Thesis (Ph. D.)--Florida State University, 2004. / Advisor: Dr. Will H. Moore, Florida State University, College of Social Sciences, Dept. of Political Science. Title and description from dissertation home page (June 18, 2004). Includes bibliographical references.

Thesis (Ph. D.)--State University of New York at Binghamton, Political Science Department, 2006. / Includes bibliographical references.

Thesis--School of Advanced Airpower Studies, Maxwell Air Force Base, Ala., 1992-93. / Title from title screen (viewed Nov. 7, 2003). "June 1994." Includes bibliographical references.

Master of Science / Department of Agricultural Economics / Tian Xia / China has always been one of the world’s largest grain producers, and Jilin is the largest grain-producing province in China. According to the Report on the Work of the Government 2018, the yield per mu (0.165 acre) has remained the first of the country for the past five years; and the grain commodity rate, the volume of transfers and the possession per capita have remained at the forefront of the country, making a significant contribution to ensuring national food security. This study is to compare efficient allocation of resources through designing a linear programming model with current allocation of resources to find out potential improvements and policy suggestions for future agricultural structure, rational cultivation of grains and market prediction for Jilin, China. In addition, this study examines what role the government regulations play in the grain production in China and how the trade war affects the grain production.

This thesis examined the impact of the U.S-China trade war on the global, U.S, and China?s agricultural exports while considering the competing suppliers? effect using a highly disaggregated HS 6-digit trade flow data in the structural gravity model. The empirical results indicate that the trade war caused about 8.6% and 17% reduction in U.S and China?s agricultural exports, respectively. However, global agricultural export was not negatively impacted during the trade war. Finally, the results also showed that tariff increases by U.S caused an increased in U.S competing suppliers? exports to China. Similarly, China?s retaliatory tariffs caused an increase in China?s competing suppliers? exports to the U.S.

The thesis assesses Made in China 2025, China's plan to improve its manufacturing base in high tech industries, and the reactions it has prompted from the international community. The roots of the current China-US trade war can also trace its roots back to MIC 2025 as the US and other Western powers have complained of unfair practices such as forced technology transfers and myriad state-backed acquisitions of foreign technology companies. China justifies its behaviour with its "developing" status, but as it assumes dominant position in multiple high tech industries, that excuse seems to ring hollow. There are signs that China will start to open its markets more and adopt fairer practices.

This study investigates the effect of protectionist tariffs on firm performance, income tax payments, and shareholder payouts and investment. Using the US–China trade war and related Section 301 tariffs as a setting, I find that US firms impacted by these tariffs experience decreased firm performance while simultaneously increasing cash tax planning to presumably decrease their total cash burden to the government. I also find that impacted firms decrease shareholder payouts and acquisitions, but do not decrease other real investment activities that may negatively impact operating performance. Cross-sectional analyses confirm that these effects apply to domestic firms, do not appear to be driven by the retaliatory Chinese tariffs, and are more pronounced for those facing higher market competition or applying for exclusions from the protectionist tariffs.

Thesis advisor: Rosen Valchev / This thesis explores the impact of Donald Trump’s tweets related to China on the financial markets in the United States and China, particularly during the U.S.-China trade war period. The study collects financial variables of interest, including the USC-CNY exchange rate and several stock indices from both countries, at hourly intervals from January 2018 to December 2020, and uses OLS regression models to examine the immediate impact of Trump’s tweets on these variables. The study finds that Trump’s tweets related to China had an immediate impact on several financial variables, including a slight negative impact on the USD-CNY exchange rate, the U.S. stock market (S&P 500), the Chinese A-share stock market (CSI 300), and the U.S. industrials sector (MSCI USA Industrials index). Multiple regression analyses show that the number of tweets has a significant impact on the U.S. stock market and the U.S. industrials sector, while the number of retweets appears to be more market-moving than the number of favorites. The study concludes that Trump’s tweets during the trade war period were perceived by the market as a signal of a potential shift in U.S. trade policy towards China, leading to uncertainty and volatility in the financial markets. / Thesis (BA) — Boston College, 2023. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Economics.

This paper examines the potential impact of the Section 232 Tariffs on Steel and Aluminum on employment using county-level data. This study finds that although employment has increased in steel and aluminum related manufacturing industries, it has decreased in a significant downstream industry of manufacturers of steel products. Furthermore, I analyzed the difference in employment trends between counties that voted majority Trump in the 2016 presidential election and counties that voted majority Clinton, and between counties that experienced marginal victories and counties that voted solidly Democrat or Republican. I find that Trump counties have experienced the impact of the tariffs more strongly than Clinton counties, whether positive or negative. Similarly, swing counties have seen a much larger positive trend in employment in the primary metal refinement and processing industries, and a much larger negative trend in steel product manufacturing from purchased steel compared to non-swing counties.

There is an ongoing trade war between the two largest economies in the world. Since the trade war is still ongoing, few studies have been done to investigate how it affects the global economy. The purpose of this thesis is to analyze the trade war’s effect on the Swedish stock market between the 2nd of March 2018 when U.S. president Donald Trump first threatened to impose tariffs on Chinese imports to the 15th of January 2020 when the phase one deal was signed. Data is collected from Donald Trump’s official twitter account and by statements from the U.S. and Chinese governments. An event study is then made by using the market model to find abnormal returns for different sectors and stocks on OMXS large cap. The study shows that the sectors react differently to the announcements. Some sectors were not affected at all and others were heavily affected. Telecommunication is a sector that had an average cumulative abnormal return close to zero both when there was positive news and negative news about the trade war. Contrarily, a sector that seems to be highly correlated to the news about the trade war is the Technology sector. Basic Resources is the most affected sector in the study when bad news occurred. From our study, we can conclude that the Swedish stock market is affected by the trade war.