period, the world FDI has increased its importance by transferring technologies and establishing marketing and procuring networks for efficient production and sales internationally (Shujiro Urata, 1998).

Through FDI, foreign investors benefit from utilizing their assets and resources efficiently, while FDI recipients benefit from acquiring technologies and from getting involved in international production and trade networks. While global FDI flows increased by 24 per cent during 1991-2000, developing countries as a group show an FDI increase of 20 per cent at constant prices (World Development Report, 2002). FDI flows to poor countries increased to almost 3 per cent of GDP. However, after reaching a peak in 2000, global FDI flows declined sharply in 2001. Inflows fell by 51 per cent and outflows by 55 per cent (World Investment Report, 2002). This was the first drop in inflows since 1991 and in outflows since 1992. More than 12 countries including the world’s three largest economies fell into recession in 2001. This slowdown in the world economy was the major factor to decrease FDI in 2001. Although, global FDI flows marked drastic fall, net FDI flow to developing countries remain almost unchanged in this year.

The determining factor for a particular firm to establish production facilities abroad is the prospect of earning higher profit which induces firms to invest abroad, primarily because of lower labour costs.

Traditional theories on trade and investment assumed that factors of production, such as labour and capital, were not internationally traded. However, in reality, factors are internationally mobile and at least since the nineteenth century, international labour movement and international investments have been very important in the global economy (Jayasuriya and Weerakoon, 2000). Although differences in labour costs may sometimes help influence firms’ decisions to locate abroad, this is far from being the whole story. As the FDI data showed, the majority of FDI still goes to the advanced countries, in particular the United States where wages are high relative to those in developing countries. The interesting point here is that there will normally be extra costs involved, at least initially, for a firm investing in a foreign country where it is not familiar with the local market and the institutions. At a theoretical level, economic analysis offers various explanatory approaches which attempting to show why, despite these disadvantages, firms may still wish to invest abroad. According to John Dunning (1977) firms undertake FDI when three factors are present and the resulting advantages are sufficient to offset the natural disadvantages of having to operate in a foreign

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The term FDI raises important conceptual questions regarding definition and interpretation, as well as practical problems of measurement. The classification of certain types of investments is sometimes based on arbitrary arguments. But we use the definition which introduced by the World Trade Organization (WTO) in 1996. The WTO indicates that FDI occurs when an investor based in one country acquires an asset in another country with the intent to manage that asset. Accordingly, the management dimension is what distinguishes FDI from portfolio investment in foreign stocks, bonds and other financial instruments.

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country. These three advantages are; ownership advantages (Hymer, 1960), locational advantages (Vernon, 1966), and international advantages (Buckley and Casson, 1976) Except the above mentioned, there are several other macro level theories in the literature which attempt to explain why foreign investment takes place. These include various theories of economic imperialism, based on different interpretations of the workings of the capitalist system2.

However, FDI provides much needed resources to developing countries such as capital, technology, managerial skills, entrepreneurial ability, brands, and access to markets. These are essential for developing countries to industrialize, develop, and create jobs attacking the poverty situation in their countries. As a result, most developing countries recognize the potential value of FDI and have liberalized their investment regimes and engaged in investment promotion activities to attract various countries.

Globalization and regional integration arrangements can change the level and pattern of FDI and also it reduces the trade costs. However, FDI flows to developing countries started to pick up in the mid-1990s largely as a result of progressive liberalization of FDI policies in most of these countries and the adoption of generally more outward- oriented policies. FDI flows of the developing and developed countries over the last two decades can be depicted in Table 1. According to the Table 1, FDI flows in the world has increased unprecedented level in the recent past. Within the developed world, the European Union, the United States and Japan accounted for 71 per cent of world inflows and 82 per cent of outflows in 2000 (World Investment Report, 2003). Inward and outward FDI stocks as a percentage of gross domestic product in the selected regions is given in Table 2.

Foreign Direct Investment flows to the developing countries of Asia and the Pacific fell from $ 134 billion in 2000 to $ 102 billion in 2001. This decline was due to an over 60 per cent drop in flows to Hong Kong, China from a record level of $ 62 billion in 2000. Excluding Hong Kong, China, inflows in 2001 reached the same level as in the peak years of the 1990s. FDI flows to South Asia started to pick up in the mid-1990s largely as a result of progressive liberalization. However, South Asia has not been generally a large recipient of FDI. In the 1980s, the average annual flow of FDI was around 2 million dollars per annum for Bangladesh, 50 millions dollars for India, around 42 million dollars for Pakistan and 41 million dollars for Sri Lanka. These figures are very low when compared to other economies of the developing world, especially of East Asia. Among South Asian neighbors India’s position is undisputable, not just because of the potential of its market but because of the level of local industrial skills and experience in the industrial production. Because of these circumstances, India could become a major destination for FDI, one of the largest in the developing world. Inward and outward FDI stocks as a percentage of gross domestic product in the selected countries in Asia is depicted in Table 3.

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Apart from above theories there are several micro level theories which explain multinational investment in rather different terms, such as Oligopolistic rivalry between firms at the global level, the empire-building motives of managers of large corporations in advanced countries or strategic entry deterrence, that is, the build up of overseas capacity in order to stop potential rivals from entering any specific market or markets. However, these theories deal with lot of factors such as , access to markets, labour costs, proximity to row materials, and fiscal incentive.

