The impact of foreign direct investment on employment opportunities: panel data analysis: empirical evidence from Pakistan, India and China.
Rizvi, Syed Zia Abbas ; Nishat, Muhammad
Over the past two decades, the continent of Asia received a large
amount of FDI from developed regions. Additionally, in the Asia, India
and China received a major chunk of foreign direct investment and FDI
flows to Pakistan also increased significantly. Many studies show that
the inflow of FDI plays a significant role in generating employment in
host countries. The objective of this study is to undertake an empirical
study on creation of employment opportunities by FDI during 1985-2008 in
the Asian region. In this regard, we have taken the sample of three
countries i.e. Pakistan, India and China from the same region. The
Im-Pesaran-Shin (IPS) test of unit root is applied to find out the order
of integration. The long run relationship is investigated through the
Pedroni (1999) test of panel cointegration. At last, the Seemingly
Unrelated Regression (SUR) method is used for estimation of the impact
of FDI inflows on employment levels in three countries. Implications for
FDI policy are spelt out in the light of these empirical results.
JEL classification: F23, E24, C23
Keywords: FDI, Employment, Panel Data
1. INTRODUCTION
One of the most important and sensitive areas for developing
countries is foreign direct investment (FDI). It is now defined as not
only a simple transfer of money, but as a mixture of financial and
intangible assets such as technologies, managerial capabilities,
marketing skills and other assets. There is a major debate in the
literature regarding the impact of FDI on economic growth. The
traditional argument states that an inflow of FDI improves economic
growth and thereby enhances employment opportunities. Most studies [Hill
and Athukorala (1998) have shown that FDI's social and
distributional impact on the host country has been generally favourable
in developing countries of various regions. Apart from bringing in a
package of highly productive resources into the host economy there have
been a visible positive impact on the creation of jobs not only in those
sectors attracting FDI inflows but also in the supportive domestic
industries.
In recent years, Asia received a large amount of FDI from developed
regions. With in the Asia, India and China received a major chunk of
foreign direct investment and FDI flows to Pakistan also increased
significantly. The objective of this study is to undertake an empirical
study regarding creation of employment opportunities by FDI in the
continent of Asia during 1985-2008. Our sample consists of three Asian
countries i.e., Pakistan, India and China. We use the panel data
technique in order to overcome some econometric problems (i.e.,
autocorrelation in time series data and heteroscedasticity in
cross-sectional data) from the data, save the time for applying tests on
each country individually and get results in disaggregated form. In
addition, as panel data technique gives disaggregated results it will
help us to recommend policies for each country individually. The papel
has been organised as follows. A brief introduction is given in Section
I while the review of literature is presented in Section II. Section III
describes the methodology and data followed by empirical results which
are discussed in Section IV. Section V provides summary and concluding
remarks.
II. REVIEW OF LITERATURE
Nunnenkamp, Bremont, and Waldkirch (2007) raised the question
whether foreign direct investment (FDI) contributed to employment
generation in Mexico and, thereby, helped overcome the country's
pressing labour market problems. The analysis drew on highly
disaggregated FDI and employment data covering almost 200 manufacturing
firms. They estimated dynamic labour demand functions for blue and white
collar workers, including both FDI and its interaction with major
industry characteristics. By employing the GMM estimator suggested by
Arellano and Bond (1991), they accounted for the relatively short time
dimension of the panel data (1994-2006). It turned out that FDI had a
significantly positive, though quantitatively modest impact on
manufacturing employment in Mexico. In contrast to a widely held view,
this applies to both white collar and blue collar employment. Moreover,
the positive effect on blue collar employment diminished with increasing
skill intensity of manufacturing industries.
Another important study was done by Altzinger and Bellak (1999).
The objective of this paper is to analyse, whether the relatively better
domestic employment performance of domestic firms (direct FDI) compared
to foreign-owned firms (indirect FDI) could be linked to FDI abroad. (1)
Based on an analysis of the sales and trade structure of a sample of
Austrian investors in Central and East European Countries (CEECs), this
paper tested the hypothesis that these two groups of investors had
different motives to invest in CEECs and therefore their activities in
CEECs differ by type (sales affiliate, production abroad) and
consequently the employment effects at home. Regression results
confirmed that direct FDI were more strongly determined by labour costs
and exhibit an employment pattern related to a deeper international
division of labour (including production), while indirect FDI was based
relatively more on market seeking investment. Empirical results also
confirmed that employment effects at home differ. The positive
(negative) effect of one additional unit of parent (affiliate) sales on
domestic employment for indirect FDI compared to direct FDI was larger
(smaller).
