• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.125-162
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• 2003

This paper investigates the short- and long- run relationship among Korean, U.S. and Japanese construction indices. We conducted the Johansen's cointegration tests on the hypotheses that the construction indices of three countries we related in the long-run as well as in the short-run. The test results show that there exists no long-run relationship among three countrie's construction indices. In addition, the cointegrating relation did not exist for three countrie's stock market indices and five major Korean construction firms. It fumed out that the U.S. indices Granger-causes Japanese and Korean indices. This finding implies that there may exist international diversification benefit through forming a portfolio from these indices.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.1
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• pp.81-89
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• 2013

The purpose of this study is to analyze the information effect about the pricing using the ETF price, the benchmark index, and the total tracking error between the ETF price and the benchmark index on the index ETF market and sector ETF markets. Furthermore, the total tracking error is distinguished between the market tracking error and the NAV tracking error. Summary of this study are as follows: First, While KODEX200 don't have impact factors on the price, the most sectors of ETF have the factors affecting the pricing decision. They are the day before the total tracking error or market tracking error. Second, for the ETF price of the most industry, we find that the day before the market tracking error have the price discovery function because it is a negative(-) coefficients. But NAV tracking error could not find such a feature. Finally, the sector ETF price of energy chemical, construction, IT, and semiconductor industries affected of the day before positive(+) impact by the benchmark index price.

• Journal of the Korean Regional Science Association
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• v.36 no.3
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• pp.29-40
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• 2020

The aims of this study to identify the relationship between regional economic growth and intraregional regional disparities. The 16 metropolitan area, the Capital region and the southeastern region of Korea were put in the spatial scope and the time range from 2005 to 2016. Regional gross domestic product data were used to show regional growth and intraregional disparity. Panel data for each spatial unit were established, panel unit root test and panel cointegration test were conducted to check the stability of the data. The DOLS method was used to identify relationship between regional economic growth and intraregional disparity, and the VECM model and Granger causality test was conducted to verify causality. The result of analysis of 16 metropolitan area units showed that the intraregional disparity increases as regional economic growth progresses. When the regional gross domestic product increased by 1%, the intraregional disparity increased by 1.258%, and there are short-term and long-term causality. Both the Capital region and the southeastern region had a mutual relationship between regional economic growth and intraregional disparity, but the disparity in the Capital region showed an increase and the southeastern region showed a decrease. The results of this study show that the regional disparity is increasing nationwide, but the Capital region and the southeastern region showed different stages of growth.

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.109-118
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• 2019

As a result of the United States (U.S) -China trade conflict, the recent instability of the stock market has led many people to invest in Bitcoin, a commodity that many previous studies have interpreted as a safe asset. However, recent Bitcoin market price fluctuations suggest that the asset's stability stems from speculative purchasing trends. Therefore, classifying the characteristics of Bitcoin assets can be an important reference point in analyzing relevant accounting information. To determine whether Bitcoin is a safe asset, this study analyzed the correlation between Bitcoin and economic indicators to verify whether gold and Bitcoin responded similarly in time series analyses. These show that the regression explanatory power between the price of gold and bitcoin is low, thus no relation between the two assets could be drawn. Additionally, the Granger causality analyses of six individual economic variables and Bitcoin did not establish any notable causality. This can be interpreted that short-term price fluctuations have a significant impact on the nature of Bitcoin as an asset.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.55-62
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• 2019

This study analyzed the relationship between housing price, purchase price, Gini coefficient, interest rate, and the employment, considering that the change in housing price was an important factor influencing macroeconomic variables and income inequality. The panel VAR model was constructed considering the panel data, and the Granger causality, Impulse response and Variance dispersion analysis were performed. As a result, when compared to before and after the global financial crisis, it was shown that the rent price had an effect on income inequality, but in the following period, both the rent price and the selling price affected the income inequality. And that it has a large impact on inequality. In addition, the causality between income inequality and employment rate, interest rate, and tax rate was confirmed. Therefore, it is expected that it will be a desirable policy to mitigate income inequality considering the influence of policy variables for economic activation including government real estate policy.