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However, the performance within the Asian regions varies from country to country. FDI growth in China continued its momentum driven by the liberalization process and industrial restructuring. However, during the last decade FDI inflows in Sri Lanka has increased considerably by 8.5 in 1990 to 15.0 in 2000 as a percentage of GDP while Indian experience was 0.5 to 4.1 in the same period (World Investment Report, 2002). Against this backdrop, this article attempts to provide a broad overview of the policy environment and experience of the FDI and economic growth in Sri Lanka.

1.1. An Overview of FDI in Sri Lanka Prior to economic liberalization, Sri Lanka has followed inward looking economic policies, which had limitations for foreign investors and free flow of FDI. Although there were limitations during the period of 1950-1977, some measures had been taken to attract FDI. For instance, in 1966, presented a white paper for FDI and also foreign investment advisory committee was set-up in 1968 in order to investigate and manipulate policies regarding foreign direct investment in Sri Lanka.

With the market oriented economic policy accepted as being the most effective engine of growth, political entities have made it their top priority to create an investment friendly economic climate in 1977.

Based on Foreign Investment Act in 1978, investment policies in Sri Lanka have been engineered to attract foreign investment. In addition, Sri Lanka was one of the longest democratic traditions in the region and over the past 20 years, successive governments have followed free market policies and continued to liberalize the economy. Investment has been actively canvassed and now there are over 1,000 companies from 55 countries operating in Sri Lanka. The country’s investment laws are transparent and automatic across a wide range of sectors. There are no restrictions on the repatriation of earnings, profits, and capital proceeds (BOI Report, 2002).

Sri Lanka offers an attractive package of fiscal incentives to foreign and local investment.

Foreign investment is encouraged in enterprises, which involve extensive use of foreign capital or sophisticated technology, in export-oriented manufacturing, and in large- scale infrastructure projects.

Apart from this, privatization and deregulation of the various sector in the country has led to the presence of global giants and attract FDI. Up to now, Sri Lanka has six free trade zones, also called export processing or investment promotion zones located in Katunayake (1978), Biyagama (1986) Koggala (1991) Pallekelle(1996)

Mirigama(1997) and Malwatte(1997). There are over 155 foreign export

processing enterprises operating in the six zones.

Another industrial zone, funded by the Overseas

Economic Cooperation Fund of Japan, is taking shape at Seethavaka, in Avissawela about 60 kilometers from Colombo. However expansion of export earnings and creation of employment opportunities are the main objectives of the establishment of Free Trade Zone in Sri Lanka. Apart from this the Government of Sri Lanka also has signed investment protection agreements with various countries including the United States (which came into force in May 1993).

In 2002, India emerged as Sri Lanka' s major investor in terms of the number of agreements signed and in terms of the total value of projects. A major factor behind this trend was the signing of the Indo-

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Lanka Free Trade Agreement that has made it attractive for Indian investors to set up plants in Sri Lanka for re-exports to India. Sri Lanka will enter into a similar agreement with Pakistan, the possibility exists for bilateral trade and investment between these two large South Asian States through Sri Lanka.

Sri Lanka’s average total gross domestic investment in the last decade has been around 25 per cent of GDP; actually it fell from 27.0 per cent of GDP in 1994 to 21.3 percent in 2002. The failure to achieve the target was mainly because of poor response from the private sector. The government too could not maintain its level of public investment as announced in the policy statement; public investment declined from 7.0 percent of GDP in 1994 to 4.6 per cent in 2002. Foreign direct investment in Malaysia is 46 times than Sri Lanka (1995). Total investment and FDI of Sri Lanka over last several years is given in Table 3.

Foreign investment inflows to Sri Lanka continued to increase over the last decade as a result of investment favorable policies adopted by the successive government. The downturn in world economic activities, slowing down in capital inflows to developing countries, deterioration of investor confidence due to the civil war and politics related uncertainty and the stagnation of the Japanese economy adversely affected the investment inflows to Sri Lanka in the past few years. Since the beginning of the 90’s decade, the annual value of FDI inflows to Sri Lanka has started to continue with an increasing rate when compared to 80’s decade. This kind of upward movement of FDI is interpreted as an outcome of the second liberalization reforms initiated in 1989. The mostly observed transformation of relocating of labourintensive production activities from rapidly growing East Asian Newly Industrialized countries to labour surplus countries in South Asia. Following these transformations, Hong Kong, Taiwan and Korean investors showed prominently in the participation of FDI projects recently.

As far as the 1978-93 period is concerned, as a whole, FDI emerges as the dominant form of private capital inflows other than portfolio investment, private short term and long term borrowings. FDI increased from a negligible level in 1978 to 9 billion Rupee or around 2 per cent of the gross domestic product by 1993. The trend of FDI corresponding to the long term investment climate produced by foreign trade and the balance of payment liberalization was influenced by economic and political stability. FDI increased initially due to favorable investment climate created by the 1977 reforms, liberalization, and increased level of openness of the economy. During the 1983-89 period, the incentives for FDI were damaged by the setbacks on foreign trade, moreover, the investment environment further deteriorated during the same period as a result of political misalignments. The incentives under structural adjustment and stabilization programme implemented in 1990s were of great importance in generating a surge in FDI. Although FDI has increased in the recent past, it remains difficult to quantify the exact magnitude of FDI basically because of the non-reporting problem. It is even more difficult to have correct estimate of sectoral FDI. The Board of Investment keeps product category-wise records of registered investment with BOI. Accordingly, number of enterprises registered under BOI has increased drastically between 1995 and 2002. Out of the total, Food & beverage and tobacco products, Services and Text/apparel and leather enterprises were the most significant enterprises

