• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.613-624
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• 2021

This paper analyzes the relationship between income distribution and energy consumption from a Pareto optimal approach. For this purpose, the causality relationship between electricity consumption per capita (kWh) with respect to country groups and energy consumption per capita (kg of oil equivalent) along with gross domestic product per capita was analyzed. In addition to this purpose, a Pareto analysis was conducted to determine the countries with the highest per capita national income, how much of the world total energy they consume, and whether the law of power in the energy and electricity markets exists. Finally, the impact of official development assistance provided to low-income countries by high-income countries on the low-income countries' electricity and energy consumption was analyzed. In other words, it was questioned whether pareto redistribution policies serve the purpose or not. The Engle-Granger causality approach was used in the analysis of the causality relationship between variables. Our analysis indicated that, first, the energy data of the country groups may be inadequate in revealing income inequalities. Second, the existence of Pareto law of power and global income inequality can be explained based on energy data. Finally, Pareto optimal redistribution policies to eliminate income inequality remain inadequate in practice.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.23-36
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• 2021

The study explores the nexus between foreign direct investment (FDI), financial innovation, and exchange rate volatility in selected South Asian countries for 1980 to 2017. The study applies the unit root test, Autoregressive Distributed Lagged, nonlinear ARDL, and causality test following Toda-Yamamoto. Unit root tests ascertain that variables are integrated in a mixed order; few variables are stationary at a level and few after the first difference. Empirical model estimation with ARDL, Long-run cointegration revealed with the tests of FPSS, WPSS, and tBDM by rejecting the null hypothesis of "no cointegration." This finding suggests that, in the long-run financial innovation, FDI inflows, and exchange rate volatility move together. Moreover, study findings established adverse effects running from FDI inflows and financial innovation to exchange rate volatility in the long run. These findings suggest that continual FDI inflows and innovativeness in the financial system assist in lessening the volatility in the foreign exchange market. Furthermore, nonlinear ARDL confirms the presence of asymmetric cointegration in the model. The standard Wald test established asymmetric effects running from FDI inflows and financial innovation to exchange rate volatility, both in the long and short run. Directional causality unveils feedback hypothesis holds for explaining causality between FDI, financial innovation, and exchange rate volatility.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.173-183
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• 2022

The objective of this research is to examine the influence of the COVID-19 pandemic on stock markets in a few developing and developed countries. This study uses daily data from January 2020 to May 2021 and obtained from World Health Organization and Thomson Reuters. The secondary data was evaluated through panel econometric methodology that includes different unit root tests, and to analyze the long-run relationship between variables, panel cointegration techniques were applied. The long-run causality among variables was examined through Panel Vector Error Correction Model. The overall findings of this study suggest a long-run association exists between several cases and death with the stock returns of the GCC and other stock markets. Furthermore, the VECM model also identified a long-run causality running from COVID cases and death towards the stock rerun of both sets of stock markets. However, a subsequent Wald test yielded mixed results, indicating no short-run causality between cases and deaths and stock returns in both groups; however, in the case of GCC, several COVID-19 cases are having a causal impact on stock markets, which is notable in light of the fact that the death rate in GCC is significantly lower than in many developed and developing countries.

• Journal of Korea Trade
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• v.25 no.1
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• pp.18-33
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• 2021

Purpose - This paper investigates the causal relationship between logistics infrastructure development and the economic growth of Korea. Considering the industrial and economic structure of Korea, it is likely that logistics infrastructure is positively associated with the economic growth of the country. Design/methodology - The causal relationship between logistics infrastructure and economic development is estimated using Vector Autoregressive (VAR) and Vector Error Correction Model (VECM) considering long-run equilibrium between the two factors. To this end, a dataset consisting of 7 logistics infrastructure proxies and 5 economic growth indicators covering the period of 1990-2017 is used. Findings - It was found that causality, in general, runs from logistics infrastructure development to economic growth. Specifically, the results indicate that maritime transport is positively associated with the economic growth of Korea in terms of GDP and international trade. In addition, other modes of transport also have a positive impact on either the GDP or international trade of Korea. Originality/value - While existing studies in this area are based on either regional observations or a specific mode of transport, this study presents empirical evidence on causality between logistics infrastructure and the economic growth of Korea using a more comprehensive dataset. In addition, the findings in this paper can provide valuable implications for transport infrastructure development policies.

