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The recent US-China Trade War leads to a decrease in GDPs and welfare levels for the US and China as well as the whole world. The US-China Trade War also leads to the largest decrease in automobiles for US’s exports to China and the largest decrease in TextWepp for China’s exports to the US. And it also leads both the US and China to decrease in most product sectors. Korea, Japan, the EU, Vietnam, India, Mexico and Brazil are expected to increase their exports to the US in manufactured goods such as TextWapp, LightMnfc, HwavyMnfc, Chemical, Electronics sectors, except in primary sectors. However, Korea, Japan, the EU, Vietnam, India, Mexico and Brazil are expected to increase or decrease their exports to China according to their trade structure versus China. The welfare effects of the US and China as well as the whole world appear to be negative. However, welfare gains are expected to be relatively small positive in all other countries.

The free-floating exchange rate system was applied in South Korea after the 1997 Asian financial crisis. Since then, a lot of studies on exchange rate determination were conducted based on the monetary approach. However, after the 2008 global financial crisis, the economic policies of major countries had a greater impact on financial markets, but fewer studies were published on how the exogenous changes in economic policies affect the foreign exchange market of small open economies. Based on the related literature, we selected explanatory variables such as money supply, income, interest rate, terms of trade, and capital account, and then constructed a Won/Dollar exchange rate determination model by adding Economic Policy Uncertainty(EPU) indexes Baker, Bloom, and Davis(2016) devised as supplementary variables. The empirical analysis period is from October 2000 to December 2020, and regression analysis was performed using both a linear multiple regression model a non-linear VECM model. Monetary model-related variables, such as money supply and interest rate were proved to be more significant factors before the financial crisis. On the other hand, the influence of the EPU indexes was greater after the financial crisis and in particular, the Korea EPU index and Japan EPU index had a significant impact.

In recent years, as the largest developing country and G2, China’s OFDI scale has been expanding, and its flow pattern and characteristics have also become an important aspect of academic research. Based on this, this paper uses panel data of 7 ‘Belt and Road’ Southeast Asian countries from 2003 to 2017 and introduces structural indicators of host countries to analyze the impact of Industrial upgrade of host countries on the flow direction of China’s OFDI. As a Result, we find that China’s OFDI has the preference of “low value-added industry”, “low GDP per capita” and “high total factor productivity”. The acceleration of industrial upgrading in the host country will lead to the decrease of China’s direct investment onto the country in the medium and long term, and make China’s OFDI flow to countries with a worse industrial structure.

A large number of empirical studies have attempted to examine an association between exchange-rate risk and international trade flows after the collapse of the Bretton Woods system in the early 1970s due to its importance in exchange-rate arrangement and trade policies. Unfortunately numerous empirical investigations not only have failed to offer conclusive evidence, but have neglected the behavior pattern of international trade flows themselves. In this paper, after setting a few preliminary elements, we first review the characterization of asymmetry and leverage effects in terms of conditional variances and news impact curve for Incheon port’s export. This paper employs the news impact curve measuring how new information is incorporated into export volatility estimates for Incheon port. We show that the news impact curve for the EGARCH model increases exponentially in both directions but with different parameters and that the EGARCH model differs from the standard GARCH model in two main respects: The EGARCH model allows good news and bad news to have a different impact on volatility, while the standard GARCH model does not, and the EGARCH model allows big news to have a greater impact on volatility than the standard GARCH model. We also show that the GJR news impact curve captures the asymmetry in the effect of news on volatility because it has a steeper slope in its negative side than on its positive side.

In order to confirm whether the concerns or relief of the international community regarding the Chinese court’s approval and enforcement system for foreign arbitral awards is appropriate, I analyzed the related cases, how the Chinese courts actually apply the provisions of the New York Convention, according to the reasons for rejection of approval and enforcement prescribed in the New York Convention. As a result of case analysis, the Chinese court ruled in most cases by accurately applying the provisions of the New York Convention. Therefore, problems such as the Chinese court’s judgment in favor of domestic enterprises, the application of incorrect legal regulations, and the lack of fruitfulness of judges, which were concerned by the international community related to commercial arbitration, seem to have been resolved to some extent. However, with regard to the approval and enforcement of foreign arbitration awards, it still exposes two problems such as that China’s lower courts are more inclined to reject enforcement of foreign arbitral awards compared to the Supreme People’s Court and Chinese law stipulates the location of the arbitral institute as a standard for determining the nationality of the arbitral awards.

VAIC(Value Added Intellectual Coefficient) is the model devised by Pulic (2000a, b) to measure firm’s intellectual capital. This indicator does not directly measure the intellectual capital of the firm, but it measures the added value created by the intellectual capital, and consists of CEE(Capital Employed Efficiency), HCE(Human Capital Efficiency), and SCE(Structural Capital Efficiency). We examine the impact of intellectual capital on corporate value and financial performance through panel data for 177 manufacturing firms among KOSPI 200 from 2011 to 2018. Panel data show that CEE, HCE, and SCE which are comprising VAIC are 5%, 83%, and 12%, respectively. Findings are as follows: First, VAIC has a positive impact on corporate value and financial performance statistically. Second, CEE and HCE have the positive impact like VAIC, however, SCE is not significant statistically. Third, RD intensity and AD intensity which is proxied by the intangible resource of the firm have different effects on corporate value and financial performance. Both variables have a positive impact on corporate value, but RD intensity has a negative relationship with financial performance, whereas AD intensity has no statistical significance. The academic contribution of our study provides practical evidence of the effect of intellectual capital on corporate value and financial performance using VAIC in the Korean context and the practical implication is that the managers who wish to create value and to achieve sustainable competitive advantage should invest human resources continuously.