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Impacts of Macroeconomic Indicators on Inward FDI in Nigeria:
1981 2016
Abstract
Introduction
–
Dr. Ochuko Benedict Emudainohwo
Government's macroeconomic intervention policy are designed to attainingfull
employment (low unemployment), stable prices (low inflation rate), high and sustainable rate of economic growth, rise in average living standards, just
distribution of income and keeping the balance of payment in equilibrium (Abata,
Kehinde & Bolarinwa 2012; Adefeso & Mobolaji, 2010). An economy that achieved
macroeconomic policy objective has an advantage of attracting inward FDI. Macroeconomic policy management is aggregating macro-economic variables
having some common features to improve the performance of an economy as a
whole.
economy as a whole.
This paper examines the impact of macroeconomic indicators on FDI inflows in
Nigeria using secondary data extracted from Central Bank of Nigeria, World Bank
World Development Indicator and UNCTAD. The study adopted Fully Modified
Ordinary Least-Square Regression Model. The study finds long-run relation among the
variables. Over the period examined, total government expenditure, trade openness
and marker sizeproxy with GDP have positive impact on FDI inflow into Nigeriawhile
real effective exchange rate has negative and insignificant bearing with FDI inflows
into Nigeria. However, only total government expenditure and trade openness are
statistically significant to explain FDI inflows into Nigeria over the period examined.
The study suggests dedicating part of government expenditure for building
infrastructural facility and strong institutions that will minimise transaction cost to
foreign investors, and adopt policy that will appreciate exchange rate in Nigeria.
Key words:macro-economic, fully modified ordinary Least-square regression,
foreign direct investment, government expenditure, exchange rate, trade
openness, and market size.
JEL Classification:C32, E70, F23, F62.
,
Figure 1: Trend of FDI (N, millions) inflow into Nigeria over the period 2006 to 2016
Source: Output of Stata13 Econometric Software
64
1. Dr .Ochuko Benedict Emudainohwo is a Lecturer in the Department of Economics, Delta State Uniberity, Abraka, Delta State, Nigeria.
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
Source: Output of Stata13 Econometric Software
Figure 1 shows that value of FDI rise from 2006 to 2013 and thereafter, it has been experiencing a downward trend. In the same vein, the macro-economic factors have
also experienced varied movement partly due to government policy to stabilise and
or improve the economy for attracting inward FDI. Given that
(OECD, 2002)
The remaining section is organised as follows: Section2 is literature review and
hypotheses formulation. Section 3 is source of data and methodology. Section 4 presents empirical re port, and section 5 is conclusion and summary.
This section review extant literatures and formulates hypotheses with important
macro-economic determinants of FDI discussed in previous literature. Among these
determinants are: government expenditure, real effective exchange rate, trade openness, market size and GDP growth potential of the host economy(Walsh & Yu,
2010). From the reviewed literatures, the specific independent variables that will be
adopted for this study are discussed as follows:
Traditional Keynesian macroeconomic predict that public expenditure contributes to positive economic growth through multiplier effects on aggregate demand,
increase in government consumption, increase in employment and investment
(Alimi, 2014).Oladipo (2013) examines the relation between government recurrent
expenditure and FDI using time series data for the period 1985-2010 in Generalised
Method of Moment (GMM) estimates, and showed that government recurrent expenditure has strong and positive im pact on FDI.Muhammad, Khan, Hunjra,
Ahmad &Chani (2011) studied the link among public spending, FDI and economic
growth in Pakistan for the period 1975 to 2008 based on simple accounting
framework. They showed that public expenditure slowdown economic growth while FDI is positively associated with growth and this remains strengthens until
public spending grow less than 6 per cent per annum and beyond this level positive
effects of FDI become fragile and becoming uninteresting to attracting FDI i nflows.
H : Government expenditure have positive relation with FDI inflow in Nigeria.
Exchange rate play a key significant role in trades and flows of FDI particularly due
to its rate of fluctuation (Ullah, Haider& Azim 2012; Chakrabarti, 2001) and it has a
major effect on macroeconomics performance of country's (
2014; Cushman,
1985). The exchange rate makes it possible to convert domestic currencies into foreign currencies and vice versa. Exchange rate is, therefore, the price of one
currency in terms of another currency. The exchange rate assumes relevance because
of cross-border flows of goods, services, financial assets and funds transfer.
