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01.INTRODUCTIONMany policy makers and academics contend that foreign direct investment (FDI) can have

important positive effects on a host countrys development effort.

In addition to the direct capital

financing it supplies, FDI can be a source of valuable technology and know-how while fostering

linkages with local firms, which can help jumpstart an economy. Based on these arguments,

industrialized and developing countries have offered incentives to encourage foreign direct

investments in their economies. Especially, 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.

In the context of Sri Lanka, before 1977 since we had practiced closed economic situation there

were plenty of limitation for international trade and FDI. However, White Paper which is

presented in 1966 and foreign advisory committee was set up in 1968 have looked to possibility

of improving contribution of FDI on economic growth of the county. In fact after realizing the

significance of market economic policies, both economists and politicians had discovered the

possibility of capturing FDI more and more. As a result of that Foreign Investment Act was

established on 1978, in order to build a proper way for the above task. All these efforts have

leaded to attract enormous FDI up to now. It specially includes free trade zones such as

Katunayake (1978), Biyagama (1986) Koggala, (1991) Pallekelle (1996) Mirigama (1997) and

Malwatte (1997) which has created thousands of employment opportunities and contributed to

national economy by providing exports income.

Therefore this study mainly focused on analyzing the effect of FDI on Sri Lanka economic

growth. According to the structure of the study here after, one can go through problem statement,


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research objective, literature review, methodology, data analysis, results and discussion and

conclusions and recommendations.

02.PROBLEM STATEMENTHowever, we had attracted significance level of FDI opportunities; the economy of Sri Lanka is

still struggling to overcome from the developing status, since our economic growth is not

sufficient to pull our economy to developed category to from the current situation. Consequently

it is doubtable the degree of significance of FDI on Sri Lanka economic growth. Therefore it is

worthwhile to create a clear picture about the effect of FDI on Sri Lanka economic growth and

hence more specifically, the research question can be interpreted as following;

Is FDI an important factor in explaining Sri Lanka economic growth?

Throughout this research paper, I have employed the number econometric tools in order to

quantify the question based relationship.

03.OBJECTIVE OF THE STUDYIn accordance with the research problem, the key objective of this research is, identify the

relationship and degree of significance of FDI on economic growth in Sri Lanka. The several

steps have been included along with the different theoretical supports to achieve the unique

objective.

04.LITERATURE REVIEW

International trade has grown radically in the past fifty years. However, in the past twenty years,

FDI has increased enormously, with a faster growth than international trade. Kreinin, Plummer

and ABE (1998) found that, in recent decades, international trade has increased at a percentage

of GDP in most major economies, but FDI and other financial flows have been growing

exponentially. The total value of inward FDI in the world increased from about US$ 200 billion


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in 1993 to US$ 1.3 trillion in 2000 (UNCTAD,2000). FDI with a rapid growth has interested

researchers and government policy makers. Foreign Direct Investment (FDI) is one form of

capital flows which have a particular impact on economic growth in developing countries and

multinational enterprises (MNEs) are the main drivers of FDI (Fortanier, F. and Maher, M.,

2002). OECD (1978) defined the main forms of FDI as follows:

Outlays for the establishment of a new enterprise or for the expansion of an existing

enterprise whose operation is controlled by the foreign investor.

Financial outlays for the acquisition of an existing enterprise (or part of it) either

through direct purchase or through purchases of equity, with a controlling interest by

the foreign investor. The notion of control is not defined, but control is assumed when

the foreign investor owns at least between 10 and 51 percent of the enterprises value

according to different definitions used by different governments.

Intra-corporate long-term loans.

