Impact of Infrastructure on Foreign Direct Investment in Nigeria: An Autoregressive Distirbuted Lag (ARDL) Approach

This study examines the roles infrastructure play in attracting foreign direct investment (FDI) into Nigeria for the period between 1981 and 2014. It also investigates the type of infrastructure that has more impact on FDI attraction. The unit root test results show that none of the variables in the study is integrated of order two, that is, I(2), a condition which justifies the use of Autoregressive Distribution Lag (ARDL) framework. The ARDL Bounds Test approach to cointegration was employed to determine the long-run relationship among the variables in our model and the result shows that there is a long-run relationship between infrastructure and FDI in Nigeria. The result of the estimation of the selected ARDL Error Correction Model shows that none of the infrastructure variables (tractor, telephone lines and electricity) employed in this study is significant to attract FDI into Nigeria in the short-run although electricity production (power supply) was found to influence FDI in the long-run. The study thus recommends that the power sector be revitalized and should be given priority as it will attract FDI, increase national output and move Nigeria closer to actualizing her dream of becoming one of the twenty leading economies in the world by the year 2020.


INTRODUCTION
Every country of the world, especially developing economies, strives to attract foreign direct investment (FDI) because it is a major source of external finance. FDI affords countries with little capital the opportunity to get finance from wealthier countries. Many experts opine that foreign direct investment (FDI) has the capability of speeding up the economic growth process of developing countries (Obiwona, 2001). There are inexhaustible benefits associated with the inflow of FDI that are put to optimal use among which are the opportunity it affords developing countries to have access to modern technology and key administrative ingenuity which are capable of increasing domestic output, creating more jobs, lowering cost of production and raising workers' wages and standard of living, among others (Cohen, 2007).
Furthermore, FDI has been arguably one of the means through which external capital is sourced to augment domestic savings in developing countries owing to the inadequacy of their financial and capital market to finance the various sectors of the economy (Adeoye, 2009). In addition, FDI plays a pivotal role in helping developing economies access the foreign markets on behalf of its people (Obiwona, 2001). Summarily, the proponents of FDI opine that it contributes positively to its recipient's economy through the supply of technology, capital and management wherewithal that are unavailable in the host country as well as creating jobs that would otherwise not be created there (Hill, 2003). It is thus apparent that FDI is important in a country to bridge resources gap, saving-investment gap, technological gap, revenue-expenditure gap, and output/export gap, among others. The aforementioned benefits of FDI are crucial for sustainable economic growth in developing countries.
However, the extent to which a country attracts FDI is a function of many factors which include: labour costs, market size, profitability expectation, human capital, FDI policy, and infrastructure, among others. Many studies have identified infrastructure as the major of source of FDI inflow. Chakrabarti et al (2012) discovered a positive relationship between infrastructure and FDI inflow. Also, Omezzine (2011), and Hakro (2011) discovered that governance infrastructure affects FDI flows significantly.
The availability of infrastructure promotes FDI because it reduces operational costs. Seetanah (2009) claimed that gains resulting from infrastructural development are closely linked with greater accessibility and a decrease in the cost of transportation. He further argued that the availability of public goods reduces a foreign company's cost of doing business thereby increasing its returns or profit significantly. Recent studies also assert that the availability of public goods plays a crucial role in determining the structure of cost and productivity of firms in the private sector (Bénassy-Quéré et al, 2007). Also, Erenberg (1993) asserts that domestic and multinational companies will operate with less efficiency and below their optimal level should public infrastructures not be extended to them because they would have to incur an additional cost of building infrastructures of their own and this will lead to duplication and wastage of the available scarce resources. The study thus, concluded that public infrastructures reduce the cost of transportation.
However, the major problem to Nigeria's low level of FDI attraction is primarily due to low level of savings and investment in infrastructure. The situation of Nigeria is such that the few available fixed assets (infrastructures) are in deplorable states, unemployment rate is on the increase, exchange rate depreciates incessantly, persistent fall in crude-oil price in the international market and a relatively high monetary policy rate (interest rate), among others.
These discourage local investors from borrowing, hinder investment and incapacitate government from fully executing capital projects.
Nigeria's quest for economic growth and development lies primarily in the attraction of Foreign Direct Investment (FDI). In recent years, the attraction of foreign direct investment has gathered impetus as the Nigerian government is spending large sums of money on infrastructures so as to attract foreign companies into the country. This effort is manifested in the signing of eleven (11) Double Taxation Treaties (DTTs) and six (6) Bilateral Investment Treaties (BITs) so as to encourage FDI inflow to Nigeria. The Nigerian government understands that, in order to attract attracting Foreign Direct Investment, it is needful to invest in infrastructure which will promote a sound macroeconomic environment in Nigeria.
The Nigerian government has put in place a number of infrastructural institutional frameworks overtime to help in the development and sustenance of infrastructures in Nigeria. The Nigerian public officials as well as state governors and federal ministers frequently visit advanced economies of the world such as USA, Australia, Europe, China, Canada, Japan and South Korea to implore foreign organizations, government and individuals to invest in Nigeria promising to give them incentives like tax incentives, low interest loan, grants, and increasing government expenditure on infrastructure, among others.
It is against this background that this study's primary objective is to empirically investigate the impacts of infrastructure on foreign direct investment inflow to Nigeria from 1981 to 2014. Specifically, it determines if there exists a long run relationship between infrastructure and FDI inflow in Nigeria or if these two macroeconomic variables converge in the long run.

