External capital is one of the major sources of investible resources in most developing Countries and is made of foreign direct investment (FDI),foreign aid (AID) and external debt. In this study, the relative impact of external capital on manufacturingoutput, on one hand, and on Economic growth, on the other hand, in Nigeria, are examined. Economic growth is proxied by gross domestic product (GDP) growth. Employing the Ordinary Least Squares (OLS) method and an annual time series data for the period between 1982 and 2013 obtained from World Bank’s website, it is found that in the short-run, a $1 inflow of FDI is accompanied by a statistically insignificant 0.45 cent reduction in manufacturingoutput, a $1 inflow of foreign aid is accompanied by a statistically significant 49 cents reduction in manufacturingoutput and a $1 inflow of external debt is accompanied by a statistically significant 18 cents reduction in manufacturingoutput. This implies that FDI has a zero impact on manufacturingoutput while AID and external debt has a significant negative impact on manufacturingoutput in Nigeria. Therefore, all forms of external capital have different levels of negative individual impact on manufacturingoutput in Nigeria. Also, it is found that in the short-run, a $1 inflow of FDI is accompanied by a statistically significant $13.4 reduction in economic growth, a $1 inflow of aid is accompanied by a statistically insignificant $5.68 increase in economic growth and a $1 external loan inflow is accompanied by a statistically insignificant $1.73 increase in economic growth. This implies that FDI has a significant impact on economic growth, while AID and external debt has an insignificant or zero impact on economic growth. Therefore, not all forms of external capital do have significant impact on economic output in Nigeria. It is therefore recommended that government should make the business environment more investor friendly, make doing business in Nigeria easy, ensure prudent borrowing, ensure appropriate utilization of borrowed funds, ensure project continuity and ensure financial inclusiveness.
Further, given the economy’s weak technological and industrial base, industrial activities were organized to depend largely on imported inputs and Nigeria has employed a number of strategies intended at attracting FDI inflows and to enhance the performance of the manufacturing productivity, in order to revamp economic growth and development. However, as a result of the collapse in global oil price in the early 1980s which is the major source of the country’s foreign earning, there is a drastic decrease in the earning from oil exports revenue. As a consequence, the import-dependent industrial structure that emerged, could not be sustained as earning from exports became inadequate to pay for the huge import bills. All the policy measures adopted to improve the situation such as the stabilization measure of 1982, as well as the restrictive monetary policy and a stringent measure of 1984, however, failed. This led to the introduction of the Structural Adjustment Program (SAP) in 1986 whose main aim is to reduce the high dependency of the economy on crude petroleum as a major foreign exchange earner by promoting non-oil exports particularly manufacturing goods. Although these went a long way in attracting FDI flows into the economy, as the country becomes the second largest recipient of FDI flows among low- income countries (CBN Statistical Bulletin 2010).
The coefficient of determination for the fitted model has a value of 0.513 as shown in table 4.3. This suggests that the estimated model explains about 51.3 per cent of the variation in manufacturing value added in Nigeria. The F-statistic for this model is 2.607, with a p-value of 0.0814. This F-statistic is significant, implying that the regressors in the model collectively have significant impacts on manufacturing value added in Nigeria. The Durbin Watson statistic for this model is 2.02. Since this statistic is approximately 2, we conclude that there is no problem of autocorrelation in the estimated model. More so, going by the result of the Breusch-Pagan Lagrange multiplier test for heteroskedasticity, we do not find evidence of heteroskedasticity in this model. The statistic for this test is 0.04, and the p-value is 0.838. Since this p-value is greater than the 5 percent and 10 per cent conventional significance levels, we do not reject null hypothesis that residuals of this model have constant variance. The variables of the model also met their respective a priori expectations aside exchange rate. Public education expenditure, primary school enrolment, FDI, per capita income and exchange rate are all expected to have positive impact on manufacturing growth in Nigeria. The estimated coefficients are positive for all these variables except exchange rate. Again, this does not present a problem, as this variable is not found to be significant in the model.