The linkage between FDI and economic growth has been studied in past twenty years. Most of

the studies focus on the impact of inward FDI on economic growth through either direct or

indirect effect. Generally speaking, inward foreign direct investment (FDI) can lead to job

creation, increase tax revenue, introduce advanced management skills and technologies, benefitthe insufficient domestic capital formation, and increase foreign exchange reserves. It provides a

unique combination of long-term finance, technology, training, know-how, managerial expertise

and marketing experience (Bende-Nabende, 1999). One of the most direct effects of inward FDI

on economic development is that inward FDI is an important financing source of domestic

capital. It can increase the production of the host country by adding to the countrys savings and

investment, and it is more stable than other forms of private capital inflows, e.g. portfolio equity

and debt flows (Fortanier, F. and Maher, M., 2002).

However, inward FDI is more than a form of capital flow. Todaro (1982), Dunning (1970) and

Krueger (1987) argued that through the capital accumulation in the host country, inward FDI was

expected to generate non-convex growth by encouraging the incorporation of new inputs and

foreign technologies in the production function of the host country. The more important effect of


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FDI is to increase the productivity of the host country through technology transfer. Although

technology can also be transferred through foreign trade, as argued earlier, inward FDI has a

unique impact on the transfer. Fortanier, F. and Maher, M. (2002) summarized four channels

through which inward FDI may lead to technology transfer, namely, vertical linkages, horizontal

linkages, labour migration and the internationalization of R&D activities. Vertical linkage

indicates backward linkages with suppliers and forward linkages with buyers (either individual

consumers or other firms). These business partners of the host country may be able to partly or

entirely absorb some explicit and implicit technology. Horizontal linkages refer to relations with

the competitors of the MNEs subsidiaries. The diffusion of technology takes place through the

competitors in two ways: demonstration and competition. The MNEs expose the superior

technology to the local firms and lead them to update their technology. The entrance of foreign

firms also strengthens the competition in the host countries and forces the local firms to improve

the production technology. These two effects are difficult to disentangle and may reinforce each

other. Labour migration is another way through which technology may be transferred and

disseminated. Employers by the MNEs acquire superior technology and management skills.

When they switch to work for local firms or start their own business, their acquired advanced

technology and management skills spread. The MNEs will also bring some R&D activities to the

host country, which may also lead to the improvement of technology.

However, economic growth can also benefit inward FDI. Economic growth induces the increase

in domestic market size which is a determinant of inward FDI. Meyer (1999) argued that output

growth was an important reflection of market size in one host country, and penetration of

foreign market is a major motive for FDI. Rapid economic growth, accompanied by an

increasing per capita income, will create huge opportunities by expanding the domestic

consumption demand (for both industrial and consumer goods) in the host country. Output

growth is considered as one important determinant for FDI inflows to a host country and this

argument is often called a market size hypothesis (OECD, 1983; Moore, 1993; Shan, 2002).

More importantly, rapid economic growth in the host country will build the confidence of

overseas investors for investing in the host country (Shan, 2002). According to the static

investment theory, a risk is always associated with an investment and investors always try to

reduce the risk in pursuing a high return. A high-speed growth which indicates a low risk in the


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investment is undoubtedly attractive for the investors. Thirdly, economic growth is associated

with an increase in capital demand. The increase in capital demand pushes the governments to

embark on incentive policies towards attracting FDI inflow in the case of shortage of domestic

capital. The increasing capital demand also raises the price of capital, indicating an increase in

the return of capital, and consequently induces inward FDI.

Finally, economic growth is also accompanied by an improvement in investment environment,

such as the infrastructure, energy supply, legal system, human capital, education, and R&D level.

A good investment environment can induce foreign investment. Hence, in empirical studies, it is

shown that the causality between inward FDI and economic growth can run in either direction,

that is, not only can inward FDI Grangercause economic growth but also economic growth can

cause FDI. Toda and Yamamoto (1995) found that there was indeed a two-way causality

between FDI and output in China. Shan (2002) also found the evidence of bi-directional

causalities between inward FDI and output growth in the case of China. However, the studies on

the causality between inward FDI and economic growth are rare as compared to the studies on

exports and economic growth.