FDI enhances
growth and economic development of the host countries, while economic
growth is directly related to attracting FDI inflows , this study intends to add to existing literature, the macro-economic drivers of FDI in
Nigeria, a developing economy.
Literature Review and Hypotheses Formulation
Government expenditure
Exchange Rate
Muhammad,
Muhammad, Amjad, Muhammad, Mansoor, Iltaf&Tehreem
1
,
,
65
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
Theoretically, depreciation of the host country currency decreases the relative total
cost of production in terms of a higher valued foreign currency and increases return on capital, and hence induces inward FDI (Seo, Tarumun& Suh 2002). Where there
is depreciation of host country currency, some assets will cost less to foreign
investors: the depreciation of the host economy currency increase the relative wealth
position of foreigners and hence lower the relative cost of capital (Froot& Stein,
1989).Similarly, weak exchange rate is assumed to make host economy currency to be
cheaper to foreign investors and thus has a systematic effect on attracting inward
FDI. Froot& Stein (1989) show that an economy with weaker currency tends to
attract inward FDI within an imperfect capital market model and thus, a stronger real
currency exchange rate of the host economy will encourage investing at
home.Sharifi-Renani&Mirfatah (2012) in their evaluation of the determinants of inward FDI in Iran using Johansen and Juseliu's co-integration system approach
model for the period 1980Q2 to 2006Q2, find that in Iran, exchange rate has positive
relationship with inward FDI. Consistent positive influence of exchange rate level
on FDI was also reported by Seo, (2002) who examined the link between
exchange rate with FDI flows to Korea over the period 1985 to 2000, using OLS. Ullah (2012) studied the relationship between FDI with exchange rate using
time series data for the periods 1980 – 2010 for Pa kistan. It was reported that FDI is
positively associated with Rupee depreciation and exchange rate volatility dissuades
FDI.Ehimare (2011) also show that exchange rate has positive effect on FDI in
Nigeria. Edwards (1990) support a significant and positive correlation between exchange rate and FDI. Oladipo (2013) also showed that exchange rates have
significant and positive correlation with FDI in Nigeria.
On another hand, it is argued that the weaker the currency of a country the less likely
for foreigners to invest in that location because, the income stream from a country
with a weak currency is associated with an exchange rate risk (Chakrabarti, 2001; Aliber, 1970).The researcher is of the view that using earnings from an economy
with a weak currency for investment in an economy with a strong currency may
result in higher cost of investment to the foreign investors. In an examining the
impact of changes in exchange rate in China on FDI, Jin&Zang (2013) used monthly
FDI data in China and index of real exchange rate of RMB for the period January
1997 to September 2012. They showed that appreciation in RMB promotes FDI after the reforms in the exchange rate regime in 2005. Strong negative correlation
between exchange rates and FDI is supported by Blonigen&Feenstra (1996).
Among the main objectives of exchange rate policy in Nigeria are to preserve the
value of the domestic currency (Naira), and the overall goal is of macroeconomic
stability. Nigeria has operated several exch ange rate regimes which can be sub-divided in to 2: fixed exchange rate regime from whence Central Bank of Nigeria
(CBN) started operation in 1959 to June 1986 when structural adjustment
programmes was introduced; and flexible exchange rate regime from June 1986
with the exchange rate liberalisation policy under SAP to date (CBN, 2016). As
noted earlier, part of exchange rate regime is to create friendly business environment that will attract foreign investors to bring their capital into an econ omy. Given the
,
et al
et al.,
66
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
volume of studies that supported positive exchange rate, this study hypothesis as
follows:H : Exchange rate have positive relation with FDI inflow in Nigeria.
Trade openness measures the international competitiveness of a country in the
global market (Ehinomen & Da'silva, 2014). It is argued theoreticallythat openness
to trade and FDI are important for enhancing industrial sector growth, attracting
foreign technology and possible spill-over, and creatingopportunities for
technology advancements ( Umer&Alam, 2013; Chakrabarti, 2001; Solow, 1957).