According to established theory, the activities of affiliates can
be related to the motives of FDI, namely efficiency seeking, market
seeking and strategic-asset seeking flows. The impact of these types of
FDI on trade patterns are explained by distinguishing four kinds of
trade linkages between the parent firm and her affiliates: (a) the
substitution of former exports through FDI, (b) growing (re-)imports of
goods and services produced abroad, (c) FDI associated exports of goods
and services and (d) FDI induced exports of other product lines neither
produced by the foreign affiliate nor exported earlier by the parent
firm [Agarwal (1996); Altzinger and Winklhofer (1998)]. The overall
impact of FDI on trade (and consequently on domestic employment) is the
sum of negative (export substitution, re-impomts) and positive effects
(associated and induced exports) and can be tested only empirically. Any
distinction between direct and indirect FDI is justified only if their
trade linkages differ.
Empirically, if different trade linkages between parent firms and
affiliates exist for direct and indirect FDI, their effect on domestic
employment will differ as well. Blomstrom, et al. (1997) argued, that
rivalry for markets is one of the main reasons for a positive
relationship between foreign production and domestic employment, which
provides one argument to distinguish market-oriented from
efficiency-oriented FDI.
A related question is, whether the trade linkages change from the
period of entry into a foreign market and the maturing of the FDI.
Several theories suggest that entry occurs first via a sales subsidiary,
which may be extended into a production unit later on e.g. [Bergsten, et
al. (1978)]. In newly developed markets with low-cost production
locations, some firms may switch their operations there over time. These
considerations lead to a number of questions, such as: Do direct and
indirect FDI follow different trajectories or are such strategies
idiosyncratic to firms? Do they result in different trade linkages
between parent firms and affiliates for direct and indirect FDI and
consequently change the effect on domestic employment?
Ajaga and Nunnenkamp (2008) investigated the long-run relationships
between inward FDI and economic outcomes in terms of value added and
employment at the level of US states. Johansen's (1988)
cointegration technique and Toda and Yamamoto's (1995) Granger
causality tests were applied to data for the period of 1977 to 2001.
They found cointegration as well as two-directional causality between
FDI and outcome variables. This holds for both measures of FDI (stocks
and employment in foreign affiliates) and independently of whether they
considered the states' overall economy or their manufacturing
sector alone.
Federico and Alfredo (2007) assessed the impact of Italy's
outward foreign direct investment (FDI) on local (domestic) employment
growth between 1996 and 2001 for 12 manufacturing industries and 103
administrative provinces. Their main result was that, controlling for
the local industrial structure and area fixed effects, FDI is associated
with faster local employment growth, relatively to the national industry
average. They also found that employment in small plants was not
negatively influenced by higher levels of FDI. Their findings did not
support the idea that FDI was detrimental to local employment growth in
the home country.
While the recent increase in foreign direct investment (FDI) to
African countries is a welcome development, the question remains as to
the impact of these resource inflows on economic development. Ndikumana
and Verick (2008) investigated a key channel of the impact of FDI on
development is through its effects on domestic factor markets,
especially domestic investment and employment. In this context, they
analysed the two-way linkages between FDI and domestic investment in
Sub-Saharan Africa. Their results suggested that firstly, FDI crowds in
domestic investment, and secondly, countries will gain much from
measures aimed at improving the domestic investment climate. Moreover,
they identified alternatives to resource endowments as a means of
attracting foreign investment to non-resource rich countries.
Buffie (1993) analysed the impact of foreign investment on
underemployment and domestic capital accumulation in a two-sector dual
economy model. He found that foreign investment in the high-wage
manufacturing sector crowded out domestic capital on a greater than
one-for-one basis and lowered the level of manufacturing sector
employment in the long-run. By contrast, foreign investment in an
enclave sector of in the primary export sector crowded in domestic
capital and unambiguously reduces underemployment. Furthermore, under
weak conditions, foreign investment in the enclave or primary export
sector was unambiguously welfare enhancing viewed over the entire
transition path.
