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Foreign Direct Investment
and Economic Growth:
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Nigeria like all other developing countries presently needs to rely especially upon FDI for such huge number of reasons. Numerous studies (Sjoholm, 1999; Obwona, 2001, 2004) specified that the inclination for FDI originated from its recognized points of interest. The exertion by the country to improve its business atmosphere originates from the longing to draw in FDI.
Indeed, (Funke & Nsouli, 2003) argued that one of the columns on which the New Partnership for Africa's Development (NEPAD) was propelled was to increment accessible cash-flow to US$64 billion through mix of changes, asset preparation and a helpful domain for FDI.
Shockingly, the endeavors of Nigeria to pull in FDI have been worthless. This is disregarding the apparent and evident requirement for FDI in the landmass. The improvement is upsetting, sending almost no desire for financial advancement and development for these nations. Further, (Morriset 2000; Asiedu, 2001) stated that the example of the FDI that exists is regularly slanted towards extractive ventures, implying that the differential pace of FDI inflow into sub-Saharan African nations has been illustrated to be because of characteristic assets, in spite of the fact that the size of the neighborhood market may likewise be a thought.
In addition, given her common asset base and enormous market size, Nigeria fits the bill to be a significant beneficiary of FDI in Africa and in fact is one of the main three driving African nations that reliably got FDI in the previous decade. In any case, the degree of FDI pulled in by Nigeria is fair as (Asiedu, 2003) contrasted and the asset base and potential need. Further, the observational linkage among FDI and monetary development in Nigeria is yet indistinct, regardless of various investigations (e.g, Adelegan, 2000; Akinlo, 2004) that have analyzed the impact of FDI on Nigeria's financial development with differing results. Nonetheless, ongoing proof avows that the connection among FDI and economic growth might be nation and period explicit. On this note Asiedu (2001) presents that the determinants of FDI in one district may not be the equivalent for different locales. In a similar vein, the determinants of FDI in nations inside a locale might be not the same as each other, and starting with one period then onto the next. The consequences of several studies on the linkage among FDI and economic growth in Nigeria are not consistent in their entries. A closer assessment of these past investigations uncovers that cognizant exertion was not made to deal with the way that more than 60 % of the FDI inflows into Nigeria is made into the extractive (oil) industry. Thus, these investigations really demonstrated the impact of common assets on Nigeria's monetary development. Also, the effect of FDI on financial development is more hostile in observational than hypothetical investigations, henceforth the need to inspect the connection among FDI and development in various monetary agreements. There is further issue of endogeneity, which has not been deliberately handled in past investigations in Nigeria. FDI may positively affect financial development prompting an augmented market size, which thus pulls in further FDI. At last, there is an expanding protection from further progression inside the economy. This restrains the alternatives accessible to the administration to source assets for improvement purposes and makes the choice of looking for FDI significantly more basic.
This current investigation adds to the existing literature by analyzing the relationship between FDI inflows and economic growth in Nigeria, thus tending to the nation's particular measurement to the FDI development banter. This inquiry is not quite the same as past investigations in scope and methodology. What's more, the impact of the significant segments of FDI on economic growth is analyzed, consequently offering the chance to evaluate the differential effect of oil FDI and non-oil FDI on Nigeria's economy.
The principal objective of this investigation subsequently is to examine the connection between FDI inflows and economic growth in Nigeria between 1981 and 2018. The rest of the paper comprises of section 2, which is review of empirical and theoretical literature, section 3 as
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methodology and data, section 4 for the result and discussion, while section five presents conclusions, recommendations respectively.
Literature Review and Theoretical Issues
Several scholars have attempted to conceptualize the FDI and the rationale behind FDI’s inflow principally to the hosting economies. Some of these authors include Onu, (2012) who concludes that FDI is relied upon to add to financial development incorporate the arrangement of outside capital just as packing in extra domestic investment. It is believe that together with the domestic investment, FDI help creates more employment opportunities, wider markets and stimulates economic activities of the receiving country. Kumar (2007) portrayed FDI in a different ways as: First it may involve the desire of parent enterprise to inoculate equity capital by purchasing shares in foreign partners. Second, it could be in a process of reinvesting the affiliate’s earning. And finally it entail how FDI as a share of Gross Domestic Product (GDP) grow over time, and maybe becoming the principal source of capital to the recipient economies.
