• 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.543-549
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• 2021

The stock market plays a crucial role in the growth of industry and trade, which eventually affects the economy. This paper studies the determinants of stock market development in Jordan using yearly time-series data (1978-2019). The autoregressive distributed lag approach is applied to examine co-integration, while the vector error correction model is employed to estimate (long-run and short-run) causal relationships. The results show that macroeconomic determinants such as gross domestic product, gross domestic savings, investment rate, credit to the private sector, broadest money supply, stock market liquidity, and inflation rate are important determinants of stock market development. These findings provide vital implications for policymakers in developed and emerging stock markets. First, economic development plays an imperative role in stock market development. Second, developing the banking sector is mandatory because it can significantly promote stock market development. Third, domestic investment is a significant determinant of stock market development, especially in emerging countries. However, it is vital to launch policies that lead to encourage investment and promote stock market development, and this could be done through (1) encouraging competition, (2) improving the institutional framework, and (3) removing trade blocks by establishing a mutual connection between foreign private investment entities and government authorities.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.561-572
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• 2021

This study aims to analyze the causality between GDP per capita, urbanization, and education. This also aims to determine the long-term and short-term relationships between economic urbanization, education, and GDP per capita by applying Vector Error Correction Model (VECM). Data was obtained from the World Bank and UNDP from 1990 to 2018. The estimation results showed that economic growth and education on urbanization have the strongest causality in VECM. Therefore, they are pull factors with a significant effect in the long and the short term. Some suggestions concerning policy implications were stated, and they include: forming area-based urbanization, where cities within one area are integrated, to get the impact of an agglomeration economy. Also, the government needs to accelerate the distribution of infrastructure and public facilities in various regions to avoid population density in one area due to urbanization, and government needs to pay attention to easier access to education and more equitable ones in various regions. On the contrary, after education is evenly distributed in all regions, the government needs to pay attention to transportation access and infrastructure.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.15-27
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• 2022

Recently, as carbon dioxide (CO₂) emissions have increased overall and contributed to air pollution, and awareness of environmental degradation has grown. This study examines the impacts and causalities of economic globalization, economic growth, energy consumption, and capital formation on CO₂ emissions in China over the period 1971-2014. The vector error correction model (VECM) and Granger causality test on time-series data are employed to observe the interactions between CO₂ emission, economic globalization, and various economic factors, including economic growth, energy consumption, and capital formation, since China's early stage of globalization. The empirical results indicate the existence of bidirectional causalities from economic growth, gross capital formation, economic globalization, and CO₂ emission to energy consumption, and bidirectional casualty from energy consumption to CO₂ emission relationships in the short run. The findings of this study suggest that indirect bidirectional causalities from economic growth, economic globalization, and capital formation to CO₂ emission through energy consumption are observed. Moreover, economic globalization accelerates CO₂ emission in the short run but decreases it in the long run. To reduce CO₂ emissions, and to ensure sustainable economic growth and economic globalization progress, some crucial energy-saving and energy-efficiency policies, regulatory rules, and laws are recommended.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.79-90
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• 2021

This study aims to investigate the relationship between urbanization, economic growth, energy consumption, and CO2 emissions in Indonesia. The data used in the study are time-series data for the period 1985-2017; the data utilized are sourced from World Development Indicators obtained on the World Bank database. The method uses a quantitative approach that applies the vector error correction model based on the Granger causality test. The empirical results reveal that, in the short run, there is evidence that urbanization and energy consumption can causes CO2 emissions, and they also prove that urbanization can cause energy consumption. Also, other findings prove the existence of long-run relationships flowing from energy consumption, economic growth, and CO2 emissions toward urbanization, as well as the existence of the relationship flowing from urbanization, economic growth, and CO2 emissions towards energy consumption. The results of testing the relationship between economic growth and CO2 emissions reveal that the environmental Kuznets curve hypothesis is proven in Indonesia. Thus, policies are needed to limit the impact of urbanization through high awareness-raising to maintain environmental quality and greater use of energy. Also, energy conservation policies are needed in all sectors, especially the electricity, industry, and transportation sectors.