05.METHODOLOGY

05.1 DataSince this study mainly based on time series data during the period of 1990- 2009, the data set

was collected by the various issues of Central Bank annual reports. In addition to that, several

issues of Socio Economic Statistics published by the Central Bank of Sri Lanka also were

considered.

05.2 Theoretical ModelIn economic literature, Cobb-Douglas production function which has been established by Charles

Cobb and Paul Douglas in 19001928 provides extensive applications for growth accounting. Since

it is the more realistic production function, current study engaged with this production function

in order to launch solid theoretical background. Cobb- Douglas production function can be

interpreted as follows.


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1LAKY

In above function;

Y- Output level

A- Total Factor Productivity

K- Capital

LLabour

and (1- ) Labour and Capital elasticity of output

Based on the Cobb Douglas production function, I formulated another model using the variables

which are appropriate for this study as follows. Especially, I established the following model by

incorporating FDI in to initial Cobb-Douglas production function. In addition to FDI I have

included several explanatory variables such as total trade and domestic investment and labour

which can be used to explain the growth rate of real GDP. Further, domestic investment has been

considered as a proxy for capital stock.

4321

0

GRTOTGRFDIGRLGRDINVGRRGDP

Where;

GRRGDP - Growth Rate of Real GDP

GRDINV - Growth Rate of Domestic Investment

GRL - Growth Rate of Labour

GRFDI - Growth Rate of Foreign direct Investment

GRTOT - Growth Rate of Total Trade


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05.3 Estimation techniques

05.4 Unit Root TestBefore moving down to empirically estimate the above model, it is wise to check data for

stationarity in order to avoid the spurious regression in time series data. Therefore unit root test

was done since; the unit root test that captures the order of integration of the time series can be

utilized to examine the stationarity. The unit root tests are carried out for all the variables in the

model by using the Augmented Dickey-Fuller (ADF) test. The ADF test for one unit root is

based on the following regression

t

n

i itittXtXX 11

whereXtcan be real inward FDI, real exports and real GDP, t represents time, t is random error

term, and n is the number of lag, selected in terms of Schwarz Criterion (SC). The null

hypothesis is = 0. If this null hypothesis is not rejected, the corresponding time series will be

non-stationary; otherwise, the time series will be regarded as stationary and said to be integrated

of order zero, denoted as I(0). Unless the null hypothesis is rejected one should correct the

variables by taking their appropriate log transformation or differences.

06.RESULTS AND DISCUSSIONAs mentioned in the above my focus is to put more weightage on econometric analysis rather

than descriptive analysis. However several graphs have been included to illustrate and identify

the relationship between various explanatory variables and the real GDP.

06.1 Descriptive Analysis

In accordance with the title of the paper, my first effort is to illustrate the relationship between

real GDP and Foreign Direct Investment (FDI) during the period of last two decades starting

from 1990.


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Figure01: Relationship between Real GDP and FDI

Source: Central Bank Annual Reports

It is apparent that both real GDP and FDI are illustrating increasing trend over the time even

though FDI has shown little bit fluctuating manner. Especially, FDI has been increasing

dramatically after 2005 compared to the other periods while the real GDP has been showing only

a gradual increment. Mainly, the outward economic policy which has been promoted during the

period of 2000s has significantly influence the inward of FDI after 2005. Apart from the

behavior of two series, the most important fact is that the positive relationship between real GDP

and FDI by showing the impact of FDI on real GDP.

In fact the contribution of international trade is vital in economic performance in the country

with the globalization. Even though it is very difficult to build a clear picture about the

underlying relationship in the context of Sri Lanka, since the total trade is indicating much more

fluctuating manner.

Figure02: Relationship between Total Trade and Economic Growth Rate

0

10000

20000

30000

40000

50000

60000

70000

80000

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

RGDP

FDI


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According to the above graph, it is obvious that no specific pattern between two series of data as

the previous graph on real GDP and FDI. It implies that total trade is not a significant factor in

explaining economic growth in Sri Lanka during the sample period.