Adegbite and Ayadi (2010) indicated that FDI is a vital engine for filling the domestic revenue-generation gap, particularly in developing economies, for the reason that without the FDI flow, most developing economies seem not to be able to generate sufficient revenue to meet their expenditure needs. More so, FDI helps greatly in transfer of technology to the developing nations. As per Omankhanlen, (2011) FDI comprises; external resources, technology, managerial and marketing expertise as well as capital inflow. It is believed that these help produce a substantial impact on host economy’s productive capabilities and facilitate the success of macroeconomic policies of stimulating the productive base of the economy. Caves (1996) sees that, the justification for expanded endeavors to pull in more FDI comes from the conviction that FDI has a few beneficial outcomes. These include improved production, introduction of new and advanced production process, technology transfers, and the introduction of new processes, managerial skills and development of marketing strategies in the domestic market, employee development, international production networks, and access to markets. Based on these statements governments have regularly given uncommon impetuses to outside firms to set up organizations in their nations.
A ton of research intrigue has been appeared on the connection between FDI and economic growth; albeit the greater part of such work has not been arranged in Africa, talk less of Nigeria.
The focal point of the exploration chip away at FDI and economic growth can be extensively ordered. Inquisitively, the experimental proof of these advantages both at the firm level and at the national level stays vague. In the first place, Jeannine (2000) utilized panel data from 40 developing economies covering the period 1975–95. The investigation determined a model which represented potential endogeneity of the illustrative factors and the outcome shows that capital inflows cultivate higher financial development, well beyond any impacts on the speculation rate, however just for economies where the financial part has arrived at a specific degree of advancement. Cuadros, Orts and Alguacil (2001) contemplated the idea of the causal connection between output level, inward FDI and trade latin American nations; Argentina, Brazil and Mexico from 1975 to 1997. Using a vector auto-backward (VAR) model the aftermath of the investigation recommends a critical effect FDI on economic growth and trade in the reviewed countries. Ayashagba and Abachi (2002) studied the impacts of FDI on economic growth in Nigeria between 1980 and 1997. Their outcome uncovered that FDI had critical effect on the growth of Nigeria’s GDP. In any case, the investigation infers that the nearness of FDI in Nigeria has not been absolutely helpful. Utilizing information from a few speculator overviews, the investigation of Asiedu (2002) Using time series data between 1970-2003, propose that macroeconomic instability, investment restrictions, corruption and political instability have a negative impact on FDI in to African countries. Specifically Akinlo (2004)
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considered the effect of the non-oil FDI on the Nigeria’s economy, with the aid of error correction model. The author investigated the impact of FDI on economic growth in Nigeria.
The study found that both private and lagged-foreign Capital are not statistically significant in the Nigeria’s economic growth. The results further argued that manufacturing FDI is not in any way supporting economic. De Gregorio (2003) notes that FDI may allow a country to bring in technologies and knowledge that are not readily available for domestic investors, and in this way increases productivity growth throughout the economy. Similarly, FDI helps in supplying the host countries with expertise that they are lacking, besides that it facilitate the growth of local markets. In general, the study found that increasing aggregate investment by 1 percentage increased the GDP of Latin American countries by 0.1% to 0.2% a year. However, increasing FDI by the same amount increased growth by approximately 0.6% a year over the period between 1950 and 1985. This shows that FDI has tripled the contributions of domestic investment under the period of the study.
In a different line of study, Makki and Somwaru (2004) analyze the role FDI and trade in economic growth of developing countries within the endogenous growth-theory framework.
