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Modeling Effects of Foreign direct Investment

on Macroeconomic Variables in SudanProfessor Dr. Issam A.W. Mohamed and Magdy Alamin

Over the past two decades, many countries around the world have experienced substantialgrowth in their economies, driven by inflow of the foreign capital especially in the form offoreign direct investment (FDI). The share of net FDI in world GDP has grown five-foldthrough recent years, making the impact and consequences of FDI on economic growth asubject of ever-growing interest. This paper attempts to make a contribution in this context,

by analyzing the existence and nature of impact of foreign direct investment on economicgrowth, if any, in Sudan during the period (1982-2007), also to investigate how to attract therequired flow of FDI that is enough to fill saving-investment gap to sustain economic growth.

With the hypothesis that sustained efforts to promote political and macroeconomic stabilityand implement essential structural reforms, and the policies of aligning some emergingmarkets has encouraged the inflow of FDI to Sudan in different sectors.The important findings are that FDI helps to promote economic growth in the Sudan, i.e.there is clear evidence of a one-way causality from FDI to economic growth for the whole

period, in the sense that FDI have a significantpositive effect on the GDP Growth, for itpromotes exports and so balance of payments, provision of job opportunities and enhancingthe quality of labor and production. However, the study finds that it is difficult to constructaccurate and comparable measures of FDI data by sector for the Sudan as in most developingcountries over several decades. Moreover, the tendency of major sources to present FDI datain broad aggregates limits the study of the effects or impacts. So the main recommendationsare that: the investment climate in the country must be improved through appropriate

measures to keep pace with global economics developments, Government needed to establisha proper investment map serving the objectives of economic growth and developmentsconsists of all data that may needed by foreign investors, supported by the necessaryinfrastructures. Government must develop and improve the periodic statistics concerninginvestment, foreign capital flows and sources of capital. Future researches in this area shouldanalyze the causal link in a multivariate VAR analysis to account for other vital determinantsof FDI and GDP growth. This is likely to improve our results and may provide moreconclusions.

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Modeling Effects of Foreign direct Investment

on Macroeconomic Variables in SudanProfessor Dr. Issam A.W. Mohamed1 and Magdy Alamin

1. Abstract........................................................................................................................... 28

2. Introduction..................................................................................................................... 29

3. Regression Variables....................................................................................................... 29

4. Trade Variables. .............................................................................................................. 30

5. Inflation Rate .................................................................................................................. 31

6. Empirical Methodology................................................................................................... 31

7. Testing for Cointegration................................................................................................. 32

8. Time Series, Economic Growth Rate and FDI in Sudan.... ....................... ......... .............. . 34

9. Unit Root Test................................................................................................................. 35

10. Cointegration test .......................................................................................................... 36

11. Granger Causality Test .................................................................................................. 36

12. Conclusions................................................................................................................... 38

13. References..................................................................................................................... 38

1.AbstractOver the past two decades, many countries around the world have experienced substantialgrowth in their economies, driven by inflow of the foreign capital especially in the form offoreign direct investment (FDI). The share of net FDI in world GDP has grown five-foldthrough recent years, making the impact and consequences of FDI on economic growth asubject of ever-growing interest. This paper attempts to make a contribution in this context,

by analyzing the existence and nature of impact of foreign direct investment on economicgrowth, if any, in Sudan during the period (1982-2007), also to investigate how to attract therequired flow of FDI that is enough to fill saving-investment gap to sustain economic growth.With the hypothesis that sustained efforts to promote political and macroeconomic stabilityand implement essential structural reforms, and the policies of aligning some emergingmarkets has encouraged the inflow of FDI to Sudan in different sectors.The important findings are that FDI helps to promote economic growth in the Sudan, i.e.there is clear evidence of a one-way causality from FDI to economic growth for the whole

period, in the sense that FDI have a significantpositive effect on the GDP Growth, for it

1Professor of Economics, Alneelain University, Khartoum-Sudan. P.O. Box 12910-11111.