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At present, several leading business missions of the world have shown a keen interest to participate in Sri Lanka' s commercial ventures when these teams visited the BOI in last year. Some of the delegation members were enthusiastic in launching projects in the areas of e-commerce, e-government, and various services sectors in the country. According to the BOI sources, its aim is to achieve US$ 300 million in FDI by the end of this year (2003). The main advantages that Sri Lanka had were the proximity to major transshipment routes and a Free Trade Agreement (FTA) with India and Pakistan that gave access to world’s biggest markets. Currently, among the areas open to foreign investment in Sri Lanka were privatization, shipbuilding, ship repairing, oil storage, power and energy, mineral processing, tourism and electronics. Infrastructure development figures high on the agenda and power, ports, IT, water supply, waste management and connectivity were identified as areas the government wanted to develop with the idea of attracting FDI to the country. Accordingly, a new series of incentives were introduced to attract more investors to develop regions other than the Western Province, which to date has received the largest share of FDI. This was part of a government policy to encourage even investment and economic development in all parts of the country with the long-term objective of creating employment opportunities and technological transfer.

However, the BOI was able to renew interest in FDI last year as a result of the peace process in the country. In 2002, 499 projects were approved compared to 385 in 2001, an increase of 30 per cent. There was also an improvement with regard to implementation of projects: 71 projects commenced construction work in 2002, which represents a 55 per cent increase from the previous year. A total of 39 per cent are locally owned Sri Lankan investment projects while 32 per cent are foreign owned. Jointly owned projects (Sri Lankan and Foreign) amount to 29 per cent. The significance of this development led in turn to a 3 per cent increase in Sri Lanka' s exports in 2002. In 2002, India emerged as Sri Lanka' s major investor in terms of the number of agreements signed and in terms of the total value of projects. At present, there are around 1,500 companies that operate under the BOI regime. They vary considerably in size and in scope and are drawn from over 22 countries. Meanwhile, Sri Lanka has been ranked among the top 20 economies in the developing Asia and Pacific region in FDI inflows.

1.2. Objectives Foreign investment inflows to Sri Lanka continued to increase over the last decade as a result of investment favorable policies adopted by the successive government. Since the beginning of the 90’s decade, the annual value of FDI inflows to Sri Lanka has started to continue with an increasing rate when compared to 80’s decade. This kind of upward movement of FDI is interpreted as an outcome of the liberalization reforms initiated in 1977.

The incentives under structural adjustment and stabilization

programme implemented in 1990s were of great importance in generating a surge in FDI. According to the previous literature the FDI inflows have a positive impact on economic growth of host countries. This

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paper focuses on the FDI-led growth hypothesis in the case of Sri Lanka. Accordingly the main objectives are; 1.

to consider the short run and long run relationship between FDI and economic growth

2.

to consider the perception of the civil society, and foreign firm toward FDI

The bi-directional causality3 between FDI and GDP can also be expected in the short-run when the economy adjusts to its long-run equilibrium. An infusion of FDI, while bringing the economy to a higher long run growth path raises growth in the short run as well. With increased growth in the short run, the economy can traverse along its transitional path4.

2. Literature Review 2.1 Previous Studies Although most countries offered a large numbers of incentives to attract FDI, experience from other countries shows that such plans often have limited impact on new investment, reduce transparency of the business climate, and lead to higher taxes for other taxpayers. Tax incentives or free trade zones are used by some countries to attract investors, despite mixed evidence about their impact on FDI flows and the potentially high costs compared to the benefits (Piritta Sorsa, 2003).

According to the study done by Pradeep Agrawal (2000) on economic impact of foreign direct investment in south Asia by undertaking time-series, cross-section analysis of panel data from five South Asian countries; India, Pakistan, Bangladesh, Sri Lanka and Nepal, that there exist complementarily and linkage effects between foreign and national investment. Further he argues that, the impact of FDI inflows on GDP growth rate is negative prior to 1980, mildly positive for early eighties and strongly positive over the late eighties and early nineties. Most South Asian countries followed the import substitution policies and had high import tariffs in the 1960s and 1970s. These policies gradually changed over the 1980s, and by the early 1990s, most countries had largely abandoned the import substitution strategy in favor of more open international trade and generally, market oriented policies (Pradeep Agrawal, 2000). The results of the analysis carried out by Archanun Kohpaiboon on the impact of FDI on growth performance in investment receiving countries through a case study of Thailand for the period 1970-1999, shows that the growth impact of FDI tends to be greater under an export promotion trade regime compared to an importsubstitution regime.

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Economic reasoning supports many different forms of causality between FDI and GDP: causality from FDI to GDP, from GDP to FDI, permanent long-run movements, and transitory short-run adjustments.

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Parantap Basu Derrick Reagle and Chandana Chakraborty “Empirical Dynamics of FDI and Growth in Developing Countries: Does Liberalization Matter?� Fordham University, USA and Montclair State University, USA

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A panel study including 23 countries was carried out for the period from 1978 to 1996 by Parantap Basu Derrick Reagle and Chandana Chakraborty to identify long run and short run effects of FDI. Accordingly, an analysis of the cointegration estimates suggests that there was a long run cointegrated relationship between FDI and GDP for the entire panel of 23 countries. Furthermore, for open economies, causality between FDI and GDP appears to be bi-directional. But causality is bi-directional only in the short run for relatively closed economies. Long run causality for relatively closed economies is uni-directional and runs mainly from GDP to FDI. According to Nguyen Nhu Binh and Jonathan Haughton (2002) the Bilateral Trade Agreement has lead to 30 per cent more FDI into Vietnam in the first year, and an eventual doubling of the flow. Result would boost economic growth by 0.6 percentage points annually.

