• The Korean Journal of Applied Statistics
• /
• v.22 no.1
• /
• pp.17-28
• /
• 2009

This study attempts to perform the statistical test for the causality between the Korean and the U.S. business conditions in association with the lead-lag relationship between the domestic stock price and the business condition. Their causal relationships are clearly identified after the outbreak of the IMF financial crisis. The vector autoregression for the corresponding period appears to reflect the strong interrelationships between the market variables and the dependency of the domestic business conditions on the U.S. market. The estimation results validate the leading effect of the stock price and the U.S. business behavior.

• Information Systems Review
• /
• v.19 no.1
• /
• pp.123-145
• /
• 2017

This study empirically examines the effects of regulation on online gaming. Going beyond ad hoc heuristic approaches on individual behavior, we investigate the effects of regulation on dynamic changes of games or service providers. In particular, we propose three theoretical perspectives: social influence to investigate the regulation effect, the role of prior experience to determine the difference in the regulation effect size through users' prior experience, and network externalities to discover the difference in the regulation effect size according to the number of users on an online gaming platform. We use the vector autoregression methodology to model patterns of the co-movement of online games and to forecast game usage. We find that online gamers are heterogeneous. Therefore, policy makers should make suitable regulations for each heterogeneous group to effectively avoid generating gaming addicts without interrupting the economic growth of the online gaming industry.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.33-42
• /
• 2021

This study aims to investigate the relationship between foreign direct investment (FDI) and economic growth at the provincial level by using time-series data in Binh Dinh from 1997 to 2019. We applied the quantitative approaches Vector Autoregression (VAR) and Autoregressive Distributed Lags (ARDL) in the model, which includes economic growth, real foreign direct investment capital, ratio of trained workers, and infrastructure. The results show that all these variables are stationary at the first difference. In ARDL analysis, we found that the economic growth positively affects FDI attraction. However, there is no evidence of the effect of FDI on economic growth in the condition of low capital implemented. Moreover, findings also show that the impact of FDI on economic growth is influenced by two factors: infrastructure and human capital. The lack of human capital, which is trained personnel and infrastructure, is the main barrier hindering and inhibiting FDI's contribution to local economic growth. In order to improve the efficiency of FDI on economic growth in the future, it is suggested that the Binh Dinh government should have proper policies in terms of the infrastructure, the human capital investment. They would allow Binh Dinh to enhance the capital absorptive capacity and capital efficiency.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.3
• /
• pp.1-12
• /
• 2022

In the event of a maritime distress accident, rapid search and rescue operations using rescue assets are very important to ensure the safety and life of drowning person's at sea. In this paper, we analyzed the surface layer current in the northwest sea area of Ulleungdo by applying machine learning such as multiple linear regression, decision tree, support vector machine, vector autoregression, and LSTM to the meteorological information collected from the maritime observation buoy. And we predicted the drowning person's route at sea based on the predicted current direction and speed information by constructing each prediction model. Comparing the various machine learning models applied in this paper through the performance evaluation measures of MAE and RMSE, the LSTM model is the best. In addition, LSTM model showed superior performance compared to the other models in the view of the difference distance between the actual and predicted movement point of drowning person.

• Journal of Korea Trade
• /
• v.25 no.1
• /
• pp.34-46
• /
• 2021

Purpose - This paper aims to analyze the impact of the terms of trade, export price, and import price on the Korean economy (that is, real GDP, CPI, money market rate, and real effective exchange rate), and vice versa in the simple vector autoregression. Design/methodology - We impose two assumptions, i.e., diagonality and bloc exogeneity, to correctly identify the impact of a factor to the others in the structural equation. With two contemporaneous assumptions in the structural VAR, this paper investigates the impacts of the terms of trade on the Korean economy and vice versa. Findings - Impulse responses to the shocks in the terms of trade and Korean economy show that 1) an impact of the terms of trade on the economy is different in export prices and in import prices. A higher export price is beneficial to the economy while a higher import price hurts the economy, and 2) an increase in real effective exchange rate and in interest rate constrains domestic production and lowers consumer prices. Originality/value - Unlike the conventional perception that a depreciation of a currency would promote exports and domestic production at the price of inflation, our result shows the opposite, and 3) real GDP and consumer prices are positively correlated. That is, an increase in real GDP does not only cause inflation, but an increase in consumer prices also promote domestic production. Yet, the only difference is that export prices and import prices end up higher with an increase in real GDP, but lower with inflation.

• Journal of Service Research and Studies
• /
• v.7 no.4
• /
• pp.139-150
• /
• 2017

Open economy tightly works with foreign economy. This paper investigates the effect of the shock of foreign bond yield on the credit spreads of domestic corporate bonds in Korea. Foreign bond is referred to as US treasury bond. Credit spreads are defined with the difference between log yields of domestic corporate bonds and log yield of Korea treasury bond. With the data of monthly three-year AA- and BBB- corporate bond yields- ratings, monthly three-year Korean treasury bond yields, monthly US dollar foreign exchange rates, and monthly three-year US Treasury bond yields during the period from October 2000 to September 2014 including global financial crisis period, the paper documents the results as follow. First of all, the yield of Korean treasury and the credit spreads are very sensitive to the increase in the level and the volatility of the yield of the US treasury bond. Changes in the level and the volatility little affect the change of the exchange rate. Second, the change in the level and the volatility negatively affect the level of Korean treasury bond yields but lead to the increase in the level of Korean treasury bond yields at the same time. Third, there exist time lags of the increases of credit spreads by the increase in the level and the volatility. These imply that credit spreads and bond yields are very sensitive to the change in the yields of foreign bonds such as US treasury bond.

• Management & Information Systems Review
• /
• v.31 no.4
• /
• pp.287-307
• /
• 2012

We empirically examine the price discovery dynamics among the VKOSPI, the KOSPI200 spot, and the KOSPI200 futures markets. The analysis employs the vector-autoregression, Granger causality, impulse response function, and variance decomposition using both daily data from 2009. 04. 13 to 2011. 12. 30 and 1 minute data from the bull market, bear market, and the flat period. The main results are as follows; First, the lead lag relationships between KOSPI200 spot(futures) yield VKOSPI returns could not be found from the daily data analysis. But KOSPI200 spot(futures) have a predictive power for VKOSPI from 1 minute data. Especially KOSPI200 spot(futures) and VKOSPI show the bi-directional effects to each other during the return rising period Second, We chose the VAR(1) the model in daily data but adopt the VAR(3) model in the one minute data to determine the lead lag time. We know that there is predictability during the very short period Third, Spot returns and futures returns makes no difference in daily data results. According to the one minite data results, VKOSPI returns have a predictive power for KOSPI200 spot return, but have no predictive power for KOSPI200 futures return.