• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1457-1469
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• 2017

Private education expenses is one of the key issues in Korea and there have been many discussions about it. Academically, most of previous researches for private education expenses have used multiple regression linear model based on ordinary least squares (OLS) method. However, if the data do not satisfy the basic assumptions of the OLS method such as the normality and homoscedasticity, there is a problem with the reliability of estimations of parameters. In this case, quantile regression model is preferred to OLS model since it does not depend on the assumptions of nonnormality and heteroscedasticity for the data. In the present study, the data from a survey on private education expenses, conducted by Statistics Korea in 2015 has been analyzed for investigation of the impacting factors for private education expenses. Since the data do not satisfy the OLS assumptions, quantile regression model has been employed in Bayesian approach by using gibbs sampling method. The analysis results show that the gender of the student, parent's age, and the time and cost of participating after school are not significant. Household income is positively significant in proportion to the same size for all levels (quantiles) of private education expenses. Spending on private education in Seoul is higher than other regions and the regional difference grows as private education expenditure increases. Total time for private education and student's achievement have positive effect on the lower quantiles than the higher quantiles. Education level of father is positively significant for midium-high quantiles only, but education level of mother is for all but low quantiles. Participating after school is positively significant for the lower quantiles but EBS textbook cost is positively significant for the higher quantiles.

• Journal of Biosystems Engineering
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• v.34 no.1
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• pp.8-14
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• 2009

When a farmer buys a tractor, the power size of a tractor is determined by various factors such as farm size, farmer's age, farming type, topographical area of farm. Relationships between tractor selection and these factors were found. Three regression models were developed to analyze the relationship. Those models were an OLS-1 model (based on 567 samples having tractors), an OLS-2 model, and a Tobit model (both based on the 1,941 samples). Regression analysis results showed that farm size and farmer's age affected selection of power size for all models at an 1% significance level. It was also shown that some farming types also had significant relationships with the tractor power size. Upland cultivating farmers and livestock farmers had larger tractors than rice cultivating farmers, while orchard farmers had smaller tractors. As for the topographical area, only middle area had significant difference with plain area. Farmers who had a rice-transplanter or a combine had larger tractors than those who didn't.

• Korea Trade Review
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• v.46 no.6
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• pp.211-224
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• 2021

Based on the perspective of international trade and cross-border e-commerce development, this paper explores the impact of cross-border e-commerce on international trade. This paper first describes the current situation of China's cross-border e-commerce and proposes a theoretical model of the influence of China's cross-border e-commerce on its international trade based on the research and summary of a large number of relevant documents. This paper establishes an extended gravity model based on the proposed theoretical model. Relevant data of 13 trading partner countries were used as sample data, and OLS regression analysis and heterogeneity analysis were conducted on gravity model by using Eviews 11.0. Then, in order to study the influence of each variable on import and export trade volume, import and export trade volume were respectively taken as explained variables and further studied by OLS regression analysis. To test the robustness of the model, the empirical analysis results show that cross-border e-commerce does promote the volume of China's international trade.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.31-39
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• 2017

The goal of this study was to efficiently analyze the relationships of the number of thefts with related factors, considering the spatial patterns of theft crimes. Theft crime data for a 5-year period (2009-2013) were collected from Haeundae Police Station. A logarithmic transformation was performed to ensure an effective statistical analysis and the number of theft crimes was used as the dependent variable. Related factors were selected through a literature review and divided into social, environmental, and defensive factors. Seven factors, were selected as independent variables: the numbers of foreigners, aged persons, single households, companies, entertainment venues, community security centers, and CCTV (Closed-Circuit Television) systems. OLS (Ordinary Least Squares) and GWR (Geographically Weighted Regression) were used to analyze the relationship between the dependent variable and independent variables. In the GWR results, each independent variable had regression coefficients that differed by location over the study area. The GWR model calculated local values for, and could explain the relationships between, variables more efficiently than the OLS model. Additionally, the adjusted R square value of the GWR model was 10% higher than that of the OLS model, and the GWR model produced a AICc (Corrected Akaike Information Criterion) value that was lower by 230, as well as lower Moran's I values. From these results, it was concluded that the GWR model was more robust in explaining the relationship between the number of thefts and the factors related to theft crime.