Broadly the literature survey shows that MNE employment can promote
growth and poverty reduction in host countries in four ways.
(i) MNE Employment has a Direct and Indirect Impact on Domestic
Employment
FDI often generates new employment (direct employment is higher in
green filed investments) and creates jobs (indirectly) through forward
and backward linkages with domestic firms. Estimates for a number of
developing countries indicate that FDI has a multiplier effect on
domestic employment. Aaron (1999) estimated that FDI in developing
countries created about 26 million direct jobs and 41.6 million indirect
jobs in 1997 (a multiplier of about 1.6). Iyanda (1999) obtained a
higher estimate for Namibia: about 2 to 4 jobs were created for each
worker (directly) employed by foreign affiliates.
(ii) MNE Employment Boosts Wages in Host Countries
A number of studies have shown that MNEs pay higher wages than
domestic firms even after controlling for firm and worker
characteristics [see Lipsey (2002) for a survey]. Furthermore, the
presence of mulfinationals sometimes generates wage spillovers: wages
tended to be higher in industries and in provinces that have a higher
foreign presence [Lipsey (1994); Lipsey and Sjoholm (2001)]. (2)
(iii) MNE Employment Fosters Technological Transfers
One of the most common and least expensive ways by which foreign
technology gets diffused in host countries' is through labour
turnover, as domestic employees (especially employees in higher level
positions) move from foreign firms to domestic firms. (3) Bloom (1992)
found substantial technological transfer in South Korea when production
managers left multinationals to join domestic firms. Indeed, foreign
firms sometimes pay higher wages in order to retain their workers, and
thereby prevent domestic firms from appropriating their superior
technology [cf., Glass and Saggi (2002)].
(iv) MNE Employment Enhances the Productivity of the Labour Force
in Host Country
Several studies have shown that workers in foreign owned
enterprises (FOEs) are more productive than workers in domestic owned
enterprises (DOEs). For example, Harrison (1996) analysed differences in
labour productivity between FOEs and locally owned firms in Morocco and
Cote d'Ivoire.
In 8 out of 12 industries in Morocco, output per worker was higher
in FOEs than in domestically owned firms, with a difference in
productivity ranging from 50 percent in electronics to about 130 percent
in nonmetallic minerals. In Cote d'Ivoire, the productivity gap
ecited in fewer industries (3 out of 12), however the gap was wider:
ranging from 50 percent in chemicals to about 500 percent in oil.
Ramachandran and Shah (1998) also report that added value per
worker is 59 percent higher for wholly owned foreign enterprises than
for local firms in Kenya, 178 percent higher for FOEs in Zimbabwe and
1,422 percent higher for FOEs in Ghana. The worker productivity gap may
be partly explained by the differences in training opportunities for
workers in FOEs and DOEs.
III. METHODOLOGY
III.1. Data
In this study, we consider a balanced panel of three countries i.e.
Pakistan, India and China over the period of 24 years from 1985-2008.
Three variables (i.e. employment, foreign direct investment and gross
domestic product) are used for empirical investigation. All of the data
except gross domestic product (GDP) of Pakistan is taken from IFS. The
GDP of Pakistan is taken from various issues of Economic Survey of
Pakistan. In order to remove the biasness from the estimates due to
differences in sizes of the economies we use employment to labour force
ratio and FDI to GDP ratio. Moreover, GDP is used in the form of growth.
The E-views 6.0 is used for empirical work.
III.2 Estimation Techniques
In order to find out the long run relation between three variables
we first check the order of integration by applying the unit root tests
given by Im-Pesaran-Shin (IPS). Then, after getting the order of the
integration the Pedroni's test of cointegration is applied.
Finally, a Seemingly Unrelated Regression (SUR) test is applied to
find out whether FDI has an impact upon employment in case of Pakistan,
India and China.
III.3. Unit Root Test
The first step in determining a potentially cointegrated
relationship is to test whether the variables involved are stationary or
non-stationary. If all the variables are stationary traditional
estimation methods can be used to estimate the (causal) relationship
among variables. If, however at least one of the series is
non-stationary more care is required. There are many tests available for
testing unit root in panel data which are;
* Fisher's (p)[lambda]) test (1932).
* Maddala and Wu (1999).
* The Levin-Lin (LL) tests (2002).
