Ayesha Serfraz (1)
(1) Assistant
Professor at University of the Punjab, Lahore, Pakistan.
Doctoral student at
University of Hamburg, Germany.
NOTE FROM AUTHOR
As this
study is based on analysis of existing literature, many studies have been cited
in which Author’s original words have been stated. All such citations also
mention the page numbers of original article from where the exact words have
been taken.
Abstract:
This paper
analyzes the relationship between Foreign Direct Investment inflows (FDI) and
Total Factor Productivity (TFP) by studying the existing literature on the
topic. Numerous studies have been conductive to test the relationship between
these two variables but there is no consensus regarding the direction of
affiliation. The basic purpose of this study is to find the reason behind
different answers and for this reason the existing body of literature on this
topic has been referred to. In addition, the concepts of FDI and TFP have been
discussed along-with the effects of FDI on developing countries and its
importance. After analyzing different studies relevant to this topic, it has
been concluded that the difference in results are mainly due to econometric
techniques applied by different researchers to test the relationship
empirically. Furthermore, some statistical figures and their analysis have been
presented in appendix.
Keywords
Foreign Direct
Investment, Total Factor Productivity, Developing economies.
Jel
Classification Codes: F21, O47, O57
1.
Introduction
The debate over relationship between
foreign direct investment inflows (FDI) and growth indicators of developing
economies has attracted researchers from all over the world to explore the
relationship. A FDI inflow not only bring capital, but new techniques, updated
technical know-how and makes such a transformation in developing economies that
the process of development accelerates and many under-developed economies are
now moved up-to the level of developing economies and that time is not far that
these developing economies will transform into developed economies.
No country can ignore the importance of
FDI inflows but everything has both positive and negative aspects. Where FDI
inflows are bringing many positive changes, the complete package of FDI also contains
some negative aspects. the main purpose of this study is to cover all sides of
FDI inflows (though there are many limitations in the form of different answers
due to difference in empirical research techniques, difference in data: panel
or time series and most importantly difference in variables or sectors).
Although there is a huge literature on impacts of FDI on growth indicators, and
relationship with other variables, still much work needs to be done. Therefore
this paper discusses existing literature which throws light on relationship
between FDI inflows and TFP. The further observe the effects of FDI inflows,
the appendix of paper makes a comparison of three most emerging economies;
China, India and Pakistan.
2.
Foreign Direct Investment (FDI)
There
are different concepts and definitions of FDI but the most widely used by Economists,
is the one given by [1]
“Direct
investment is a category of cross-border investment made by a resident in one
economy (the direct investor) with the objective of establishing a lasting
interest in an enterprise (the direct investment enterprise) that is resident
in an economy other than that of the direct investor. The motivation of the
direct investor is a strategic long-term relationship with the direct investment
enterprise to ensure a significant degree of influence by the direct investor
in the management of the direct investment enterprise. “(Page 80)
Based
on the above definition, FDI can be beneficial for host country or it can cause
harm to host country’s economy, the exact effect depends on the adjustment of
two opposing forces.
Lately, however, the exceptional advantages of
FDI and mainly the kinds of motivations offered to foreign firms in practice,
have become questionable. Moving on with this debate, the empirical evidence
for FDI generating positive spillovers for host countries is showing ambiguous
results at both the micro and macro levels.
According
to [2], there is weak evidence that
FDI generates positive spillovers for host economies. Empirical research thus
provides little support for the idea that promoting FDI is warranted on welfare
grounds. However, there is a need for more research related to effects of FDI
on recipient country as higher taxes result in decrease in FDI. In addition,
the behavior of Multinational Enterprises (MNEs) tend to behave differently
based on location where investment is made.
[3] Used panel dataset covering 72 developed and
developing countries in order to analyze the relationship between FDI inflows
and economic growth. The study performs both a cross-sectional OLS analysis as well as a dynamic panel data
analysis using GMM. The paper concludes that there is no robust link running
from inward FDI to host country economic growth.
On the
other hand, [4] carried out an empirical
analysis using cross country data between 1975 and 1995. They divided their
model in two data sets; first data set consists of 20 OECD countries and 51
non-OECD countries whereas second data set includes 20 OECD countries and 20
on-OECD countries. The main emphasis of their study is based upon examining
relationship among FDI, financial market and economic growth. Their findings
suggest that countries with better financial system attract more FDI, however
the impact of FDI on economic growth is ambiguous.