However not only FDI, but domestic investment also plays a massive role, therefore it is wise to

identify the actual performance of both domestic investment and FDI.

Figure03: Domestic Investment Ratio and Growth Rate of FDI

-50

0

50

100

150

200

250

300

350

400

450

GRRGDP

TOT


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It is obvious that domestic investment shows a smoothing pattern over the time while growth rate

of FDI indicate fluctuate pattern as usually. Basically FDI inflows depend on various factors

including both domestic and international economic conditions. Consequently FDI more

generally more capricious compared to domestic investment. Therefore it is very essential to

maintain a stable domestic economic and political culture in order to maximize the FDI inflows

since we are unable to influence the global scenarios.

06.2 Econometric AnalysisBefore moving to estimate the VAR model, I checked the stationary of the variables as

mentioned in the methodology. I used Augmented Dickey Fuller (ADF) test as a unit root test

along with the Akaike Info Criteria (AIC) and according to the ADF results all the variables are

stationary in their level forms. The following table indicates the stationarity of all other variables

at their level forms since the probability value of each series is less than 0.05.

Table- 01: ADF test results for level form of the variables

-100

-50

0

50

100

150

200

250

300

350

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

DINVEST

GRFDI


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Series Prob. Lag Max Lag Obs

GRFDI 0.0065 1 3 16

GRL 0.0001 0 3 18

GRRGDP 0.0158 0 3 18

GRDINVEST 0.0295 1 3 17

GRTOT 0.0096 0 3 18

Since all the variables are stationary at the level forms, they can be interpreted as I(0) variables

where both OLS and VAR models can be applied to analyze the effect of FDI on economic

growth of Sri Lanka. However, it is quite better to apply VAR model rather than OLS method,

since VAR model facilitates a path way to identify the short run dynamics of concerned

relationship. Once the initial VAR model estimated, I re-estimated the VAR model by applying

the appropriate lag length. In the lag selection criteria, the Schwarz Information Criteria was

employed since the research dealing with the small time period. According to the Schwarz

Information Criteria, one lag was included and this lag length was justified by the other criteria

as well. Furthermore the stability of the VAR model is quite crucial to provide a solid basis for

policy analysis. Hence, the Auto Regressive Root Graph was considered for that task and the

graph can be illustrated as follows.

Auto Regressive Root Graph

In accordance with the following graph, since all the variables are inside the circle and

consequently the estimated VAR model is pretty well to explain the short run dynamic of FDI on

economic growth. Apart from the stability of VAR model, in accordance with the methodology

after estimating the VAR model I used Impulse Response Function (IRF), Variance

Decomposition (VD) and Granger Casualty Test (GCT) to interpret the results of VAR model.

Figure04: Auto Regressive Root Graph


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Impulse Response Function

IRFs trace out the expected responses of current and future values of each of the variables to a

shock in one of the VAR equations. In this regards, shocks can be defined or measured in

different ways. The shock may be equal to the one standard deviation or one unit of the residual;

otherwise one can follow the generalized impulse method depending on the statistical package

which they are using. In this study I gave shock to the residual of each endogenous variable

which is equal to the one standard deviation and the following graphs illustrate the possible

outcomes of these shocks.

Figure05: Impulse Response Functions

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

Inverse Roots of AR Characteristic Polynomial


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According to the results of the Impulse Response Function, it can be seen that at 5 percent

significance level the response of GRRGDP is not statistically significance with respect to the

shocks of each endogenous variables. Even though the shock of GRFDI was unable to create a

-4

-2

0

2

4

6

1 2 3 4 5 6 7 8 9 10

Response of GRRGDP to GRL

-4

-2

0

2

4

6

1 2 3 4 5 6 7 8 9 10

Response of GRRGDP to GRRGDP

-4

-2

0

2

4

6

1 2 3 4 5 6 7 8 9 10

Response of GRRGDP to GRFDI

-4

-2

0

2

4

6

1 2 3 4 5 6 7 8 9 10

Response of GRRGDP to TOT

-4

-2

0

2

4

6

1 2 3 4 5 6 7 8 910

Response of GRRGDP to DINVEST

Response to Nonfactorized One S.D. Innovations 2 S.E.


