• Health Policy and Management
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• v.30 no.2
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• pp.199-210
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• 2020

Background: Based on the importance of ceasing smoking programs to control the regional disparity of smoking behavior in Korea, this study aims to reveal the variation of smoke rate and determinants of it for 229 provinces. An evaluation of the relative efficiency of the cease smoking program under the consideration of regional characteristics was followed. Methods: The main sources of data are the Korean Statistical Information Service and a national survey on the expenditure of public health centers. Multivariate regression is performed to figure the determinants of regional variation of smoking rate. Based on the result of the regression model, clustering analysis was conducted to group 229 regions by their characteristics. Three clusters were generated. Using data envelopment analysis (DEA), relative efficiency scores are calculated. Results from the pooled model which put 229 provinces in one model to score relative efficiency were compared with the cluster-separated model of each cluster. Results: First, the maximum variation of the smoking rate was 16.9%p. Second, sex ration, the proportion of the elder, and high risk drinking alcohol behavior have a significant role in the regional variation of smoking. Third, the population and proportion of the elder are the main variables for clustering. Fourth, dissimilarity on the results of relative efficiency was found between the pooled model and cluster-separated model, especially for cluster 2. Conclusion: This study figured regional variation of smoking rate and its determinants on the regional level. Unconformity of the DEA results between different models implies the issues on regional features when the regional evaluation performed especially on the programs of public health centers.

• Journal of the Korean Regional Science Association
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• v.31 no.3
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• pp.3-17
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• 2015

In Korea, the private education spending of the households accounted for about 3% of GDP and such a education fever has been associated with the financial burden of households. The main purpose of this paper is to investigate the effects of regional education environment on the private education expenditure of the households using the Korean Labor and Income Panel Survey(KLIPS) data. The quantile regression model is used to examine whether the effects of regional education environment such as the degree of education fever differ across the 'quantiles' in the conditional distribution of private education expenditure. The empirical results showed that the amount of private education expenditure is under the influence of the regions where the households reside. In addition, it was found that the private education spending of the households in the upper quantile groups are more likely to be affected by the regional education environments than those in the lower quantile groups.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.2
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• pp.142-158
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• 2009

The purpose of this paper is to identify determinants of regional export in Korea using the interregional input-output table and SUR(Seemingly Unrelated Regression) model. Regional exports are classified into four groups; intraindustry intraregional export, interindustry intraregional export, intraindustry interregional export and interindustry interregional export. Labor productivity, scale economies, market size, and international trade volumes have positively influenced regional exports while the interregional distances having a negative effect on them. These results imply that it is necessary to operate regional strategies to enhance productivities and market size and to reduce transportation and distribution costs for revitalize a regional economy by increasing regional exports.

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.2
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• pp.106-124
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• 1984

Monthly streanflow of watersheds is one of the most important elements for the planning, design, and management of water resources development projects, e.g., determination of storage requirement of reservoirs and control of release-water in lowflow rivers. Modeling of longterm runoff is theoretically based on water-balance analysis for a certain time interval. The effect of the casual factors of rainfall, evaporation, and soil-moisture storage on streamflow might be explained by multiple regression analysis. Using the basic concepts of water-balance and regression analysis, it was possible to develop a generalized model called the Regionalized Regression Model for Monthly Streamflow in Korean Watersheds. Based on model verification, it is felt that the model can be reliably applied to any proposed station in Korean watersheds to estimate monthly streamflow for the planning, design, and management of water resources development projects, especially those involving irrigation. Modeling processes and properties are summarized as follows; 1. From a simplified equation of water-balance on a watershed a regression model for monthly streamflow using the variables of rainfall, pan evaporation, and previous-month streamflow was formulated. 2. The hydrologic response of a watershed was represented lumpedly, qualitatively, and deductively using the regression coefficients of the water-balance regression model. 3. Regionalization was carried out to classify 33 watersheds on the basis of similarity through cluster analysis and resulted in 4 regional groups. 4. Prediction equations for the regional coefficients were derived from the stepwise regression analysis of watershed characteristics. It was also possible to explain geographic influences on streamflow through those prediction equations. 5. A model requiring the simple input of the data for rainfall, pan evaporation, and geographic factors was developed to estimate monthly streamflow at ungaged stations. The results of evaluating the performance of the model generally satisfactory.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.33-42
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• 2019

In this study, the channel and floodplain widths are indirectly measured for three different watersheds using satellite images to reflect the shape of Korean channels in the Soil and Water Assessment Tool (SWAT) model. For measuring the channel and floodplain widths, multiple satellite images were referred to ensure the widest width of certain points. In the single channel, the widths at the multiple points were measured. Based on the measured data, the regression equations were derived to estimate the channel and floodplain widths according to watershed areas. Applying these developed equations, this study evaluated the effect of the change of channel and floodplain widths on the SWAT simulation by comparing to the measured streamflow data. The developed equations estimated larger channel width and smaller floodplain compared with those calculated in the current SWAT model. As shown in the results, there was no considerable changes in the predicted streamflow using the current and developed equations. However, the flow velocity and channel depth calculated from the developed equations were smaller than those of the current equations. The differences were caused by the effect of different channel geometries used for calculating the hydraulic characteristics. The channel geometries also affected the water quality simulation in channels because the hydraulic characteristics calculated by the channel geometries are directly related to the water quality simulation. Therefore, application of the river cross-sectional regression equation reflecting the domestic stream shape is necessary for accurate water quantity / quality and water ecosystem simulation using hydrological model.

