• Environmental and Resource Economics Review
• /
• v.33 no.1
• /
• pp.59-86
• /
• 2024

Recently, research on city gas demand is increasing by reflecting the characteristics of each region. The similarity of the social structure of the adjacent region and the density of the supply infrastructure induce spatial correlation with the clustering that has a microscopic relationship between regions. Accordingly, as a result of analyzing the spatial correlation after dividing the demand for city gas for civilian use into a total of 54 regions based on the jurisdiction of 34 city gas companies, it was confirmed that there was a positive spatial correlation from a global and local perspective. In this study, the demand for city gas for civilian use for 54 regions from January 2014 to December 2022 was composed of panel data, and the spatial panel regression analysis and the general panel regression analysis were compared, and it was found that the spatial error model (SEM) was the most suitable model. This presents policy and practical implications by confirming that the demand for city gas for civilian use in one region has a significant relationship with the adjacent region.

• The Korean Journal of Applied Statistics
• /
• v.29 no.5
• /
• pp.873-885
• /
• 2016

Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.6
• /
• pp.1253-1262
• /
• 2014

Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.

• Journal of the Economic Geographical Society of Korea
• /
• v.26 no.3
• /
• pp.310-323
• /
• 2023

Urbanization and income distribution issues are global interest, and the results of studies on the impact of urbanization on income inequality are different for each country and period. This study analyzes the impact of urbanization on income inequality using regional data from 2000-2021. In particular, serial correlation, spatial dependence, and common factor effects of the Gini coefficient are confirmed and analyzed through a dynamic spatial panel regression model. As a result, urbanization has a positive effect on reducing income inequality. Therefore, it is necessary to continuously promote regional urbanization to improve the income distribution problem. Areas with already high urbanization rates should reduce income inequality by narrowing the wage gap by expanding training opportunities for low-skilled workers, and need to come up with measures to prevent counter-urbanization.

• Journal of the Korean Regional Science Association
• /
• v.40 no.2
• /
• pp.91-106
• /
• 2024

Around the world, many countries experiencing the issue of shrinking cities are continually expanding high-speed rail networks to enhance regional accessibility and address imbalances. This study analyzed the effects of high-speed train operations on the age-specific population migration in South Korean municipalities from 2012 to 2019, taking into account the risk levels of shrinking cities. For this purpose, an analysis was conducted using age-specific net in-migration population as the dependent variable, employing the spatial panel autoregressive model. The research results indicated that the influence of high-speed rail on regional population inflow varies depending on the risk level of shrinking city. In other words, high-speed railway operations had positive effects on population inflow in the capital areas and some major cities, while explained population outflow in the other regions. High-speed railways particularly exerted a significant impact on the inflow of the young and middle-aged population, representing the working age, but this effect was also limited to regions with a low risk of shrinkage. The findings of this study emphasize the importance of considering planned population and industrial attraction when installing high-speed rail with the goal of achieving regional balanced development and mitigating shrinkage. The results of this study also suggest the need for subsequent research to explore factors that positively influence population structure and inflow based on the level of shrinkage risk in each region, as well as the introduction of new policies tailored to the specific situations of each local government.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.2
• /
• pp.228-237
• /
• 2018

The purpose of this study is to develop an index to measure regional creativity factors from previous research, as well as to empirically analyze the relationship between regional creativity and regional growth. We conduct panel analysis on the balanced panel data of regional creativity in fifteen Korean cities and provinces during 2008-2012. The result of hypothesis testing are as follows: First, amongst factors of regional creativity, sub-factors such as creative personnel and intangible asset (of the basic asset factor), creative enterprise (of the economic agent factor), and convergence and creative industries (of the core industry factor) showed significant influential relationships with GRDP (Gross Regional Domestic Product) as positive. Concerning the systemization factor, all sub-factors showed no significant relationship with GRDP. Second, amongst the factors, creative personnel (of the basic asset factor), start-up and entrepreneurship (of the systemization factor), creative enterprise (of the economic agent factor), the regional space factor, and convergence industry (of the core industry factor) showed significant positive relationships with employment rate. However, tangible and intangible creative asset (of the basic asset factor), convergence management and administration (of the systemization factor), Large/middle/small enterprises and central government/municipalities (of the economic agent factor), and creative industry (of the core industry factor) showed no significant relationship with employment rate. The results of this study will provide insight into the current situation for regional creativity, and review the process and short and long term performance. In addition, it will be a basic means to lead the central government's policy of strengthening local autonomy and decentralization.

• Korean Journal of Social Welfare
• /
• v.67 no.2
• /
• pp.137-159
• /
• 2015

This longitudinal study examined the influence of substandard housing conditions and housing affordability on physical and mental health. Using data from the Korea Welfare Panel Study, this study followed 8,583 adults who continued to participate in the survey from 2009 to 2013. Multivariate analyses involved linear and logistic regression models with the hybrid method that incorporates both fixed and random effects. Results show that substandard housing conditions and excess housing cost burden had significant adverse effects on adults' mental health (e.g., depressive symptoms). About one fourth of the entire sample and one third of those in poverty reported having lived in substandard housing conditions. Additionally, nearly one fourth of those in poverty reported having experienced excess housing cost burden, which is 4 times greater than that of the entire sample. Our findings show that a substantial proportion of individuals, particularly among the poor, have a difficulty in accessing to decent, affordable housing, and that housing assistance may have additional benefits of improving the mental health of individuals with housing issues.

• Journal of agricultural medicine and community health
• /
• v.46 no.4
• /
• pp.280-294
• /
• 2021

Objectives: The purpose of this study is to investigate the effects of social capital characteristics, socio-demographic characteristics, physical condition, and health behavior characteristics on health-related quality of life of the elderly in Korea. Methods: T-test, one-way ANOVA, and regression analysis were performed by applying a complex sample design to 57.787 people aged 65 and over using the 2019 Community Health Survey. Results: First, as a result of complex-sample T-test and ANOVA analysis, it was found that there were differences in health-related quality of life according to social capital characteristics, physical condition & health behavior characteristics, and socio-demographic characteristics. Complex Sample Regression Analysis Results, the explanatory power of the model was 28%. When living in the metropolitan area, living in an apartment building, having a spouse, having a higher household income, economic activity, higher educational attainment, increase sleeping time, walking time, frequent binge drinking, health checkup, networking, trust, and social participation showed higher health-related quality of life. When people were older, their gender was female, higher BMI, number of chronic diseases, and severe stress that showed lower health-related quality of life. Conclusions: It was proved that the factors affecting the health-related quality of life of the elderly are not only physical condition and health behavior factors, but also social capital and socio-demographic characteristics. It was found that the role as a member was important.