issamawmohamed@hotmail.com

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promotes exports and so balance of payments, provision of job opportunities and enhancingthe quality of labor and production. However, the study finds that it is difficult to constructaccurate and comparable measures of FDI data by sector for the Sudan as in most developingcountries over several decades. Moreover, the tendency of major sources to present FDI datain broad aggregates limits the study of the effects or impacts. So the main recommendationsare that: the investment climate in the country must be improved through appropriate

measures to keep pace with global economics developments, the government needed toestablish a proper investment map serving the objectives of economic growth anddevelopments consists of all data that is required by foreign investors supported by thenecessary infrastructures. Government must develop and improve the periodic statisticsconcerning investment, foreign capital flows and sources of capital. Future researches in thisarea should analyze the causal link in a multivariate VAR analysis to account for other vitaldeterminants of FDI and GDP growth. This is likely to improve our results and may providemore conclusions.

2.IntroductionMost developing countries creating a suitable climate to attract foreign direct investment

based on the assumption that foreign direct investment contributes directly to improving theeconomic situation in the receiving or host countries. It is obvious for our review of the flowof direct investment to the Sudan in previous chapter of this research that there is aconsiderable leap achieved in attracting foreign investment reflected in the performance ofthe economic situation. Through this we are trying to identify the impact of the flow offoreign direct investment on the economic growth in the Sudan, specifically trying to identifythe role of foreign direct investment in technology transfer, employment, improve the balanceof payments and other indicators of economic performance. That is rather than specifying afew particular explanatory variables to describe the impact of the FDI on economic growth inSudan, which means making ad hoc assumptions about their behavioral link to each other andto economic growth, the study will estimate unrestricted model incorporating major types of

policy and non-policy variables suggested by the economic theory as important to economic

growth. Then we eliminate the least significant variables to reach the appropriatespecification i.e., to allow the data to select the most appropriate model structure.The model will include the following types of variables: monetary, trade, fiscal andexogenous factors. The model will contain variables which are routinely used in growthregression, in particular, investment (capital formation) and human capital (population). Thesources of data are the IMF, World Bank, Sudans Ministry of Finance and the Central Bankof Sudan. We will describe different policy and non-policy variable proxies that we will usein the regression. The selection for these various proxies is guided by previous finding ofempirical work on growth theory as well as the theoretical advances in this field.

3.Regression VariablesThose are the GDP growth rate as a dependent variable of the regression. The data on the per

capita GDP is not complete in some years. Then Gross Capital formation and investment asone of the few variables that survived as robust and significantly related to economic growthin thousand of regressions (Levine and Renelt, 1992). While investment-growth relationshipwas central to most growth theories, different studies emphasize the importance of differenttypes of investment. In particular, private investment was shown to be more productive than

public investment (Khan 1996)2. However, it is reasonable to assume that an expansion in the

2Mathieson, A. The Implications of International Capital Flows for Macroeconomic and Financial Policies:

Introduction.International Journal of Finance and Economics, July 1996.

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level of public goods of physical infrastructure; e.g., transport and communication will beassociated with greater economic efficiency. Studies that emphasis productive publicexpenditure, such as health and education included Diamond (1989), Otani and Villanuenva(1990) and Barro (1991). Those that focus on fixed investment are Diamond (1989),Orsmond (1990) and Barro (1991). In this paper we will use the Gross Capital formation(GPF) as a proxy for investment levels. However, the interpretation of the GPF as a variable

influencing growth performance could be problematic. On the one hand, it is highlyassociated with trade and institutional variables. In the case of Sudan, country with weakgovernment institutions, these factors are expected to discourage investment. The argumentfor institution affecting investment and economic growth is controversial, e.g., Russia andChina are countries with high growth and non-market oriented institutions.The encouragement of FDI remains at the forefront of policy outcomes for both developedand developing countries largely because of the economic benefits perceived from this formof investment. It has been extensively argued that government policy should be directed tothe removal of capital barriers and other regulatory restrictions that may impede FDI toensure that benefits to economic growth are maximized. In particular in the recent empiricalliterature, greater attention has been paid to the legal and institutional as well as economicsettings that may facilitate FDI in promoting growth outcomes. So the study provides a new