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statistically significance response, the trend is much crucial. Specifically, the graph of response

of GRRGDP to GRFDI is showing that a positive shock of GRFDI will create a positive and

increasing effect on GRRGDP up to 2 years and then this effect gradually decreasing and after 3

years time the effect will die out. Furthermore all other variables such as growth rate of total

trade, growth rate of domestic investment and growth rate of labour have not been able to

maintain a considerable effect on growth rate of real GDP. As a whole, FDI can influence

GRRGDP compared to the other endogenous variables, even though the relationship is not

statistically significance.

Variance Decomposition Analysis

Variance decomposition decomposes variance in an endogenous variable in to the component

shocks to the endogenous variables in the VAR. The variance decomposition gives the

information about the relative importance of each random innovation in the VAR. The column

S.E. in the below Variance Decomposition table is the forecast error of the variable for each

forecast horizon. The source of this forecast error is the variation in current and future values of

the innovations to each endogenous variable in the VAR.

Table- 02: Variance Decomposition Analysis

Period S.E. GRL GRRGDP GRFDI TOT DINVEST

1 2.203661 1.252729 98.74727 0.000000 0.000000 0.000000

2 2.725159 1.206248 93.07922 3.091372 0.844502 1.778662

3 2.800075 1.167074 92.49826 3.022618 1.185792 2.126255

4 2.822757 1.165754 92.40363 3.015655 1.256422 2.158538

5 2.827174 1.165268 92.39060 3.014418 1.268709 2.161003

6 2.827545 1.165219 92.38993 3.014289 1.269493 2.161068

7 2.827584 1.165219 92.38991 3.014292 1.269514 2.161065

8 2.827586 1.165219 92.38990 3.014294 1.269516 2.161071

9 2.827586 1.165219 92.38990 3.014294 1.269517 2.16107310 2.827586 1.165219 92.38990 3.014294 1.269518 2.161074

Moreover, it can be seen according to the above graph, GRRGDP accounts for its variance in a

magnificent proportion followed by the GRFDI. Even though GRFDI maintained the second best


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relative importance among the other endogenous variables, its accounts only for quite low

proportion. Consequently, the effect of the GRFDI on GRRGDP is considerably low in the Sri

Lanka economy.

Granger Causality Test

Basically, Granger Causality Test can be employed in order to examine the direction of the

causality among the variables. Granger-causality requires that lagged values of particular

variable are related to subsequent values in another variable, keeping constant the lagged values

of secondly mentioned variable and any other explanatory variables. The results of the Granger

Causality test can summarized as follows.1

GRFDI does not Granger Cause GRRGDP 16 0.09430* 0.9107GRRGDP does not Granger Cause GRFDI 0.60541 0.5631

* - Significance at 10 percent level

The results of Granger Causality Test imply that GRFDI Granger cause GRRGDP, however this

causality is significant only at 10% significance level and there is no reverse relationship inbetween these two variables. This direction of causality stresses that even though GRFDI causes

to influence the GRRGDP, in fact the magnitude of this relationship is quite low since it is only

significant at 10% level. The same results can be found by reviewing the literature also, for a

example Athukorala(2003). According to the Athulorala (2003), It is evident in the results that

the regression analysis does not provide much support for the view of a robust link between FDI

and growth in Sri Lanka. In fact, the inflows of FDI maintain a considerable level; the economic

and political back ground of the country is still unfavorable and insufficient to get the maximum

benefits from the inward FDI. Therefore the contribution of FDI on economic growth is still

maintaining a lower level. Moving to the other pair wise causalities, there is bi direction

causality in between growth rate of total trade and growth rate of FDI and also it is significant at

5% level. The rationale behind this is when the trade agreements are expanded and when the

1Refer the appendices for the full output


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country is more open to the world, total trade shows a increasing pattern and since the country is

more open to the world there is a higher potential to attract the FDI. Moreover GRFDI also

Granger causes to GRDINVEST and this causality is significance at 10% level. It is obvious that

when the foreign companies setup their business domestically, there should be an encouragable

infrastructure facilities and stable financial system. Thus, in order to ensure attraction business

vicinity, domestic investment should be increased.