But the analysis of Brecher and Diaz-Alejandro (1977), gives us evidence that foreign capital can lower the economic growth by earning excessive profits in a country with severe trade distortions such as high tariffs. Maria Carkovic and Ross Levine (2002) also concluded in their econometric study on FDI and GDP growth that the exogenous component of FDI does not exert a robust, independent influence on growth.

However, no consensus has yet been reached on the steady state as well as dynamic effects of FDI on growth. While some studies argue that the impact of FDI on growth is highly heterogeneous across countries with relatively open economies showing statistically significant results, the other studies maintains that the direction of causality between the two variables depends on the recipient country’s trade regime. However, most studies don’t pay any serious attention to the possibility of a bi-directional link between the two variables in reference.

2.2 Analytical Framework The methodology involves estimating an econometric model as well as simple calculations such as average and percentage.

The model to investigate the impact of FDI on growth, we use a simple

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production function , but add several slight difference variables. The starting point of model formulation is; Y= f (A, FDI, K) --------- (1) Where Y is output; Gross Domestic Product (GDP), and K is capital stock. The variable A captures the total factor productivity of growth in output not accounting for increasing in factor inputs (K, L and FDI). The effect of trade liberalization on economic growth is operating through Total Export and Import to GDP (TP).

Y = F (FDI DIN TP) ---------- (2) A reliable data series on capital stock is not available. As a result in most studies, (Barro, 1999) ratio of the gross fixed domestic investment to GDP is employed as a proxy variable represent K. In this study we employed the gross domestic investment except FDI as a proxy variable for K. As our interest is

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Here, I dropped the variable L (labour) from the model as Sri Lanka is a labour surplus economy.

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in studying the impact of FDI inflows on economics growth, we consider the nationally owned investment defined as gross fixed domestic investment minus the net FDI inflows and FDI as different variables.

Accordingly, the estimating equation used in this study is; GDP = β0FDIβ1 DINβ2 TPβ3 U ---------- (3) Where GDP = gross domestic product (in log form) FDI = foreign direct investment (in percentage form) DIN = Domestic investment 6(in log form) TP = Trade liberalization 7(in log form) U= stochastic error term The coefficients β1and β2 are the output elasticity with respect to FDI and DIN. The impact of FDI on growth (Y) is given by β1. Note that the coefficient, β1, of this variable should be equal to the coefficient, β2, of DIN if FDI is just as efficient in promoting GDP growth as nationally owned investment.

If the greater technology, human capital or exporting capabilities of FDI make it more efficient in promoting growth, the co-efficient, β1, can be expected to be greater than the coefficient, β2. On the other hand, if FDI takes excessive profits out of the country without contributing much in terms of technology etc., the co- efficient, β1, should be smaller than the coefficient, β2.

2.3 Methodology and Data The first step of the estimation process is to examine the time series properties of the data series.

We look at patterns and trends in the data and test for stationary and the order of integration. In fact most economic variables are non-stationary (integrated) in their level form. These non stationary time series may result to spurious regressions. Although a simple least squares regression of integrated variables may be spurious, one or more linear combinations of the series may exist that result in a stationary residual. For this purpose we employed the following forms of Dickey-Fuller and the augmented Dickey-Fuller (ADF) test where each form differs in the assumed deterministic component(s) in the series: Yt = Yt-1 +Ut ……………………………………..(1) Yt = 1 + Yt-1 +Ut………………………………… (2) Yt = 1 + 2t + Yt-1 +Ut…………………………...(3) In each case the null hypothesis is that = 0, that is, there is a Unit Root. As the error term Ut is autocorrelated, we use the following equation with lagged difference term instead of equation 3 Yt = 1 + 2t + Yt-1 + i

Yt-i + Ut

………… (4), where i = 1….n

After selecting the order of integrating, next step involve to test the cointegration rank. Here, we form a Vector Autoregressive Regression (VAR) system. This step involves testing for the appropriate lag length of the system, including residual diagnostic tests. We specify the VAR as a four variable system 6 7

Domestic private and government investment TP = Openness of the trade policy regime proxied by OPEN = the ratio of total merchandise trade (import + export) to goods GDP.

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with a maximum of two lags. The model includes the log of the real GDP, real FDI, real DIN and trade liberalization. Various procedures have been suggested for determining the appropriate lag length in a dynamic model. The adjusted R2 is one possibility. Other include the Akaike(1973) Information Criterion (AIC) and Schwartz’s criterion (SC)8. I used above two critererias to select the appropriate lag length for this study.

Basic structure of VAR is as following

Zt =

Z1

Gross Domestic Product

Z2

Foreign Direct Investment

Z3

=

Z4

Domestic Investment Trade Liberalization

n

Zt =

+

ti Zt-i +

Zt-1 + Ut

i=1

This gives the long-run and short-run dynamics of a group of integrated variables. Zt is a vector of I(1) variables, Ut is a vector of white noise residuals, and

is a constant vector. The adjustments to

disequilibrium are captured over n lagged periods in the coefficient matrix ti. This part of the ECM represents a traditional vector autoregression of the differenced variables. The Zt-1 terms represent longrun equilibrium or cointegrating relationships, and the coefficient matrix can be decomposed into 9

matrix .

’

A procedure developed by Johansen (1991) provides a means to investigate the cointegrating

relationship between integrated series. The Johansen test was used to determine the cointegrating rank10.

