• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.101-110
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• 2020

Energy and energy consumption play an important role in strategies for socio-economic development of the country. In 1995, Vietnam officially entered the 500 kV North-South transmission power line exploits, with a full length of 1,487 km. The purpose of this study is to investigate the breakpoint and the transition effect of energy consumption to economic growth in Vietnam during the period of 1980-1994, and 1995-2016. The Autoregressive Distributed Lag (ARDL) approach and the Bounds test are used to test for the presence of cointegration, whereas the Toda and Yamamoto procedure Granger causality test is used for the direction of causality. The result of the Bounds test validates the existence of cointegration among the included variables. The empirical results provide evidence that energy consumption has a positive impact on the economic growth of Vietnam in the long run. The causality test shows that there is bi-directional causality between energy consumption and economic growth, supported feedback hypothesis. There is a breakpoint in 1995 and the contribution of energy consumption in economic growth in the period of 1995-2016 is lower than the stage 1980-1994. This study suggests Government authorities explore new sources of energy to achieve sustainable economic development in the long run.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.37-46
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• 2020

The paper examines the dynamic relationship of domestic credit and stock market liquidity on the economic growth of the Philippines from 1995 to 2018 applying the autoregressive distributed lag (ARDL) bounds testing approach to cointegration, together with Granger causality test based on vector error correction model (VECM). The ARDL model indicated a long-run relationship of domestic credit and stock market liquidity on GDP growth. When the GDP per capita is the dependent variable there is weak cointegration. Also, the Johansen cointegration test confirmed the existence of long-run relationship of domestic credit and stock market liquidity both on GDP growth and GDP per capita. The VECM concludes a long-run causality running from domestic credit and stock market liquidity to GDP growth. At levels, domestic credit has significant short-run causal relationship with GDP growth. As for stock market liquidity at first lag, has significant short-run causal relationship with GDP growth. With regards to VECM for GDP per capita, domestic credit and stock market liquidity indicates no significant dynamic adjustment to a new equilibrium if a disturbance occurs in the whole system. At levels, the results indicated the presence of short-run causality from stock market liquidity and GDP per capita. The CUSUMSQ plot complements the findings of the CUSUM plot that the estimated models for GDP growth and GDP per capita were stable.

• Agribusiness and Information Management
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• v.12 no.2
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• pp.40-54
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• 2021

Market integration and prices in pulse crops like black gram play an important role in determining the production decisions of the farmers and diversification towards high value nutritious crops. In this context, the present study explores extent of market integration and price transmission in selected major black gram markets in Andhra Pradesh using Johansen co-integration, Vector Error Correction Model and Granger causality test. The study used monthly prices data of black gram (Rs/quintal) sourced from selected markets of Srikakulam, Krishna and Kurnool spanning January, 1990 to December, 2019. The results of the study strongly buttressed the existence of co-integration and interdependence of selected black gram markets in Andhra Pradesh. However, the speed of adjustment of the prices found to be moderate in Krishna market and quite weaker in Srikakulam market and thereby prices correct a small percentage of the disequilibrium in these markets with the greatest percentage by the external and internal forces. So, it necessitates the need for future research, to investigate the influence of external and internal factors such as market infrastructure, Government policy and self-sufficient production, product characteristics and utilization towards market integration. As there exists only unidirectional causality from Krishna to Kurnool and from Krishna to Srikakulam markets, it calls for strengthening the information technology for flow of market information regularly to help the farmers for increasing their income.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.265-268
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• 2009

The purpose of this study is to analyze the casual relationship among Housing Transaction Index, Jeonse Rental Index and Interest Rate. To analyze the influence of interest rate in more detail, CD Interest rate and Spread are used as variables. Granger Casualty Test is used as a analysis tool, As a result, Spread is the cause variable of the Housing Transaction Index and the Housing Transaction Index is the cause variable of the CD Interest Rate. And also, CD Interest rate influences the Jeonse Rental Index and the Jeonse Rental Index has influence on the other variables.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.87-104
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• 2022

Considering the complex structure and high volatility in the shipping market, it is important to investigate the connectedness amongst influencing factors. This study explores the dynamic relationship between supply-demand factors and shipping freight indices. We choose Capesize and Panamax in the bulk carrier market and use quarterly data of GDP, world fleet, BCI, and BPI from 1999 to 2021. Applying the wavelet analysis and wavelet Granger causality test, the simultaneous examination of co-movement and causality between two factors and the shipping market in both the time and frequency domains is achieved. We find that co-movement and causality vary across time and frequencies, thereby existing dynamic relationships between variables. Second, compared to multiple coherencies using demand and supply factors together, partial coherencies indicate noticeable causalities. It implies that analyzing demand and supply factors separately is essential. Finally, shipping freight indices show a high correlation with the demand factor in a good market and with the supply factor in a bad market. Generally, GDP positively leads shipping freights in the recovery phase while the world fleet negatively leads shipping freights in the downturn. The research is meaningful in that the rarely-applied wavelet analysis is adopted in the shipping market and that it gives a reasonable ground to explain the role of supply and/or demand factors in different phases of the market cycle.

