A Comparative Analysis on Macroeconomic Effects of the Korea-EU FTA : A Critical Investigation of Simulation Results
Bibliographic record
Abstract
Since the Korean economic crisis in 1997, Korean government has place more emphasis on regional policy cooperation rather than multilateral cooperation in order to minimize negative effects of other FTAs. Since the first FTA with Chile took effect in 2004, three more FTAs, with Singapore, EFTA, and ASEAN, have come into effect but Korea is still negotiating free trading with Mexico, Peru, Australia, New Zealand, GCC, and Canada. Korean government has considered the Korea-EU FTA very important because the EU is the world's largest economic bloc which includes 27 european countries with a total population of 487 million people. The EU is one of major trading partners to Korea. In 2007, the EU is the second largest export market to Korea and the fourth largest importing partner. Furthermore, the EU is also one of major foreign investors in Korea and its investment share is 41.2% of Korea's total foreign direct investment in 2007. Despite the importance of the Korea-EU FTA, its economic effects have not been evaluated enough yet in contrast with much debate on the Korea-U.S. FTA. In particular, as most of studies did not consider the tariff cuts due to free trade movement during the 2000s in the world, the macroeconomic effects of the Korea-EU FTA has not been fully examined and the issue is still an open question. It has been argued that the economic effects of Korea-EU FTA would not be fully evaluated for lack of information about the content and negotiation process which should have been provided by government. This paper critically investigates the effects of a Korea-EU FTA using the CGE model under various scenarios including the Korea-U.S. FTA. In simulating such economic effects, the paper uses the GTAP static model based on a new GTAP data set. The paper also comparatively analyzes the macroeconomic effects of the bilateral FTA between Korea and EU can be caused by either tariff reduction or elimination of non-tariff trade barriers. The former economic effects can be examined quantitatively in the CGE model framework but the latter effects can be evaluated qualitatively but hardly analyzed quantitatively. This study will place more emphasis on quantitative effects of tariff reduction between Korea and EU, rather than those of elimination of non-tariff trade barriers. Most of all, the simulated results show that Korea's real GDP would increase by 0.14-0.18% due to the Korea-EU FTA, under the assumption of the full elimination of tariffs in all agricultural and manufacturing sectors except service industries. On the other hand, under the same scenario additionally with reduction in trade barriers in service sectors by 50%, the real GDP effect of the Korea-EU FTA would be expected to increase by 0.54-0.86%. However, it is hard to measure exactly trade barriers to the service sectors because of lack in information and cross-country data on the trade barriers. For this reason, the paper uses Hoekman's tariff equivalents(1995) in the service industries but Hoekman's measures are still controversial. Considering the limitation to Hoekman's measures, the simulation results for the economic effect of the Korea-EU FTA under the scinario would not be that credible in contrast to the government argument. Next, the CGE simulation results show that both the Korea-EU FTA and the Korea-U.S. FTA would not be complementary. The economic effects of the Korea-EU FTA would be offset by the Korea-U.S. FTA. This implies that there is no robust evidence for government argument that both the FTAs have complementary effects. Finally, the results show that the real GDP effect of the Korea-EU FTA could be smaller when the GTAP DB version 7 is used for the CGE model rather than when the GTAP version 6 is used. This implies that the economic effects of the Korea-EU FTA and the Korea-U.S. FTA as well would be smaller over time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".