Obviously, for a long-run relationship to exist, at least the first column must contain non-zero elements. If

8 Akaike(1973) Information Criterion (AIC) ; AIC(p) = Ln (e’e /T)+ (2P/T) Schwartz’s criterion (SC); SC(p) = AIC(p) + (P/T) ( lnT -2 ) P = Number of Lags T = Time = n = sample size e’e = Residuals some of squire 9 This matrix must have lower than full rank, otherwise it can be shown that Zt is entirely a function of the residuals and therefore must be stationary.

10 In general, if Y is I(d) and X is also I(d), where d is the same value, these two series can be cointegrated. Cointegration means that despite being individually nonstationary, a linear combination of two or more time series can be stationary. Cointegration of two or more time series suggests that there is a long-run, or equilibrium, relationship between them. As a proper test for cointegration trace test was used.

The CI rank: the trace statistic; Trace = -T ln ( 1- i ) i = r+1 ……..k Which allows for the test of H (r) : the rank of is r, Against the alternative that the rank of is k.

The results of the trace test are: 1. The hypothesis that r = 0 is rejected if sample value > critical value 2. The hypothesis that r rank(1,2..) is not rejected if sample value < critical value A large value of the trace statistic is evidence against H (r): that is, with r = 0, a value of the trace statistic greater than the appropriate critical value allows us to reject r = 0 in favor of r > 0 . The test may then be repeated for r = 1, and so on.

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more than one linear combination occurs, we can normalize and combine them to investigate pair-wise effects between the variables. This cointegrating relationship represents the foundation of a complete dynamic error correction model. For this paper, the ECM and cointegrating relationship allows us to compare the immediate and overall effects and then, the model will show how fast adjustments occur.

Third, we interpret the cointegrating relations and test for weak exogeneity. Based on these results a vector error correction model (VECM)11 of the endogenous variables is specified.

The model is estimated using annual data for the period 1959- 2002. Data on gross domestic product (GDP), Domestic investment (DIN) export and import are obtained from the Central Bank Annual Reports. Data on FDI are obtained from Central Bank Annual Report and the Board of Investment. Data to investigate of perception of civil society and foreign firms were collected by interviewing company representatives and various people who lived in and around Pallakale Industrial Zone.

3. Results and Discussion Figure 1 shows the trend of GDP, FDI, DIN and TP over the last 43 years period. According to the graphs, a clear trend can be observed of the GDP,DIN, and TP in Sri Lanka over this period. However FDI trend was somewhat not clear as the result of low level of FDI before the economic liberalization period.

3.1. Econometric results Before estimating any relationships between GDP and its explanatory variables, we need to check for the stationary of each series. As our graphs also do not give a clear picture regarding the stationary, this property is tested using the Dickey-Fuller (DF) test and the Augmented Dickey-Fuller (ADF) test for a unit root. The DF and ADF results for the four series involved in our equation are presented in Table 5. Our result shows that all variables exhibit integrated order one12. This means that the series are non-stationary in level but stationary in first-differences. The implication is that there is a possibility to have a co-integrating vector whose coefficient can directly be interpreted as long-term equalibrium. Therefore, as next step, Johansen trace test is used to check whether we have a cointegration relationship. Result of the trace test is reported in Table 6 which gives the number of cointegrating vectors. According to the Table 6, we can reject the hypothesis that no cointegration exists but fails to reject a hypothesis of more than one stationary linear combination. The implied cointegrating relationship is obtained from first row of the standardized beta eigenvector.

It is interpreted as the GDP; GDPt =

-5.885 + 0.164FDIt + 0.948DINt + 0.104TPt + Ut

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At least three steps are necessary to employ the VECM approach. First, we test the three performance variables for non-stationary.

Second, if the variables are integrated of the same order, we check for the presence of a cointegrating relationship. Third, if there is cointegration, we distill the lagged error terms from the estimated cointegrating vector and incorporate the lagged error terms in the VECM process

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Here according to the DF test, FDI is I(0). But as ADF test is the proper test I used ADF to determine the stationary of the series.

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The error correction model provides a generalization of the partial adjustment model and permits the estimation of short-run and long-run elasticities. This long-run association would show us the elasticities of GDP with respect to FDI, DIN and TP. According to the results, a 1 per cent increase FDI results in a 0.164 percentage increase in GDP but this variable is not significantly different from zero. If the level of DIN, goes up 1 per cent GDP increase by 0.948 a percentage point. For TP, the result is a 0.104 per cent increase in GDP. Although the coefficient of FDI is not significance, the coefficients of DIN and TP are significantly different from zero. Here the magnitude of TP implies very inelastic with respect GDP. In order to appropriately model the full dynamic behavior of GDP, we need to incorporate shortrun adjustment factors along with the cointegrating equilibrium relationship. This is best done using the error-correction model technique introduced above. In our case there is only one stationary linear combination of the four integrated variables. The simplified ECM for two lags period

n Zt =

+ i=1 i Zt-i +

Ut-1 + t

Where n =2 The vector Zt includes the GDP FDI DIN and TP and the coefficients represent the short-run elasticites. We can determine if the variables actually adjust to disequilibrium by examining the coefficient. This parameter will be stable if its absolute value is less than one, and its sign should be negative since a positive shock to a system should result in adjustment in the opposite direction. If all values of this coefficient are insignificant any long-run relationship is pointless since the model never actually achieves it. Table 7 shows the estimates of the ECM. The two most important equations in our error correction model are those containing DIN and TP as dependent variables. The other two indicate a small relationship. We can see that 12 per cent of the GDP response to disequilibrium occurs within the immediate period after a shock, and around 62 per cent of the domestic investment response occurs within this period. The short-run elasticity with respect to DIN is approximately 0.622 and. The second equation highlights the impact that GDP, DIN and TP can have on foreign direct investment. Accordingly total elasticity of GDP in relation to the FDI is 3.923 and elasticity of DIN in relation to the FDI is 6.108.