• Journal of Labour Economics
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• v.28 no.1
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• pp.135-156
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• 2005

This paper analyzes the distribution and determinants of income of the self-employed, in comparison with salaried workers. Relative to salaried workers, in general, the self-employed tend to have a larger dispersion of income and larger heterogeneity. In this regard, the quantile regression analysis was used, along with a typical OLS regression analysis. According to the empirical findings, the income of the self-employed is larger than that of salaried workers, and this difference is larger for higher income group. The marginal effect of education is larger for higher income groups for both the self-employed and salaried workers, implying the return on education is larger for higher income groups. In contrast, for self-employed women, the marginal effect of education is smaller for higher income groups. Put differently, the return on education in the labor market is larger for salaried workers and self-employed men of high income groups as compared to those of low income groups, whereas the opposite holds for self-employed women.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.223-235
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• 2011

Although ordinary least squares (OLS) regression analysis can be used to examine the spatial relationships between environmental equity and urban quality of life, this global method may mask the local variations in the relationships between them. These geographical variations can not be captured without using local methods. In this context, this paper explores the spatially varying relationships between environmental equity and urban quality of life across the Atlanta metropolitan area by geographically weighted regression (GWR), a local method. Environmental equity and urban quality of life were quantified with an integrated approach of GIS and remote sensing. Results show that generally, there is a negatively significant relationship between them over the Atlanta metropolitan area. The results also suggest that the relationships between environmental equity and urban quality of life vary significantly over space and the GWR (local) model is a significant improvement on the OLS (global) model for the Atlanta metropolitan area.

• New & Renewable Energy
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• v.17 no.3
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• pp.24-31
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• 2021

Through 'The Renewable Energy 3020 Implementation Plan' for carbon neutrality, the government promised to raise the proportion of renewable energy generation to 20% and renewable energy installation capacity to 63.8% by 2030. Therefore, we plan to test a 5.5 MW offshore wind turbine near Maldo, Gunsan. In this project, we measure the level of public acceptance and perform ordinary least squares (OLS) regression analysis to show the determinants of public acceptance. The regression results are as followed. First, it is judged that the closer the distance to the offshore wind turbine, the more the economic effects considered by residents. Second, especially in Maldo, the experience of being discriminated from the Saemangeum project, is understood to have caused distrust in the surrounding fishing villages chief/Fisheries Cooperatives, converted into a local community effect. Finally, the policy implications are as follows. First, a bottom-up problem-solving method is required to improve public acceptance, based on the Living Lab. Second, the island community may be indifferent to the briefings or forums of outsiders. Therefore, a gradual approach is required through (in)formal channels based on reliability from a long-term perspective with nearby universities and research institutes using SamsØ Energy Academy.

• The Journal of shipping and logistics
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• v.35 no.1
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• pp.21-50
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• 2019

The aim of this study is to analyse a characteristic analysis of coastal passenger vessels' voyage scheduling using the Panel Regression Analysis. The GLS and Fixed Effect Analysis show that the number of canceled flights and passenger transport performance have a positive impact on the voyage scheduling, and that the freight transport performance and freight income vary from model to model. Also, through the LSDV and OLS analysis, the trend of cluster formation by regional office was confirmed. This indicates that there are frequent changes in passenger ship companies and ships, and in-depth plans are needed in various respects rather than the expansion of unconditional ships. Subsequent studies need to generate more detailed and practical results by further analysis of detailed factors, dividing them by route and vessel type.

• Analytical Science and Technology
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• v.16 no.3
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• pp.185-190
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• 2003

We applied modified least square method (MLS) and ordinary least square method (OLS) to 1st order equation for the comparison of the uncertainties calculated by these methods. The uncertainty calculated by OLS covered statistically safe interval because it was over-estimated in many cases of measurement and concentration level. But, if the uncertainty of the concentration as a reference value was comparably large (about 5% of the relative standard deviation of random scattering from the regression line and about 7% of relative standard uncertainty of reference values), then uncertainty calculated by OLS was seriously under-estimated at high concentration level. It was revealed that the calculated uncertainty didn't cover statistically safe interval at the stated confidence level. It was found that the method, MLS, described in the previously article would be valid for this calculation of uncertainty.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.525-532
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• 2021

This study examines the association between a firm's business strategy and audit report lags. This study employs 5,072 firm-year observations from 2015 to 2019. Our sample comprises all of the firms listed on the Korea Composite Stock Price Index (KOSPI) market and Korea Securities Dealers Automated Quotation (KOSDAQ). We perform OLS regression analysis to test our hypothesis. The OLS regression analysis was conducted through the SAS and STATA programs. We find that business strategy is positively associated with audit report lags. Especially, we find that defender firms are negatively associated with audit report lags. The findings of this study suggest that prospector-like firms would increase their performance uncertainty as well as audit risk. Therefore, prospector-like firms interfere with the efficient audit procedures of auditors. On the other hand, our findings indicate that defender-like firms would decrease their performance uncertainty as well as an audit risk because they focus on simple product lines and cost-efficiency. For this reason, auditors will be able to carry out the audit procedures much more easily. Our results present that a prospector-like business strategy degrades audit effectiveness as it exacerbates a company's financial risk, willingness to accept uncertainty, and the complexity of organizational structure.