The Case of Korea, China, and Japan

학위논문 (석사)-- 서울대학교 대학원 : 국제대학원 국제학과(국제통상전공), 2019. 2. 안덕근.In regards to U.S. bilateral trade deficits, the United States has frequently used retaliatory threats under Section 301 of US Trade Law to restrict imports or open foreign markets. Section 301 of the Trade Act of 1974 provides the President discretionary authority to impose tariffs or other trade restrictions against foreign countries that are considered to be engaged in "unjustifiable, unreasonable, or discriminatory" trade practices. In the 1980s, as the United States faced with recession, appreciation of the dollar, and increasing trade deficit, the Reagan Administration adopted even more aggressive trade stance and increased the use of section 301 against trading partners beginning in 1985 to reach satisfactory agreement and gain market access. In addition, the Trade and Tariff Act of 1984 urged vigorous action by authorizing the United States Trade Representative (USTR) to self-initiate investigations. Section 301 was effectively used not only in bilateral negotiations, but also exercised leverage during the Uruguay Round negotiations. Since the World Trade Organization emerged, however, the United States rarely invoked section 301 until the Trump Administration called for a new approach in 2017. The Trump Administration revived section 301 of the 1974 Trade Act and launched an investigation against China's policies on intellectual property rights and technology transfer. Accordingly, this paper seeks to analyze section 301 cases involving Japan, Korea and China between 1975 and 2018, and examine trading partners' responses to US unilateral trade pressure. The paper first brings the re-emerging issue in section 301 and delves into developments of section 301 provisions. Then, it reviews all section 301 cases involving Japan, Korea, and China based on economic and political background, and provides significant case study of each country. Finally, concludes with the implications of ongoing US-China trade issue.미국은 무역수지 적자 문제가 발생된 경우 교역 상대국의 관행을 불공정 무역행위로 간주하고, 무역법 301조를 사용하여 상대국의 수입을 제한하거나 시장 개방을 목적으로 압력을 행사하곤 했다. 1974년 제정된 무역법 301조는 "부당하고 비합리적이거나 또는 차별적인" 무역 관행으로 간주되는 외국 정부에 대해 미 대통령의 권한으로 관세를 부과하거나 기타 무역을 제한할 수 있는 재량권을 부여하였다. 1980년대에는 미국이 불황을 겪으면서 달러가 절상되고 무역 적자가 증가하게 되는데, 이를 타개하기 위해 레이건 행정부는 1985년을 기점으로 적극적인 301조 조사를 통해 보다 만족스러운 협정을 도출하고 미국 기업의 해외 시장 접근성을 강화하였다. 또한, 1984년 무역관세법을 통하여 미국 무역대표부의 자체적 발의로 조사개시를 가능하게 함으로써 무역 상대국에 대해 공격적인 행동을 촉구하였다. 301조는 양자 간 협상에서뿐만 아니라 우루과이 라운드 협상에서도 영향력을 행사하는데 중요한 역할을 하였다. 하지만 세계무역기구가 설립된 이후 미국은 301조를 거의 사용하지 않았는데, 2017년 트럼프 행정부 출범 후 미 행정부는 301조를 적용해 중국의 지적재산권 정책에 대한 조사를 개시하였다. 이에 따라, 본 논문은 1975년부터 2018년도까지 미국이 일본, 한국, 중국에 적용한 301조 사건들을 분석하고 미국의 통상 압박에 따른 결과와 무역 상대국의 입장을 확인하고자 한다. 먼저, 301조가 재부상하게 된 배경과 미국 무역법상 301조 조항의 발전 과정에 대해 살펴본다. 그리고 일본, 한국, 중국과 미국 간의 경제적, 정치적 배경에 기초하여 발생된 301조의 모든 사례를 연구하고, 각국의 중요한 사례를 제공한다. 마지막으로 최근 대두되고 있는 미-중 무역 분쟁에 대한 시사점과 결론을 도출한다.Chapter I. Introduction . 1 1.1 Re-emerging issue in Section 301 1 1.2 Research Question 3 Chapter II. Historical Evolution of Section 301 5 2.1 Trade Expansion Act of 1962 . 5 2.2 Trade Act of 1974 . 7 2.3 Trade Agreements Act of 1979 10 2.4 Trade and Tariff Act of 1984 11 2.5 Omnibus Trade and Competitiveness Act of 1988 . 13 Chapter III. US Trade Disputes with Japan, Korea, and China under Section 301 17 3.1 US-Japan Trade Conflict 17 3.1.1 Political and Economic Background . 17 3.1.2 Section 301 Cases Targeting Japan . 20 3.1.3 Case Study - Semiconductors (Case No. 301-48) 25 3.2 US-Korea Trade Conflict . 26 3.2.1 Political and Economic Background . 26 3.2.2 Section 301 Cases Targeting Korea . 29 3.2.3 Case Study - Intellectual Property Rights (Case No. 301-52) . 32 3.3 US-China Trade Conflict 34 3.3.1 Political and Economic Background . 34 3.3.2 Section 301 Cases Targeting China . 36 3.3.3 Case Study - Market Access Barriers (Case No. 301-88) 39 Chapter IV. The Re-emergence of Trade Friction and Its Implications 42 4.1 US-China Trade War in 2018 . 42 4.2 China's Retaliatory Action 45 4.3 Implications 47 Chapter V. Conclusion 49 BIBLIOGRAPHY 51 국문초록 55Maste