• Journal of Navigation and Port Research
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• v.41 no.1
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• pp.25-32
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• 2017

The purpose of this investigation is to analyze the synchronization between the representative global freight index, the Baltic Dry bulk Index (BDI) and the China Container Freight Index (CCFI) with monthly data from 2000 to 2016. Using the non-stationarity of the business cycle that is able to include common trends, we employ the Engle-Granger 2 stage co-integration test and found no synchronization. On the contrary, we additionally estimated the causality between the markets and revealed the causality, which implies that the Chinese economy has a significant effect on the global market. The results of this empirical analysis demonstrate that the CCFI of China is appropriate for analyzing the shipping industry. In practice, this means that it is more appropriate to include CCFI in the global market outlook than use it as a substitute for the global freight rate index, the BDI. This is a case study of the synchronization of the economic fluctuations of the shipping industry. It suggests that the economic fluctuations of China need to be considered in the unstable global market forecast. In particular, this case applies to the fluctuations in the shipping industry synchronism and provides important results in scientific terms.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.198-210
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• 2016

This study firstly aims to estimate a leading-price of Jeju flounders with various price-classes by fish weight and secondly plans to provide policy implications of flounder purchase projects by understanding dynamic changes and interactions among flounder producer price-classes caused by price impulses in the market. This study applies an unit root test for stability of data, uses a Granger causality test to estimate the leading-price among producer prices by fish weight, employs the vector autoregressive model to analyze statistical impacts among t-1 variables used in models, and finally utilizes impulse response analyses and forecast error variance decomposition analyses to understand dynamic changes and interactions among change rates of the producer prices caused by price impulses in the market. The results of the study are as follows. Firstly, KPSS, PP, and ADF tests show that the change rate of Jeju flounder monthly producer prices by fish weight differentiated by logarithm is stable. Secondly, the Granger causality test presents that the change rate of the 1kg flounder producer price strongly leads it of 500g, 700g, and 2kg flounder producer prices respectively. Thirdly, the vector autoregressive model indicates that the change rate of the 1kg producer price in t-1 period statistically, significantly influences it of own weight in t period and also slightly affects price change rates of other weights in t period. Fourthly, the impulse response analysis indicates that impulse responses of structural shocks for the change rate of the 1kg producer price are relatively more powerful in its own weight and in other weights than shocks emanating from price change rates of other weights. Fifthly, the variance decomposition analysis points out that the change rate of the 1kg producer price is relatively more influential than it of 500g, 700g, and 2kg producer prices respectively. In conclusion, the change rate of the 1kg Jeju flounder producer price leads the change rates of other ones and Jeju purchase projects need to be targeted to the 1kg Jeju flounder producer price as the purchase project implemented in 2014.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.475-487
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• 2013

The aim of this study is to examine an existence of mutual interdependency in terms of military expenditure and arms imports between Northeast Asian countries such as South Korea, North Korea, China, Japan, and U.S. Recently, the mood of post cold war and intensified globalization lead to be disarmament in pursuing a policy on national defence in many countries. Since potential menace to national security has been receiving more concern rather than a direct armed clash, mutual interdependency on military spending should be fully understood. For a methodological tools, ${\beta}$ and ${\sigma}$-convergences, convergence with rational expectation, and Granger causality test are employed. Empirical evidence shows that the convergences which are evaluated by ${\beta}$, ${\sigma}$, and by a model based on rational expectation are in general revealed, and differences are more sensitive to a military decision making procedures. Granger causality, however, is not being existed. To this end, it would be concluded that the Northeast Asian countries are going with a trend in the world than forming their own tendency in this region.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.349-357
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• 2017

The environmental problems affecting marine resources and slow growth in the fisheries industry is causing many countries to look for alternative inputs that can boost the fisheries sector. This study focuses on the effects of technological innovation in the fisheries industry on the gross domestic product (GDP) per capita across Organization for Economic Cooperation and Development (OECD) countries. Using a panel dataset, this study attempts to estimate the different effects of technological innovations in the fisheries industry from country to country using the differences-in-differences (DiD) method. After the DiD method, the Granger causality test is applied to determine the interactive relations between economic growth and the selected variables associated with technological innovation in the fisheries industry, such as government spending on fisheries R&D, the number of patents in fisheries, and employment. The results obtained from the DiD estimation show that government spending on fisheries R&D, fisheries technology development, and fisheries employment positively influences the GDP per capita across OECD counties. From the causality test, we found different bi-directional causal relationships between the GDP per capita and (spending) on fisheries technology development across countries.

• International Area Studies Review
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• v.14 no.1
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• pp.99-119
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• 2010

This study explores the natural gas market and the oil market in the U.S. and the European oil market. It focuses on two kinds of analyses; one is to confirm whether there is the predictive power between spot and futures within homogeneous commodity market(or inter-heterogeneous commodity market) through Granger-causality test in terms of the return rate and the volatility. The other is to examine the spot price stabilizing effect of futures price through regression analysis. When it comes to the predictive power of inter-commodity market, there was a conflicting aspect between the return rate of spot and futures. Overall, however, its statistical significance was low. With respect to the volatility, we found that the natural gas market has little influence on the oil market unlike the predictive power of oil market on natural gas market. Concerning the return rate of the predictive power within homogeneous commodity market, we found that the return rate of spot has the predictive power on futures only in the European market. In addition, we identified that there is feedback between spot and futures in the all commodity markets regarding volatility. As a result of the spot price stabilizing effect analysis of futures price, futures volatility increased the spot volatility.