The study used cross-sectional data for a sample 66 developing counties covering three decades. The findings of the study revealed that FDI and trade significantly contribute to the growth of GDP in developing countries. It further revealed that FDI is often the main channel through which advanced technology is transferred in those countries. In addition, Jerome and Ogunkola (2004) assessed the magnitude, direction and prospects of FDI in Nigeria. The study found that while the FDI regime in Nigeria was generally improving, there are still some deficiencies that make it somehow ineffective. These deficiencies are mainly in the area of the corporate environment such as corporate law, bankruptcy, labour law and the institutional uncertainty, as well as the rule of law.
Relating evidence from developed and developing countries, Blonigen and Wang (2005) noted that the performance of FDI depends on the determining factors of FDIa growth in each case.
Stimulatingly, the study found that FDI is evidently constructive in the emerging economies compared to the advanced economies. It further revealed from the findings the crowding-out effect of FDI on domestic investment in the advanced economies. In a panel analysis of the effects of FDI on economic growth from 47 African countries covering the period between 1980 and 2000, Lumbila (2005) utilize a seemingly unrelated regressions (SUR) technique of analysis, the study revealed that FDI exerts a positive impact on growth in the sampled countries. Similarly, Adewumi (2006) examine the impact of FDI on economic growth in Africa with the aid of graphical and regression analysis. The study discovered that though the relationship between FDI and GDP growth is positive, it is however insignificant. Moreover, Chowdhury and Mavrotas (2006) examines the causal relationship between FDI and economic growth for Chile, Malaysia and Thailand by using time-series data covering the period between 1969 and 2000, using the Toda and Yamamoto causality test approach. The findings exposed that in the case of Chile the causality is unidirectional GDP to FDI, whereas for Malaysia and Thailand, the causality is bi-directional between the two variables.
In another development, Ayadi (2009) researches the connection among FDI and economic growth in Nigeria and found weak relationship and causality between the factors and prescribes that infrastructural improvement, human capital structure and vital arrangements towards pulling in FDI ought to be heightened. Moreover, Vu and Noy (2009) study on sectoral analysis of FDI and growth in developed countries with a particular emphasis on the sector impacts of FDI on growth. The study disclosed that there is significant positive relationship between FDI and GDP growth through its interaction with labour. What is more, the study established that
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the effects seem to be very different across countries and economic sectors. In the same manner, Osinubi and Amaghionyediwe (2010) examined the relationship between foreign private investment (FPI) and economic growth in Nigeria. Their findings suggest that FPI, domestic investment growth, net export growth and the lagged error term were statistically significant in explaining variations in Nigeria economic growth. Correspondingly, Ruxanda and Muraru (2010) examined the relationship between FDI and economic growth in the Romanian economy using simultaneous equations model. The study displayed a bi-directional causation between FDI and economic growth.
Omankhanlen, (2011) analyzed the effect of FDI on the Nigerian economy covering a period of 29 years, between 1980 and 2009. The author examined empirically if the following growth determining variables in the economy-Balance on current account. Inflation and Exchange rate have effect on FDI and so is FDI on GDP growth. The study developed Econometric models to investigate the relationships between the above-mentioned variables and FDI. Based on the data analysis, it was discovered that FDI has positive and significant impact on current account balance though inflation was seen not to have significant impact on FDI inflows.
Additionally, Egwaikhide (2012) examines the relationship between FDI and economic growth in Nigeria, using Johansen Cointegration technique and Vector Error Correction Method in which FDI is disaggregated into various components. The Johansen Cointegration result founds that the impact of the disaggregated FDI on real growth in Nigeria namely: agriculture, mining, manufacturing and petroleum sectors is very little with the exception of the telecom sector which has a good and promising future, especially in the long run. What's more, past level of FDI and level of infrastructures are FDI enhancing. Olokoyo, (2012) employed the use of Ordinary Least Square (OLS) regression technique examined the effects of FDI on economic development in Nigeria on a time series data covering the period 1970 – 2007. The study tried to answer the question: what are the determinants of FDI in Nigeria and how do they affect the economy in general? The Cochrane-Orcutt iterative method was also used to correct for autocorrelation. The model used hypothesizes that there is a functional relationship between the economy development of Nigeria using the real gross domestic product (RGDP) and FDI.
