• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.229-238
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• 2021

The article applies the ECM - ARDL model to examine the relationship between economic indicators and the existence of the disease in the long run of 10 ASEAN countries from 2000 to 2019. There are two models: The first model investigates the impact of GDP per capita, net inflow FDI, unemployment rate, and inflation rate on the proportion of export to GDP of ASEAN countries, the second model is similar to the first one but adds one more variable to the independent variable list - 'the variable for disease'. The results prove the long-run effect of GDP per capita, FDI, unemployment and inflation rate on export of the selected countries, though individual country shows differences in the sign and magnitude of these impacts. Surprisingly, the number of people suffering from disease does not affect the export of all selected countries as expected. The results of the two models also indicate that the disequilibrium in the short run converges to the equilibrium in the long run with a high proportion, especially in the case of Cambodia and the Philippines, with the rate of 95.65% and 151.94%, respectively. The findings can be useful for policymakers in promulgating efficient policies to enhance the trading activities of the selected countries.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.106-110
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• 2021

In this study, the main factors affecting the number of passengers and cargo volume transported by air between Korea, China and Japan over the past 20 years are to be identified. For the analysis, data from three countries' GDP and per capita as well as exchange rates and international oil prices were used, and OLS multiple regression analysis and fixed effect analysis were performed. As a result of the analysis, both the number of passengers and cargo volume transported by air showed a negative (-) direction for GDP, which represents the country's economic power, and a positive (+) direction, for per capita GDP, which represents income level. And the increase in the exchange rate between China and Japan acted in a positive (+) direction on the increase in the number of passengers, and the effect of oil prices was found to be limited.

• Environmental and Resource Economics Review
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• v.16 no.3
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• pp.643-651
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• 2007

The Environmental Kuznets Curve Hypothesis postulates an inverted-U shaped relationship between GDP per capita and various pollutants. Pollutants emission increases up to a certain level as income goes up; after that, it decreases. This paper investigates the relationship between industry pollutants taking industrial sulfur dioxide omission as example, and economic growth by using province-panel data set from 1989 to 2004 in 28 provinces of P. R. China. The result shows that the EKC hypothesis may be supported in the case of industrial sulfur dioxide, and the GDP per capital of turning point is about RMB 13,548 (at 1978 price). Except Shanghai, all the provinces GDP per capital in this study are less than RMB 13,548, indicating the amount of industrial sulfur dioxide emission will be increasing in the near future. To realize sustainable development and pollutants abatement, the central and local government should adopt an integrated strategy to protect environment.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.11-18
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• 2022

Recently, the relevance of the Air Quality Index considering major factors related to the air environment and the local economy and community was analyzed in abraod. In Korea, a comprehensive air-quality index has been proposed. In this study, the comprehensive air-quality index and the index that can integrate Gross Domestic Product per capita were summarized as regional attractiveness. As a result of the analysis, Ulsan, Chungnam, Seoul, Chungbuk, and Jeonnam had the highest Gross domestic product per capita, and Jeju, Gyeongnam, and Gyeongbuk had the best Comprehensive air-quality index, and Ulsan had the highest attractiveness. As a result of the correlation analysis, it was found that there was no correlation between the two variables, Gross domestic product per capita and Comprehensive air-quality index, because various factors such as topographical characteristics, hazardous substances, and local government's efforts were not taken into account. As a result of sensitivity analysis, Ulsan had the highest sensitivity and variance for Gross domestic product per capita and Comprehensive air-quality index. As for the relative ratio of attractiveness between regions, Ulsan's attractiveness was 2.95 times that of Daegu's, indicating a large difference between regions.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.335-356
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• 2021

This study analyzed the trends and current status in public libraries in Korea for 14 years, focusing on the overview and facilities of public libraries using public library statistics from 2007 to 2020. The research data were collected from the National Library Statistics System and compared with the population and GDP per capita of Korea. As a result, the number of public libraries in Korea is 1,172 as of 2020, which has nearly doubled compared to 2007, and it was found that this increase has a very strong correlation with GDP per capita and population. There were 229 contracting out public libraries operating by the local government in 2020, and the contracting out rate increased from 18.8% in 2007 to 25.1%. Although the site area of public libraries varies greatly from library to library, it tends to get larger over time. The total floor area of public libraries operating by the Office of Education is larger than that of public libraries operating by the local government, and it gradually increases over time, but the total floor area of public libraries operating by the local government have decreased slightly. The total number of seats in the library is decreasing in all libraries, and the reading seats for children and the reading seats for the elderly and the disabled tend to slightly increase.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.89-112
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• 2016

In this paper, as a determining factor of the Environment Kuznets Curve hypothesis, we analyzed the impact of technological innovation. In this paper, in order to empirically validate the role of technological innovation to an inverted U-shaped Environments Kuznets Curve hypothesis, we utilize the 2SLS considering relationship between R&D and the GDP per capita. Also, using the Panel VAR (Panel Vector Auto Regression) model to analyze with what time lag R&D per capita has impact on the emissions of greenhouse gases per capita. Empirical results show that R&D per capita(proxy of innovation) is a important factor to explain Environmental Kuznets Curve hypothesis, and that the external shock such as R&D per capita reduces greenhouse gas emissions per capita with about 3 time lag.