• Korea Trade Review
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• v.48 no.1
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• pp.127-163
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• 2023

The objective of this study is to investigate the volatility spillover effects among BDI, CCFI and SCFI. This paper will divide the empirical analysis section into two periods to analyze and compare the differences in volatility spillover effect between shipping freight indices before and after the outbreak of COVID-19 separately. First, in order to compare the mean spillover impact and index lead-lag correlations in BDI and CCFI indices, along with BDI and SCFI indices before and after COVID-19, the co-integration analysis and the test of Granger causality built on the VAR model were utilized. Second, the impulse response and variance decomposition are employed in this work to investigate how the shipping freight index responds to shocks experienced by itself and other freight indices in a short period. Before the COVID-19 epidemic, the results demonstrated that the BDI freight index is the Granger cause of the variable CCFI freight index. But the BDI and CCFI freight indices have no apparent lead-lag relationships after COVID-19, and this empirical result echoes the cointegration test result. After the COVID-19 epidemic, the SCFI index leads the BDI index. This study employs the VAR-BEKK-GARCH joint model to explore the volatility spillover results between dry bulk and container transport markets before and after COVID-19. The empirical results demonstrate that after COVID-19, fluctuations in the BDI index still affect the CCFI index in the maritime market. However, there is no proof of a volatility spillover relationship between the BDI and SCFI after the COVID-19 epidemic. This study will provide an insight into the volatility relationship among BDI, CCFI and SCFI before and after the the COVID-19 epidemic occurred.

• Journal of Technology Innovation
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• v.11 no.1
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• pp.79-97
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• 2003

R&D expenditure of Korean firms has been increasing drastically since 1980 and occupied 84% of total R&D expenditure in 1994. After 1994, however, the growth rate of industry R&D expenditure has dropped below single digit. R&D concentration rate of upper 20 companies declined from 61.9% in 1999 to 49.8% in 2001. The technology trade balance has diverged by 2.8 billion dollars in 2000 compared to around 0.3 billion dollars in 1985. We find several reasons on declining the industry R&D growth rate in Korea. First, we carefully say there might be an crowding out effect in increasing government R&D investment from Granger causality test between industry R&D and government R&D. Second, the decreasing benefit of tax credit since 1992 on industry R&D expenditure has caused the decrease of industry R&D growth rate. Third, the type of R&D cost becomes to similar to matured countries type of cost, which means the portion of capital expenditure has been decreased since late of 1980s. Therefore, industry R&D growth rate gets to saturation point. We draw several policy implications from the changing structure of business R&D of Korean company. Firstly, to stimulate industry R&D investment Korean government needs to strengthen tax credit policy. Secondly, to induce foreign direct investment Korean government needs to establish technology infrastructures and high quality of manpower. To utilize foreign technology resources Korean government need to introduce global R&D program executed by foreign scientist as an Project Leader.

• The Journal of Fisheries Business Administration
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• v.46 no.2
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• pp.31-41
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• 2015

This study aimed to analyze the relationship between sea surface temperature as a climatic element and catch amount of offshore and coastal fisheries in Korea using annual time series data from 1970 to 2013. It also tried to predict the future changes in catch amount of fisheries by climate change. Time series data on variables were estimated to be non-stationary from unit root tests, but one long-term equilibrium relation between variables was found from a cointegration test. The result of Granger causality test indicated that the sea surface temperature would cause directly changes in catch amount of offshore and coastal fisheries. The result of regression analysis on sea surface temperature and catch amount showed that the sea surface temperature would have negative impacts on the catch amount of offshore and coastal fisheries. Therefore, if the sea surface temperature would increase, all other things including the current level of fishing effort being equal, the catch amount of offshore and coastal fisheries was predicted to decrease.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.151-162
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• 2019

The paper examines the effects of Foreign Direct Investment (FDI) on the economic growth of Lao People's Democratic Republic (Lao PDR) between 1993 and 2015. The investigation is based on the influence of growth and economic absorptive capability determinants such as human capital, trade openness, and institutional quality. The methodological analysis uses a multivariate framework accounting capital stock, labor stock, FDI, human capital, trade openness, and institutional quality in regression of the Vector Autoregressive model. Augmented Dickey-Fuller unit root test, Johansen Cointegration test, and Granger Causality test were applied as parts of the econometric time-series analysis approach. The empirical results demonstrate the positive effects of FDI and trade openness, and the negative effects of human capital and institutional quality on the economic growth of the Lao PDR over the 1993 to 2015 period. The findings confirm that trade openness complemented by a sufficient level of infrastructure, education, quality institutions, and transparency significantly influence economic growth and attract more FDI. Research results lend credence to the need for the Lao PDR's government to focus on improving its economic absorptive capability and economic competitiveness regionally and globally by improving wealth and resource management strategies, as failure to take this course of action could lead to the Dutch Disease effects.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1573-1583
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• 2016

It is necessary to check mutual correlations between related variables because housing prices are influenced by a lot of variables of the economy both internally and externally. In this paper, employing the Granger causality test, we have validated interrelated relationship between the variables. In addition, there is cointegration associations in the results of the cointegration test between the variables. Therefore, an analysis using a vector error correction model including an error correction term has been attempted. As a result of the empirical comparative analysis of the forecasting performance with ARIMA and VAR models, it is confirmed that the forecasting performance by vector error correction model is superior to those of the former two models.