The regression analysis results evidently do not provide much support for the view of a robust link between FDI and economic growth in Nigeria as in the case of previous studies. Though the result does not imply that FDI is insignificant, the results of the study reduce the confidence in the belief that FDI has exerted an independent growth effect in Nigeria. Eravwoke and Imide (2013) emphasized on the empirical investigation of the impact of corruption, foreign direct investment and its impact on exchange rate of the Nigerian economy using the ordinary least squares regression analyses, augmented dickey fuller unit root test and the co-integration test.
The unit root test revealed that all the variables were stationary at first difference and the short run result revealed that corruption is very high in Nigeria and that have help to depreciate the currency of the country with regards its exchange to other currencies.
Saibu and Keke (2014) examined the impact of foreign private investment on economic growth using annual time series data from Nigerian economy. The paper employed Cointegration and Error Correction Mechanism (ECM) techniques to empirically analyze the relationship between foreign private investment and economic growth and to draw policy inferences on the observed relationship. The study revealed that there was a substantial feedback of 116% and 78% from previous disequilibria between long-run economic growth and foreign private investment respectively. The findings also indicated that a substantial proportion of capital inflow were not productively invested however the relatively small proportion (22%) of net capital inflows invested, contributed significantly to economic growth in the Nigerian
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economy. The political environment was found to be unfavorable and overwhelmed the positive impact of foreign private investment.
It should be noted that FDI could be constructive in the short run but not in the long term.
Durham (2004), for example, failed to establish a positive relationship between FDI and growth, but instead suggests that the effects of FDI are contingent on the “absorptive capability” of host economies.
The review shows that the debate on the impact of FDI on economic growth is far from being conclusive. The role of FDI seems to be country specific, and can be positive, negative or insignificant, depending on the economic, institutional and technological conditions in the recipient countries.
Most studies on FDI and growth are cross-country evidences, while the role of FDI in economic growth can be country specific. Further, only a few of the country specific studies actually took conscious note of the endogenous nature of the relationship between FDI and growth in their analyses, thereby raising some questions on the robustness of their findings. Finally, the relationship between FDI and growth is conditional on the macroeconomic dispensation the country in question is passing through. In fact, Zhang (2001) asserts that “the extent to which FDI contributes to growth depends on the economic and social condition or in short, the quality of the environment of the recipient country”. In essence, the impact FDI has on the growth of any economy may be country and period specific, and as such there is the need for country specific studies.
The neoclassical financial experts contend that FDI impacts economic growth by expand ing the measure of capital per person. Be that as it may, in view of consistent losses to capital, it doesn't impact since a long time ago run financial development. Bengos and Sanchez-Robles (2003) attest that despite the fact that FDI is emphatically corresponded with financial development, have nations require least human capital, monetary security and changed markets so as to profit by long haul FDI inflows. Strangely, Bende-Nabende et al. (2002) found that immediate long haul effect of FDI on output productivity is critical and positive for relatively financially less propelled Philippines and Thailand, however negative in the more monetarily propelled Japan and Taiwan. Consequently, (Romer, 1986; Lucas, 1988) asserted that the degree of economic improvement may not be the fundamental empowering factor in FDI development nexus. Then again, the endogenous way of thinking opines that FDI additionally impacts since quite a while ago run factors, for example, innovative work (R&D) and human capital.
Theoretically, the notion that FDI is positively correlated with economic growth is situated in growth theory that emphasizes the role of improved technology, efficiency and productivity in promoting growth (Lim, 2001). The potential contribution of FDI to growth depends strictly on the circumstances in recipient countries. Certain host country conditions are necessary to facilitate the spillover effects. The effect of FDI on economic growth is analyzed in the standard growth accounting framework. To begin with, the capital stock is assumed to consist of two components: domestic and foreign owned capital stock. So,
Kt = Kdt + Kft
Now let’s adopt an augmented Solow production function Solow, (1956) as emphasized in Mankiw, et.al, (1992) that makes output a function of stocks of capital, labour, human capital
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and productivity. However, specifying domestic and foreign owned capital stock separately in a Cobb–Douglas (Cobb and Douglas, 1928) production function.