• Journal of Korea Trade
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• v.24 no.8
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• pp.133-152
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• 2020

Purpose - The purpose of this study is to analyze the determinants of commodity trade in Korea and China and to examine the implications of China's GVC shift from export to domestic market on its impact on Korea's trade. Design/methodology - This study selected 30 major trading partner countries. The dependent variable is the trade volume, and the independent variables are general economic factors such as gross domestic product (GDP), GDP per capita, distance, and FTA. Findings - The trade pattern of Korea's commodities shows that GDP has a positive relationship with trade, import, and export. Distance has a significant negative relationship with total trade, import, and export. FTA is significant for import but it is not significant for total trade and export. The trade pattern of China's commodities shows that GDP has a significant positive relationship with total trade, import, and export. Distance has a negative relationship with trade, import, and export. GDP per capita is not significant for total trade and import, but it is significant for export. FTA is significant for total trade and export, but it is not significant for import. Originality/value - Existing papers were studied mainly in certain industrial sectors such as agriculture, manufacturing, automobile industry and steel industry. This paper attempts to collects vast amounts of data about the 30 countries of Korea and China respectively and analyzes by Random Effect Model dividing the goods (0 to 9) in units of STIC (Rev. 4). The major contribution is that the decision factors affecting commodity trade can be analyzed in SITC units (0-9) to obtain analysis results that are subdivided by product group and organized by product.

• The Journal of Fisheries Business Administration
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• v.47 no.2
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• pp.15-32
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• 2016

The Association of Southeast Asian Nations(ASEAN) has been the most essential organization in Asia. In spite of the world economic crisis, Southeast Asian countries have shown fast economic growth since 2000, and they have been actively expanding investments and trades especially with major countries. Research on competitiveness in ASEAN market has spawned an increasingly large literature, but empirical research on the determinants of Korea's export to ASEAN is limited. The purpose of this study is to draw out the determinant of Korean fisheries export to ASEAN by carrying out a panel analysis. For achieving such a purpose, pooled OLS, Hausman Test, Fixed Effect, Random Effect are performed. The last 20 years' data over the period of 1995 to 2014 concentrated on the ASEAN 6 countries such as Indonesia, Malaysia, Philippine, Singapore, Thailand, Vietnam is used in this study. Amount of aquatic products export to ASEAN is used as the dependent variable; real exchange rate, real GDP, relative price level and GDP per capita are used as the explanatory variables and FTA as dummy variable. Empirical results show that fixed-effect analysis is the best model among all the models. As the fixed effect model shows, real exchange rate, real GDP, GDP per capita and dummy variable(FTA) play positive and statistically significant roles in fisheries export to ASEAN, while price variable plays a negative and statistically significant role to the dependent variable.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.909-917
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• 2020

The research aims to analyze the firm-specific and macroeconomic factors that affect insurance company's financial performance. The research explores the variables that influence the financial performance of the United Arab Emirates (UAE)' insurance companies. The analysis for determining financial performance considers the following variables: the firm's age, retention ratio, capital adequacy, underwriting risk/loss ratio, financial-leverage, reinsurance dependency, and macro-economic factors such as GDP per capita, inflation rate considered as independent factors. The return-on-asset (ROA) is the key measuring indicator; it is regarded as the dependent variable for financial performance measures. The research focuses on secondary information obtained from insurance companies' financial statements. The researcher targeted 18 insurance companies listed on the UAE stock exchanges for study purposes. The research examines the overall factors that influence the financial performance of an insurance company. For analysis of data, software package of social sciences (SPSS version 20) is used. The studies used correlation and multiple linear regression analysis to determine financial performance and their effects. The analysis suggests that there are important and constructive relationships between the size, capital adequacy, and reinsurance dependency, while loss ratio, retention ratio, and financial leverage indicate a major negative relationship. And there's no link between GDP per capita and inflation.

• Korean Management Science Review
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• v.34 no.1
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• pp.15-25
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• 2017

We evaluated industry growth and employment effects of every possible pairs of 22 manufacturing sectors and 16 regions (i.e, 352 region-sectors). We used annual data of manufacturing sectors from 2008 to 2014 for the evaluation. The evaluation comprises of two steps; We first find several region-sectors that outperform others with respect to the effects of industry growth and employment, which are measured by location quotient analysis, shift share method, employment to GDP ratio and employment elasticity. In addition, cross-efficiency analysis follows to classify region-sector pairs into two sub-categories : efficient region-sectors that deserve to hold the current level of investments and inefficient region-sectors where we should consider efficiency improvements. To examine the efficiency, R&D investment, employment size, and capital investment were used as input factors and production volume, added value, changes in employment size, changes in annual salary per capita were used as output factors. For region-sector pairs that have outstanding growth and employment effects but are inefficient, we employed a CCR DEA model and analyzed how much to adjust the values of input and output factors to improve the efficiency scores. The analysis results showed that inefficiency is mainly due to several factors such as R&D investment, changes in employment size and changes in annual salary per capita.