The
secretary general of United Nations [5]
summarized the importance of FDI to the developing economies as follows ‘‘With the enormous potential to create jobs,
raise productivity, enhance exports and transfer technology, foreign direct
investment is a vital factor in the long-term economic development of the
developing countries’’ (United Nations, 2003 page iii).
Different Economists and policy makers give
diverse conclusions but most of them have consensus that the policies and
environment of host country play the vital role in determining the impact of
FDI.
3.
Total Factor Productivity (TFP)
According to [6],
“TFP is the part of output that is not
attributed to the use of capital and labor. In other words, TFP represents the
efficiency with which the production inputs are utilized. The importance of TFP
in economic growth is indisputable.” (Page 11)
Another important statement given by
author (quoting author’s words)
“TFP
reflects not just technology but also organizational innovations, improvements
in the allocation of capital and labor, and returns to scale, for example.
Technology and innovation constitute a big portion of TFP and FDI is said to
positively contribute to such innovations by bringing in new technology, which
results in knowledge spillovers and durable increase in the productivity.”
Regarding determinants of TFP, there is
an ongoing debate where different researchers have pointed out different
determinants but as in the case of FDI, TFP is also affected by a country’s
policy, environment, availability of educational facilities etc.
According to [7], the factors which are important for increasing TFP include
macroeconomic policy, human capital, institutional and socioeconomic factors.
[8] Empirically examined the relationship between FDI and TFP using a
sample of 33 developing countries covering the time period of 1980-2005. After
applying panel Cointegration techniques, the results suggested that FDI has a
positive effect on TFP over a long run time period and there exists a
bi-directional causation between FDI and TFP.
Measurement
of TFP is a separate and complex exercise. According [9]
“By linking the TFP growth rate to
innovation, endogenous growth models shed light on the determinants of TFP
growth. R&D subsidies and an abundance of skilled labor reduce the marginal
cost of conducting R&D and increase the rate of innovation development and
therefore, the TFP growth rate. Increases in the size of markets increase the
innovators’ revenues, leading to more innovation and higher TFP growth.” (Page
2)
[10] States
“From the outset, it is assumed that capital intensity
is one of the main determinants of TFP and that policies that encourage
investment also have a positive impact on TFP growth. Both a medium- and
long-term view of determinants are provided. “(Page 1)
BASED ON THESE VIEWS TFP CAN BE MEASRED USING
CAPITAL FORMATION AS A PROXY VARIABLE
In case of developing countries, it is
argued that as FDI inflows bring technology transfer, it has spillover effects
over labor productivity and “A simple labor” is transformed into “human
resource or human capital”.
Because of new technology and technical
know-how in host country, the labor learns new and better ways to perform
assigned work more properly and in a better way
According to [11]
“Contact
with firms of a higher level of efficiency enables the relatively backward ones
to improve not only by copying or imitating but also by inducing them to
"try harder," as in the well-known Avis motto. As in many fields of
human endeavor, the visible example of a high standard can inspire those with a
lower level of achievement to perform better”. The Relationship and Methods
[12] States that FDI inflows can help increase productivity in developing
countries, there has been little research that examines directly the linkage
between FDI and productivity at the macro level. The author examined the link
between FDI and TFP in fourteen Sub-Saharan economies by applying Granger
Causality test (4). The results found limited evidence that FDI
inflows contribute to higher TFP.
According to [13], the role of FDI for developing countries is well known but
the relationship between FDI and TFP is furnished with mix results. Major
reason pointed out by the author is the presence of endogeneity factor and the
inability of recipient country to absorber new technology. The study used panel
data for 49 countries over the time period 1974-2008 and found that increased
FDI stock leads to higher productivity growth.
There is another interesting aspect of
relationship between FDI and TFP which has been explored by [14]. They performed cross- country
regressions on a sample of 69 developing countries and their results suggested
that FDI contributes more to growth and domestic investment. Moreover they
found that there is a strong complementary effect of FDI and human capital.
Their empirical results imply that FDI is more productive than domestic
investment only when the host country has a minimum threshold stock of human
capital.
[15] Used panel data approach to study
the effects of FDI on TFP in a sample of 5 BRIC countries and
Turkey. Results suggest that FDI has a negative impact on TFP for these
countries.