Yit = Ait 𝐾𝑑𝑖𝑡∝ 𝐾𝑓𝑖𝑡𝜆 𝐿𝛽𝑖𝑡 𝐻𝑖𝑡𝛾 (1)
Where Y is the flow of output, dt ft K K represent the domestic and foreign owned capital stocks, respectively, L is the labour, H is the human skills capital stock, and A is the total factor productivity, which explains the output growth that is not accounted for by the growth in factors of production specified. Taking logs and differentiating Eqn. 1 with respect to time, the analysis obtain the familiar growth equation:
Yit = ait +α𝑘𝑑𝑖𝑡 + λkfit+ βlit + γhit (2)
where lower case letters represent the growth rates of output, domestic capital stock, foreign capital stock, and labour and human capital, and a, l, b and g represent the elasticity of output, domestic capital stock, foreign capital stock, labour and human skill capital, respectively. In a world of perfect competition and constant returns to scale, these elasticity coefficients can be interpreted as respective factor shares in total output. Eqn. 2 is a fundamental growth accounting equation, which decomposes the growth rate of output into growth rate of total factor productivity plus a weighted sum of the growth rates of capital stocks, human capital stock and the growth rate of labour. Theoretically, a, b and g are expected to be positive while the sign of l would depend on the relative strength of competition and linkage effects and other externalities that FDI generates in the development process as discussed in previous sections.
Following the established practice in the literature, Kd and Kf are proxied by domestic investment to GDP ratio (Id) and FDI to GDP ratio (If), respectively in view of problems associated with measurement of capital stock. The use of rate of investment is hinged on the assumption of a steady state situation or a linearization around a steady state. The final form of Equation 2 therefore is
Yit = ai + αIdit + λIfit + γhit + ε it (3) Where it ε is an error term.
Methodology
As has been stated earlier the main aim of this research is to examine the impact of foreign direct investment on economic growth in Nigeria between 1981 and 2018. Time series data used in this analysis was secondary data sourced from central bank of Nigeria (CBN) statistical bulletin (2018) and the World Bank statistical Database (WDI, 2018). The study focuses on four chosen macroeconomic variables: the real gross domestic product (RGDP), trade openness (TOI), foreign direct investment (FDI) and exchange rate (EXR).
Model Specification
The functional form of the relationship of the model is writing as:
RGDP=F (FDI, TOI, EXR,)……….………... (1) Where:
RGDP = Real Gross Domestic Product (dependent variable) FDI = foreign direct investment (independent variable) TOI = trade openness (independent variable)
EXR = exchange rate (independent variable)
The equation (1) model can be change into mathematical model as follows:
RGDP = α0 + β1FDI + β2TOI + β3EXR……… (2) β1> 0; β2> 0; & β3>0 .
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The above equation (2) displays the mathematical shape of relationship between RGDP, which is the explained variable and FDI, TOI, and EXR which are the explanatory variables.
Moreover, the equation (2) can be changed from mathematical to Econometric Model.
RGDP = α0 + β1FDI + β2TOI + β3EXR + ∈t …………..……..……… (3) In equation (3) error term was introduce into the model to estimate the variables that were not captured by the model but affect the dependent variable
∈t = Error term
To get the best result, the equation (3) must be in log for all variables. This is to see the percentage of change in dependent variables when the independent variables change around 1 percent.
