Cointegration Test

The test of cointegration is basically to establish a long-run stable equilibrium or stationary relationship between non-stationary series. The notion of cointegration is when variables in a hypothesizes relationship should not depart from each other in the long-run or if they do diverge in the short-mn, the divergence should diminish in the long-run so that the series will be on the same path.

Table 4.2: Johansen Cointegration Test Results

Trace Test Max-Eigenvalue Test

Null Alternative Statistics 5% Critical Value Statistics 5% Critical Value

r < 0 ^{r 1 154.5838* 125.6154} 57.4694* 46.23142

r < 1 r-2 97.11448* 95.75366 35.42209 40.07757

r~ 2 r-3 61.69239 69.81889 25.18081 33.87687

r~ 3 r-4 36.51158 47.85613 16.97767 27.58434

r~ 4 ^{r-5 19.53390 29.79707 10.67450 21.13162}

r~ 5 ^{r-6 8.859402 15.49471 6.834745 14.26460}

r~ 6 r-7 2.024658 3.841466 2.024658 3.841466

Source: Author s compzlatzon ' from Evzews 6.

Note: (*) indicates cointegration equation at the 5% criticallevel.

This study employs the Johansen approach to cointegration test and the results of the trace test indicate two cointegrating equations and the max-eigen value indicates one cointegrating equation at 5 percent level (Annex 3). We therefore fail to accept the null hypothesis of "no cointegration" and fail to reject the altemate hypothesis of "cointegration." The null hypothesis can be rejected if and only if the number of cointegrating equations is greater than one. In this study, the normalised cointegrating coefficients are based on the max-eigen value test.

4.4.3 The Error Correction Model (ECM)

Having established a long-run relationship among the series, I have to account for the short-run dynamics as well as the long-run equilibrium relationship by using an error correction madel.

There are two (2) types of the ECM; the Hendry ECM madel and the Engle-Granger ECM model. This study adopted the Hendry method of ECM because it is easier and less complex.

The general mathematical formulation of the Hendry ECM madel, is as shawn below:

L\Y

=

 + ~ ^A v + ~ ^A v + +  !::X + f3 Y + f3 X_, + fJzXt-2 + .... + f3kXt-k + fl, ... (4)

1 0 /1,1 L.l/1. 11 /1,2 L.l/1. 21 " " k kt ^{0 t-l 1 1}

k k

= f3o~-I

⁵

where:

?t,0 == constant

fi0 == error correction coefficient ), ),2' ... Âk = short-term dynamics

fi,,[J2, ... f3k = long-term dynamics

Renee the linear specification of the error correction model is as below:

D(LGDPPC)

=

a

0 + a₁D(FDI)+ a₂D(LGFCF)+ a3D(LGEX)+ a⁴D(POP)+ a⁵D(OPNS) + a

6D(GFC)+ a₇LGDPPC(-1)+ a₈FDI(-1)+ a9LGFCF(-1)+ a¹⁰(LGEX) + a

11POP(-1)+ a

120PNS(-1)+ a₁₃GFC(-1)+ J11 .... . . ..... (6)

Where;

D

~t

4.4.4 Granger Causality

=Difference operator, defined as D(X)

1

=

Xt - Xt-1

=Constant

= the error term

= the equilibrium correction coefficient

=Coefficients of the short-run model

=Coefficients of the long-run model

Granger causality test is widely used in econometrie studies to establish the direction of causality between or among variables. This test is normally preferred to other tests because it is very robust. The Granger causality technique was proposed by Granger (1969) and subsequently modified by Toda and Yamamoto (1995).

In this study GDP and FDI are expected to have a causal relationship as shown in equations 7 and 8.

d d

GDPPC

1

= /3

₀ + L Y₁;GDPPCH + L81iFDIH +7]11 ... (7)

l=l i=l

d d

FDfl

=

f3o + L Yz;FDit-1 + Lt5z;GDPPCH +7]21 ... (8)

i=l i=l

Equation (7) hypothesises that current GDPPC is related to past lagged values of FDI and itself and equation (8) also hypothesises that current FDI is related to past lagged values of GDPPC and itself. Where d is an assurned autoregressive lag order of the variables in the system and ^yt1

and 1'/2 are assurned to be white noises. Each variable is regressed on each other variable lagged

from 1 up to d lags in the system. For the granger causality test, four ( 4) scenarios must be considered before establishing the direction of causality. The scenarios are as indicated below;

For unidirectional causality from FDI to GDPPC, the estimated coefficient of the lagged FDI in equation (7) must be statistically different from zero, that is, 81 i 0 and the coefficient of the lagged GDPPC is equation (8) is not statistically different from zero, that is 8² =O.