insight into these issues in Sudan by investigating the impact of FDI using a wide assortmentof variables, which reveal some important findings. For example, the Sudanese governmenthas taken several measures to create an investment climate through conducting severalamendments to the investment acts and other laws in order to create conducive legal and legelenvironment for investment, including a number of financial incentives and inducements.Although the laws concerning investment, especially to attract foreign capital is moredistinctive laws in the area, but there is some weaknesses related to public culture concerningthe implementation of these law, some are related to the fluctuations in the political systemled to the continuous change in the economic policy of investment. Some are related to thelack of the investment map which shows the activities that need to invest in.The Sudanese government established the Ministry for investment in the year 2002, then theministry has adopted a unified force in the granting of licenses for investment projects, a stepthat has worked to simplify the procedures required to obtain certification for investment

projects, but still less than the required level. The government has adopted various means topromote the opportunities available for investment included those means holding conferencesand forums for businessmen and embassies to provide information on investmentopportunities available. It has also taken serious steps to establish security and politicalstability, through the signing of the Comprehensive Peace Agreement. On the other hand, thecorrelation between investment and growth does not mean causation (King and Levine,1994;

3Kenny and Williams, 2001)

4and it might be the case that both investment and growth

are caused by a third factor (e.g., favorable terms of trade). Nevertheless, in this study we willassume that high levels of investment will bring about high levels of growth since the study isnot purely a test for the growth behavior but rather economic growth is taken as a policy

performance indicator.4.Trade VariablesTrade is one of the few variables that show robust relation with growth in most of theempirical work and when the trade variables were not robust it was suggested that theimportance of trade probably work through investment (rather than through resource

3RG King, R Levine: Capital Fundamentalism, and Economic Development, and Economic Growth- Carnegie

Rochester Conference Series on public policy, 1994.4

C Kenney, D Williams, What do we Know about Economic growth. World Development, volume 29, 1, 2001.

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allocation). Knight, Loayza and Villanueva (1993) assumed that trade influences growth andtechnical progress in two ways: through technological transfers, and through foreignexchange, which enables countries to purchase technologically superior capital goods. Theyfound that trade openness, has significantly positive impact on growth.The study uses the sum of the exports and the imports as percentage of GDP =(X+M)/GDP)% as a proxy for the trade policy measuring the degree of openness in the

economy. This will capture both imports and exports policies. On the export side,government has repeatedly switched between self-sufficiency policies and export growth

promoting policies. On the import side, the government followed extreme policies as such astotal banning for imports. Attention should be drawn to the large gap between imports andexports making the former five times as large as the later in some years. Consequently, theselected proxy (X+M)/GDP) could be dominated by the imports behavior. However, this ismainly attributed to the government policies distortion. More dynamic variables such asexport growth could be used as a proxy of government trade policy. However, the variabledoes not reflect the government policy in the 1970s and 1980s which was, basically,concerned about imports controlling than about exports promoting.

5.Inflation Rate

Although it is agreed between economists that countries with high inflation rates shouldadopt policies that lower inflation in order to promote growth, the inability to find simplecross-country regressions supporting this contention is, according to Levine and Zervos(1993)

5, both surprising and troubling. However, the evidence suggests that mild inflation,

up to 5 percent to 8 percent, is positively beneficial to inflation. After that, the effects of highinflation can be seriously damaging (Thirlwall, 1999)

6. Unfortunately, the average annual

inflation in Sudan has never been less than 15 percent since 1973. The lowest rate was 12percent in the year 2000. Consequently, we would expect negative relation between inflationand economic growth in Sudan. Inflation can be perceived as an indicator for how much thegovernment has resorted to taxing domestic financial assets through money creation(sometimes it is called inflation tax policy). Inflation could also be perceived as an indicatorof macroeconomic instability. In both cases, De Gregorio (1992, 1993a)

7finds evidence of a

negative relation between inflation and growth. However, Bruno and Easterly (1995)8

wereunable to find a long run relationship between inflation and growth.