Trade openness is expected to minimise hurdles to trade, improves total factor
production, reduces costs of production, increase efficiencies through competition,
facilitates the flow of international capital and redirects factor of production to more
productive sectors (Romer, 1990). Trade openness suggests limited controls in
taxes, quotas or state monopolies on businesses rather than to improve business
environment competitiveness for attracti ng inward FDIs (Boateng, Hua, &Wud
2015).
Trade openness is expected to positively attract inward FDI (Asiedu, 2002).
Empirical studies support positive and significant relation between openness and
inward FDI (Boateng 2015; Chakrabarti, 2001; Edwards, 1990). Pradhan
(2010) also showed that in India, trade openness had positive and statistically
significant impact on FDI inflows in the post-globalisation-era (1991-2007) but not
statistically significant during the pre-globalisation-era (1980-1990 ). However,
insignificant bearings from trade openness on FDI inflows have also been reported
from an empirical examination (Pradhan &Kelkar, 2014; Wheeler &Mody, 1992).
The opposing argument is that trade openness leads to macroeconomic imbalance in
the host country (Levine &Renelt, 1992). Since equilibrium rate of growth differs
among countries and regions, it is argued that trade openness perceived benefits may
not always hold (Edwards, 1998). Empirical study has found that the bearing
between openness and inward FDI is negative and s tatis tically
significant(Umer&Alam, 2013).
As part of measure to improve business environment, Nigeria liberalised trade and
investment to support development and also to attract FDI inflows. Liberal policies
are expected to minimise transaction costs (Walsh & Yu, 2010; Edwards, 1990), it
portrays open and secured markets for trade and investing partners (Klasra, 2011)
and it eased extreme controls that minimised bureaucratic barriers for foreign
2
Trade openness
,
et al.,
67
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
investors. Other than liberalisation policy from SAP of 1986, NIPC Decree and
Foreign exchange (monitoring and miscellaneous provision) Decree both of 1995, brings trade openness with it, further liberalisation of the foreign exchange market in
2006 (CBN, 2006) and adoption in October 2005 of the Economic Community of
West African States tariff (UNCTAD, 2009) have greatly improved trade openness
in Nigeria. Though, World Economic Forum (2014, p. 24) remarked that 'Nigeria's
market is very open, yet many non-tariff barriers are hindering trade development'.
Oladipo (2013) used (GMM) estimates to show that
trade openness is significant and positively correlate to FDI in Nigeria.Following
theoretical arguments for liberal trade policy (Umer&Alam, 2013;Chakrabarti,
2001; Edwards, 1990; Solow, 195) and empirical findings (Boateng 2015;
Chakrabarti, 2001; Edwards, 1990), trade openness was expected to attract higher
level of FDI activity (Uwubanmwen&Ajao, 2012; Kyrkilis&Pantelidis, 2003).
Thus, the study hypothesis that:
H : Trade openness is positively related to FDI inflows in Nigeria.
The market size hypothesis contends that a large market is necessary for efficient
utilisation of resources and exploitation of economies of scale (Chakrabarti, 2001).
It is argued that increasing market size will attract inward FDI (Sahoo, 2006;
Chakrabarti, 2001; Wang & Swain, 1995). The above argument is supported by
Dunning's (1993) eclectic paradigm which asserted that access to large market size
in the host country is one of the primary motives for internalisation. The above
assertions are empirical supported that market size havepositive and statistically
significant influence on inward FDI (Jadhav, 2012; Buckley, Forsans&Munjal
2012; Grosse & Trevino, 2005; Dunning, 1980).
Market size have been shown to be the most robust and positively traditional
determinant of FDI (Chakrabarti, 2001; Fedderke&Romm, 2006;
, 2012). Boateng (2015) and Boateng (2011)
remarked that the larger the market size of a host country, in terms of the country's
GDP, the higher the FDI inflows into the host country. Notwithstanding, market size
had also been reported to have insignificant influence on inward FDI
(Villaverde&Maza, 2015; Uwubanmwen&Ajao, 2012;
, 2010;Asiedu, 2002; Edwards, 1990).
