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NURHIKMAH OLA LAIRI (LAILUOLA)
Ph.D International Trade
Student Id : 10104610
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This study investigates the causal links between trade, economic
growth and inward foreign direct investment (FDI) in China at the
aggregate level.
The integration and cointegration properties of quarterly data are
analysed. Long-run relationships between growth, exports, imports and
FDI are identified in a cointegration framework,in which this paper finds
bi-directional causality between economic growth, FDI and exports.
Economic development, exports and FDI appear to be mutually
reinforcing under the open-door policy.
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Many studies have investigated the relations
between China’s inward FDI and other aspects of
the Chinese economy. However, there has been
little detailed empirical study of causal links
between FDI, trade and economic growth in
China, especially in a multivariate framework.
Understanding the causal connections between
these phenomena is important for development
strategies in China and other developing
countries.
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Two limitations of the previous research are
Bivariate causality tests may be seriously biased if
relevant covariates are omitted
test outcomes from equations estimated in levels
may be unreliable if data are non-stationary.
The contribution of this paper is to examine the
causal relationship between economic growth, trade
and FDI in China by using multivariate Granger
causality tests in a co integration framework.
This study tests the integration properties of the
data, then employs the Johansen procedure to detect
the number of cointegrating vectors, and then tests
causality in the resulting restricted VARECM.
This study is interested in the interplay of four
variables, GDP, FDI, Imports, and Exports; to
set the scene, therefore, consider a VAR
involving four variables, W;X;Y;and Z. In a
stationary setting, a Granger causality test in
such a structure would be carried out
(following Ghartey,1993)
The following regression s are applied
Quarterly exports (EX) and imports (IM) from 1981:1 to1997:4 are
obtained from the International Financial Statistics Yearbook. We treat
exports and imports separately to allow for the possibility that their
influence is asymmetric. Quarterly inward FDI data for the same period
are acquired from various sources, including the China State Statistical
Bureau and Journal of International Trade (in Chinese). These series are
deflated using the GDP deflator (1990 =100). No quarterly or monthly
GDP statistics for China are available, only monthly gross industrial
output (GIO) at 1990 constant prices, so this study must construct
an estimated quarterly series
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TESTING FOR INTEGRATION
This study works throughout with the Logarithms
of the variables, so that first differences
correspond to growth rates. The null hypothesis of
a unit root in the logarithm is not rejected for any
of the four variables. However, each of the logged
series is stationary in first differences, so all the
variables are integrated of order one. Therefore,
the causality tests in this paper are based on
estimation of Equation 5 with seasonal dummies
and further lagged differences on the RHS
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TESTING FOR COINTEGRATION
After a general-to-specific search starting with a
system with 4 lags, constant and seasonal
dummies, a model with constant and seasonal
dummies constrained to lie in the cointegrating
space was chosen. Three lagged differences are
required since the reduction of lag length from 3
to 2 was rejected by the residual diagnostics. The
fitted series and residuals, and the residual
diagnostics for the maintained model are shown in
Table 3. The test for cointegration rank described
by Johansen and Juselius (1990) is reported in
Table 2
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Testing for weak exogeneity and causality
Maintaining a cointegration rank of two, two normalizing and two
exclusion restrictions for identification are introduced; that is, this study
normalizes on LGDP in Equation 7 below, and on LFDI in Equation 8, and
excludes LFDI from Equation 7 and LGDP from Equation 8, which leads to
the cointegrating relations below: where SD represents seasonal dummy
variables.
Equation 8 reflects the relationship between FDI, exports and imports.
Under the policy of export requirements,f oreign invested enterprises (FIEs)
will tend to be export-orientated firms. FIEs are allowed to access world
markets and are able to operate with the minimum of administrative and
other restrictions after they set up in China. As a result, FIEs have made a
great contribution to the growth of Chinese exports
Multivariate causality tests, applied to quarterly data from
1981:1 to 1997:4, conducted in the VARECM framework
show that two-way causal connections exist between
economic growth, FDI and exports, with rather weaker
evidence of feedback from imports to the other three.
The results also show that failure to account for
interaction
between FDI, growth and external trade can produce
spurious results in the analysis of the relationships
between
these four variables, as may be evident in some
previously
reported studies.