6.Empirical MethodologyThe econometric strategy of the study starts with simple time series analysis for the FDIimpact on economic growth in Sudan. This examines the stability of the long run growth inSudan. If for example, the growth is found to fluctuate around a constant mean this couldimply that either the inflow of the FDI has failed to produce large changes in the economicgrowth or the persistent movement in these variables is offsetting. A formal test by DF andADF will follow test for co-integration under different assumptions will be conducted.The study uses quantitative techniques consisting of both econometrics model and statisticalmethods. The approach of Granger causality, and simple regression will follow to test

relation and correlation between FDI and economic growth. The individual time series shouldbe non-stationary for inclusion in the Granger and simple regression analysis.

5 Levine, R. and Zervos, S. Inflation and Growth, in search of stable relationship. American EconomicAssociation, 1993.6

Anthony P. Thirlwall; Inflation and Savings Ratio Across Countries; Journal of Development Studies,University of Kent at Canterbury Princeton University, USA, 1999.7

De Gregorio, Jose, 1992. "The effects of inflation on economic growth: Lessons from Latin America,"European Economic Review, Elsevier, vol. 36(2-3), pages 417-425.8

M Bruno, W Easterly; Inflation and Growth Federal Reserve of ST. Louis, 1995.

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Cointegration procedure requires time series in the system to be non-stationary in their level.Similarly, it is imperative that all time series in the co integrating equation have the sameorder of integration. Consequently, the study first ascertained the time series properties of allthe variables. The study uses the Augmented Dickey Fuller (ADF) test (Dickey and Fuller1981)9 to test for unit roots. In order to model the variable in a manner that captures theinherent characteristics of its time-series. As such, a unit-root test is often necessary before

empirical studies. Based on the result by Dickey and Fuller(1979)10. The simple form of theDF test could be expressed as:

(1)1 ttt yy

DF test equation with a constant:

(2)1 ttt yy DF test equation with a constant and trend:

(3)1 tttt ytrendy

Where; t the variable under study t random variable, ),0(~2t The null

hypothesis is that 0 and alternative hypothesis 1 .The Augmented Dickey and Fuller(ADF) test that we use in the study is as shown below:

yt = + t +(-1) yt-1 + i yt-1 + twhere = 1- L yt is a macroeconomic variable such as GDP or export; t is a trend variable; atis a white noise term. The null hypothesis is H0 =1 and yt is said to possess the unit root

property if one fails to reject H0.

7.Testing for CointegrationGiven a group of non-stationary series, we may be interested in determining whether theseries are cointegrated, and if they are, in identifying the cointegrating (long-run equilibrium)relationships. EViews implements VAR-based cointegration tests using the methodologydeveloped by Johansen (1991, 1995). Johansens method is to test the restrictions imposed bycointegration on the unrestricted VAR involving the series.

Johansens Cointegration Test is applied as follows,Consider a VAR of order p:

ttptptt BxyAyAy 11 Where yt is a k-vector of non-stationary I (1) variables, xt is a d vector of deterministicvariables, and t is a vector of innovations. We can rewrite the VAR as:

1

11

p

ittititt

Bxyyy

Where

p

i

p

ijjii AIA

1 1

;

Grangers representation theorem asserts that if the coefficient matrix has reduced rank r

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error correction model. Johansens method is to estimate the matrix in an unrestricted form,then test whether we can reject the restrictions implied by the reduced rank of . Johansen

proposes two different likelihood ratio tests of the significance of these canonical correlationsand thereby the reduced rank of the matrix: the trace test and maximum eigenvalue test,shown respectively.

)1ln(

^

1i

n

ritrace TJ

)1ln( ^ 1max rTJ

Here T is the sample size and^

i

is the ith is the largest canonical correlation. The trace testtests the null hypothesis of r cointegrating vectors against the alternative hypothesis of ncointegrating vectors. The maximum eigenvalue test, on the other hand, tests the nullhypothesis of r cointegrating vectors against the alternative hypothesis of r + 1 cointegratingvectors. Neither of these test statistics follows a chi square distribution in general; asymptoticcritical values can be found in Johansen and Juselius (1990) and are also given by mosteconometric software packages. Since the critical values used for the maximum eigenvalueand trace test statistics are based on a pure unit-root assumption, they will no longer becorrect when the variables in the system are near-unit-root processes. Thus, the real questionis how sensitive Johansens procedures are to deviations from the pure-unit root assumption.The Granger causality test is used in time series analysis to examine the direction of causality