정부 설탕 정책의 가격 안정성 효과 분석: NAFTA를 통한 시장개방 전후를 중심으로

학위논문 (석사)-- 서울대학교 대학원 농업생명과학대학 농경제사회학부, 2017. 8. 김관수.This paper measures the price stabilization effects of the U.S. sugar programs in the midst of complete sugar market liberalization with Mexico under the NAFTA. Previous research reveals that market liberalization in terms of opening a domestic market can either stabilize or increase the volatility of the domestic prices depending on the characteristics of market liberalization. In this regard, we measure the effectiveness of three sugar program pillars (marketing allotments, price support, and tariff rate quota) on mean price and volatility separately. Given the possibility of time-varying volatility reflected by the heteroscedasticity of the error terms, we utilize the Generalized Least Squares model to the U.S. raw cane sugar market, based on monthly data for the period of FY1991-FY2016. The estimation results indicate that the price volatility was exceptionally widened during the NAFTA as it is further evidenced by relatively high value of coefficient of variation. We found that price support through loan program performed as a price shifter while the elimination of import quotas on Mexican sugar weakened the price stabilization effects of the program.1. Introduction 1 2. An Overview of the United States Sugar Market and Policy 4 2.1 The Global Market for Sugar: production, consumption, and trade 4 2.2 A History of U.S. Sugar Program 9 2.3 U.S. Sugar Policy Instruments 11 2.3.1 Price Supports through Loan Program 11 2.3.2 Domestic Marketing Allotments 13 2.3.3 Tariff Rate Import Quota (TRQ) 15 2.3.4 Feedstock Flexibility Program 19 3. U.S.-Mexico Sugar Market Liberalization 20 3.1 U.S. Sugar Market Liberalization 20 3.2 Impact of NAFTA on U.S and Mexico Sugar Markets 23 3.3 Suspension Agreements on Sugar from Mexico 25 4. Pricing Models and Data 26 4.1 Basic Pricing Model with Stock and the Government Program 26 4.2 Additional Consideration for Raw Cane Sugar Price Model 28 4.3 Empirical Methods 30 4.4 Data 37 5. Estimation Results 41 5.1 Empirical Results for Raw Cane Sugar Equation 41 5.2 Discussion 46 6. Concluding Remarks 48 References 52 국문초록 58 Appendix 61 Appendix 1. Expected Volatility (E(σ ̂_t^2)) of U.S. Raw Cane Sugar Prices, Oct 1991–Dec 2016 61Maste

Cluster Analysis of Food Ingredients Consumption Patterns during the COVID-19 Pandemic