07.CONCLUSIONS AND RECOMMENDATIONSThis study attempted to quantify the relationship between FDI and economic growth of Sri

Lanka using VAR analysis. As a whole, even though GRFDI shows positive effect on GRRGDP

the magnitude of this effect is quite low. According to the Impulse Response Function, a shock

in GRFDI may cause to increase the economic growth for two years and then it leads to pull

down to economic growth and however after three years time the effect will die out. Variance

decomposition proposed that the variation which is explained by GRFDI is quite low. Moreover,

Granger causality test discovered that one way causality which is going from GRFDI to

GRRGDP and however there is an only 90% confidence about this direction of causality. In fact

this also justified that even though GRFDI can influence the GRRGDP in a positive manner this

is considerably low. Furthermore, the results indicated that there is a bi-directional causality in

between GRFDI and GRTOT.

In the current context of Sri Lanka, the significance of FDI is at a lower level even though there

is a potential to utilize FDI to enhance the growth rate in Sri Lanka. However, the factors which

can enhance the contribution of FDI such as infrastructure facilities, stable economic and

political situations are not working smoothly currently. In fact after finishing the civil war

situation, FDI inward has grown rapidly even if the encouragable vicinity is not present yet.

Therefore, this study strongly recommends that to build and maintain supportable infrastructure

facilities along with stability economic condition in the country to improve the performance of

FDI in order to achieve a higher contribution to economic growth.


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REFERENCES

APPENDICES

01.Lag Selection Criteria of VARVAR Lag Order Selection CriteriaEndogenous variables: GRL GRRGDP GRFDI TOTDINVEST

Exogenous variables: C @TREND

Date: 04/29/11 Time: 22:15

Sample: 1990 2008

Included observations: 17

Lag LogL LR FPE AIC SC HQ

0 -306.4447 NA* 1.02e+10* 37.22879* 37.71892* 37.27751*1 -288.5269 21.07973 3.02e+10 38.06199 39.77743 38.23251

* indicates lag order selected by the criterion

LR: sequential modified LR test statistic (each test at 5% level)

FPE: Final prediction error

AIC: Akaike information criterion

SC: Schwarz information criterion

HQ: Hannan-Quinn information criterion


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02.Re-estimation of VAR with selected lag lengthVector Autoregression Estimates

Date: 04/25/11 Time: 09:56Sample (adjusted): 1991 2007

Included observations: 17 after adjustments

Standard errors in ( ) & t-statistics in [ ]

GRL GRRGDP GRFDI TOT DINVEST

GRL(-1) -0.188427 -0.004981 -3.075031 -6.958239 -0.052814

(0.25790) (0.35023) (11.3149) (12.6476) (0.19659)

[-0.73061] [-0.01422] [-0.27177] [-0.55016] [-0.26865]

GRRGDP(-1) -0.157946 -0.176813 -8.887991 2.792415 0.497850

(0.25901) (0.35174) (11.3636) (12.7021) (0.19744)

[-0.60979] [-0.50269] [-0.78215] [ 0.21984] [ 2.52152]

GRFDI(-1) 0.010269 0.004898 0.024353 0.007831 -0.003589

(0.00740) (0.01005) (0.32476) (0.36301) (0.00564)

[ 1.38723] [ 0.48728] [ 0.07499] [ 0.02157] [-0.63604]

TOT(-1) -0.009409 -5.61E-05 0.080391 -0.070772 0.003328

(0.00754) (0.01024) (0.33080) (0.36977) (0.00575)