LITERATURE REVIEW
There are myriads of studies conducted on the relationship between infrastructure and foreign direct investment (FDI) for different countries of the world. The objective of the studies was to investigate or examine the relationship between infrastructure and FDI as well as how this relationship influences economic growth. Attraction of foreign investment is not an end in itself but a means to an end as its ultimate goal is to achieve economic growth.
Chakrabarti et al (2012)  show that FDI and economic growth has a significant positive relationship and that the interaction between trade openness and infrastructure increases FDI inflow slightly.
Wheeler and Mody (1992) where ∆ denotes the first difference operator, α 0 is the drift component, and ɛ t is the white noise residuals

Unit Root Test
It is a standard practice to carry out unit root test for macroeconomic variables to help examine their stationarity state and thereby prevent spurious results. Thus, this study employs the Augmented Dickey-Fuller (ADF) and Phillip Perron (PP) approach to unit root to test the stationarity state of the variables.
Although unit root test is not required in Autoregressive Distributed Lag (ARDL) framework, it is necessary to test for unit root to ensure that no variable in the model is found to be stationary after second difference, that is, I(2) because ARDL procedure does not accommodate I(2) series. Pesaran et al. (2001) and Narayan (2005) assert that the computed F-Statistics from the estimation of a model with I(2) variables using ARDL approach will not be valid and reliable.  -4.428800a* -6.028332b* I(0) -4.737311a* -5.631615b* I(0) Source: Author's Computation using Eviews9 Note: * and ** imply statistical significance at 1 percent and 5 percent respectively. a, b and c imply model with intercept, trend and intercept, and none respectively. I(0) and I(1) imply that the time series is stationary at level and first difference respectively.