In
case of developing countries, an important factor which gives them extra
benefit is that they do not need to introduce a new technology. As [16] states
“Fortunately,
the developing countries need not recreate the technology that has already been
created in advanced countries since they can benefit from technological
diffusion. The most effective and less costly channel through which technology
transfers from developed to developing countries is via Foreign Direct
investment (FDI)”. (Page 1)
The
study constructs an alternative analytical model, within the externalities type
endogenous growth theory, in which technological spillovers from FDI generates
long run growth of the host economy, through its positive effect on its TFP and
tested the model using panel data from 22 Sub-Saharan African countries. The
empirical results obtained from both static and dynamic panel models conform to
the theoretical model according to which FDI has positive effect on TFP in the
long-run and negative effect in the short run.
Although it seems that FDI has a positive
impact on TFP, but there are so many different answers.
A comprehensive study by [17] points out the reasons for getting
different results. According to the author, there are three types of studies
·
CASE STUDIES which are specific
for a country and their result cannot be generalized although they are very
informative and use many variables.
·
Industry level studies using
CROSS-SECTIONAL DATA. Author states:
“Their
disadvantage is the difficulty in establishing the direction of causality. It
is possible that this positive association is caused by the fact that
multinationals tend to locate in high-productivity industries rather than by
genuine productivity spillovers. The positive correlation may also be a result
of FDI inflows forcing less productive domestic firms to exit and/or of
multinationals increasing their share of host country market, both of which
would raise the average productivity in the industry.” (Page 605)
·
Third type of
study is based on firm level PANEL DATA, which is based on examining the
correlation between the productivity of domestic firms and presence of foreign
investment.
The study uses firm level Panel data set
from Lithuania. The empirical results find that productivity benefits are
associated partially with FDI.
[18] Used time series data for eight
East Asian countries and found a positive relation between FDI and total Factor
productivity.
[19], conducted a research on Taiwan’s manufacturing sector. They used
firm-level data and found that FDI has a positive spillover effect on
productivity and suggested that developing economies should adopt encouraging
policies for attracting FDI, in this way there would be more spillover effects
in the form of technology and knowledge.
[20] Conducted a study on Pakistan
using time series data covering the sample from 1960 to 2003 and found a
positive relation between FDI and TFP.
The impact of FDI on TFP has largely been
explored by many researchers but the empirical literature shows mixed results.
[21], discuss this problem in much detail. In their research, they have used
both time series and panel data analysis for a sample of OECD and non-OECD
countries in the period 1970-90.
Their study makes a comparison between
Time Series and Panel data models for examining the impact of FDI on TFP in
host countries.
“Empirical
work on cross-country and time series growth has been directed at dealing with
two basic problems; namely, the lack of unconditional convergence of growth
rates across countries and high estimates of the elasticity of output with
respect to capital stocks. Although conventional neo-classical growth in the
Solovian tradition predicts that the elasticity of output with respect to
capital should be equal to the capital share in output, cross-country estimates
point to a much higher value. High capital elasticities can nevertheless be
explained on the grounds of simultaneity and omitted variable biases.”(Page
133)
According to their empirical findings,
time series analysis shows that there is a positive relation between FDI and
TFC via knowledge transfer. In case of Panel data analysis, FDI appears to have
a positive impact on TFP in the OECD Panel where as in the non-OECD Panel there
seems to be a negative relation between FDI and TFP.
“This is because it is well known that,
in the case of cross-country and times-series estimations, the correlation
between the error term and the regressors in standard growth accounting-based,
time-series production function estimations leads to simultaneity and omitted
variables biases.” (Page143)
[22] Conducted an empirical study by using firm level data of Venezuela
and found that more foreign presence in the same industry would decrease the
productivity of domestic firms. This happens because multinationals crowd out
the latter by market stealing effect.
According to [23] and [24], the
problem of endogeniety between FDI and growth has not been taken into
consideration in most of the cross sectional studies, moreover the
time-invariant factor has been ignored.
[24] Used panel data for 84 countries over the period of 1970-99 and
found a significant endogenous relation between FDI, economic growth and
productivity in case of developing countries. There is not enough evidence of
positive relation between FDI and TFP because very few studies have used TFP as
a dependent variable.
[25] Empirically investigated the effect of FDI on TFP by using a large
sample of 90 countries in 1970-2000 and found a positive relation whereas the
absorptive capacities do not affect the impact of FDI.
According to [26] and [27], FDI is
favorable for growth only if host country has strong financial institutions but
later they found that countries with well-developed financial institutions
achieve significantly from FDI via TFP improvements. Both studies are based on
cross country models.
