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From table 5 we can see that generally trade openness is affecting a country’s GDP in a positive way. But in the short run, trade openness in the CJK is still below the equilibrium. This suggests that trade openness is still finding its form in this area. Although we might not see regionalism which liberalize trade in the short run, but the trend towards openness in trade Vis a Vis regionalism is progressing in a respectful manner. We can see this through the adjustment rate for the long run equilibrium (the coefficients of residuals) that yields an average of 1.1; consequently we might see regionalism in North East Asia happen in the future. As expected, IIT, TCI and Spillover effect for the case of Japan (table 6), Korea (table 7) and China (table 8) have positive influence on ASEAN4’s income (GDPCAP). The result shows us the importance of these factors for ASEAN’s welfare. The spillover effect variable which is included in the above regression has a more detail specification. Below is the explanation:
Spill-Over Effect: From table 9 we can conclude that the North East Asian (Japan, Korea and China) economic growth boost the ASEAN4 economic growth, it confirms the proposition of this study. Investment flows, in the form of FDI, has also operated as a dominant integrating power in East Asia as whole. Although we cannot find legitimate determinant for FDI in the output, but it is clear that FDI is trade related in nature. With its essentially open and outward-looking economies, the region is highly dependent on foreign investment for its economic growth. But still, the boosting power is not as much as in the spillover effect from the giant countries of Japan, Korea and China. Japan, in terms of GDP growth, has the biggest influence towards ASEAN4 followed by China and Korea at the second and third place. This fact is described by the coefficient parameter that gives the value of 0.546, 0.311 and 0.250 for Japan, China and Korea respectively.
The ranking of influence is presumably caused by the number FDI inflows to ASEAN from these countries as described in Table 10. The only bias is on China and Korea, even though the cumulative FDI from Korea to ASEAN4 was bigger than China’s, but it does not seem to be reflected on the ranking of influence. As for this, it is assumed that the high economic growth rate of China had been the major contributing factor that overtook the influence of Korea’s cumulative FDI flow to ASEAN4. However, such factor is not enough to surpass (From the ECM simulation as confirmed earlier, we found that China has taken over Japan’s role in East Asia. But this is true if we address the long run effect. This section only measures the present condition in the absence of the intertemporal problem.) Japan’s influence to ASEAN4’s economic growth since Japan’s FDI contribution to ASEAN4 outweighed China’s by more than one hundred folds.
The story goes hand in hand with the flying-geese hypothesis that was developed by Japanese economist, Kaname Akamatsu. his model has been frequently proposed to examine the patterns and characteristics of East Asian economic integration. “The premise of the flying-geese pattern suggests that a group of nations in this region are flying together in layers with Japan at the front layer. The layers signify the different stages of economic development achieved in various countries”. In the flying-geese model of regional economic development, Japan as the leading goose leads the second-tier geese (China Korea) which, in their turn, are followed by the third-tier geese (ASEAN4).

Table 7. Korea-ASEAN4 relation

Dependent Variable: LOG(GDPCAP(ASEAN4))
Independent Variables Coefficient
IIT Korea-ASEAN4 3.412017
TCI Korea-ASEAN4 0.027086
Spillover Effect (Korea-ASEAN4) 1.425999
TAX -0.071816
R-squared 0.850145

Table 8. China-ASEAN4 relation

Dependent Variable: LOG(GDPCAP(ASEAN4))
Independent Variables Coefficient
IIT China-ASEAN4 0.233899
TCI China-ASEAN4 0.018696
Spillover Effect (Korea-ASEAN4) 0.389208
TAX -0.232781
R-squared 0.526109

Table 9. Two Stage Least Squares Regression Output

Dependent Variables Y C I X
Independent Variables
Y na 0.776
-0.087 na
C 0.470
na na -0.64
I 0.025 na na na
X 0.072 na na na
Instrumental variables
Y (Japan) 0.546
na na 2.949
Y (China) 0.311
na na 1.112
Y (Korea) 0.250
na na -3.760
C na 0.01 na na
r na na 0.137 na
Y na na na na
EX na na na 0
G 0.122 na na na

Table 10. FDI flows to ASEAN 4 (US$ million)

Host country Indonesia Thailand Malaysia Phillipines Total Cummulative 1995-2003
Source Country
Japan 288.06 8,096.02 4,761.11 3,055.68 16200.87
Korea 331.88 235.58 98.51 238.13 904.1
China -36.78 50.16 120.72 4.07 138.17