• The Korean Journal of Applied Statistics
• /
• v.20 no.1
• /
• pp.11-22
• /
• 2007

In this study, we have proposed the new statistical methods to convert the statistics based of workplace units into the statistics based of industrial units using the industrial survey data published by National Statistical Once in 2001. It could help to apprehend the weight of service sectors of korea small business in terms of the Gross Domestic Product (GDP).

• The Journal of Asian Finance, Economics and Business
• /
• v.5 no.3
• /
• pp.43-50
• /
• 2018

The paper aims to investigate the impact of trade cost on export: A Case Study Vietnam. The study conducts a static linear panel data analysis on annual data covering bilateral export between Vietnam and 70 major importers of Vietnam from 2001 to 2013. The gravity model has been one of the most successful applications in empirical trade. In this paper we apply the gravity model to estimate the impact of trade cost on Vietnamese bilateral export value. The paper uses gravity model to estimate the impact of trade cost on Vietnamese bilateral export value. The empirical results derive from a static linear panel data analysis (fixed effects model) indicates that trade cost plays a crucial role in determining the export value that occurs between Vietnam and trading partners. Besides, population of importing country, trade openness of importing country, gross domestic product of importing country and gross domestic product of Vietnam are also significant determinants of Vietnamese bilateral export value. The main findings indicates that trade cost plays a very important role in the Vietnamese bilateral export performance. This suggests that the Vietnamese government should attempt to improve domestic trade costs to enhance competitiveness and increase export growth sustainably.

• Environmental and Resource Economics Review
• /
• v.30 no.3
• /
• pp.503-533
• /
• 2021

This paper analyzes the relationships among the energy consumption, renewable energy production, real gross regional domestic product(GRDP), and greenhouse gas(GHG) emissions. It uses the metropolitan city and province level data for Korea from 2010 to 2018, employing a panal vector autoregressive(VAR) model. We find that an increase in energy consumption has a limited impact on boosting renewable energy production or gross regional domestic product, while it leads to an increase in greenhouse gas emissions. A rise in renewable energy production can increase gross regional domestic product, but it has no meaningful effects on energy consumption and the reduction of green house gas emissions. Our finding indicates that it is crucial to expand the supply of renewable energy as well as to decrease energy consumption in order to achieve the goal of reducing greenhouse gas emissions and reaching economic growth.

• The Korean Journal of Pain
• /
• v.34 no.1
• /
• pp.82-93
• /
• 2021

Background: This study used bibliometric analysis of articles published about the topic of regional anesthesia from 1980-2019 with the aim of determining which countries, organizations, and authors were effective, engaged in international cooperation, and had the most cited articles and journals. Methods: All articles published from 1980-2019 included in the Web of Science database and found using the keywords regional anesthesia/anaesthesia, spinal anesthesia/anaesthesia, epidural anesthesia/anaesthesia, neuraxial anesthesia/anaesthesia, combined spinal-epidural, and peripheral nerve block in the title section had bibliometric analysis performed. Correlations between the number of publications from a country with gross domestic product (GDP), gross domestic product (at purchasing power parity) per capita (GDP PPP), and human development index (HDI) values were investigated with the Spearman correlation coefficient. The number of articles that will be published in the future was estimated with linear regression analysis. Results: Literature screening found 11,156 publications. Of these publications, 6,452 were articles. The top 4 countries producing articles were United States of America (n = 1,583), Germany (585), United Kingdom (510), and Turkey (386). There was a significant positive correlation found between the GDP, GDP PPP, and HDI markers for global countries with publication productivity (r = 0.644, P < 0.001; r = 0.623, P < 0.001, r = 0.542, P < 0.001). The most productive organizations were Harvard University and the University of Toronto. Conclusions: This comprehensive study presenting a holistic summary and evaluation of 6,452 articles about this topic may direct anesthesiologists, doctors, academics, and students interested in this topic.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.507-515
• /
• 2002