Generalised Method of Moment
et al.,
,
et al., et al.,
3
Market size
Buchanan,
Quan&Meenakshi
Ramakrishnan,
Kushwah&Kateja
68
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
In spite large market size (proxy with GDP per capita) in Nigeria, poor infrastructure
and weak institutions may likely limit the potential from market size in Nigeria as they may increase transaction costs of doing business (see:Modrego, Mccann,
Foster &Olfert 2014; Ma, 2013). The market size role in triggering cross-border
acquisitions may be limited even with free trade (Fikru&Lahiri, 2014). Nego (2010,
p. 1401) captured this fact by saying that 'the efficacy of market is significantly
affected by the institutional environment in which economic operate.' WEF (2014) noted that many non-tariff barriers are hindering trade development and the
advantages of market size in Nigeria. We expect poor infrastructure (see:Modrego
2014; Ma, 2013) and weak institutional environment (Fikru&Lahiri, 2014;
Nego, 2010) to limit market size in Nigeria, due to their effects on total transaction
costs on FDI. Hence, the study hypothesis that:H : There is a negative association between market size and FDI inflows in Nigeria
Secondary time series data are gathered from several sources are used for the
analysis of this study. These sources of secondary data have been severally used by researchers in FDI. The sources of the data and the adopted measurement of the
variables used in this study are as listed in table 1.
,
et
al.,
4
Sources of Data and measurement
69
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
Analytical Method
Model Specification
Results Presentation
Summary statistics of the time series data
Using ordinary least squares (OLS) regression on time series variables may produce spurious regression, with very high R even though there is no meaningful
relationship among the variables (Gujarati and Porter, 2010). Thus, the study will
empirical analysis the data for the study's objective in a co-integration model after
testing for the data's stationarity.Fully modified ordinary least-squared regression
(FMOLS) models will be employed for the study's analysis (Wang and Wu, 2012).The FMOLS analytical approaches includes firstly, investigating the unit root of
variables, by assuming the null hypothesis of the series has a unit root (non-
stationary) which is tested against the alternative of no unit root (stationary). The
FMOLS was first used in a study by Phillips & Hansen (1990) to provide optimal estimates of co-integrating regressions (see: Saboori, Maimunah&Maizan 2014).
FMOLS model modifies least squares (standard OLS) to account for serial
correlation effects and eradicates the endogeneity problems in the regressors that
results from the existence of a co-integration regression relationship (Saboori .,
2014). FMOLS produces estimates of a unit root in time series regression that are hyper-consistent in the sense that their rate of convergence exceeds that of the OLS
estimator (Phillip, 1995). Thus, FMOLS approach eliminates the problems caused
by the long-run correlation between the co-integrating equation and stochastic
regressors changes (Saboori ., 2014; Phillips, 1995).
The construct estimates from FMOLS have no nuisance parameters in their asymptotic distribution and it allows practitioners to use standard normal
asymptotic inference when investigating the properties of co-integrating space
(Gregoir, 2010). Because FMOLS is asymptotically unbiased, it is then possible to
construct Wald test statistics that are asymptotically distributed as Chi-square
statistical inference (Saboori ., 2014; Gregoir, 2010). It has also been credited to deliver the best results in terms of bias, efficiency and Type I errors of asymptotic
tests (Di Iorio&Fachin, 2012). Thus, only variables stationary at first level will be
employed for the analysis and the model will be run after first using information
criteria to select the maximum lag that will be included in the regression.
Following Wang and Wu(2012), this study's specific model is as follows:
FDI TGE ExcR Trop MktSize + e
Where: FDI is foreign direct investment, TGE is total government expenditure,
Trop is trade openness, MktSize is market size proxy with gross domestic product at current basic price, is constant term, to are the coefficient of the regressors,
eis the stochastic term and t is time. The variables value is annually.
Table 2 shows the summary of the time series data for the study: it shows the mean, range, standard deviation, minimum and maximum statistics.The dependent
variable, Foreigndirect investment (FDI) is in millions of Naira and this study use
the log of value of FDI. The maximum val ue of FDI is about 15.2 while the
minimum is about 5.6. FDI has a standard deviation of about 3 and mean of about 11
for FDI inflow into Nigeria, over the period 1981 – 2016. Total government
2
,
et al
et al
et al
t 1 t 2 t 3 t 4 t t
1 4
= β + β + β + β + β
β β β
˳
˳
70
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
expenditure is in millions of Naira. It has a maximum value of N5,185,319 million
and minimum of N9,636.5 million, given rise to a great disparity in range of N5,175,682 million and a standard deviation of N1,857,414 million. The real
effective exchange rate has 2010 as base year.Its minimum is about 50 % and
maximum is about 546 %. It has a mean value of about 153 % and a standard
deviation from mean of about 125 %. Lastly is market size proxy with real GDP in
millions of Naira. The study uses the log of the value of real GDP. The minimum value in log is about 16, maximum about 18, mean about 17 while the standard
deviation is about 0.54.