Almost all estimated regression in this third equation is significance. The regressors in this model explain about 50 per cent of the variation in the dependent variable, and autocorrelation in the residuals is not a problem as its value is almost equal to two. Another interesting point in our estimations is the relationship between FDI and DIN. If there is a crowding out effect, this relationship should be negative. But both equation give us the positive sign implying that a crowding in effect in Sri Lanka.

We used the Engle-Granger method as alternative techniques of estimation to see the direction of causality as the last step. Results of the causality test are reported in the Table 8. These results suggest that the direction of causality is from GDP to FDI since the estimated F value is significant at the 5 per cent level; the critical F value is 3.23. On the other hand there is no reverse causation from FDI to GDP, since

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the computed F value is not statistically significant. And also causality could be observed from DIN and TP to GDP as well as from GDP to DIN and TP. The implication is the direct growth impact of FDI on the Sri Lankan economy has not existed so for. However these results were directly affected the inward economic policy implemented up to 1977 in the country. Because, almost all the years from 1959 to 1976 negative FDI flows were recorded and the contribution of FDI to the overall performance of the Sri Lankan economy was not significant during the 1950s, 1960s and 1970s. But after 1977 it is recorded a continuous FDI growth in the country. And also the new FDI firms in 1990s are more export-oriented relatively to those in the early 1980s.

3.2. Attitudes Analysis Perception of the civil society and foreign firm about the importance of FDI on domestic economic development in the past is mixed. But their perception seems more aligned towards the positive aspects of FDI. Most of the responses represent strong agreement or partial agreement with all the positive aspects of FDI. Tables 9, 10, and 11 show the summary results of the civil society and foreign firms. To express the summary of responses in terms of a single number, an index13 is constructed by taking weighted average of number of response of each type. Accordingly a positive value of the index implies positive impact, and a negative value of the index implies negative impact. And also larger positive value of the index implies a stronger positive impact. It is evident from the tables that except for price impact, the index is positive for all issues regarding the impact of FDI on various economic activities. Although perception of the civil society regarding the impact of FDI is positive, net attitudes of foreign firms toward FDI reveals, that the investment climate has not improved in Sri Lanka as a result of lack of good governance, corruption, political instability and disturbance, bureaucratic inertia, and poor low and order situation.

4. Conclusion This paper has examined the relationship between FDI and GDP using time series data from the Sri Lankan economy. In Sri Lanka FDI has increased dramatically since the 1980s. Many studies find a positive link between FDI and growth. But our econometric result shows that FDI inflows do not exert an independent influence on economic growth. And also the direction of causation is not towards from FDI to GDP growth but GDP growth to FDI. That is the direct growth impact of FDI on the Sri Lankan economy has not existed so for. The impact of DIN and TP on GDP growth rate is found to be positive and direct independent causality could be observed from DIN and TP to GDP as well as from GDP to DIN and TP. Net attitude of the civil society and foreign firm towards FDI in the country is positive. But net attitude reveals that the investment climate has not improved in Sri Lanka as a result of; political instability and 13

* Index is formed by taking weighted average of number of response by assuming following numerical values: strong positive impact = 2, positive impact = 1, no effect = 0, negative effect = -1, strong negative impact = -2, . By construction, index ranges from 2 to +2. A positive value implies positive impact, and a negative value implies negative impact.

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disturbance, poor low and order situation, direct and indirect regulatory barriers, political instability and the implied policy instability, poorly developed infrastructure facilities, low levels of human capital, lack of transparency in the trade policy. Accordingly, the protectionist trade policies, direct and indirect regulatory barriers ( that raised the costs of investment to foreign firms, for example, in Sri Lanka about 13 per cent of capital costs and 30 percent of profits are lost due to impediments in the regulatory framework), political instability and the implied policy instability, poorly develop infrastructure facilities, low levels of literacy and investment in human capital, the war against terrorism (in the first place this has diverted the country’s resources amounting to 5 per cent of GDP and also this created uncertainty and risk which discourage investment), lack of transparency in the trade policy, discrimination against non- export oriented sectors like plantations, and high lending rate are found as the major constraints to FDI flows in Sri Lanka.

The importance of FDI cannot be overstated. As a result, the investment climate in the country must be improved through appropriate measures such as de-regulation in economic activity, increase domestic serving, developing the port network, road network, railways and telecommunication facilities etc, creating more transparency in the trade policy and more flexible labour markets and setting a suitable regulatory framework and tariff structure. Currently Sri Lanka provides an attractive investment regime but the response from the investor has not been very encouraging. If the ultimate objective of the government is to attract FDI for development, poverty reduction and growth, then an appropriate policy mix is necessary to achieve these.

Reference Agrawal P.( 2000) Economic impact of foreign direct investment in south Asia Indira Gandhi Institute of Development Research, Gen. A.K. Bombay; India Asia- Europe exploratory roundtable on foreign direct investment and the environment (2001), Background Paper; Regional Institute of Environmental Technology Athukorala P.P.A.W (2003) “ The Impact of Foreign Direct Investment on Economic Growth in Sri Lanka” Proceedings of the Paradeniya University Research Sessions. Vol 8, pp,40.