• Korea Trade Review
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• v.44 no.2
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• pp.173-188
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• 2019

The purpose of this study is to investigate the causal relationship between the logistics industry and the economic growth in Korea, and to provide implications for the contribution of the logistics industry to economic growth. Unlike Previous Related Studies, we derive short-term and long-term effects through dynamic panel analysis such as panel Granger causality test and impulse response function estimation using panel vector error correction model. The results of the empirical analysis are as follows: Labor input of the logistics industry has the greatest positive impact on economic growth. And capital input and total sales of the logistics industry have a negative effect on economic growth. This means that Korea's logistics industry features labor-intensive growth. In addition, We have also found that the growth (sales) and capital input of the logistics industry have not yet had a direct positive impact on economic growth. Therefore, the results of this analysis provide implications for the direction of logistics industry policy to enhance contribution of the logistics industry to economic growth.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.449-457
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• 2022

The Port of Busan is currently ranked as the seventh largest container port worldwide in terms of cargo throughput. However, port competition in the Far-East region is fierce. The growth rate of container throughput handled by the port of Busan has recently slowed down. In this study, we analyzed how economic conditions and multiple external shocks could influence cargo throughput and identified potential implications for port business. The aim of this study was to build a model to accurately forecast port throughput using the ARIMA model, which could incorporate external socio-economic shocks, and the VEC model considering causal variables having long-term effects on transshipment cargo. Findings of this study suggest that there are three main areas affecting container throughput in the port of Busan, namely the Russia-Ukraine war, the increased competition for transshipment cargo of Chinese ports, and the weaker growth rate of the Korean economy. Based on the forecast, in order for the Port of the Port of Busan to continue to grow as a logistics hub in Northeast-Asia, policy intervention is necessary to diversify the demand for transshipment cargo and maximize benefits of planned infrastructural investments.

• Journal of Korea Trade
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• v.24 no.4
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• pp.18-33
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• 2020

Purpose - This paper investigated the effect of international trade affects income inequality. It also compares the different effects between developing and developed countries over the period from 2005 to 2014 for 58 countries. Design/methodology - The econometric estimation was used to identify the relationship between export, import, FDI, GDP, unemployment and income inequality. In this empirical analysis, we utilized a Vector Error Correction (VEC) model using panel data. Findings - The findings show that there is a close correlated between trade and income inequality. The higher export ratio of GDP tends to have a 1.79 times more income inequality in developing countries than in developed countries. The higher import ratio of GDP tends to have a 2.44 times higher income inequality in developing countries than in developed countries. Further, Increasing FDI tend to have an approximately 1.43 times higher income inequality in developing countries than in developed countries. Korea is in the middle of developed and developing countries' result. Originality/value - To correct the global income inequality regarding trade, developed countries' proactive trade policies, such as granting preferential tariff benefits to developing countries, are likely to be needed and Income Safety Net in international trade must be taken into account.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1664-1673
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• 2022

Achieving sustainable development requires an increasing share of green technologies. World energy demand is expected to rise significantly especially in developing economies. The increasing energy demands will be entertained with conventional energy sources at the cost of higher emissions unless eco-friendly technologies are used. This study examines the asymmetric effects of nuclear energy on carbon emissions for Pakistan from 1974 to 2019. Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) unit root tests suggest that variables are integrated of order one and bound test of Autoregressive Distributed Lag (ARDL) and nonlinear ARDL confirm a long-run relationship among selected variables. The ARDL, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS) results show that the coefficient of nuclear energy has a negative and significant impact on emissions in both short and long run. Further, the NARDL finding shows that there exists an asymmetric long-run association between nuclear energy and CO₂ emissions. The vector error correction method (VECM) results indicate that there exists a bidirectional causal relationship between nuclear energy and carbon emissions in both the short and long run. Additionally, the impact of nuclear energy on ecological footprint has been examined and our findings remain robust.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.203-212
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• 2023

This research work aims to investigate the role of FDI in Economic Development by assessing its relationship with GDP per capita in Vietnam +5 from 1986-2020. Through descriptive statistical, correlation matrix analysis, and econometric models, including Vector Error Correction Model (VECM) and Feasible Generalized Least Squares (FGLS) estimation methods using Stata 15.1. The VECM estimation method results show that FDI positively impacts Economic Development in the short run while not finding a long-run relationship. In addition, it is found that a clear relationship between Exports and Economic Development in both the short run and the long run. Meanwhile, CO2 emissions and Employment Opportunities have no clear relationship with Economic Development in the short run. However, the relationship is reversed in the long run, as the empirical study in Vietnam. The results of the FGLS estimation method show that FDI, CO2 emissions, and Exports have a significant and positive impact on Economic Development in five selected Southeast Asian countries without Employment Opportunities in the long run. From these findings, the author proposes some policy implications of attaching FDI to sustainable Economic Development in Vietnam next time.