Table 3 show the results of the augmented Dickey-Fuller unit root test for
stationarity. The result shows that the variables are non-stationary at level but were
stationary at first difference. The result suggests that the variables may be co-integrated at order 1, i.e. I (1). (Gujarati and Porter, 2010).
Unit Root Test
71
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
Since the unit root test in table 3 indicates that the variables may be integrated of
order 1, I(1), the study finds out whether there is at least one linear combination of the variables that is integrated of order zero, I(0), and also to confirm if there is any long-
run relationship between the variables. The study employs the Johansen tests to
determine number of co-integrating vectors. However, the first step is to test for the
optimal lags to be included in the Johansen tests. Table 4 presen ts the results of the
selection order criteria for optimal lags to be included in the Johansen co-integration test.
An inspection of table 4 indicates that Final Prediction Error (FPE), Akaike
Information Criterion (AIC), and Hannan-Quinn Information Criterion (HQIC) favour the inclusion of 4 lags in the Johansen co-integration test. On the other hand,
and Schwarz Bayesian Information Criterion (SBIC)favour the inclusion of 1 lag in
the Johansen co-integration test. The information criteria selec tion was also
significant at 1 %. Thus the study include lag 4 in the Johansen co-integration test.
Table 5 presents the Johansen tests for co-integration. The test provides the trace
statistic which tests the null hypothesis (r = 0) of no co-integration vector against the
alternative hypothesis (r = 1) of a least one co-integrating vector. The trace statistic is
greater than the critical value at the 5 percent level of significance up to maximum
rank 2. It suggests that there are 3 co-integrating vectors. Thus, we reject the null hypothesis of no co-integrating vector rather co-integrating vector and accept that
there is co-indicating vector up to maximum rank 3. This confirm that there is a long
relationship among the variables and the study can proceed to run FMOLS
regression model.
Trend: constant Number of obs = 32
Sample: 1981-2016 Lags = 4
Johansen tests for co-integration.
Table 5: Johansen Tests for Co-integration
72
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
An inspection of theFMOLS regression model(table 6) shows that the model fits the
data. The model has an adjusted R of about 77 percent. The results show that the regressors(total government expenditure, real effective exchange rate, trade
openness and market size proxy with real GDP) explain about 77 percent of the
variation in the regressand (changes in FDI).
The results indicate that total government expenditure has a positive and statistically
significant (p = 0.019) influence on FDI inflow in Nigeria on the examined period. The result supports the study's hypothesis that says 'total government expenditure impact positively on FDI inflow into Nigeria', and it is sufficient to explain
movement of FDI inflows into Nigeria over the period 1981 to 2016.The result
supports the Keynesian macroeconomic prediction that public expenditure will spur further economic activities and this include the activities of foreign investors' that
will bring their private capital activities. The result su pports Emudainohwo (2015)
and Oladipo (2013) that show government expenditure have positive and strong influence on movement of FDI inflows in Nigeria. This study also confirmed that
government expenditure has the strongest impact on attracting inward FDI into Nigeria over the period examined. The study suggests that increased government
expenditure particularly when channelled to facilities that will reduce cost to foreign
investors, will attract foreign direct investment in Nigeria.
2
73
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
Table 6 shows that exchange rate has negative and insignificant impact on inward
FDI in Nigeria over the period examined. However, it is not sufficient to explain inward FDI in Nigeria over the period 1981-2016. Table 6 shows that trade openness
has positive and statistically significant influence on FDI inflows in Nigeria over the
examined period. The result supports the study's hypothesis that 'trade openness has
positive bearing on inward FDI in Nigeria' and also collaborate Edwards (1990),
Chakrabarti (2001), Boateng et al. (2015) and Emudainohwo (2015) that found positive and significant influence of trade openness on inward FDI. It however,
negated Wheeler &Mody (1992), Pradhan and Kelker (2014) that reported negative
and insignificant bearing of trade openness on inward FDI and Umer&Alam (2014)
that showed trade openness has negative and significant influence on inward FDI.