Board of Investment , Various reports, Colombo :Sri Lanka Bautan.L. and M.A. Sumlihskhi,(1999) “Trends in private investment in developing countries”, Statistics for 1970-1995, Discussion paper, IFC The World Bank, Washington D.C. Carkovic M. and Levine R.,(2002) Does Foreign Direct investment Accelerate Economic Growth?, University of Minnesota Dunning H.J. and Narula Rajeneesh (1999), “Foreign direct investment and governments” A catalysts for economic restructuring, Roulledge, Landon and New York.

Investment for development, Investment Performance and Perceptions Report (2002), Consumer Unity and Trust Society DFID, UK Investment for development, Investment Policy Country Report (2002) , Consumer Unity and Trust Society DFID, UK

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Kohpaiboon K. Foreign Trade Regime and FDI-Growth Nexus : A Case Study of Thailand, Ph D Scholar, Division of Economics, Research School of Pacific and Asian Studies, Australian National University Manoj Pant,( 2002), Brainstorming Meeting on Competition and Investment International Working Group on the Doha Agenda, CUTS , Uganda Shujiro Urata ( 1998) Japanese foreign direct investment in Asia: Its impact on export expantion and technology acquisition of the host economies, Waseda University and Japan Center for Economic research.

Tadesse B. and Avenue W.M, The FDI-Trade Relationship: Are Developing Countries Different?, Western Michigan University, Kalamazoo.

World Investment Report (2002), Transnational Corporation and Export Competitiveness, UNTACD: New York and Geneva

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Table 1: Inward and outward FDI stocks as a percentage of gross domestic product Country World

1980 Inward 6.0 Outward 5.4 Developed Inward 4.8 Countries Outward 6.2 Developing Inward 10.2 Countries Outward 1.3 Source: World Investment Report 2002.

1985 7.8 6.2 6.2 7.2 13.9 1.7

1990 9.2 8.4 8.1 9.6 13.0 2.8

1995 10.0 9.9 8.9 11.3 15.3 5.1

2000 20.0 19.6 17.1 22.1 30.9 11.9

Table 2: Inward and outward FDI stocks as a percentage of gross domestic product in the selected regions Region 1980 1985 1990 1995 2000 European Union Inward 6.1 9.2 10.6 12.9 30.3 Outward 6.1 10.2 11.6 15.0 40.1 Western Europe Inward 6.2 9.3 10.8 13.1 30.2 Outward 6.4 10.5 12.1 16.1 41.4 Central and Outward 0.2 1.7 5.4 18.9 Eastern Europe Inward 0.4 0.9 2.7 North America Inward 4.5 5.5 8.0 8.3 13.5 Outward 7.9 6.2 8.1 10.3 14.5 Latin America Inward 6.5 11.0 10.4 11.8 30.9 Outward 1.2 1.9 1.8 3.0 6.2 South America Inward 5.9 8.9 8.5 8.6 30.0 Outward 1.5 1.8 1.5 1.9 5.0 Africa Inward 8.8 10.3 10.7 15.6 25.5 Outward 2.2 4.1 5.9 7.9 9.2 The Pacific Outward 22.7 24.8 29.0 26.9 37.6 Inward 0.3 1.0 2.1 7.3 14.6 Asia Inward 13.0 16.3 14.8 17.0 31.6 Outward 0.9 1.0 2.7 5.7 15.2 Source: World Investment Report 2002.

Table 3: Inward and outward FDI stocks as a percentage of gross domestic product in the selected countries in Asia Country 1980 1985 1990 1995 2000 China Inward 3.1 3.4 7.0 19.6 32.3 Outward 0.7 2.3 2.4 Hong Kong Inward 436.2 372.1 198.1 125.0 263.8 Outward 0.5 6.7 15.9 56.6 224.9 Thailand Inward 3.0 5.1 9.6 10.4 20.0 Outward 0.5 1.3 2.0 Indonesia Inward 13.2 28.2 34.0 25.0 39.6 Outward 0.1 0.1 0.6 1.5 Pakistan Inward 2.9 3.5 4.8 9.1 11.2 Outward 0.2 0.4 0.6 0.7 0.8 Singapore Inward 52.9 73.6 77.9 71.5 103.8 Outward 31.7 24.8 21.3 42.0 57.5 India Inward 0.6 0.5 0.5 1.6 4.1 Outward 0.1 0.1 0.1 0.1 0.3 Sri Lanka Inward 5.7 8.6 8.5 10.0 15.0 Outward 0.1 0.3 0.5 Source: World Investment Report 2001.

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Table 4: Foreign direct investment and total investment of Sri Lanka Year Total investment Foreign direct investment (Rs. Million) (Rs. Million) 1990 71455 1294 1991 85156 2634 1992 103239 5315 1993 127675 9107 1994 156510 7815 1995 171825 2931 1996 186264 6606 1997 217103 25504 1998 255889 12379 1999 301823 12449 2000 352632 13326 2001 309684 14129 2002 337782 16489 Source: Economic and Social Statistics of Sri Lanka Figure 1: Trend of the Variables GDP Rs. Million

Trend of GDP

1000000 900000 800000 700000 600000 500000 400000 300000 200000 100000 0

Ye ar

FDI Rs. Million

Trend of FDI

30000 25000 20000 15000 10000 5000 0 -5000

Year

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Domestic Investment 400000 Rs.Million

Trend of Domestic Investment

350000 300000 250000 200000 150000 100000 50000 0

Year T rade Index 1 .4

Trend of the Trade Index

1 .2 1 0 .8

0 .6 0 .4 0 .2 0

Year

Table 5: Summary of DF and ADF Unit Root Test Result Series DF Test ADF Test Computed t- stat of Computed t- stat of GDPt 0.185 -0.401 FDIt -6.637** -2.431 DINt -1.101 -1.182 TPt 0.788 -0.525 GDPt -5.434** -2.973** FDIt -13.172** -6.953** DINt -6.469** -4.018** TPt -4.293** -3.886** Notes: ** denotes rejection of null hypothesis at a 5 % level of significance.