For unidirectional causality from GDPPC to FDI, the estimated coefficient of the lagged GDPPC in equation (5) must be statistically different from zero, that is, 82 i 0 and the coefficient of the lagged FDI is equation (4) is not statistically different from zero, that is 81 =O.

For bi-causality or feedback effect, the estimated coefficient of the lag of both FDI and GDPPC are statistically different from zero in equations (7) and (8); that is 81

i

0 and 82

i

O.

Lastly, for independence or non causality in either direction, the estimated coefficients of GDP and FDI in both equations are not statistically different from zero, that is 81 = 0 and 82 = O.

The essence of carrying out the granger causality test is to find out whether FDI causes growth and/or vice-versa in Ghana.

The result of the estimation of the error correction model and the granger causality tests are shown below.

Table 4.3: Results of the Error Correction Model

Dependent Variable: D(LGDPPC), Sample (adjusted): 1971 2005

Variable Coefficient t-stat. Pro b. Variable Coefficient t-stat. Pro b.

c

^{3.00 2.54 0.02**} LGDPPC(-1) -0.69 -2.98 0.01 ***

D(FDI) -0.05 -2.54 0.04** FDI(-1) -0.08 -2.70 0.01 ***

D(LGFCF) ^0.25 3.56 0.00*** LGFCF(-1) 0.21 2.04 0.06*

D(LGEX) 0.04 1.49 0.15 LGEX(-1) 0.01 0.70 0.49 . D(POP) 0.07 0.69 0.50 POP(-1) -0.08 -1.58 0.12 D(OPNS) -0.47 -2.06 0.05** OPNS(-1) -0.44 -2.33 0.03**

D(GFC) -0.01 -0.56 0.58 GFC(-1) 0.01 0.85 0.40

R 0.753 DW-stat 2.003 Prob.(F -statistic) 0.0017

Adj. R² 0.584 F-statistic 4.451 Number of observations 33 Source: Author 's computation from Eviews 6

Note:(***), (**)and(*) indicate significance at 1%, 5% and 10% respectively.

Table 4.4: Results of Granger Causality Test (Long-run) Pairwise Granger Causality

Observations: 35 (1970-2006)

Null Hypothesis (H₀₎ lag 1 lag 2 lag 3

GDPPC does not granger cause FDI 6.227 3.196 2.025

(0.018)** (0.055)* (0.134)

FDI does not granger cause GDPPC 0.480 0.121 0.372

(0.493) (0.887) (0.774)

Source: Author's computation from Eviews 6

5% d JO%

u · . . h t t ·

z

es (* *) emd (*) renresent o an o 1vote: Fzgures zn parentheszs are t e asymp o zc p-va u · ^r

significance leve! respectively.

Table 4.5: Results of Granger Causality Test (Short-run) Pairwise Granger Causality

Observations: 35 (1970-2006)

Null Hypothesis (Ho) Iag 1

D(GDPPC) does not granger cause D(FDI) 2.138 (0.153) D(FDI) does not granger cause D(GDPPC) 0.760

(0.390) Source: Author 's computation from Eviews 6

Note: Figures in parenthesis are the asymptotic p-values.

4.4.5 Diagnostic Tests

In order to validate the model, I conducted diagnostic tests which included all the statistical tests;

Heteroscedasticity (White, Arch and Breusch-Pagan-Godfrey), Ramsey Reset, Breusch-Godfrey Seriai Correlation LM Test, Cusum and Cusum of Squares and Normality Tests (Annexes 4 to 10). All the tests were statistically significant with probabilities greater than 0.05. In view of the fact that the model has been validated through the various statistical tests, it can be concluded that the model is good and can be adopted for po licy and forecasting.

4.4.6 Interpretation and Analysis of Results

Based on the results obtained from the estimation of the ECM, I can make the following statistical inferences:

From Table 4.3, it can be observed that the R² explains about 75.3 percent of the variations in the endogenous variable while other factors that were not included in the model explain the remaining 24.7 percent of variations in the endogenous variable. The probability of the F-statistic is significant at 5 percent implying that the model fit is good and the Durbin-Watson statistic of 2.003 indicate that the errors are not correlated. The estimated.results indicate foreign direct investment (FDI), gross fixed capital formation (GFCF) and openness of the economy (OPNS) as the significant variables both in the short-run and long-run. The remaining variables in the model

population (POP) are insignificant in the short-run and long-run. The equilibrium correction coefficient, LGDPPC (-1), has the required negative sign and is significant, bence the ECM model is valid. This therefore goes to suggest that there is a fairly high speed of adjustrnent to equilibrium after a shock. Approximately 69 percent of disequilibra from the previous year's shock converge back to the long-run equilibrium in the following year. From our model, a shock that occurs in the short-run is reabsorbed within a period of 1year and 5 months (this is obtained by dividing 1 by the error correction coefficient, -0.69).