Perhaps, on the general side, trade openness that have been implemented in Nigeria can be said to have att racted inward FDI I Nigeria over the examined period.
Notwithstanding, some of the macro-economic variables are either weak or not
stable such as interest rate, exchange rate and institutions (bribery and bureaucracy).
The study thus, suggests that efforts should be made to improve on the weak and unstable macro-economic factors and the weak institutions.
Lastly, table 6 shows that market size proxy with GDP has positive and insignificant
influence on inward FDIs in Nigeria. The result did not su pport the study's
hypothesis that expects 'negative association between market size and FDI inflows in
Nigeria over the examined period. Thus, the result is not sufficient to explain inward FDI in Nigeria over the period 1981-2016
The study used times series data to examine the macro-economic determinants of
inward FDI in Nigeria over the period 1981 to 2016. The study confirmed the
existence of co-movement among the dependent and independent variables using Johansen co-integration test. The FMOLS regression model showed that total
government expenditure, real effective exchange rate and market size proxy with
real GDP has positive and strong impact on inward FDI in Nigeria.And, real effective
exchange rate has negative and insignificant impact on inward FDIs in Nigeria over
the examined period. Total government expenditure and trade openness have a statistically significant effect on inward FDI. The study suggests that government
should undertake macro-economic policies that will impro ve the weak and unstable
macroeconomic variables and strengthen the existing weak institutions. In addition,
government expenditure should be dedicated to building infrastructure that will help
reduce transaction cost to investors in Nigeria. Thus, the study has contributed to literature on the drivers of inward FDI in an economy.
Summary and Conclusion
74
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
References
1
7
Asiedu E. 2002. On the Determinants of Foreign Direct Investment to Developing Countries: Is Africa Different?
107 119.
22
47Buchanan B.G., Quan V.L. &Meenakshi R. 2012. Foreign direct investment and
institutional quality: Some empirical evidence. , 21: 81 89.
21
54
67
6
Pre 1986
Abata M.A., Kehinde J.S. &Bolarinwa S.A. 2012. Fiscal/Monetary policy and economic growth in Nigeria: A theoretical exploration.
(5): 75–88.
Adefeso H.A. &Mobolaji H.I. 2010. The fiscal-monetary policy and economic
growth in Nigeria: Further empirical evidence.
(2): 137–142.Aliber R. 1970. A Theory of direct foreign investment [in C. P. Kindleberger (Ed),
The international corporation] AssymposiumCombrite MA. MIT. Press.
Alimi R. S. 2014. A time series and panel analysis of government spending an d
national income. .
–Blonigen B.A. &Feenstra F.C. 1996. Effect of US trade protection and promotion
policies. (Cambridge, M. A.) Working
Paper No 5285.Boateng A. Naraidoo R. & Uddin M. 2011. An analysis of the inward cross-border
mergers and acquisitions in the UK: A macroeconomic perspective. (2): 91–113.
Boateng A., Hua X., Nisar S. &Wud J. 2015. Examining the determinants of inward
FDI: Evidence from Norway. , : 118–127.
–
Buckley P.J., Forsans N. &Munjal S. 2012. Host-home country linkages an d host-home country specific advantages as determinants of foreign acquisitions by Indian firms. , : 878–890.
Chakrabarti A. 2001. The determinants of foreign direct investment: Sensitivity
analyses of cross-country regressions. (1): 89–114.
Cushman D.O. 1985. Real exchange rate risk, expectations, and the level of direct
investment. , (2): 297–308.
Di Iorio F. &Fachin S. 2012. A note on the estimation of long-run relationships in panel equations with cross-section linkages. (2012-19 | June 6, 2012): 1–16.
Dunning H.J. 1980. Toward an eclectic theory of international production: Some
empirical tests. (
): 9–31.
Dunning H.J. 1993. The globalisation of business. The challenge of the 1990s. Routledge, London, UK; ,
Chatham, Kent, UK.