Abstract- The research investigates the effect of foreign direct investment (FDI) on the manufacturing sector in Nigeria, and its importance in the Nigeria economy in general. The main issues in this paper relates to understanding the effects and impact of foreign direct investments on the manufacturing sector, as well as our ability to attract adequate funds, sufficient enough to accelerate the pace of our economic growth and development. In order to analyse the data, both econometric and statistical methods were used. The econometric regression model of ordinary least square was applied in evaluating the relationship between foreign direct investment and major economic indicators such as manufacturingoutput, exchange rate and interest rate. The model revealed a positive relationship between foreign direct investment and each of the variables (manufacturingoutput, exchange rate and interest rate). Foreign Direct Investment has a positive relationship on the manufacturing sector in Nigeria. In addition, there is a positive and significant relationship between Exchange rate (EXCH) and manufacturingoutput (MOUTPUT) in Nigeria. Some recommendations were made therein that government should step up efforts in attracting foreign direct investment into the sector by ensuring that investor confidence is protected. The study also suggest that despite the fact that the importance of FDI cannot be over accentuated, there is the need for government and policy makers to realize the fact that the fundamental element in any successful development strategy ought to be the encouragement of domestic investors first before going after foreign investors.
Foreign Direct Investment (FDI), especially Multinational Enterprises (MNEs) 1 , through by bringing in a bundle of tangible and intangible assets such as technology and know-how, skill, efficient marketing and distribution networks, managerial capabilities etc., provides impetus in accelerating export performance in host economies. This is especially true for an emerging market economy including India. MNEs access foreign markets with much more ease than their domestic counterparts in the host country and often use the host country as an export platform. Again the MNEs, given their scale of operations and a wide array of intangible assets also have the capability to overcome the huge sunk costs while entering export markets. 2 These specific advantages give the foreign firms an edge in the export market than the domestic firms. Apart from ownership, the recent literature shows that firm heterogeneity measured in terms of differences in productivity and/or sunk costs is one such factor determining export performance. This paper investigates into the factors including ownership (foreign vis-à-vis domestic) pattern of firms explain post-reforms export performance across manufacturing industries in India.
My hypothesis is that the effect of industry-level FDI, in terms of spillovers, will be differential based on the size of the plant. My empirical analysis, that covers 5425 plants in India’s manufactur- ing sector, confirms this hypothesis. While larger plants experience a differential increase in total employment – which includes employment of both skilled and unskilled workers —– as well as average wages paid out to both skilled and unskilled workers, relative to average sized and smaller plants, the smaller plants experience negative spillovers for employment of production workers and average wages paid out to both skilled and unskilled workers. This suggests that there are strong market reallocation effects, and mainly poaching of higher quality production and skilled workers from average sized to small plants as there is increased foreign-ownership of plants in an indus- try. Further, increased industry-level FDI is associated with a relative increase in demand for male blue-collar workers at bigger plants relative to average sized to small plants while the demand for female blue-collar workers remains unaffected. While there is evidence of an increase in skilled workers, there are no differential compositional changes at big plants, neither is there evidence of an increase in relative wage skill premium at bigger plants. While this may suggest that increase in industry-level FDI in India is not skill-biased in its demand for workers nor does it contribute to an increasing pool of skilled workers, a careful analysis at the regional level provides a better picture of the actual effects. Analyzing the effects of industry-level FDI on different regions reveals that even average to small sized plants in regions that receive the highest FDI experience an increase in skill composition of workers as well as the wage skill premium. This indicates that perhaps a critical mass of FDI is required in order to influence the demand for skilled workers at plants as well as contribute to the pool of skilled workers in an industry.
parametric approach. In fact, there is a substantial part of studies estimating technical efficiency by using parametric, non-parametric approach or both of them. Badunenko, Fritsch, & Stephan (2006) examines determinants of technical efficiency of German manufacturing firms by exploiting a database of Germany cost structure Census from 1992 to 2004 including 35.000 firms within 252 industries. Technical efficiency depends on the location of the firm headquarters, firm’s size and R&D intensity. Burki&Dek (1998) study technical efficiency and economy of scale of the Pakistani firms in the 09 manufacturing industries by applying Data Envelop Analysis (DEA – non-parametric approach). The result is that surveyed firms could increase output by 6% to 29% by improving technical efficiency. Lundvall &Battese (2000) exploit a unbalanced panel data to calculate technical efficiency of the Kenyan manufacturing firms by applying stochastic frontier production method (SFP-parametric approach). The authors find that technical efficiency could be affected by the firm’s size. In addition, Mahadeven (2000) calculates technical efficiency of the 28 Singapore manufacturing industries from 1975 to 1994 by applying SFP method. The result is that the technical efficiency of the observed firms is 73% in average. Moreover, there are two important determinants of the technical efficiency: the capital intensity and the labour quality. Interestingly, Wu (2000) uses input-oriented distance function approach to calculate the technical efficiency of FDI firms in China between 1983 and 1995 and finds that the FDI performance has inverted J-shape form.