between two economic series has been one of the main subjects of many econometrics studiesfor the past three decades. Recent studies have shown that the conventional F-test fordetermining joint significance of regression-derived parameters, used as a test of causality, isnot valid if the variables are non-stationary and the test statistic does not have a standarddistribution (Frimpong, 2007)11.Generally, causality between two economic variables has been tested using Granger and Simscausality test (see Granger 1969 and Sims 1972). Within a bivariate context, the Granger-typetest states that if a variable x Granger causes variable y, the mean square error (MSE) of aforecast of y based on the past values of both variables is lower than that of a forecast that

uses only past values of y. This Granger test is implemented by running the followingregression: yt = + t yt-1 + yt x t-1 + tand testing the joint hypothesis H0: y1 = y2 = yp = 0 against H1: y1 y2 yp 0 Grangercausality from the y variable to the coincident variable x is established if the null hypothesisof the asymptotic chi-square (x) test is rejected. A significant test statistic indicates that the xvariable has predictive value for forecasting movements in y over and above the informationcontained in the latters past. Following the criticisms in recent studies (Kholdy, 1995)

12of

the traditional assumption of a one-way causal link from FDI to growth, new studies havealso considered the possibility of a two-way (bi-directional) or non-existent causality amongvariables of interest. In other words, not only FDI can Granger cause GDP growth (witheither positive or negative impacts), but GDP growth can also affect the inflow of FDI or

there could be no causal link. From the numerous existing studies, the causal link betweenFDI and economic growth as an empirical question seems to be dependent upon the set ofconditions in the specific host country economy. Chowdhury and Mavrotas (2005)

13have

suggested that individual country studies be done to examine the causal links between FDI

11Frimpong et al., Bivariate causality analysis between FDI inflows and economic growth in Ghana, Munich

Personal RePEcArchivePaper No. 351. 2007.12

Kholdy (1995) Causality Between Foreign Investment and Spillover Efficiency. Applied Economics.13

Chowdhury, A. and Mavrotas, G. (2005): FDI and Growth: A Causal Relationship, UNU-WIDER ResearchPaper No. 2005/25, UNU-WIDER.

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and economic growth since it is country specific. The relation between two variables, or thesimple regression is used for testing hypotheses about the relation between a dependentvariable Y and explanatory variable X. and for prediction. The regression takes the form:

X t10 tty (8)

where The error term with zero mean and constant variance.To look for direct effect of FDI on economic growth we estimate the following equation:GROWTHi = 0 + 1 INITIAL GDPi + 2 FDIi + 3 CONTROLSi + viCONTROL variables may include inflation, trade volume, population growth, institutionalquality or government consumption.

8.Time Series, Economic Growth Rate and FDI in SudanThe study will start the analysis with some basic descriptive statistics and graphic

presentation. This will include looking at the mean, and the standard error, shift in the mean,and simple normality test. Then, we use formal test to check whether the process can bedescribed as a random walk or not by employing formal tests as DF, ADF and spectrumanalysis. The following shows that the mean values of the growth rate in Sudan fluctuatedfrom 1.7% during 1982-1989 to 7.3% during 1999-2007. The mean value was about 4.9

percent for the whole period 1982-2007, which is biased by low growth rate in eighties. The

mean low rates during the execution of the SAPS in 1980,s recording a figure of 1.7 percentcompared to 7.3 during the oil era. For example there is a huge increase during the last fouryears (2004-2007), which are 9.1%, 8.3%, 9.3% and 10.2% respectively. They are consideredamong highest rates in the world. When we look at the standard deviations the deviations inthe 1980s indicate large level of instability in economic growth process for that period.Statistics of GDP Growth and FDI in Sudan (1960-2007)

GDP growth FDIPeriod

Simple Mean St. Dv. Mean St. Dv.