* The Im-Pesaran-Shin (IPS) test (2003).
Although the Fisher test can be applied but the disadvantage is
that the p- values have to be derived through Monte Carlo simulation.
So, we apply Im-Pesaran-Shin (IPS) test for unit root because it does
not have only comparative advantage over all other tests but it is
appropriate for our data as well. More over IPS test is the most
powerful test as compared to the other tests. Another reason for using
IPS test is that we have a balanced panel instead of different time
series for different samples. In addition, the IPS test is the most
cited unit root test in the literature. Another advantage of using the
IPS test is that it is based on heterogeneity of the autoregressive
parameters (there is a possibility of heterogeneity in the error
variances and the serial correlation structure of the errors).
III.4. Cointegration Test
With confirmation on the integrated order of variables of interest,
the question is that they might of might not have a common stochastic
trend, of, they might or might not be cointegrated. We resolve this
question by looking for a long-run relationship among the variables
using the panel cointegration technique. The available methods for panel
data cointegration are given as follows.
* Johansen (1988).
* Larsson, Lyhagen and Lothgren (2001).
* Pedroni (1999).
We apply the Pedroni (1999) test of cointegration. This technique
is a significant improvement over the conventional cointegration tests
applied on a single series. As explained in Pedroni (1999), conventional
cointegration tests usually suffer from unacceptable low power when
applied on data series of restricted length. The Panel cointegration
technique addresses this issue by allowing one to pool information
regarding common long-run relationships between a set of variables from
individual members of a panel. Further, with no requirement for
exogeneity of the regressors, it allows the short-run dynamics, the
fixed effects, and the cointegrating vectors of the long-run
relationship to vary across the members of the panel. Furthermore, it
provides appropriate critical values even for more complex multivariate
regressions. Pedroni (1999) refers to seven different statistics for
testing unit roots in the residuals of the postulated long-run
relationship. Of these seven statistics, the first four are referred to
as panel cointegration statistics; the last three are known as group
mean panel cointegration statistics. In the presence of a cointegrating
relation, the residuals are expected to be stationary. A positive value
for the first statistic and large negative values for the remaining six
statistics allows rejection of the null hypothesis.
III.5. Seemingly Unrelated Regressions (SUR)
The seemingly unrelated regression (SUR) method, also known as the
multivariate regression, of Zellner's method, estimates the
parameters of the system, accounting for heteroskedasticity and
contemporaneous correlation in the errors across equations.
III.6. Impulse Responses
An impulse response function traces the effect of a one-time shock
to one of the innovations on current and future values of the endogenous
variables.
IV. EMPIRICAL FINDINGS
We used the Im-Pesaran-Shin (IPS) test (2003) in order to find out
order of the integration of all three series used in the study. The
Appendix Table 1 reports these results. The t-value of Employment to GDP
ratio (EMP/GDP) is -3.67 at level with zero lag, FDI and GDP ratio
(FDI/GDP) is -4.94 at level with zero lag and GDP growth is -3.66 at
level with zero lag. Therefore each variable was seen to have a unit
root at level so we could investigate cointegration of the series at
level.
After knowing the order of integration we applied the test of
cointegration given by Pedroni (1999). Results are given in Appendix
Table 2. The result shows that first panel statistic is positive (v =
0.5) and rest of three panel statistics is negative (rho= -1.15, PP =
-2.22 and ADF = -2.24). On the basis of Pedroni test we can conclude
that series are cointegrated and have a long run relationship.
Then we used Pooled Estimation of Seemingly Unrelated Regression
(SUR) approach described in Agosin and Mayer (2000). In this model we
used one lag for estimating the equation. The optimum lag length is
found through Schwarz Information Criteria (SIC). Our result suggests
that only GDP has a significant impact upon level of employment in all
of the three countries. Results are reported in Appendix Table-3. In
addition, FDI does not have any impact upon the creation of employment
in Pakistan, India and China.
We also used standard techniques for estimating the impulse
response shocks of employment to the only significant variable including
in our model i.e. GDP growth. The results are prescribed in Appendix
Graph A. We found that GDP shocks explain 0.75 percent change in
employment during the second year then it gradually bottom out.
V. CONCLUDING REMARKS AND POLICY RECOMMENDATIONS
Our results are similar to those of Ndikumana and Verick (2008).