[-1.24779] [-0.00548] [ 0.24302] [-0.19140] [ 0.57906]

DINVEST(-1) 0.134220 -0.316694 1.345447 -3.231800 0.682953

(0.29323) (0.39820) (12.8646) (14.3799) (0.22352)

[ 0.45773] [-0.79532] [ 0.10459] [-0.22474] [ 3.05546]

C -1.702748 12.29321 71.72536 48.74796 6.103630(7.88097) (10.7022) (345.757) (386.483) (6.00745)

[-0.21606] [ 1.14866] [ 0.20744] [ 0.12613] [ 1.01601]

@TREND 0.100077 0.226718 -1.891894 7.220164 -0.054734

(0.12446) (0.16901) (5.46033) (6.10349) (0.09487)

[ 0.80409] [ 1.34142] [-0.34648] [ 1.18296] [-0.57692]

R-squared 0.390179 0.191375 0.110276 0.161284 0.642348

Adj. R-squared 0.024286 -0.293800 -0.423559 -0.341945 0.427757

Sum sq. resids 48.56123 89.55192 93469.89 116786.1 28.21704

S.E. equation 2.203661 2.992523 96.67983 108.0676 1.679793

F-statistic 1.066374 0.394446 0.206573 0.320498 2.993360

Log likelihood -33.04366 -38.24560 -97.32550 -99.21848 -28.42901

Akaike AIC 4.711019 5.323012 12.27359 12.49629 4.168119Schwarz SC 5.054107 5.666100 12.61668 12.83938 4.511207

Mean dependent 1.522056 5.735961 39.81887 37.17824 25.12941

S.D. dependent 2.230918 2.630898 81.03043 93.28849 2.220576

Determinant resid covariance (dof adj.) 5.39E+09

Determinant resid covariance 3.80E+08

Log likelihood -288.5269

Akaike information criterion 38.06199

Schwarz criterion 39.77743


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03.Variance Decomposition (Multiple Graph)

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10

Percent GRRGDP variance due to GRL

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10

Percent GRRGDP variance due to GRRGDP

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10

Percent GRRGDP variance due to GRFDI

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10

Percent GRRGDP variance due to TOT

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10

Percent GRRGDP variance due to DINVEST

Variance Decomposition


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04.Granger Causality TestPair wise Granger Causality Tests

Date: 05/02/11 Time: 22:47

Sample: 1990 2008

Lags: 2

Null Hypothesis: Obs F-Statistic Prob.

GRRGDP does not Granger Cause GRL 17 3.81695 0.0521

GRL does not Granger Cause GRRGDP 0.06351 0.9388

GRFDI does not Granger Cause GRL 16 1.36654 0.2951

GRL does not Granger Cause GRFDI 1.00847 0.3961

TOT does not Granger Cause GRL 17 1.79098 0.2086

GRL does not Granger Cause TOT 0.37585 0.6945

DINVEST does not Granger Cause GRL 17 1.07134 0.3732

GRL does not Granger Cause DINVEST 0.88814 0.4368

GRFDI does not Granger Cause GRRGDP 16 0.09430 0.9107

GRRGDP does not Granger Cause GRFDI 0.60541 0.5631

TOT does not Granger Cause GRRGDP 17 1.51781 0.2584

GRRGDP does not Granger Cause TOT 0.04270 0.9583

DINVEST does not Granger Cause GRRGDP 17 0.71308 0.5098

GRRGDP does not Granger Cause DINVEST 5.94303 0.0161

TOT does not Granger Cause GRFDI 16 0.04848 0.9529

GRFDI does not Granger Cause TOT 0.02182 0.9785

DINVEST does not Granger Cause GRFDI 16 0.12103 0.8872GRFDI does not Granger Cause DINVEST 0.07149 0.9314

DINVEST does not Granger Cause TOT 17 1.26513 0.3173

TOT does not Granger Cause DINVEST 1.00747 0.3940

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