• Atmosphere
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• v.25 no.4
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• pp.669-683
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• 2015

In this study, we investigated the prediction skills of four multiple linear regression methods for monthly air temperature over South Korea. We used simulation results from four regional climate models (RegCM4, SNURCM, WRF, and YSURSM) driven by two boundary conditions (NCEP/DOE Reanalysis 2 and ERA-Interim). We selected 15 years (1989~2003) as the training period and the last 5 years (2004~2008) as validation period. The four regression methods used in this study are as follows: 1) Homogeneous Multiple linear Regression (HMR), 2) Homogeneous Multiple linear Regression constraining the regression coefficients to be nonnegative (HMR+), 3) non-homogeneous multiple linear regression (EMOS; Ensemble Model Output Statistics), 4) EMOS with positive coefficients (EMOS+). It is same method as the third method except for constraining the coefficients to be nonnegative. The four regression methods showed similar prediction skills for the monthly air temperature over South Korea. However, the prediction skills of regression methods which don't constrain regression coefficients to be nonnegative are clearly impacted by the existence of outliers. Among the four multiple linear regression methods, HMR+ and EMOS+ methods showed the best skill during the validation period. HMR+ and EMOS+ methods showed a very similar performance in terms of the MAE and RMSE. Therefore, we recommend the HMR+ as the best method because of ease of development and applications.

• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.21-38
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• 2024

Understanding the interrelationship between regional population dynamics and cultivated land is crucial for promoting regional economic vitality and enhancing food security. While prior research often addressed population migration and changes in crop area separately, this study employs a Panel Vector Auto Regression Model to examine the dynamic interaction between regional population shifts, changes in crop area, and the influx of foreign workers in agriculture. The results reveal a reciprocal relationship between population influx and crop area, indicating a negative impact on each other. Moreover, the analysis demonstrates that an expansion in crop area, particularly in field cultivation, significantly correlates with an increase in foreign workers. These findings underscore the mutual influence of labor shortages and diminished land availability in agriculture, with the influx of foreign workers potentially offering a positive impact on addressing structural challenges in rural areas.

• The Korean Journal of Financial Management
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• v.15 no.2
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• pp.401-419
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• 1998

This paper examines the international arbitrage pricing model (IAPM) in regional equity markets setting. Factor analyses are used to estimate the international common risk factors. And the cross-sectional regression analyses are used to test the validity of regional IAPMs and Chow tests are used to evaluate the integration of regional equity markets. The results of factor analyses show that the number of common factors in each regional group is seven. The cross-sectional regression results lead us not to reject that the IAPMs are regionally valid but Chow test results lead us to reject that regional equity markets are integrated.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.4
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• pp.97-107
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• 2017

This study is to determine the coefficients of regression equations and to select the optimal regression equation in the LOADEST model after classifying the whole study period into 5 flow conditions for 16 watersheds located in the Nakdonggang waterbody. The optimized coefficients of regression equations were derived using the gradient descent method as a learning method in Tensorflow which is the engine of machine-learning method. In South Korea, the variability of streamflow is relatively high, and rainfall is concentrated in summer that can significantly affect the characteristic analysis of pollutant loads. Thus, unlike the previous application of the LOADEST model (adjusting whole study period), the study period was classified into 5 flow conditions to estimate the optimized coefficients and regression equations in the LOADEST model. As shown in the results, the equation #9 which has 7 coefficients related to flow and seasonal characteristics was selected for each flow condition in the study watersheds. When compared the simulated load (SS) to observed load, the simulation showed a similar pattern to the observation for the high flow condition due to the flow parameters related to precipitation directly. On the other hand, although the simulated load showed a similar pattern to observation in several watersheds, most of study watersheds showed large differences for the low flow conditions. This is because the pollutant load during low flow conditions might be significantly affected by baseflow or point-source pollutant load. Thus, based on the results of this study, it can be found that to estimate the continuous pollutant load properly the regression equations need to be determined with proper coefficients based on various flow conditions in watersheds. Furthermore, the machine-learning method can be useful to estimate the coefficients of regression equations in the LOADEST model.

• The Journal of Fisheries Business Administration
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• v.51 no.1
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• pp.81-96
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• 2020

The purpose of this paper is to analyze factors affecting the net income of regional and industrial fisheries cooperatives in South Korea using panel data. This paper utilizes linear or GLS regression models such as pooled OLS model, fixed effects model, and random effects model to estimate affecting factors of the net income of regional and industrial fisheries cooperatives. After reviewing various tests, we eventually select random effects model. The results, based on panel data between 2013 and 2018 year and 64 fisheries cooperatives, indicate that capital and area dummy variables have positive effects and employment has negative effect on the net income of regional and industrial fisheries cooperatives as predicted. However, debt are opposite with our predictions. Specifically, it turns out that debt has positive effect on the net income of regional and industrial fisheries cooperatives although it has been increased. Additionally, this paper shows that the member of confreres does not show any significant effect on the net income of regional and industrial fisheries cooperatives in South Korea. This study is significant in that it analyzes the major factors influencing changes in the net income that have not been conducted recently for the fisheries cooperatives by region and industry.