RGDP = α0 + β1FDI + β2TOI + β3EXR + ∈t ………… (4) Estimation Technique
A three stage procedure was followed to test the direction of causality. In the first stage the order of integration will be tested using the Augmented Dickey-Fuller unit root tests. The second stage involves testing for the existence of a long-run equilibrium relationship between real gross domestic product, foreign direct investment, trade openness and exchange rate. The third stage involves testing the causal relationship between the variables so as to know the cause of one variable and another this can be achieve by constructing granger causality test The Unit Root Test
Unit root test is applied to see the stationary of the series at the level and first difference test by using Augmented Dickey Fuller (ADF) and also Akaike Information Criteria (AIC). The hypothesis in this test is: H0: δ = 0 (unit root test / not stationary), H1: δ ≠ 0 (no unit root test / stationary). If the value of t-statistic is greater than ADF critical value, the null hypothesis is not rejected (unit root test exists) but if the t-statistic is less than ADF critical value, the unit root test does not exists (so, the null hypothesis is rejected). The following equation 5 and 6 are the equations at level without constant and trend and with constant and trend.
Without constant and trend
∆Yt= δYt-1 + Ut……… (5) With constant and trend
∆Yt = α + βT + δYt-1 + Ut……… (6) The Co-integration Test
The second step is the testing of the presence or otherwise of co -integration between the series of the same order of integration through forming a integration equation. A lack of co-integration suggests that such variables have no long-run relationship. If Yt is a vector of n stochastic variables, then there exists a p-lag vector auto regression with Gaussian errors of the following form:
Auto regression (VAR) of the P given by
Yt = µ +1t-1 + t-p +t ………...(7) Where
Yt is an nx1 vector of variables that are integrated order commonly denoted (1) and t is an nx1 vector of innovations.
This VAR can be rewritten as
Yt = µ + yt-1 + it-1 +t ……………….. ……….. (8)
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To determine the number of co-integration vector, (Johansen 1988; and Johansen Juselius 1990) suggested two statistic tests, the first one is the trace test (trace). It tests the null hypothesis that the number of distinct co-integrating vector is less than or equal to q against a general unrestricted alternatives q = r. the test calculated as follows:
Trace (r) = 〔1⌃t〕 ……….. (9) T is the number of usable observation, and the 1 are the estimated eigenvalue from the matrix.
Granger-Causality Test
The causality test is to see a reaction between the variables. For example, if variable X is granger cause to Y and Y is also granger cause to X, it means that the value after X can help to expected value for the next period of Y and also the value after Y can help to expected value for the next period of X (Sorensen, 2005). The following equation 10 and 11 are the formula for granger causality regression test for two-way variable and Y
Yt = pi=1iYt-1 +iq =1βjXt -1+μ1t………... (10)
Yt = pi=1γiYt-1 +iq =1δjXt -1+μ2t……….. (11)
Results and Discussions
Table 1: Unit Root Test Results
Source; researcher’s Computation from E-views 9.0, * denotes 1% level of significant. ** 5%.
From the ADF test which is presented in table1 above, it is clear that all the variables are not stationary at levels except for foreign direct investment but all were stationary at first difference. This is because, at levels, the observed values of the ADF statistics are not greater than their respective critical values in both intercept and linear trend with the exception of foreign direct investment. While at the first difference, the null hypotheses of all the variables are rejected, given that the observed values of ADF statistics are not less than the corresponding critical values, all at 1% significance level.