Economic Era

1982-1989 1.7 7.4 91.7 77.5 SAPS

1990-1998 5.6 1.9 116.8 214.7 Economic strategy

1999-2007 7.3 1.4 1325.3 1127.3 Oil Era

1982-2007 4.9 4.8 498.5 851.7 Whole PeriodFigure (1) GDP Growth rateFigure (1) shows the GDPgrowth rate for the period1982-2007. From this figure, itis clear that the growth processin Sudan has been fluctuatingall the time with increasingattitude. To sum up, the aboveresults show that the objectiveof raising the GDP growth hasnot been achieved despite the

introduction of the SAPS in1980/1981. Moreover, thelevels of the standarddeviations in 1980s and thefigure, suggest that the SAPS failed to produce more stability in the economy. When wecompare the SAPS in the 1990s with the SAPS in the 1980s we find high and stable growthin the former. Unfortunately, the fairly large standard deviations will undermine our ability todraw strong conclusions about the growth process in Sudan. Consequently, formal tests will

growth

0

2

4

6

8

10

12

14

198219851988199119941997200020032006

growth

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be provided to check whether or not the growth process in Sudan has been fluctuating arounda constant mean.FDI is sharply and steadily increased since 1999, due to starting production and exporting oil,and huge amount of foreign capital in the form of FDI invested in this sector. During the

period 2001- 2004, the foreign direct investment (FDI) inflow to Sudan almost tripled from$574 million in 2001 to $1.5 billion in 2004, according to 2005 World Investment Report

issued by the United Nations Conference on Trade and Development. Among Arab countries,Sudan came in third in attracting foreign direct investments. The performance of theSudanese economy in attracting investments is truly impressive as the country jumped fromthe 62nd place in 2000 to the 18th in 2004 on the UNCTADs Inward FDI Performance Index.From figure (2) it is obvious that till the mid 1997 FDI was less than 500 million dollar, butsince 1998 it began to increase with low rate, till the year 2004, from which it began to risesharply and steadily. Accordingly, it is seemingly that there is consistency in the trend andattitude of GDP growth rate and trend of increase in FDI.

9.Unit Root TestThe study uses the Augmented Dickey Fuller (ADF) test (Dickey and Fuller 1981) to test forunit roots. In order to model the variable in a manner that captures the inherent characteristics

of its time-series. Blough (1992)

14

discusses the trade-off between the size and power of unitroot tests, namely that they must have either a high probability of falsely rejecting the null ofnon-stationarity when the DGP is a nearly stationary process, or low power against astationary alternative. This is because infinite samples it has been found that some unit root

processes display behavior closer to stationary white noise than to a non-stationary randomwalk, while some trend stationary processes behave more like random walks. Thus, as

pointed out by Blough (1992), unit root tests with high power against any stationaryalternative will have a high probability of a false rejection of the unit root when applied tonear stationary processes. These problems, occurring when there is near equivalence of

Nonstationary and stationary processes in finite samples are partly due to using critical valuesbased on the DF asymptotic distribution, bearing in mind all these potential problems intesting for unit roots. The following table depicts the unit root test results.

Unit root testCritical Values*

Order of integration10%5%1%ADFVariables

Gdp ~I(2)-2.67-2.67-2.67-3.14487136GdpFDI ~I(1)-2.67-2.67-2.67-4.45015204FDI

Export ~I(2)-2.6756-2.6756-2.6756-3.95632658ExportImport ~I(1)-2.67-2.67-2.67-6.10832785Import

Inflation ~I(1)-2.67-2.67-2.67-3.37621052Inflation

M2~I(1)-2.67-2.67-2.67-5.79234125M2Openness ~I(2)-2.6756-2.6756-2.6756-2.98443007Openness

Term of trade ~I(1)-2.67-2.67-2.67-5.36225919Term or tradePopulation ~I(2)-2.6756-2.6756-2.6756-3.49870401Population

Exchange ~I(2)-2.6756-2.6756-2.6756-3.69751239Exchange

Growth ~I(1)-2.67-2.67-2.67-2.85907571GrowthCapital ~I(1)-2.67-2.67-2.67-7.4319049Capital

*MacKinnon critical values for rejection of hypothesis of a unit root.

14Blough, N. Near Observational Equivalence and Theoretical size Problems with Unit Root Tests, Cambridge

University Press, 1992.