Remote Sensing Monitoring and Loss Estimated System of Flood Disaster based on GIS is an integrated system comprised flood disaster information receiving and collection, flood disaster simulation, and flood disaster estimation. When the system receives and collects remote sensing monitoring and conventional investigation information, the distributional features of flood disaster on space and time is obtained by means of image processing and information fusion. The economic loss of flood disaster can be classified into two pus: direct economic loss and indirect economic loss. The estimation of direct economic loss applies macroscopic economic analysis methods, i.e. applying Product (Industry and Agriculture Gross Product or Gross Domestic Product - GDP) or Unit Synthetic Economic Loss Index, direct economic loss can be estimated. Estimating indirect economic loss applies reduction coefficient methods with direct economic loss. The system can real-timely ascertains flood disaster and estimates flood Loss, so that the science basis fur decision-making of flood control and relieving disaster may be provided.

• Journal of Korean Society of Rural Planning
• /
• v.29 no.3
• /
• pp.91-97
• /
• 2023

The purpose of this research is to apply the regional development attractiveness of the national level determined in the previous study to the city and county level of Chungcheongnam-do. We verified results with the population change of the floating population data. In order to measure regional development attractiveness in 2020, Chungcheongnam-do's integrated air environment index and per capita gross regional product were gathered. Population movement data over the past five years have been used to analyze population changes in the floating population data. Regional development attractiveness depended on the data of GDP per capita, which had a large difference between the maximum and minimum values. The rate of increase or decrease in population change by city and county in Chungcheongnam-do over the past five years has changed significantly since 2021 and characteristics of each group were grouped into four groups. Based on the environment and economic feasibility of the region, it can be the starting point for a new analysis of Korea's regional development projects and the selection of target sites. Policy suggestions can also be made in spatial plans such as short-term comprehensive plans, long-term comprehensive plans, and development plans. It can be a limit of this research that regional development attractiveness was determined by the relatively large per capita gross domestic product. It is necessary to further develop regional development attractiveness by closely investigating the characteristics of the region, social problems, and emissions of environmentally harmful substances.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.12
• /
• pp.109-114
• /
• 2020

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia's growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.1
• /
• pp.103-112
• /
• 2021

The labor force plays an important role in attracting foreign direct investment (FDI) both in developed and developing countries. In countries where there are appropriate policies for training human resources and maintaining the health of human resources, such countries have a competitive advantage and can attract FDI inflows, besides having a workforce to meet the needs of foreign investors. The purpose of this paper is to analyze the effect of the labor force and several other factors on FDI attraction in Vietnam. The empirical model is employed to perform regression and correlation on the impact of the labor force, real gross domestic product, inflation, index of business freedom, and index of investment freedom on Vietnam's FDI attraction by using a secondary time series data set during the period 1995-2018. The empirical results found that both labor force and inflation have a positive influence on FDI at a 5% significance level; index of business freedom has a positive impact on FDI at a 10% significance level, and real gross domestic product and index of investment freedom have a positive impact on FDI at a 1% significance level. From these results, this study proposes several important policy implications for Vietnam in attracting FDI in the future.

• Asian Journal of Business Environment
• /
• v.11 no.1
• /
• pp.39-50
• /
• 2021

Purpose: This study seeks to establish the environmental damage theory applicable to Kenya. The analysis is based on annual data drawn from World Bank on carbon dioxide emissions (CO2e) and gross domestic product per capita (GDPPC) for Kenya spanning 1963 to 2017. Research Methodology: The study adopts explanatory research design and autoregressive distributed lag model for analysis. Results: The results revealed a coefficient of -0.017 for GDPPC and 0.004 for GDPPC squared indicating that economic growth has negative effect on CO2e in the initial stages of growth but positive effect in the high growth regime with the marginal effect being higher in the initial growth regime. The findings suggest a U-shaped relationship consistent with Brundtland Curve Hypothesis (BCH). Conclusions: The findings emphasize the need for sustainable development path that enables present generations to meet own needs without compromising the capacity of future generations to meet their own. Sustainable development may include, investment in renewable energies like wind, solar and adoption of energy efficient technologies in production and manufacturing. The study concludes that BCH is applicable to Kenya and that developing affordable and effective mechanisms to boost sustainable development implementation is necessary to decrease the anthropogenic impact in the environment without any attendant reduction in the economic growth.

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