[28] used panel
data approach to examine the relation between FDI and TFP in a sample of 16 OECD countries and found a
positive relation between two variables and the reason mentioned by the author
is that this positive relation is may be due to the possibility that FDI is a
channel trough which technologies are transferred internationally.
According [29],
"Most
empirical studies conclude that FDI contributes to both factor productivity and
income growth in host countries, beyond what domestic investment normally would
trigger. It is more difficult, however, to assess the magnitude of this impact,
not least because large FDI inflows to developing countries often concur with
unusually high growth rates triggered by unrelated factors.” (Page 9)
Based upon above
studies, results are summarized in a table.
RELATIONSHIP RESULTS AND EMPIRCAL APPROACH
RESEARCHER/
RESERCHERS
|
DATA TYPE
|
COUNTRIES AND
TIME PERIOD
|
RESUULTS/
CONCLUSIONS
|
Herzer (2010)
|
Panel Cointegration Techniques
|
33 Developing countries
(1980-2005)
|
Positive and Long-Run relationship between FDI
and TFP
|
Thiam (2007)
|
Time Series
|
14 Sub-Saharan
(1970-2004)
|
Limited evidence that FDI inflows result in
higher TFP
|
Baltabaev (2013)
|
Panel data
|
49 countries
(1974-2008)
|
Increased in FDI higher stock leads to
productivity growth.
|
Borensztein et el (1998)
|
Cross- country regressions
|
69 developing countries
(1970-2011)
|
Positive relation but FDI is more productive
than domestic investment only when the host country has a minimum threshold
stock of human capital.
|
Filiz (2014)
|
Panel data
|
Sample of 5 countries BRIC countries and Turkey
(1990-2012)
|
FDI has a negative impact on TFP for BRIC.
|
Senbeta
(2008)
|
Panel data
|
22 Sub-Saharan African countries
(1970-2000)
|
FDI inflow has negative short-term effects and
positive long-run effects on total factor productivity.
|
Javorick (2004)
|
Firm level Panel data set
|
Lithuania
( 1996–2000)
|
Partial association between FDI inflows and TFP
|
Pratoomchat (2012)
|
Time Series
|
Eight East Asian countries
Rolling regression technique for 20
Periods, starting from 1980-1990 to 1999-2009.
|
Positive relation between FDI inflows and TFP.
|
Lin and Chuang (1999)
|
Firm level Panel data set
|
Taiwan
( census data 1991)
|
FDI has a positive spillover effect on
productivity
|
Khan (2006)
|
Time Series
|
Pakistan
(1960-2003)
|
positive relation between FDI and TFP
|
Luiz and de Mello (1999)
|
Both Time series and Panel data
|
OECD and non-OECD countries
(1970-1990)
|
Time series analysis shows that there is a
positive relation between FDI and TFC via knowledge transfer. In case of
Panel data analysis, FDI appears to have a positive impact on TFP in the OECD
Panel where as in the non-OECD Panel there seems to be a negative relation
between FDI and TFP.
|
Aitken and Harrison (1999)
|
Firm level Panel data
|
Venezuela
(1976-1989)
|
More foreign presence in the same industry
decreases the productivity of domestic firms.
|
Li and Liu (2005)
|
Panel data
|
84 countries
(1970-1999)
|
Significant endogenous relation between FDI and
TFP
|
Woo (2009)
|
Both cross-sectional and Time series
|
90 countries
(1970-2000)
|
Positive relation whereas the absorptive
capacities do not affect the impact of FDI
|
Alfaro et al. (2004, 2009)
|
Cross-country
regression
|
For (2004)
20 OECD countries and 51 non-OECD countries.
(1975-1995)
For (2009)
62 countries
(1975–1995)
|
FDI is favorable for growth only if host
country has strong financial institutions but later they found that countries
with well-developed financial institutions achieve significantly from FDI via
TFP improvements
|
Pessoa (2005)
|
Panel data
|
16 OECD
( 1985-2002)
|
Positive relation between FDI and TFP
|
Source: Author(s) All results in this
table are based on literature discussed above
4.
Effects of FDI
No doubt, FDI inflows have helped
developing countries in reducing dual gaps: saving-investment gap and
export-imports gap. Moreover, all economists have consensus that FDI brings a
complete package including technology, technical know-how, growth, and increase
in productivity and many others.