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The computed ADF test-statistics to the all variables is non stationary in the level, but thevariables FDI, Import, Inflation, M2 Terms of Trade, Growth and Capital Formation arestationary in the first difference. The variables GDP, Exports, Openness, Population andExchange Rate are stationary in the second difference. The foreign reserve and oil price arenon stationary in the level but they are in the first difference. These results support the

previous descriptive statistics finding that either economic policy in Sudan has failed to bring

about large changes in the GDP growth rate or what has been happening was offsetting.10. Cointegration testWe conduct Cointegration tests by employing Engle and Granger (1987)15 approach as wellas Johansens (1988)

16approach which allows for Cointegration in a system of equations.

Cointegration test (Growth FDI Exchange GDP Population Export)

Eigen value LikelihoodRatio

5%CriticalValue

1%CriticalValue

HypothesizedNo. of CE(s)

0.972917 208.3167 94.15 103.18 None **

0.908567 125.3135 68.52 76.07 At most 1 **

0.807706 70.2941 47.21 54.46 At most 2 **

0.553555 32.37333 29.68 35.65 At most 3 *0.31166 13.82521 15.41 20.04 At most 4

0.203576 5.235349 3.76 6.65 At most 5 *

*(**) denotes rejection of the hypothesis at 5%(1%) significance level.L.R. test indicates 5 cointegrating equation(s) at 5% significance level. This implies that theresiduals are stationary and hence there is Cointegration between the variables i.e., there islong run relationship between the variables.

11. Granger Causality TestThe use of Granger causality tests to trace the direction of causality between two economicvariables is not uncommon in empirical work. The direction of causality has generally beentested using either the Granger or Sims tests (Granger 1969)17. A causality test could provide

insight on whether a single or simultaneous equation model is appropriate for FDI-growthrelationship. The fact is that FDI inflow volume and economic growth are in tandem revealednothing about the causal direction. Therefore, the issues of causality between FDI andeconomic growth need to be investigated.These tests are based on null hypotheses formulated as zero restrictions on the coefficients ofthe lags of a subset of the variables. However, such tests are grounded in asymptotic theory;yet, it must be borne in mind that asymptotic theory is only valid for stationary variables, thusif a series is known to be non-stationary, I(1), then such inferences can only be made if theVAR is estimated in first differences, and therefore stationary. This causes problems becausethe unit root tests to test the null hypothesis of stationarity have low power against thealternative hypothesis of trend stationarity. Similarly, the tests for cointegrating rank inJohansens tests are sensitive to the values of trend and constant terms in finite samples and

thus not very reliable for typical time series sample sizes. In other words, it is possible thatincorrect inferences could be made about causality simply due to the sensitivity ofstationarity or Cointegration tests. The study uses the methodology of Pair wise GrangerCausality Tests for causality in the FDI-Growth relationship. Pair wise Granger Causality

15 R. Engel, C. Granger. Cointegration and Error Correction: Representation, Estimation and Testing-Econometrica. 1987.16 Soren, J. Role of the Constant and Linear Terms in Cointegration Analysis of Nonstationary Variables, 1994.17

Granger. Investigating Causal Relations by Econometric Models and Cross-spectral Methods, Econometrica.Vol. 37, No. 3, 1969.

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Tests avoid the problems outlined above by ignoring any possible non-stationarity orCointegration between series when testing for causality, thereby minimizing the risksassociated with possibly wrongly identifying the orders of integration of the series, or the

presence of Cointegration, and minimizes the distortion of the tests sizes as a result of pre-testing (Mavrotas and Kelly 2001)18.Granger causality Test

Obs. F-statistic Prob.FDI does not follow Granger Cause GROWTH23 4.14159 0.03314

GROWTH does follow not Granger Cause FDI 0.41215 0.66832

The Granger-causality (Granger, 1969) between FDI and growth in at least one direction asone variable can help determine the other. Overall, we find clear evidence of a one-waycausality from FDI to economic growth for the whole period. However there is generally noevidence of causal from economic growth to foreign direct investment. The fact that Growth-driven FDI was not identified during the period of the study, which clearly shows thateconomic growth is just a necessary, but not a sufficient condition to attract FDI inflows. It istherefore very important to pay increased attention to the overall role and then quality ofgrowth as a vital determinant of FDI along with the quality of human capital, infrastructure,institutions, governance, legal framework, ICT, tax systems, etc., in Sudan, in consequence,the provision of an enabling environment that captures the above listed parameters would