Edwards S. 1990. Capital flows, foreign direct investment, and debt equity swaps in
developing countries. (Cambridge,
M. A.) Working Paper No. 3497.Ehimare O.
International Journal
of Academic Research in economics and Management Sciences,
Pakistan Journal of social
Sciences,
Munich Personal RePEc Archive
National Bureau of Economic Research
Journal of International Financial Management and Accounting,
Economic Modelling
International Business Review
KYKLOS,
The Review of Economics and Statistics
Journal of International Business Studies, Spring
1980
Reprinted 1995 Mackays of Chatham PLC
National Bureau of Economic Research,
World Development,30 (1):
International Review of Financial Analysis
Central Bank of Nigeria. 2006. CBN Statistical Bulletin, 17: December, 2006.
A. 2011. Foreign direct investment and its effect on the Nigerian economy.
(2): 253–261.Business Intelligence Journal, 4
75
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
Ehinomen C. &Da'silva D. 2014. Impact of Trade Openness on the Output
Growth in the Nigerian Economy.
106
Gregoir S. 2010. Fully modified estimation of seasonally co-integrated processes. , 26: 1491 1528.
Gujarati D.N. & Porter D.C. 2010. Essentials of econometrics, 4 Ed. McGraw-Hill International Edition, Singapore.
Jadhav P. 2012. Determinants of foreign direct investment in BRICS
economies: Analysis of economic, institutional and political factor. 37: 5 14.
Kyrkilis D. &Pantelidis P. 2003. Macroeco nomic determinants of outward
foreign direct investment. 30 (7/8): 827 836.
Levine R. &Renelt D. 1992. A sensitivity analysis of cross-country growth
regressions. , 82: 942 963.
9
British Journal of Economics, Management and Trade, 4 (5): 755 768.
Impact of government policy, institutions and macroeconomic factors on FDI in Nigeria. PhD Thesis, Department of Accountancy, Glasgow School for Business and Society Glasgow Caledonian University, Glasgow, UK.
23
34
Econometric TheoryGrosse R. & Trevino L.J. 2005. New institutional economics and FDI location in
Central and Eastern Europe. Management International Review, 45 (2): 123 145.
Procedia-Social and Behavioral Sciences,
Jin W. &Zang Q. 2013. Impact of change in exchange rate on foreign direct
Investment: Evidence from China. Lingnan Journal of Banking, Finance and Economics, 4 (1): 1 17.
Klasra M.A. 2011. Foreign direct investment, trade openness and economic growth in Pakistan and Turkey: an investigation using bounds test. Quality Quantity, 45 (1): 223-231.
International Journal of Social Economics,
American Economics ReviewMarket size, local sourcing and policy competition for foreign direct
investment. Review of International Economics,21 (5): 984 995.
–
Emudainohwo O.B. 2015.
–
–
Froot K.A. & Stein J.C. 1991. Exchange rates and foreign direct investment: An
imperfect capital markets approach. (4):
1191–1217.
–
–
–
–
–
–
–Modrego F., Mccann P, Foster W.E. &Olfert M.R. 2014. Regional market potential
and the number and size of firms: observations and evidence from Chile. , (3): 327–348.
Muhammad A., Khan H., Hunjra A.I, Ahmad H.M. &Chani M.I. 2011. Institutions,
macroeconomic policy and foreign direct investment: South Asian countries case. Munich Personal RePEc Archive.
Fedderke J.W. &Romm A.T. 2006. Growth impact and determinants of foreign direct investment into South Africa, 1956–2003. Economic Modelling, (2): 738 760
Fikru M.G. &Lahiri S. 2014.Cross-border mergers with flexible policy regime: The role of efficiency and market size. Journal of the Japanese and International Economies, : 58 70.
Quarterly Journal of Economics,
Ma J. 2013.
Spatial Economic Analysis
th
76
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
Muhammad B., Muhammad I., Amjad A., Muhammad S., Mansoor A., Iltaf H.
&Tehreem F. 2014. Impact of exchange rate on foreign direct investment in Pakistan. , 2 (6): 223 231.
2
Phillips P.C.B. & Hansen B.E. 1990. Statistical inference in instrumental variables regression with I(1) processes. 57: 99 125.
Phillips P.C.B. 1995. Fully modified least squares and vector autoregression. 63 (5): 1023 1078
Pradhan A.K. &Kelkar S. 2014. Macroeconomic determinants of foreign direct
investment in India: An empirical investigation (1991 2012). 5 (4): 530 544.