According to [29],
“Given
the appropriate host-country policies and a basic level of development, a
preponderance of studies shows that FDI triggers technology spillovers, assists
human capital formation, contributes to international trade integration, helps
create a more competitive business environment and enhances enterprise
development. All of these contribute to higher economic growth, which is the
most potent tool for alleviating poverty in developing countries. Moreover,
beyond the strictly economic benefits, FDI may help improve environmental and
social conditions in the host country by, for example, transferring “cleaner”
technologies and leading to more socially responsible corporate policies.” (Page 5)
Coming towards negative aspect, the role
of Multinationals is the most heated topic. In most developing countries, it
has been observed that they are harmful to domestic firms as MNEs with their
lower marginal costs increase production relative to their domestic competitor,
when imperfectly competitive firms of the host country face fixed costs of
production. In this environment, foreign firms that produce for the domestic
market draw demand from local firms, causing them to reduce the production. The
productivity of local firms falls as their fixed costs are spread over a
smaller market which forces them to back up their average cost curves.
According to [22], when the productivity decrease from this demand effect is
large enough, total domestic productivity can diminish even if the MNE
transfers technology or its firm-specific asset to local firms.
Regarding wages and productivity, there
can be both positive and negative spillovers. According to [30], if foreign firms hire the best workers, domestic firms will
be left with relatively lower quality workers and wage spillover could be
negative. On the other hand, productivity spillovers could be negative if
foreign firms take a major share of market and domestic firms have limited
share in market, leading to reduction in productivity.
Although there are many different
viewpoints about the impact of FDI inflows on host country and it is hard to
arrive at a single conclusion. Whether FDI inflows are beneficial or harmful, the outcome depends
upon liberalization policies, environment, infrastructure, availability of
productive resources etc. Moreover, all countries do not benefit at the same
level, the above mentioned factors vary from country to country, more favorable
circumstances will attract more FDI inflows and as a result more are the gains
and vice versa. In addition, the impact of FDI depends on the behavior of
multinationals in host countries.
5.
Conclusion
This study tries to find out whether FDI
inflows affect TFP and for this purpose the existing literature has been
studied in detail. The impact of FDI on TFP cannot be ignored whether it is
positive, negative or has partial results. There are so many different answers
and it may be due to difference in techniques, variables, methodology and the
right question being tested by researcher. Same data can give different results
depending on Panel, cross-country or time-series technique.
In my view, Panel Data provides best
results if sample size is large (e.g. analysis of many countries, many firms or
a large number of variables of interest). Cross- country provides accurate
results when a comparative study is being carried out. If only one country is
being analyzed, then data availability becomes an issue. Moreover in case of
single country analysis, the number of variables cannot be large enough to make
a proper Panel Data study.
No matter, whatever the technique is, it
cannot be ignored that FDI is beneficial for developing countries as they are
in need of capital, technology and innovations. The spillover effects are
clearly observed in case of increase in productivity whether it is factor
productivity or productivity of sectors; industry, agriculture or
services.
Negative or harmful effects are a part of
package; they can be in the form of inequality, monopoly power of
multinationals, hidden conditionalities or interference in culture or
traditional values.
The gains for
every country depends on net effect of these two opposing factors. More liberal
an economy is, more FDI it attracts and more benefits are gained from FDI but
FDI does increase growth, resources and productivity and this fact has not been
ignored by researches.
6.
References
[1]OECD
(2008), “FDI flows and stocks”, in OECD Factbook 2008: Economic, Environment
and Social Statistics, OECD Publishing.
[2]Hanson, G. H. (2001).
Should countries promote foreign direct investment?
[3] Carkovic,
M. V., & Levine, R. (2002). “Does foreign direct investment accelerate
economic growth?” University of Minnesota Department of Finance Working
Paper.
[4]Alfaro, et
al. (2004). “FDI and economic growth: the role of local financial
markets”, Journal of international economics, 64(1),
89-112.
[5]Unctad, M. United Nations Conference on
Trade and Development (2003). World
Investment report: FDI Policies for Development: National and International
Perspectives, New York and Geneva: United Nations
[6]Ilboudo,
P.S. (2014). "Foreign Direct Investment and Total Factor Productivity in
the Mining Sector: the Case of Chile" (2014). Economics Honors Papers. Paper 18
[7]Loko, B.,
& Diouf, M. A. (2009). Revisiting the Determinants of Productivity Growth:
What's New? IMF Working Papers, 1-29.
[8]Herzer, D.
(2010). The long-run relationship between outward FDI and total factor
productivity: evidence for developing countries (No. 199).
Ibero-America Institute for Economic Research.
[9]Comin, D.