provide a better incentive to attract FDI inflows than the usual piecemeal approaches such aspetitioning via investment tours, organization of trade-expos and myriad special initiativesaimed at attracting specific investments into the country. Sudan economy has, however,

begun to show recovery symptoms. Sudan's GDP grew by 6% in 1999 and inflation droppedsharply to 16% after peaking at 166% in 1996. By 2004 the inflation rate was down to 8.8%.The GDP real growth rate for 2004 was 5.9%. The growth is attributed to oil, which has

boosted state income since exports began in mid-1999, and to the new program of IMFreforms started in 1997. Nevertheless, oil exports that now account for about some 70% ofexport earnings (77% in the first quarter of 2001), are unlikely to boost the economysignificantly unless the civil war can be ended. GDP growth, driven by developments in the

oil sector, is expected to remain strong in the next few years. Furthermore, there are risks toentering the international market as control of natural resources is one of the key issues in thecivil war. These findings suggest Sudans capacity to progress on economic growth anddevelopment will depend on its performance in attracting foreign capital. Sudans outwardlooking development strategy should include FDI as an essential part in addition to export.Regression Analysis: Dependent Variable: DLOG (GROWTH)

Variable Coefficient Std. Error t-Statistic Prob.

C -0.951189973 0.764413477 -1.244339617 0.2353

FDI(-1) 0.000233735 9.27965E-05 2.518794254 0.0257

D(LOG(EXPORT)) -1.611224765 0.307325259 -5.242734593 0.0002

LOG(GROWTH(-1)) -0.965044315 0.171140619 -5.638896945 0.0001

LOG(TOT) 0.69634461 0.182240496 3.821020162 0.0021

R-squared 0.819585921 Mean dependent var 0.072406Adjusted R-squared 0.764073897 S.D. dependent var 0.632487

S.E. of regression 0.307212982 Akaike info criterion 0.707582Sum squared resid 1.226937616 Schwarz criterion 0.954908

Log likelihood -1.368239672 F-statistic 14.764115Durbin-Watson stat 1.495721908 Prob(F-statistic) 0.000093

18A Chowdhury, G Mavrotas FDI and Growth: What Causes What, World Economy, Blackwell Synergy, 2001.

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Where log growth and log export are the change in the logarithm of growth rate andexport, respectively. FDI(-1) is the lagged foreign direct investment, and log(TOT) is thelogarithm of term of trade. Then according to the results shown in the equation above we findthat the lagged foreign direct investment and term of trade are statistically significant and thecoefficients of these variables are positive. But the first difference of the logarithm of exportand lagged growth are statistically significant and the coefficients of these variables are

negative. The set of explanatory variable explains 81 percent of total variation in thedependent variable.The stability of the model

Ramsey RESET Test

F-statistic 3.02363285 Probability 0.0753

Log likelihood ratio 7.60834483 Probability 0.0223

Ramsey Reset test accepts the hypothesis of the absence of model miss-specification, by bothtests.

12. ConclusionsRecent theoretical and empirical advancement on growth accounting and endogenous growthfront has emphasized that FDI can be a catalyzed for development of development countries.

FDI can contribute to the domestic stock of knowledge and its very presence generates a hostof externalities enhancing productivity and competitiveness of the host country. Theincreasing importance of international capital flows and especially FDI seems to be anotherimportant component of outward-looking development policies that should not be ignored.FDI can contribute in growth both direct and indirect ways. First, introduction of newtechnology by MNCs has high skill content. This is reflected by new vintages of capital,quality control and precision in production and accompanying increased training skill upgradation (World Bank 1997). They brought with them a package of market knowledge andmarketing skill accumulated from their long-standing experience and broader exposure toworld wide competitive markets. The indirect contributions of FDI in enriching the over allknowledge of the host economy, these include productivity and export spillovers. Thus, theresearch examines the effects of FDI in the Sudan economic growth by taking into account

the openness link. In this study, we analysis existence of causality between growth, FDI inSudan over the period 1982-2007.We found the long run relation among foreign directinvestment, export and domestic growth.

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