Pradhan R.P. 2010. Trade openness and foreign direct investment in India: The globalisation experience. 16 (3):
26 43.Ramakrishnan S., Kushwah S.V. &Kateja A. 2010. Determinants of foreign
direct investment: an empirical analysis. ,
3 (1 & 2): 12 16.Romer P.M. 1990. Endogenous technological change.
s71 s103.
66
Sahoo P. 2006. Foreign direct investment in South Asia: Policy, trends, impact and determinants. .
l
Solow R.M. 1957. Technical change and aggregate pro duction function. , 39: 12 20.
Advances in Economics and Business
77
Oni L.B., Aninkan O.O. &Akinsanya T.A. 2014. Joint effects of capital and
recurrent expenditures in Nigeria's economic growth. European Journal of Globalization and Development Research,9 (1): 529–543.
Review of Economics Studies,
Econometrica,
Journal of Commerce and Management Thought,
The IUP Journal of Applied Finance,
ASBM Journal of Managements
Journal of Political Economy, 98 (5/2):
ADB Institute Discussion Paper No. 56
Review of Economics and Statistics
–
–
Oladipo S.O. 2013. Macroeconomic determinant of foreign direct investment in
Nigeria (1985-2010): a GMM approach.
(4): 801–817.
–
–
––
–
–
–Saboori B., Maimunah S.I. Maizan B.B. 2014. Economic growth, energy
consumption and CO2 emissions in OECD (Organization for Economic Co-operation and Development)'s transport sector: A fully modified bi-directional relationship approach. , : 150–161.
Seo J., Tarumun S. & Suh C. 2002. Do exchange rates have any impact on FDI flows in the Asia: Experiences of Kore a. Paper presented at Korea and the world
economy. First Annual Conference of the AKES, a Joint Conference of AKES,
KDI and RCIE, Yonsei University, Seoul, Korea.
Sharifi-Renani H. &Mirfatah M. 2012. The impact of exchange rate volatility on
foreign direct investment in Iran. , (1): 365–373.
–
Nego B. 2010. No shortcut to stability: Democratic accountability and sustainable development in Ethiopia. Social Research, (4): 1401 1446.
Journal of Emerging issues in Economics, Finance and Banking: An Online International Monthly Journal,
Organisation for Economic Corporation and Development (OECD). 2002. Foreign
direct investment for development: maximising benefits, minimising costs.
Energy
Procedia Economics and Finance
77
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–
Ullah S., Haider S.Z. & Azim P. 2012.
–
–
2009. World
investment report 2009: Transnational corporations, agricultural production and development.
–
–
–
–
–
World Economic Forum. 2014. Global Competitiveness Index Data Platform
Impact of exchange rate volatility on
foreign direct investment: A case study of Pakistan. 50 (2): 121 138.
Umer F. &Alam S. 2013. Effect of openness to trade and FDI on industrial sector growth: A case study for Pakistan. , 16 (48): 179 198.
Uwubanmwen A.E. &Ajao G.I. 2012. The determinants and impacts of foreign direct investment in Nigeria.
, 7 (24): 67 77.
Walsh J.P. & Yu J. 2010. Determinants of foreign direct investment: A sectoral
and institutional approach. : WP/10/187.Wang Q. & Wu N. 2012. Long-run covariance and its applications in co-
integration regression. , 12 (3): 515 542.Wang Z. & Swain N. 1995. The determinants of foreign direct investment in
transforming economies: Empirical evidence from Hungary and China.
, 129: 359 381.Wheeler D. &Mody A. 1992. International investment location decisions.
, 33: 57 76.
Pakistan Economic and Social Review,
The Romanian Economic Journal
United Nations Conference On Trade and Development (UNCTAD). 2009.
Assessing the impact of the current financial and economic crisis on global FDI flows.
United Nations Conference On Trade and Development (UNCTAD).
International Journal of Business and
ManagementVillaverde J. &Maza A. 2015. The determinants of inward foreign direct
investment: Evidence from the European regions. International Business
Review, 24: 209 223.
IMF Working Paper
The Stata Journal
Weltwirtschaftiches
Journal of International Economics
78
Impacts of Macroeconomic Indicators on Inward FDI in Nigeria: 1981 2016–