(2006). “Total Factor Productivity” New
York University and NBER.
[10]Isaksson,
A. (2007). Determinants of total factor productivity: A literature
review. Research and Statistics Branch, UNIDO.
[11]Findlay,
R. (1978), “Relative Backwardness,
Direct Foreign Investment and the Transfer of Technology: A Simple Dynamic
Model,” Quarterly Journal of Economics, Vol.
92(1), pp.1-16.
[12]Thiam, N.H. (2007), “Foreign Direct
Investment and Productivity: Evidence from Sub-Saharan Africa”, Research and
Statistics Branch UNIDO.
[13]Baltabaev,
B. (2013). FDI and Total Factor Productivity Growth: New Macro Evidence (No.
27-13). Monash University, Department of Economics.
[14]Borensztein
et al. (1998), “How does Foreign Direct Investment Affect Economic Growth”, Journal of International Economics, Vol.
45, pp. 115–135.
[15]Filiz, K.
(2014), “FDI and total factor productivity relations: An Empirical Analysis for
BRIC and Turkey”,
[16]Senbeta, S. (2008), “The nexus between FDI
and Total Factor Productivity Growth in Sub Saharan Africa”, From MPRA http://mpra.ub.uni-muenchen.de/31067/
[17]Javorcik,
B. S. (2004). “Does foreign direct investment increase the productivity of
domestic firms? In search of spillovers through backward linkages”. American
economic review, Vol 94(3): pp. 605-627.
[18]Pratoomchat, P. (2012), “Foreign Direct Investment
and Total Productivity Growth in East Asia: Which one happened first?”
Department of Economics, University of Utah,
[19]Chuang,
Y.C. and Lin, C.M., (1999), “Foreign Direct Investment, R&D and Spillover
Efficiency: Evidence from Taiwan's Manufacturing Firms”, Journal of Development Studies, Vol. 35(4), pp. 117-137.
[20]Khan
(2006), “Macro Determinants of Total Factor Productivity in Pakistan,” SBP Research Bulletn, Vol, 2(2): pp.
383-401.
[21]De Mello, L. R. (1999), “Foreign Direct
Investment-led growth: Evidence from Time Series and Panel Data” Oxford
economic papers, Vol, 51(1):
pp. 133-151.
[22]Aitken, B.
J., & Harrison, A. E. (1999), “Do Domestic Firms Benefit from Direct Foreign Investment? Evidence from
Venezuela”, American Economic Review, Vol, 39(3): pp. 605-618.
[23]Choe, J. I.
(2003), “Do Foreign Direct Investment and Gross Domestic Investment Promote
Economic Growth?” Review of Development Economics, Vol, 7(1):
pp. 44-57.
[24]Li, X.,
& Liu, X. (2005), “Foreign Direct Investment and Economic Growth: An
Increasingly Endogenous Relationship”, World development, Vol, 33(3): pp. 393-407.
[25]Woo, J. (2009). Productivity growth and
technological diffusion through foreign direct investment. Economic Inquiry, 47(2), 226-248.
[26]Alfaro, et
al. (2004). “FDI and economic growth: the role of local financial
markets”, Journal of international economics, 64(1),
89-112
[27]Pessoa, A.
(2005), “Foreign Direct
Investment and Total Factor Productivity in OECD Countries: Evidence from
Aggregate Data”. Faculdade
de Economia, Universidade do Porto.
[28][29]Organization
for Economic Co-operation and Development. (2002), “Foreign Direct Investment For Development:
Maximizing Benefits, Minimizing Costs”, OECD Publishing.
[30]Aitken, B.
J., & Harrison, A. E. (1999), “Do Domestic Firms Benefit from Direct Foreign Investment? Evidence from
Venezuela”, American Economic Review, Vol, 39(3): pp. 605-618.
[31]Lipsey, R.E
and F. Sjöholm (2004), “FDI and Wage Spillovers in Indonesian Manufacturing”, Review of World Economics, Vol. 140 (2),
pp. 321-332.