We contribute to the existing literature in several ways. First, we argue that prevailing measurement of vertical linkages does not allow proper identification of entire spillover benefits as it fails to differentiate between the channels through which spillovers occur. This is, to our best knowledge, the first study that investigates the spillover effects of foreign firms on the total factor productivity of local manufacturing firms by using four measures of vertical FDI spillovers: two related to backward linkages and two to forward linkages, each arising from manufacturing and service sectors, respectively. This enables us to shed more light on the customer-supplier relationship between domestic and foreign firms in two main sectors of the economy. Second, drawing on the notion of absorptive capacity (Cohen and Levinthal, 1990; George and Zahra, 2002; Narula and Marin, 2003), which highlights that ability of local firms to absorb the external knowledge depends on the interaction between the mechanisms by which they occur and the existing absorptive capacity (Blalock and Simon, 2009; Sanchez-Sellero et al., 2014), we evaluate the moderating role of domestic firms’ investment in intangible assets and human capital. By using interaction terms between foreign presence and human capital, we explore the additional channel of horizontal spillovers related to worker mobility. Third, we investigate the heterogeneity of forward linkages in services which depends on the knowledge intensity of the service sector.
Today, in order to flow with the trend of globalization and trade liberalization in global economic system, Nigeria is a member of and signatory to many international and regional trade agreements such as International Monetary Fund (IMF), World Trade Organization (WTO), Organization of the Petroleum Exporting Countries (OPEC), Economic Community of West African States (ECOWAS), and so many others. The policy response of such economic partnership on trade has been to remove trade barriers, reduce tariffs and embark on outward – oriented trade policies. Despite all her efforts to meet up with the demands of those economic partnerships in terms of opening up her border, the economy has struggled vigorously to stimulate growth through openness to trade. In fact, it appears that as the country makes conscious effort to boost her economic growth by opening up to trade with the global economy the more she becomes worse- off relative to her trading partners in terms of country output growth. Based on the above challenges, the study answers the following research questions: What are the effects of degree of openness on financial integration output in Nigeria? Has exchange rate impacted the manufacturing sector output as a result of globalization in Nigeria? What is the impact of trade openness on Transportation sector as a result of Globalization in Nigeria? What is the impact of oil price shocks on exchange rate as a result of Globalization?
Paradoxically, the distortionsinbuilt in an overestimated exchange rate period are barely a topic of debate in developing countries, especially Nigeria that rely on importation for production and consumption (Obadan, 2006).In Nigeria, the exchange rate policy has undergone substantial transformation from the immediate. However, in spite of these different methods of determining exchange rate, a realistic exchange rate has not been found for naira because the existing exchange rate systems had continued to widen thegap between the official and the parallel markets and had failed to prevent disequilibrium in the foreign exchange market (Amassoma, 2016). Intuitively, it is suggested that employment growth, exchange and inflation rate reduction are closely related. This is based on the fact increase in employment are enhances industrial performance (output), while reduction in exchange and inflation has the capacity of increasing employment and thus, industrial output increase. Olotu et al. (2015) view this scenario as a result of an inability to fully utilize available factors of production and argue that unemployment growth rate in Nigeria is rising as a result of the extreme high number of graduates produced every year, and industries lack the ability to absorb them. The country’s growth and business environment which has not been able to significantly expand the formal sector has left the economy largely trapped in its pre-2001 trajectory when it started to witness a sustained expansion in its non-oil economy.