FDI has a negative and significant impact on GDPPC both in the short-run and the long-run. The variable is statistically different from zero at 5 percent and 1 percent with a coefficient of -0.05 and -0.12 respectively. This means in the short-run, a 5 percent increase in FDI will cause a 0.25 percent decrease in economie growth, while in the long-run a 1 percent increase in FDI will cause growth to decrease by 0.12 percent. This negative relationship between FDI and growth is consistent with studies like Oteng-Abayie and Frimpong (2006). Borenzstein et al. (1998) in their study argued that FDI has a significant impact on growth in economies with a high level of human capital whiles the impact is negative in economies with low human capital stock.

This empirical fmding is not surprising in the sense that about 70 percent of FDI inflows to Ghana are into the mining sector. Meanwhile the mining sector's contribution to GDP is 3 percent while its' cost to GDP is 4 percent, implying that the mining sector's net contribution to economie growth is -1 percent. Since the mining sector does not generate direct growth impacts on the wider economy, it is crucial to attract export-oriented FDI into the agricultural and industrial sectors if FDI is to impact positively on growth. Secondly, Ghana as developing economy has a significantly low level ofhuman capital to absorb the technology that cornes with FDI.

Capital investment proxied by gross fixed capital formation has a positive sign and is statistically significant at 1 percent in the short-run with an elasticity of 0.25. This implies that a 1 percent increase in FDI willlead to a 0.25 percent increase in economie

~owth.

The long-run elasticity is 0.3 and is significant at 10 percent. This implies that a 10 percent increase in gross fixed capital formation will lead to a 3 percent increase in economie growth. This result of a positive relationship between gross fixed capital formation and growth is however consistent with other

studies like Oteng-Abayie and Frimpong (2006). According to the neo-classical growth theory, an economy with a high capital stock tends to growth faster. This is because an increase in investment will lead to a higher capital per worker ratio leading to a higher productivity and hence a higher output level.

Openness of the economy has a negative sign and is statistically significant at 5 percent in the short-mn and the long-run. The coefficient of openness of the economy to growth is obtained as-0.47 in the short-run and -0.64 in the long-run. This therefore implies that a 5 percent increase in economie openness willlead to a 2.35 percent decrease in economie growth in the short-run and a 3.2 percent decrease in economie growth in the long-run. This result is however in contrast with that of Oteng-Abayie and Frimpong (2006) who found a positive impact of economie openness on economie growth in Ghana. However, other researchers such as Sash and Warner (1995) and Onafowora and Owoye (1998) found a negative relationship between openness and growth.

Though economie theory supports the fact that openness of the economy is one reason for developing economies to acquire technological transfer in order to boost economie growth, it is of outmost importance for sorne developing countries including Ghana to take a second and critical look at their libralisation policies. According to Chang et al. (2005), "output gains a:fter trade liberalisation depends on the degree of labour market flexibility. They argued that trade protection may ameliorate the problem of underdevelopment (or underproduction) in sectors affected by labour market distortions." According to international policy, for a country to engage in international trade she must have a comparative advantage to benefit from trade. Ghana can be said to have a comparative advantage in gold and cocoa production whose priees she does not determine. That is to say the terms of trade are also deteriorating and hence Ghana does not benefit much from international trade. As much as Ghana has benefited from being a member of ACP-EU and WTO it has also been a bane to Ghana's quest to attain economie development due to the influx of shoddy and below standard goods that has crippled a lot of businesses in ' Ghana.

From the Granger Causality test results, the null hypothesis that "GDPPC does not granger cause FDl" is rejected at the 95 percent confidence interval for lag 1 and 90 percent confidence interval for lag 2. There was no evidence of causality among the variables for lag 3. However, I fail to reject the null hypothesis that FDI does not granger cause GDPPC at the 5 percent significance lev el.

The granger causality results indicate that there is a unidirectional causality from GDPPC to FDI in the long-mn (table 4.4). The findings of this study are consistent with Sekmen (2007) who found a one-way causality from economie growth to foreign direct investment. However, there was no causality among the variables in the short-mn (table 4.5).