Appendix 1
DATA
OF PAKISTAN
YEARS
|
FDI
|
CF
|
GDP (PC)
|
1994
|
421024638.5
|
19.54642
|
420.3678
|
1995
|
722631560.7
|
18.54552
|
478.6193
|
1996
|
921976182.5
|
18.99666
|
486.7648
|
1997
|
716253125.4
|
17.9192
|
467.3242
|
1998
|
506000000
|
17.7112
|
453.4948
|
1999
|
532000000
|
15.56494
|
447.9562
|
2000
|
308000000
|
17.22663
|
514.158
|
2001
|
383000000
|
16.99636
|
492.3817
|
2002
|
823000000
|
16.58276
|
483.0319
|
2003
|
534000000
|
16.75802
|
546.1541
|
2004
|
1118000000
|
16.57801
|
631.4978
|
2005
|
2201000000
|
19.08126
|
693.1767
|
2006
|
4273000000
|
19.332
|
853.071
|
2007
|
5590000000
|
18.78707
|
929.5874
|
2008
|
5438000000
|
19.20584
|
1018.381
|
2009
|
2338000000
|
17.54948
|
986.9541
|
2010
|
2018000000
|
15.80456
|
1023.196
|
2011
|
1308770000
|
14.12137
|
1212.419
|
2012
|
858730000
|
15.07596
|
1252.42
|
2013
|
1307000000
|
14.56922
|
1275.302
|
2014
|
1867000000
|
14.98356
|
1315.268
|
2015
|
979000000
|
15.11762
|
1428.988
|
FDI = Foreign direct investment, net
inflows (BoP, current US$)
|
||
CF = Gross capital formation (%of GDP)
|
||
GDP (PC) = GDP per capita (current US$)
|
Data from database: World
Development Indicators
DESCRIPTIVE STATISTICS
Sample: 1994 2015
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CFI
|
FDII
|
GDP (PC)
|
|
|
|
|
|
|
|
|
|
|
|
Mean
|
30.12118
|
1.66E+10
|
864.9002
|
|
Median
|
31.42613
|
6.52E+09
|
694.9125
|
|
Maximum
|
38.03419
|
4.42E+10
|
1581.589
|
|
Minimum
|
22.05740
|
9.73E+08
|
354.8549
|
|
Std. Dev.
|
5.564276
|
1.53E+10
|
468.7199
|
|
Skewness
|
-0.030365
|
0.518644
|
0.452657
|
|
Kurtosis
|
1.318355
|
1.703057
|
1.557597
|
|
|
|
|
|
|
Jarque-Bera
|
2.477666
|
2.528189
|
2.658444
|
|
Probability
|
0.289722
|
0.282495
|
0.264683
|
|
|
|
|
|
|
Sum
|
632.5448
|
3.64E+11
|
19027.80
|
|
Sum Sq. Dev.
|
619.2233
|
4.92E+21
|
4613665.
|
|
|
|
|
|
|
Observations
|
21
|
22
|
22
|
|
|
|
|
|
|
Appendix 2
DATA OF INDIA
YEARS
|
FDI
|
CF
|
GDP (PC)
|
1994
|
9.73E+08
|
23.19394
|
354.8549
|
1995
|
2.14E+09
|
26.05334
|
383.5509
|
1996
|
2.43E+09
|
22.0574
|
410.8184
|
1997
|
3.58E+09
|
24.51326
|
427.2362
|
1998
|
2.63E+09
|
23.51399
|
425.4453
|
1999
|
2.17E+09
|
26.82388
|
455.4735
|
2000
|
3.58E+09
|
24.11475
|
457.2835
|
2001
|
5.47E+09
|
25.57282
|
466.2142
|
2002
|
5.63E+09
|
24.96828
|
486.6405
|
2003
|
4.32E+09
|
26.13817
|
565.3355
|
2004
|
5.77E+09
|
32.45414
|
649.7106
|
2005
|
7.27E+09
|
34.27964
|
740.1143
|
2006
|
2E+10
|
35.87169
|
830.1632
|
2007
|
2.52E+10
|
38.03419
|
1068.679
|
2008
|
4.34E+10
|
35.5254
|
1042.084
|
2009
|
3.56E+10
|
36.29696
|
1147.239
|
2010
|
2.74E+10
|
36.52843
|
1417.074
|
2011
|
3.65E+10
|
36.3866
|
1539.606
|
2012
|
2.4E+10
|
34.69901
|
1503.004
|
2013
|
2.82E+10
|
31.42613
|
1498.872
|
2014
|
3.387E + 10
|
34.09285
|
1576.818
|
2015
|
4.420E + 10
|
N.A
|
1581.589
|
FDI = Foreign direct
investment, net inflows (BoP, current US$)
|
|||
CF = Gross capital
formation (%of GDP)
|
|||
GDP (PC) = GDP per
capita (current US$)
|
Data from
database: World Development Indicators
DESCRIPTIVE STATISTICS
Sample: 1994 2015
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CFI
|
FDII
|
GDP (PC)
|
|
|
|
|
|
|
|
|
|
|
|
Mean
|
30.12118
|
1.66E+10
|
864.9002
|
|
Median
|
31.42613
|
6.52E+09
|
694.9125
|
|
Maximum
|
38.03419
|
4.42E+10
|
1581.589
|
|
Minimum
|
22.05740
|
9.73E+08
|
354.8549
|
|
Std. Dev.