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.47-59
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• 2017

The objective of this study is to determine the short run and long run dynamics between maritime import volume (IMV), industrial production (IP), and real effective exchange rate (REER) of the Korean Won over the REER of certain major currencies (US Dollar, Chinese Yuan, and Japanese Yen) in Korea's Jeonnam province. The Johansen and Juselius cointegration results reveal that at least one cointegration vector or long-run relationship exists. Hence, this study estimated the long run equilibrium equation, which indicates that both IP and REER are inelastic, although the former is bigger than the latter. Moreover, the dynamic causality analysis reveals short and long-run unidirectional causality from IP and REER to IMV in all three models. Further, in all the models, the results indicate short run unidirectional causality from REER to IP. In addition, the impulse response (IR) results show that the impulse of IP and REER decayed after four months. Additionally, the IR analysis results indicate that the REER of the Korean Won over the REER of Japanese Yen is the biggest with respect to the impact of relative REER on IP, which is the proxy variable of regional real income. Thus, empirical results indicated that real income and REER play an important role in determining the Jeonnam's maritime import demand behavior in the short run and long run. More importantly, substantial actions reducing unexpected fluctuation of the REER and real income based on micro and macro economic policies will increase the imported volume in the ports of the Jeonnam province.

• Journal of Korea Water Resources Association
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• v.37 no.10
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• pp.869-880
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• 2004

The purpose of this study is to examine relationship between water consumption and economic growth in Korea, and to obtain policy implications of the results. To this end, we attempt to provide more careful consideration of the causality issues by applying rigorous techniques of Granger causality. Tests for unit roots, co-integration, and Granger causality based on an error-correction model are presented. The existence of bi-directional causality between water consumption and economic growth in Korea is detected. This finding has various implications for policy analysts and forecasters in Korea. Economic growth requires enormous water consumption, though there are many other factors contributing to economic growth, and water consumption is but one part of it. Thus, this study generates confidence in decisions to invest in the water supply infrastructure. Moreover, this study lends support to the argument that an increase in real income, ceteris paribus, gives rise to water consumption. Economic growth results in a higher proportion of national income spent on water supply services and stimulates further water consumption.

• 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.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.233-260
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• 2022

In this paper, we analyzed how oil price fluctuations affect stock price by industry using the non-parametric quantile causality test method. We used weekly data of WTI spot price, KOSPI index, and 22 industrial stock indices from January 1998 to April 2021. The empirical results show that the effect of changes in oil prices on the KOSPI index was not significant, which can be attributed to mixed responses of diverse stock prices in several industries included in the KOSPI index. Looking at the stock price response to oil price by industry, the 9 of 18 industries, including Cloth, Paper, and Medicine show a causality with oil prices, while 9 industries, including Food, Chemical, and Non-metal do not show a causal relationship. Four industries including Medicine and Communication (0.45~0.85), Cloth (0.15~0.45), and Construction (0.5~0.6) show causality with oil prices more than three quantiles consecutively. However, the quantiles in which causality appeared were different for each industry. From the result, we find that the effects of oil price on the stock prices differ significantly by industry, and even in one industry, and the response to oil price changes is different depending on the market situation. This suggests that the government's macroeconomic policies, such as industrial and employment policies, should be performed in consideration of the differences in the effects of oil price fluctuations by industry and market conditions. It also shows that investors have to rebalance their portfolio by industry when oil prices fluctuate.

• Journal of Service Research and Studies
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• v.6 no.1
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• pp.83-95
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• 2016

We examine the information transmission between the Service Industrial Production Index and the Service Industrial Wholesale and Retail Index, based on the returns data offered by the Korea Bank. The data includes daily return data from January 2000 to September 2015. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the Service Industrial Production Index precede and have explanatory power the Service Industrial Wholesale and Retail Index However the results also identified a greater causality and explanatory power of the Service Industrial Wholesale and Retail Index over the Service Industrial Production Index. Secondly, the results of impulse response function suggest that the Service Industrial Production Index show immediate response to the Service Industrial Wholesale and Retail Index and are influenced by till time 5 From time 2, the impact gradually disappears. Also the Service Industrial Wholesale and Retail Index show immediate response to the Service Industrial Production Index and are influenced by till time 2.5, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of Service Industrial Production Index are dependent on those of the Service Industrial Wholesale and Retail Index. This implies that returns on the Service Industrial Production Index have a significant influence over returns on the Service Industrial Wholesale and Retail Index. It contributes to the understanding of market price formation function through analysis of detached the Service Industrial Production Index and Service Industrial Wholesale and Retail Index. Finally, our results can be used as a guide by the Korea Bank and Republic of Korea and as well as Statistics Korea.

• Proceedings of the Technology Innovation Conference
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• 1999.12a
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• pp.181-196
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• 1999