Table 2: Johasen Multivariate Cointegration Test (Trace)
Hypotheses
Eigenvalue
(𝝀𝒕𝒓𝒂𝒄𝒆) Statistic
0.05
Critical Value
Prob.**
H0 H1
r=0 r>0 0.402564 47.26544 47.85613 0.0567
r≤1 r>1 0.342425 24.20501 29.79707 0.1919
r≤2 r>2 0.182196 9.533135 15.49471 0.3184
r≤3 r>3 0.068764 2.493499 3.841466 0.1743
Source; researcher’s Computation from E-views 9.0 Trace test indicates no cointegration at 5% significant level
Variables ADF
Level(int.& trend) ADF
First Difference(int.& trend) Order of integration t-statistics p. value t-statistics p. value
RGDP 3.235993 1.0000 5.753704 0.0002* I (1)
FDI 3.567120 0.0116 8.155061 0.0000* I (1)
TOI 1.432173 0.9999 5.590952 0.0005* I(1)
EXR 0.289043 0.9879 7.314104 0.0000* I(2 )
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Table 3: Johasen Multivariate Cointegration Maximum Eigen value
Hypotheses
MAXIMUM Eigenvalue
(𝝀𝒕𝒓𝒂𝒄𝒆) Max-Eigen Statistic
0.05
Critical Value
Prob.**
H0 H1
r=0 r>0 0.482564 23.06042 27.58434 0.1709
r≤1 r>1 0.342425 14.67188 21.13162 0.3126
r≤2 r>2 0.182196 7.039636 14.26460 0.4845
r≤3 r>3 0.068764 2.493499 3.841466 0.1143
Source; researcher’s Computation from E-views 9.0
From the above table 2 & 3, it can be observed that the trace and maximum eigen test reject the null hypothesis of no cointegration i.e (r = 0) at the 5% level of significance. This implies that there is no long run relationship among the variables of interest. Categorically speaking both the trace and maximum eigen test indicate the existence of zero cointegrating vector at the 5% level of significance.
Table 4. Causality Test
Null hypothesis Obs F. statistics Probability
FDI does not Granger cause RGDP
RGDP does not Granger cause FDI 37
0.36077 1.08130
0.7001 0.3520 TOI does not Granger cause RGDP
RGDP does not Granger cause TOI 37
3.53240 1.32569
0.0419 0.2807 EXR does not Granger cause RGDP
RGDP does not Granger cause EXR 37
8.08634 3.16637
0.0016 0.0565 EXR does not granger cause FDI
FDI does not Granger cause TOI 37
0.93036 3.69471
0.4055 0.2008 TOI does not granger cause FDI
FDI does not granger cause EXR 37
0.52670 0.37325
0.5959 0.6916 EXR DOES NOT Granger cause TOI
TOI does not Granger cause EXR 37
0.75954 0.79495
0.4767 0.4609 Source: Authors compilation from Eviews 9.0
From the table above, the focus of this analysis is to examine the relationship between RGDP, FDI, TOI, and EXR. The granger causality test reveal that there is no causal relationship between the variables with an exception of EXR, this is because the probability value of the null hypothesis was less than 0.05 which implies rejection of the null hypothesis. However in the case of foreign direct investment, trade openness and real gross domestic product the result shows absence of causal relationships.
Table 5 VECM
VError correction D(REAL GDP) D(FDI) D(TOI) D(EXR)
Coint Eq 1 0.034 (0.009 ) 1.01 (1.3E) -1.88 (5.0E) 1.11 (1.2E) D(GDP) -1 0.0195 (0.220) -1.63E 92.9E) -2.57E (1.1E) -3.76E (2.7E) D(GDP) -2 -0.3181 (0.224) -2.57E (2.9E) 3.19E (1.2E) 1.58E (2.7E) D(FDI) -1 2.98 (1.6) -0.29 (0.21) -2.36 (0.85) 0.29 (2.00) D(FDI) -2 2.51 (1.6) -0.21 (0.202) -1.23 (0.801) 0.26 (1.895) D(TOI)-1 -1.35 (3.5) -0.04 (0.05) -0.138 (0.18) -0.192 (0.43)
D(TOI)-2 -7.68 (3.3) 0.03 (0.04) 0.34 (0.171) 0.287 (0.406)
D(EXR)-1 -2.59 (2.3) -0.016 (0.03) 0.168 (0.120) 0.530 (0.28) D(EXR)-2 -1.60 (2.5) 0.009 (0.033) 0.377 (0.130) 0.211 (0.031)
C 2.21 (6.7) 0.733 (0.871) -7.49 (3.44) 8.76 (8.15)
Adjusted R2 0.5359 0.2730 0.5715 0.3665
AIC 59.55 4.8150 7.5971 9.2877
Source; researcher’s Computation from E-views 9.0