A growing corpus of literature has explored the changes in food consumption behaviors during the COVID-19 pandemic, but the demand-side responses at the firm-level are still not yet fully understood. This paper uses data from the 2016∼2020 Korean Food Ingredients Consumption Survey to develop a classification scheme for food ingredients into groups that have similar usage patterns during the pandemic. Using the K-means clustering and one-way ANOVA, 107 main food ingredients were classified into four groups and two groups were identified as being related to the pandemic. The change in purchase price and price variability are found to be the most important factors associated with differences in the consumption patterns.N

Tournament Based Ranking CNN for the Cataract grading

백내장 진단을 위한 토너먼트 기반의 랭킹 컨볼루셔널 뉴럴 네트워크 동작 방법 및 장치가 제시된다. 본 발명에서 제안하는 백내장 진단을 위한 토너먼트 기반의 랭킹 컨볼루셔널 뉴럴 네트워크 동작 방법은 백내장 데이터셋을 구성하는 복수의 클래스들을 복수의 집합으로 나누는 단계, 상기 복수의 집합으로 나누는 과정을 상기 복수의 클래스 모두가 하나의 집합에 하나의 클래스가 소속될 때까지 반복하는 단계, 상기 복수의 집합으로 나누어진 순서대로 토너먼트 구조를 생성하는 단계, 상기 복수의 집합으로 나누어진 백내장 데이터 셋을 판별하는 이진 컨볼루셔널 뉴럴 네트워크 모델(binary cnn model)을 학습시키는 단계 및 상기 학습시킨 이진 컨볼루셔널 뉴럴 네트워크 모델을 사용하여 입력 이미지(input image)의 이진 컨볼루셔널 뉴럴 네트워크 모델의 이진 출력을 획득하고, 획득된 이진 출력에 기초하여 토너먼트 구조에 따라 복수의 레이블 중 하나를 결정하는 단계를 포함한다

A 2-stage ranking-CNN for diagnosis of glaucoma from fundus images using CAM-extracted ROI as an intermediate input

안저 사진에서 녹내장 진단을 위해 CAM에서 추출된 ROI를 중간 입력자로 사용하는 2단계 랭킹 컨볼루셔널 뉴럴 네트워크가 제시된다. 본 발명에서 제안하는 안저 사진에서 녹내장 진단을 위해 CAM에서 추출된 ROI를 중간 입력자로 사용하는 2단계 랭킹 컨볼루셔널 뉴럴 네트워크 동작 방법은 제1-스테이지 랭킹 CNN을 통해 CAM(Class Activation Map) 마크 필터 이미지와 원본 안저 이미지를 결합하여 CAM으로부터 ROI(Region of Interests)를 추출하는 단계 및 제2-스테이지 랭킹 CNN을 통해 랭킹-CNN(Ranking-Convolutional Neural Networks)이 상기 ROI를 입력으로 사용하여 CNN을 다시 랭킹하고 최종 예측 값을 출력하는 단계를 포함한다

TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes

In this paper, we proposed Transferable Ranking Convolutional Neural Network (TRk-CNN) that can be effectively applied when the classes of images to be classified show a high correlation with each other. The multi-class classification method based on the softmax function, which is generally used, is not effective in this case because the inter-class relationship is ignored. Although there is a Ranking-CNN that takes into account the ordinal classes, it cannot reflect the inter-class relationship to the final prediction. TRk-CNN, on the other hand, combines the weights of the primitive classification model to reflect the inter-class information to the final classification phase. We evaluated TRk-CNN in glaucoma image dataset that was labeled into three classes: normal, glaucoma suspect, and glaucoma eyes. Based on the literature we surveyed, this study is the first to classify three status of glaucoma fundus image dataset into three different classes. We compared the evaluation results of TRk- CNN with Ranking-CNN (Rk-CNN) and multi-class CNN (MC?CNN) using the DenseNet as the backbone CNN model. As a result, TRk-CNN achieved an average accuracy of 92.96%, specificity of 93.33%, sensitivity for glaucoma suspect of 95.12% and sensitivity for glaucoma of 93.98%. Based on average accuracy, TRk-CNN is 8.04% and 9.54% higher than Rk-CNN and MC?CNN and surprisingly 26.83% higher for sensitivity for suspicious than multi-class CNN. Our TRk-CNN is expected to be effectively applied to the medical image classification problem where the disease state is continuous and increases in the positive class direction