NURHIKMAH OLA LAIRI (LAILUOLA) Ph.D International Trade Student Id :

 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.

 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.

 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

 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

 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

 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 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.