Electricity is regarded as sine quo non for any meaningful social, economic and modern scientific advancement of any country in the world. It is regarded as a force and engine room of the industrial sector. However, in Nigeria, instability in power supply is negatively affecting manufacturing efficiency. Time series data for 1981 until 2015 was used to examine the symmetric relationship between the electric consumption, manufacturingoutput and financial development in Nigeria. The result indicates the co-movement in the variable over long time horizon, meaning that any inefficiency in electricity supply would impedes industrial output. Moreover, the Granger causality test based on vector error correction framework shows the presence of causality between power utilization of manufacturing firms and economic growth without feedback. In this sense it can be stress that stable electricity consumption is important factor for Nigeria’s manufacturing sector. The result of variance decomposition further indicates that the variation in the industrial output responds more to shocks in the electricity supply than its own shock. This finding suggests that energy is the engine of manufacturing sector in Nigeria.
First the UECM is estimated that contains Carbon dioxide emissions per capita as dependent variable as shown in Table 2. The estimated UECM is given below which includes long run as well as short run coefficients. This is parsimonious form of equation, from which insignificant terms are deleted. The outcome of test depends on the lag selection that is p=1, selected on the basis of AIC (Akaike criterion). In the model dummy variables are also included to check the impact of structural breaks in data. The significant dummies were in year 2007 and 2008. The year 2007 dummy represent structural break in FDI inflow in transport, storage and communication sector. The year 2008 dummy show structural break in FDI inflow manufacturing sector. Both dummies are significant. As stated by the Board of Investment Pakistan, Foreign direct investment inflow in the country was at 485 million dollars during 2001-02, following which there was a rise in FDI inflow in the country for the subsequent six years. The FDI inflow spiked in the year 2007-08, attaining a massive level of 5409 million dollars. After that, there was a gradual fall till 2011-12 level. If the spike through 2007-08 is taken as a point of reference among 2001 and 2012, 10–15 percent increase was recorded till 2007-08, after that there was a decline of 89 percent till 2011-12. One of the reasons was the democratic government in Pakistan which gained foreign confidence and engrossed foreign direct investment in Pakistan. Secondly the democratic government failed to solve the problems of the energy sector. Energy crisis has increased in the past three years. Continuous power cut downs and riots took place in Pakistan, specifically at
At the firm level, the empirical studies provide mixed evidence of the spillover effect on the local firms. Most empirical studies focus on horizontal (intra-industry) spillovers and find no or negative effects of FDI on the efficiency of domestic firms (Haddad and Harrison (1993), Aitken and Harrison (1999), Konings (2001), Yudaeva et al. (2003)). Several studies, particularly on vertical (inter-industry) spillovers, provide positive evidence of technology spillovers from foreign to domestic firms (Blalock and Gertler (2002), Schoors and Van der Tol (2002), Smarzynska (2004)).
Firms in Anambra State of Nigeria are facing a competitive environment characterized by the globalization of markets, increasingly complex business problems, and the acceleration of change phenomena. Consequently, the traditional sources of competitive advantage, such as protected markets, and physical and financial assets, have lost importance compared to knowledge assets (Foray and Lundvall 1996; Grant, 1996; Johnson and Rolf, 1998). Knowledge management is frequently cited as an entacedent of organizational performance. If organizations implement KM practices successfully, they are able to perform intelligently to sustain their competitive advantage by developing their knowledge assets (Wiig, 1999). Thus it is essential to know how to generate knowledge, how to disseminate it in the organization and what factors facilitate these processes (Stewart, 1997; Davenport and Prusak, 1998). Most of the firms in Anambra State do not put KM programs in place because of inadequate planning and so control becomes very difficult. Some organizations in Anambra State of Nigeria are no investing much on Research and Development (R and D) and investment in research by the state government is irregular.
longer matter, knowledge intensive business services (KIBS) heavily rely on tacit or combination of codified and tacit knowledge (Miles, 2005; Kox and Rubalcaba, 2007; Shearmur and Doloreux, 2008), thus making spatial proximity a fundamental attribute (Koch and Stahlecker, 2006; Landry et al., 2012; Doloreaux and Sharmour, 2012; Ciarli et al. 2012). A defining feature of KIBS is that knowledge is their essential asset (Miles, 1994). They provide intermediate products to companies and offer intangible services with the possibility of high adaptation according to the client needs (den Hertog, 2000; Toivonen, 2004). Their continuous creation and transfer of knowledge requires cooperation and high interaction with customers in order to transfer tacit knowledge (Koch and Stahlecker, 2006; Arundel et al., 2007; Doloreaux and Shearmur, 2012). This in turn creates the incentive for MNCs to internationalize their knowledge intensive activities through investing abroad (Miozzo and Soete, 2001), and providing stronger forward linkages with their clients (Miozzo and Grimshaw, 2008; Mariotti et al., 2013). Hence, MNCs in KIBS are inherently different from those in manufacturing industries. KIBS can supply various types of inputs at varying levels of complexity, which support and/or improve the users’ existing innovation processes (Shearmur and Doloreux, 2013). In this context, they bring new knowledge, provide solutions and add or compensate for missing internal capacity by transforming information and knowledge into personalized solutions aimed at specific users’ needs (Tether and Hipp, 2002). Internationalized firms in the manufacturing sector are often required to develop new routines and organizational processes and therefore must acquire new knowledge (Ripolles-Melia et al., 2010). This implies that the interaction with KIBS may increase their internal capabilities (Shearmur et al., 2015).