The policy implication is that whatever other benefits may accrue from
FDI it should not be expected to create employment opportunity in any of
the three countries directly and FDI enhancement policies must be
supplemented by the other measure to stimulate employment growth. Our
estimation of the impulse response shows that the growth elasticity of
employment on average in the three countries is extremely low and
employment enhancing policies must be priorities. Employment growth will
not occur in these three countries as a spontaneous consequence of
growth in GDP. As rising formal sector unemployment especially of
technical and professional manpower is becoming and increasingly
important problem in all three countries.
However some important limitations of the research must be noted.
We did not explicitly differentiate between direct and indirect impact
of DFI growth as was done by Altzinger and Bellak (1999). Had we done
so, their results might have been modified? Also it is likely that
employment impact of FDI might vary from industry to industry and the
over all insignificant relationship between FDI and employment growth
might reflect a canceling out of positive and negative impact of FDI
flows on employment in different industries. Therefore disaggregating
the data at least at an ISIC 3-digit level might also identified
significant relationship between manufacturing employment and FDI flows
in a group of industrial branches. We did not find impact of FDI on
employment opportunities in Pakistan, India and China. It may be due to
time lag because FDI can also have impact on employment through economic
growth.
Appendix Table 1
Im, Pesaran and Shin Test of Unit Root
Variable Test for Unit Root in Lag Length
Employment Level 0
FDI Level 0
GDP Level 0
Appendix Table 2
Pedroni Residual CointeRration Test
Statistic
Panel v-Statistic 0.57
Panel rho-Statistic -1.15
Panel PP-Statistic -2.22
Panel ADF-Statistic -2.24
Appendix Table 3
Seemingly Unrelated Regression
Coefficient Std. Error t-Statistic
Pakistan Intercept 0.860 0.039 21.947
[GDP.sub.t] -0.017 0.007 -2.237
[GDP.sub.t-1] -0.010 0.006 -1.681
[FDI.sub.t] 0.002 0.004 0.664
[FDI.sub.t-1] 0.000 0.004 0.108
India Intercept 0.854 0.039 22.150
[GDP.sub.t] -0.009 0.005 -1.620
[GDP.sub.t-1] -0.017 0.005 -3.072
[FDI.sub.t] 0.001 0.003 0.457
[FDI.sub.t-1] 0.001 0.003 0.473
China Intercept 0.853 0.039 21.874
[GDP.sub.t] -0.003 0.006 -0.564
[GDP.sub.t-1] -0.022 0.007 -2.976
[FDI.sub.t] 0.000 0.003 0.145
[FDI.sub.t-1] 0.002 0.004 0.427
Prob.
Pakistan Intercept 0.000
[GDP.sub.t] 0.027
[GDP.sub.t-1] 0.095
[FDI.sub.t] 0.508
[FDI.sub.t-1] 0.915
India Intercept 0.000
[GDP.sub.t] 0.107
[GDP.sub.t-1] 0.002
[FDI.sub.t] 0.648
[FDI.sub.t-1] 0.637
China Intercept 0.000
[GDP.sub.t] 0.574
[GDP.sub.t-1] 0.003
[FDI.sub.t] 0.885
[FDI.sub.t-1] 0.670
[GRAPHIC OMITTED]
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(1) Indirect FDI is a characteristic of outward FDI made by any
country's owned firms. While direct FDI is a characteristic of
outward FDI in which a large part is carried out by firms, which
themselves are affiliates of foreign Multinational. Enterprises (MNEs)
Altzinger and Bellak (1999).
(2) The conclusions of Lipsey (1994) and Lipsey and Sjoholm (2001)
are based on data from the United States and Indonesia, respectively.
The empirical evidence regarding wage spillovers is mixed. For example,
Aitken, et al. (1996) do not find evidence of wage spillovers in Mexico
and Venezuela. For a discussion of this issue see Lipsey (2002).
(3) See Blomstrom and Kokko (1998) for a survey of the literature
on FDI and technological spillovers.
Syed Zia Abbas Rizvi <zia.rizvi@yahoo.com> is Lecturer al
Institute of Business Management (IoBM), Karachi. Muhammad Nishat
<mnishat@iba.edu.pk> is Professor, Department of Finance and
Economics, Institute of Business Administration (IBA), Karachi.