|
5.564276
|
1.53E+10
|
468.7199
|
|
Skewness
|
-0.030365
|
0.518644
|
0.452657
|
|
Kurtosis
|
1.318355
|
1.703057
|
1.557597
|
|
|
|
|
|
|
Jarque-Bera
|
2.477666
|
2.528189
|
2.658444
|
|
Probability
|
0.289722
|
0.282495
|
0.264683
|
|
|
|
|
|
|
Sum
|
632.5448
|
3.64E+11
|
19027.80
|
|
Sum Sq. Dev.
|
619.2233
|
4.92E+21
|
4613665.
|
|
|
|
|
|
|
Observations
|
21
|
22
|
22
|
|
|
|
|
|
|
Appendix 3
DATA OF CHINA
YEARS
|
FDI
|
CF
|
GDP (PC)
|
1994
|
3.38E+10
|
42.20333
|
469.2128
|
1995
|
3.58E+10
|
41.89593
|
604.2284
|
1996
|
4.02E+10
|
40.44153
|
703.1207
|
1997
|
4.42E+10
|
37.94713
|
774.4675
|
1998
|
4.38E+10
|
37.10113
|
820.8658
|
1999
|
3.88E+10
|
36.74463
|
864.7308
|
2000
|
3.84E+10
|
35.11864
|
949.1781
|
2001
|
4.42E+10
|
36.26769
|
1041.638
|
2002
|
4.93E+10
|
37.86585
|
1135.448
|
2003
|
4.95E+10
|
41.20296
|
1273.641
|
2004
|
6.21E+10
|
43.26315
|
1490.38
|
2006
|
1.33E+11
|
42.97174
|
2069.344
|
2007
|
1.69E+11
|
41.73775
|
2651.26
|
2008
|
1.87E+11
|
44.04627
|
3413.589
|
2009
|
1.67E+11
|
48.24343
|
3748.504
|
2010
|
2.73E+11
|
48.21862
|
4433.341
|
2011
|
3.32E+11
|
48.26513
|
5447.309
|
2012
|
2.96E+11
|
48.65982
|
6092.782
|
2013
|
3.48E+11
|
49.28513
|
6807.431
|
2014
|
2.68097E+11
|
46.19884
|
7587.289
|
2015
|
2.49859E+11
|
N.A
|
7924.654
|
FDI = Foreign direct
investment, net inflows (BoP, current US$)
|
|||
CF = Gross capital
formation (%of GDP)
|
|||
GDP (PC) = GDP per
capita (current US$)
|
Data from database: World Development Indicator
DESCRIPTIVE
STATISTICS
Sample: 1994 2015
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CFC
|
FDIC
|
GDP (PC)
|
|
|
|
|
|
|
|
|
|
|
|
Mean
|
42.37037
|
1.37E+11
|
2819.706
|
|
Median
|
42.09902
|
8.67E+10
|
1610.753
|
|
Maximum
|
49.28513
|
3.48E+11
|
7924.654
|
|
Minimum
|
35.11864
|
3.38E+10
|
469.2128
|
|
Std. Dev.
|
4.496380
|
1.11E+11
|
2473.413
|
|
Skewness
|
0.072439
|
0.645757
|
0.905664
|
|
Kurtosis
|
1.846591
|
1.897270
|
2.375695
|
|
|
|
|
|
|
Jarque-Bera
|
1.182424
|
2.643685
|
3.364779
|
|
Probability
|
0.553656
|
0.266644
|
0.185929
|
|
|
|
|
|
|
Sum
|
889.7777
|
3.01E+12
|
62033.54
|
|
Sum Sq. Dev.
|
404.3487
|
2.58E+23
|
1.28E+08
|
|
|
|
|
|
|
Observations
|
21
|
22
|
22
|
|
|
|
|
|
|
Appendix 3
COMPARATIVE ANALYSIS
Ranking of countries
according to FDI inflows
1-
China
2-
India
3-
Pakistan