Augmented Lags 1 1 1 1 1 1 2 1

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Table 6: Test of cointegration among variables A constant within the cointegrating No constant in the cointegrating Vectors Vectors R T Critical D T Critical Values Values r=0 91.664 75.74 R 74.111 68.68 r<1 51.679 53.42 F* 34.331 47.21 r<2 18.030 34.80 F 8.352 29.38 r<3 8.299 19.99 F 0.004 3.84

D R F F F

The number of cointegrating vectors (r) is tested using the trace test with the constant within and outside the cointegrating vectors. The test statistic (T) is the calculated trace test, associated with the number of cointegrating vectors. The critical values are taken under 5 % level. The column labeled â&#x20AC;&#x2DC;Dâ&#x20AC;&#x2122; gives our decision to reject ( R ) or fail to reject (F) , at a 5 per cent level of significance, the null hypothesis of the number of cointegrating vectors. The symbol * indicates the stopping point.

Table 7: Error Correction Model representation Dependent Variable Independent GDPt FDIt DINt GDPt

3.923 (4.829) *

GDPt-1

0.119 (0.561)

-1.875 (-1..575)

GDPt-2

-0.137 (-0.798)

1.334 (1.361)

FDIt

0.115 (0.482)

FDIt-1

0.616 (-4.180) *

0.640 (4.800) *

0.368 (1.835)

-0.311 (-1.600)

-0.213 (-1.267) 0.169 (43.697) *

-0.046 (-1.321)

0.526 (2.852)

-0.096 (-3.131) *

FDIt-2

0.001 (0.034)

-0.029 (-0.199)

0.005 (-3.131) *

DINt

0.622 (-4.180) *

5.805 (43.697) *

DINt-1

0.276 (1.368)

-3.006 (-2.804)

0.549 (3.062) *

DINt-2

-0.003 (-0.019)

0.170 (0.186)

-0.033 (-0.213)

0.221 (1.382) -0.163 (-355.390) * 0.086 (2.884) -0.005(-0.226) 0.951 (45.312) *

TPt

0.705 (4.800) *

6.108 (-355.390) *

1.037 (45.311) *

TPt-1

-0.285 (-1.338)

3.232 (2.876)

-0.593 (-3.156) *

TPt-2

TPt

-0.496(-2.907) 0.032 (-2.836) 0.533 (2.907)

0.003 (0.022)

-0.168 (-0.187)

0.033 (0.214)

-0.031 (-0.215)

Ut-1

-0.121 (3.489)*

-0.001 (-0.106)

-0.300 (-2.962) *

0.201(-3.063) *

R2

0.508

0.40

0.510

0.321

DW

1.971

1.966

1.973

1.966

Notes: * Denotes rejection of null hypothesis at least than 5 % level of significance Table 8: Granger Type Causality Direction FDI to GDP GDP to FDI DIN to GDP GDP to DIN TP to GDP GDP to TP

F Value 0.722 12.062* 5.228* 4.988* 7.052* 4.932*

Critical Value 3.23 3.23 2.84 2.84 3.23 3.23

Notes: F values are calculated by using different set of variables. Critical values are different due to the different lag length. * Denotes rejection of null hypothesis at least than 5 % level of significance.

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Table 9: Perception towards FDI FDI or Foreign Investor

Strong positive 11 8 12 18 17 12

Positive impact 18 19 19 14 11 17

No impact 3 2 8 5 9 10

Negative impact 15 12 5 6 8 9

Strong Negative 1 5 4 5 2 3

Index * 0.479 0.283 0.625 0.708 0.702 0.509

A valuable source of foreign capital Increases access to World market FDI helps to enhance export FDI helps to reduce import Do care about civil society Investors do care about employees Source: Survey Data * Index is formed by taking weighted average of number of response by assuming following numerical values: strong positive impact = 2, positive impact = 1, no effect = 0, negative effect = -1, strong negative impact = -2, . By construction, index ranges from -2 to +2. A positive value implies positive impact, and a negative value implies negative impact.

Table 10: Perception towards FDI Item (increase) Strong positive Quality of Jobs 14 Quantity of jobs 12 Source of new technology 9 Competition in the market 8 Quality of products 11 Prices of products 8 Effect on growth 12 Source: Survey Data Table 11: Constraint to the FDI flows Item (increase) Strong positive Regulatory barriers 15 Political instability 12 Policy instability 22 Lack of transparency 26 Lack of infrastructures 18 poor low and order situation 16 Lack of human capital 15

Positive impact 15 14 18 16 13 8 14

No impact 4 2 4 5 9 12 6

Negative impact 13 13 12 6 8 6 9

Strong Negative 1 6 6 4 5 7 7

Positive impact 17 19 11 18 16 21 19

No impact 13 7 8 4 9 8 10

Negative impact 8 7 4 3 7 4 4

Strong Negative 2 6 5 6 4 5 8

Index* 0.595 0.333 0.245 0.717 0.369 -0.044 0.312

Index* 0.636 0.470 0.820 0.964 0.685 0.722 0.517

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