• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.157-169
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• 2018

The purpose of this study was to examine the volatility of bitcoin, diagnose if bitcoin are a systematic risk asset, and evaluate their effectiveness by estimating market beta representing systematic risk using GARCH (Generalized Auto Regressive Conditional Heteroskedastieity) model. First, the empirical results showed that the market beta of Bitcoin using the OLS model was estimated at 0.7745. Second, using GARCH (1, 2) model, the market beta of Bitcoin was estimated to be significant, and the effects of ARCH and GARCH were found to be significant over time, resulting in conditional volatility. Third, the estimated market beta of the GARCH (1, 2), AR (1)-GARCH (1), and MA (1)-GARCH (1, 2) models were also less than 1 at 0.8819, 0.8835, and 0.8775 respectively, showing that there is no systematic risk. Finally, in terms of efficiency, GARCH model was more efficient because the standard error of a market beta was less than that of the OLS model. Among the GARCH models, the MA (1)-GARCH (1, 2) model considering non-simultaneous transactions was estimated to be the most appropriate model.

• Bulletin of the Korean Chemical Society
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• v.6 no.6
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• pp.378-378
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• 1985

• 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 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.

• Journal of the Korean Regional Science Association
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• v.33 no.2
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• pp.25-37
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• 2017

The paper is basically designed to investigate how regional consumption affects to regional income in Korea by introducing a model with panel cointegration, rational expectation and FM-OLS cointegration methodology. Empirical evidence reveals that the regional income could be stimulated by manipulating the regional consumption due to the fact that current regional consumption and first-lagged regional income are positively related to the level of regional income. Although there exists a possibility to increase the regional income which is associated with a spending multiplier in the group of regions with highly calculated MPC, but not in the groups of regions with middle and low calculated MPCs. To this end, it could be tentatively concluded that market-oriented system should be implemented elaborately to enable that the spending multipliers are appropriately operated in these two groups.

• Korea journal of population studies
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• v.26 no.1
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• pp.143-170
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• 2003

During the last few decades dramatic expansion of education occurred for women as well as men in Korea. Taking into account such a rapid expansion of education, this study examines trends in the effects of education on first occupational attainment among Korean women. Using the data from "the 4th Survey on Women's Employment," conducted by Korean Women's Development Institute in 2001, this study investigates the trends across three cohorts classified on the basis of the year of labor force entry after schooling: before 1980, 19801989, and 1990 or later. First, log-linear models are applied to the data to detect the temporal change in the overall association between education and first occupational attainment controlling for marginal distribution. The log-linear analysis shows that the strength of association between education and first occupation has declined over time. An additional analysis of OLS regression is conducted to see how the effects of each level of educational attainment on occupational prestige have changed across the three cohorts. The results of OLS regression suggest that the differences in prestige scores between the lowest and each of other educational levels are narrower in recent cohorts.t cohorts.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.43-51
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• 2013

This study aims to examine the presence of non-stationary relationship between water quality and land use in watersheds. In investigating the relationships between land use and water quality, most previous studies adopted OLS method which is assumed stationarity. However, this approach is difficult to capture the local variation of the relationships. We used 146 sampling data and land cover data of Korean Ministry of Environment to build conventional regressions and GWR models for BOD, TN and TP. Regression model and GWR models of BOD, TN, TP were compared with $R^2$, AICc and Moran's I. The results of comparisons and descriptive statistics of GWR models strongly indicated the presence of Non-Stationarity between water quality and land use.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.725-735
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• 2015

The aim of this study is to specifically understand the officetel market by empirical analysis for the determining factors that affect determining the price of the officetel in Busan. In my opinion, it can help officetel providers to select the appropriate size and location that analysis for the factors determining officetel price with market price, and also it can help customers officetel to choice depending on the purpose. So I was conducting this study. In this study, I analyzes the factors determining the price of Officetel using a OLS linear regression, semi-log model, and a robust regression-Busan area Officetel Real Transaction Price as the dependent variable and factors representing the physical characteristics, locational characteristics and regional characteristics as independent variables.

• Health Policy and Management
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• v.30 no.1
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• pp.26-36
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• 2020

Background: The purpose of this study was to analyze the relationship between the regional characteristics and the age-adjusted cardio-cerebrovascular disease mortality rates (SCDMR) in 229 si·gun·gu administrative regions. Methods: SCDMR of man and woman was used as a dependent variable using the statistical data of death cause in 2017. As a representative index of regional characteristics, health behavior factors, socio-demographic and economic factors, physical environment factors, and health care factors were selected as independent variables. Ordinary least square (OLS) regression and geographically weighted regression (GWR) were performed to identify their relationship. Results: OLS analysis showed significant factors affecting the mortality rates of cardio-cerebrovascular disease as follows: high-risk drinking rates, the ratio of elderly living alone, financial independence, and walking practice rates. GWR analysis showed that the regression coefficients were varied by regions and the influence directions of the independent variables on the dependent variable were mixed. GWR showed higher adjusted R² and Akaike information criterion values than those of OLS. Conclusion: If there is a spatial heterogeneity problem as Korea, it is appropriate to use the GWR model to estimate the influence of regional characteristics. Therefore, results using the GWR model suggest that it needs to establish customized health policies and projects for each region considering the socio-economic characteristics of each region.

• Journal of Korean Society of Forest Science
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• v.79 no.3
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• pp.260-268
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• 1990

Two types of ridge regression estimators were compared with the ordinary least squares (OLS) estimator in order to select the "best" estimator when multicollinearitc existed. The ridge estimators were Mallows's (1973) $C_P$-like statistic, and Allen's (1974) PRESS-like statistic. The evaluation was conducted based on the predictive ability of a yield model developed by Matney et al. (1988). A total of 522 plots from the data of the Southwide Loblolly Pine Seed Source study was used in this study. All of ridge estimators were better in predictive ability than the OLS estimator. The ridge estimator obtained by using Mallows's statistic performed the best. Thus, ridge estimators can be recommended as an alternative estimator when multicollinearity exists among independent variables.