Therefore with the integration of international capital markets, FDI story of Nigeria today is dominated by the oil industry, which was not so, at independence in 1960, there was a widespread of FDI presence in the economy. Policy design thereafter narrowed FDI performance and decades of political instability, endemic corruption and economic mismanagement further reduced Nigeria ability to attract and retain FDI. The return of democracy in 1999 has created the opportunity for economic renewal and the attraction of more seeking FDI to Nigeria. The Government of Nigeria undertook ambitious measures to reap the benefits from FDI with a view to improve the investment climate, the policy has started bearing fruits and will certainly provide a more conducive environment to private investment and enhance the attractiveness of FDI to the Nigeria’s large and growing market. The policies were the induction of the National Economic Empowerment and Development Strategy (NEEDS), at the national level and it was associated with poverty reduction at the state and local levels, State Economic Empowerment and Development Strategy (SEEDS) and the Local Economic Empowerment and Development Strategy (LEEDS). NEEDS was adopted in 2003, it was meant to guide public policies until 2007. The broad agenda of the social and economic reforms (NEEDS, SEEDS and LEEDS) were based on four key major strategies:
This paper follows a systematic time series econometrics approach to investigate the determinants of FDI flow to Nigeria during 1970-2006. The results of unit root test and co-integration test are presented in Table 1. In this study the unit root tests confirm that all the variables are non-stationary at level (Table 1). Augmented Dickey Fuller (ADF) and Phillips Perron (PP) Tests also confirm that all the variables are difference stationary (see panel A of Table 1). Hence Unit Root Test results strongly suggest that all the variable are integration of order one or I(1). Since all the variables are in same order of integration we should apply co-integration technique. Fig 1 also confirms the co-integration among natural resource outflow and FDI flow to Nigeria during 1970 -2006. Applying Johansen (1988) approach we find the number of co- integration equations among the variables. Co-integration test results are presented in the Panel B of Table 1. At 5 percent level of significance, results suggest only one co- integrating equation and confirm significant long run relationship among the variables. Here error correction model (ECM) is useful for short run dynamics with
This paper investigates the recent surge of FDI in Nigeria, which is poor in terms of income but rich in natural resources. This study examines empirically whether FDI is resource seeking in Nigeria and its determining factors. Applying time series technique this paper observes that FDI flow to Nigeria is resource-seeking FDI during 1970-2006. In long run, the natural resource outflow, market size and openness have direct impact on FDI inflow while risk factors like inflation rate and foreign exchange rate have indirect effect. Finding in long run supports the literature. The contribution of this paper is the short run dynamics among major macroeconomic variables and direction of their causal linkage. It should be helpful for policy makers and macroeconomics managers for managing the nation.
For the statement that there is no positive Global Effect of Product Manufacturing on the Nigeria Business Competitive Position on Some Selected Institutions in South east Nigeria, the responses are Strongly Agree, Agree, Undecided, Disagree and Strongly Disagree. They have numbers of 7, 6, 7, 199 and 281 respective. These give a calculated z value of -45.950. All in all, the first statement which is a negative statement had a negative z value of -45.950. The two positive statements have positive z values of 45.950 and 45.606 respectively. The two negative statements have calculated z values which are less than the table z value at 95% confidence level which is 1.645. The positive statements have calculated z values which are more than the Table z values at 95% confidence level which is 1.645. This means that most of the respondents disagree or strongly disagree with the negative statements. Also most of the respondents strongly agree or agree with the positive statements.