The fact the study failed to confirm FDI led growth in Ghana suggests that FDI is a necessary but not a sufficient condition to attain economie growth.

CHAPTER FIVE

EMPIRICAL FINDINGS, POLICY IMPLICATIONS AND CONCLUSION

This chapter focuses on the major findings from the study, policy implications and the conclusion. Recommendation is also made for areas where further research can be undertaken.

5.1 Empirical Findings of the Research

The objective of the research is to analyse the impact of foreign direct investment on economie growth in Ghana over the period 1970-2006. The empirical results suggest that FDI has a negative and significant impact on GDP per capita both in the short-run and the long-run; gross fixed capital formation ( domestic investment) has a positive and significant impact on GDP per capita in the short-run and the long-run; openness of the economy has a negative and significant impact on growth both in the short-run and the long-run.

5.2 Policy Implications

Based on the empirical findings, I draw the following policy inferences:

a. Investment Policy Reforms

There is the need for government to take a second look at the investment policy and the investment climate in general in order to reap the full benefit of foreign investment in the country. The fact that about 70 percent of FDI inflows make their way into the mining and extraction sectors to the neglect of the other sectors leave much to be desired. Since the mining sector does not generate direct growth impacts on the wider economy, it is crucial to attract export-oriented FDI into the agricultural and industrial sectors if FDI is to impact positively on growth. With Ghana's oil find, it becomes even more imperative to make the other sectors attractive enough to foreign investors. Most importantly, the ag!icultural and industrial sectors that have been identified as the sectors to champion Ghana's development agenda have not benefited much from foreign investrnent and it is important that government reform these sectors

so as to attract more foreign investment. Secondly, there is the need to promote sectorallinkages between the mining sub-sector and the other sectors so asto ensure spill-overs from the mining sub-sector to all the other sectors.

b. Increase Capital Formation (Domestic Investment)

A lot have been done since 2000 to promote the private sector to champion the development process. Credit to the private sector has increased from 11 percent in 2001 to 94.9 percent in 2006, commercial bank lending interest rates have also declined substantially from 47 percent in 2000 to 22 percent in 2006. Institutional reforms in the financial sector, customs (through the introduction of GCNET and export-rays) and legal system (introduction of the fast track court system and court computerisation) in order to reduce structural bottlenecks and stimulate investment is a step in the right direction. However, there is the need to do more in the macroeconomie sector like reducing inflation from the current 18 percent to a single digit. Cost of investment is still high if we consider the fact that most of the industries are either small-scale or medium-scale enterprises and the high cost of borrowing will cripple such businesses.

Govemment must also increase its investment in productive sectors, education and also in research and development.

c. Trade Policy Reforms

Openness of an economy through trade liberalisation is good and it ought to lead to growth of the economy. In the case of Ghana, trade liberalisation came as a package of the ERP and it has been argued by sorne researchers that most of these developing economies did not have the proper institutional structures in place to support such an initiative and it was a move by the West to exploit the developing countries. Ghana must learn from the East Asian "tigers" experience where they embarked on export-led industrialisation and practiced sophisticated interventionism.

There is the need to identify the comparative advantage sector and get government involvement to promote export-led industrialisation. In any case the market economie system that came with liberalisation has been identified as one of the banes of our uilderdevelopment. Indeed most economists who have studied the East Asian "miracle" believe that the low rate of protections

helped them to grow. Secondly, there is the need to diversify the export base to capture other non-traditional experts and also embark on an intensive export promotion.

5.3 Conclusion

Ghana has received quite a substantial amount of FDI inflows (above the average for a non-producing oil country in Africa) but this has not contributed positively to growth because foreign investors concentrate on the mining sector to the neglect of the other sectors. The study exarnined the impact of foreign direct investment on growth from 1970-2006. The empirical findings from the error correction model show that FDI, capital investment, openness of the economy and population have a significant impact on GDP per capita. Further research can be undertaken on the impact of trade liberalisation on foreign direct investment in Ghana. In sum, there should be better policies to utilise foreign capital inflows. There should also be increase in capital investment and lastly, there is the need to insist on better trade agreements, policies to strategically positioning Ghana in the global market and promote export-led industrialisation.

The study also confirmed a unidirectional causality from economie growth to FDI inflows in Ghana. It however failed to confirm FDI led growth. The fact that the study failed to confirm FDI led growth in Ghana clearly shows that FDI is a necessary but not a sufficient condition to attain economie growth.

Further researchers should use disaggregated FDI data to find analyse the impact on growth in Ghana.

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