Autoregressive Distributed Lag (ARDL) Bounds Test Approach to Cointegration
Sequel to the result of the unit root test, cointegration test will be carried out using ARDL Bounds Test approach to cointegration. The choice of this approach is premised on the fact that our variables are integrated of different orders [(I(0) and I(1)], thus negating the use of Engle-granger and Johansen Cointegration test approach. Pesaran and Shin (1999) and Pesaran et al (2001) developed the ARDL cointegration approach which has three major advantages over other traditional cointegration approaches. Firstly, the ARDL framework does not require that all the variables under study be of the same order of integration; it accommodates series which are I(0) or I(1) or both. Secondly, it is relatively more efficient using small sample sizes. Thirdly, the ARDL framework obtains unbiased estimates of the long-run model (Harris and Sollis, 2003).
Cointegration test is carried out to determine the existence of a long-run relationship between the dependent and explanatory variables. The rule of ARDL Bounds test of cointegration states that the null hypothesis should be rejected if the value of the computed Fstatistic is greater than the upper bounds value and accepted if the F-statistic is less than the lower bounds value. The ARDL cointegration test will be said to be inconclusive should the computed F-statistic fall within the lower and upper bound.
The result of ARDL Bound Test is presented in table 2 below. The result shows that the null hypothesis of no cointegration among the variables should be rejected since the value of the computed F-statistic (4.71) is greater the upper bound critical value of 4.35 at 5 percent level of significance. This implies that there is a long-run relationship among the dependent variable (LFDI) and the explanatory variables. Since the variables of the model are cointegrated, we will proceed to estimating the ARDL Error Correction Model (ECM). Since the empirical findings lead to the conclusion that there is a long run relationship among the variables in our model, the marginal impacts of electricity production, telephone lines and tractors on foreign direct investment in Nigeria is examined by estimating equation (II) for the short-run (ECM) and long-run coefficients of the ARDL (2,1,0,0) model selected using the Schwarz Criterion (SC). The result of the estimation is presented in Table 3.
The result of the estimation of the long-run coefficient of equation (II) shows that, in the long run, electricity production has a positive and significant influence on the inflow of foreign direct investment to Nigeria such that a one percent increase electricity production will lead to approximately 2.48 percent increase in foreign direct investment (FDI). The result also shows that, in the long run, a one percent increase in telephone lines and tractor will lead to approximately 0.01 percent and 0.66 percent decline in the inflow of foreign direct investment to Nigeria respectively. However, telephone lines and tractors do not have significant effect in attracting FDI to Nigeria in the long run. The result of the estimation of the short-run coefficient from the error correction model (ECM) version of the selected ARDL (2,1,0,0) model is presented in Table 4. The result shows that the error correction term is negative and significant at 1 percent thereby validating the existence of a stable long-term relationship among the variables of the model.
The error correction coefficient (-0.84) reveals that the speed of adjustment from a short-run deviation is quite fast as approximately 84 percent of the disequilibrium in foreign direct investment resulting from the shock in the previous period will converge to the long-run equilibrium in the current period. Furthermore, the result shows that the estimated coefficient of first-period lag of FDI has a negative and significant relationship with FDI in the short run.
Also, there is a positive relationship between electricity production and FDI in the short run such that a one percent increase in electricity production leads to approximately 0.92 percent increase in FDI. This result is plausible and in consonance with Essia and Onyema (2012) and Anyadike (2012) because the availability of power supply reduces cost of production and increases investors' profit. An inverse relationship exists between telephone lines and FDI such that a one percent increase in the former discourages foreign investor from investing in Nigeria by reducing the volume of FDI by approximately 0.01 percent. Also, an inverse relationship was found to exist between tractor and FDI in the short-run such that a one percent increase in number of tractors used in agriculture will lead to a 0.55 percent decline in FDI. This result is plausible in that the oil and service sector are the targets and destinations of foreign investors because they are the booming sectors of the Nigerian economy. However, the result shows that electricity production, telephone lines and tractors do not have significant effect on the attraction of FDI into Nigeria. In addition, the adjusted R-Squared value shows that the model explains about 88 percent of the variation in FDI.
Also, the probability value of the F-Statistic shows that the explanatory variables in the model jointly influence the volume of FDI inflow to Nigeria in the short-run. The Durbin-Watson Statistic shows the absence of autocorrelation in the model.  Lastly, the stability of the long-run coefficient and the short-run movements for the ARDL Error Correction Model is examined using the Cumulative Sum (CUSUM) and Cumulative Sum Squares (CUSUMSQ). The rule is that if the plots of the CUSUM and CUSUMSQ statistics stay within the critical bounds of 5 percent significance level, the model is said to be stable. In line with this condition, a critical look at the plots in Figure 1 and 2 below shows that the ARDL Error Correction Model is stable because the CUSUM and CUSUMSQ statistics fall within the 5% critical bounds.

CONCLUSION AND POLICY RECOMMENDATIONS
This study examined the impact infrastructure on foreign direct investment inflow to Nigeria using Autoregressive Distributed Lag (ARDL) framework. The infrastructures considered in this study are electricity production, telephone lines and tractors which are important drivers of output in the manufacturing, services and agricultural sector respectively. The results of the unit root test show that none of the variables is integrated of order two, I (2) which justifies the use of ARDL Bound Test approach to cointegration and the estimation of longrun and short-run ARDL model. The result of the cointegration test shows that the long-run relationship exists among the variables in the ARDL model as the computed F-statistic is greater that the upper bound critical value at 5 percent significance level. The result of the long-run coefficient reveals that only electricity production has a positive and significant impact on FDI in the long-run which implies that electricity production plays a significant role in attracting foreign direct investment to Nigeria. However, none of the infrastructure variables has significant effect on FDI inflow in the short-run. Diagnostic and stability test results show that the model is stable and does not violate any of the OLS assumptions of homoscedaticity, no serial correlation and normality of residuals.
The significant impact electricity has in attracting FDI to Nigeria in the long run shows that the Nigerian government and the private sector should gear efforts towards resuscitating the ailing power sector, standardizing it and devising others means of generating alternative power supply so as to realize the goal of becoming one of the leading twenty economies in the world by the year 2020. Due to the pivotal role power (electricity) supply plays as a propeller of the FDI and economy growth, it should be given adequate attention and preference. Also, international donor agencies like UNO, Paris Club, World Bank, IMF and Nigeria's friend countries, among others, should focus primarily on developing the Nigerian power sector.