• Journal of the Korean Regional Science Association
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• v.33 no.2
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• pp.3-23
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• 2017

This study aims to understand how human capital is related to the inter-regional wage gap between the capital region and the non-capital region in Korea. We focus more specifically on whether the inter-regional wage gap is due to high levels of human capital in the capital region or due to high returns to human capital in the capital region. The decomposition method based on the unconditional quantile regression was used to examine how the relationship between human capital and the inter-regional wage gap varies along the wage distribution. When first estimating earnings functions from the two regions to apply this decomposition method, we included not only conventional indicators of human capital, such as education and on-the-job training, but also occupational skills including cognitive-interactive skills, technical skills, and physical skills. As a result, other things being equal, a large part of the inter-regional wage gap was explained by the human capital variables. Although the composition effect of the human capital variables existed in all the wage quantiles, the more important factor was the wage structure effect of the human capital variables. In addition, among the various human capital variables, the wage structure effect of years of education was a key factor in explaining the inter-regional wage gap. This study is meaningful in that it shows that the relationship between human capital and the inter-regional wage gap may vary depending on the wage quantiles.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.1036-1045
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• 2013

The purpose of this study was to examine the effects of Simulation as a Problem-Based Learning (S-PBL) on critical thinking disposition, self-efficacy, and learning attitude and to compare an ordinary least square and a quantile regression method in impacting factors on critical thinking disposition. 143 students from six classes were randomly selected from a total of ten fundamental classes were assigned 66 in the control group and 77 in the experimental group. The results were that the experimental group received S-PBL and improved their critical thinking disposition and self-efficacy compared to the traditional learning method. In ordinary least square, affecting factors on critical thinking were the learning method and self-efficacy and these variables explained 41.0% in the critical thinking disposition. The results of the quantile regression method showed that affecting factors of critical thinking disposition were learning attitude of 0.1 quantile to 0.7 quantile and self-efficacy of all quantiles, and learning attitude of 0.4, 0.6, and 0.7 quantiles. Conclusion: The S-PBL is an effective method for nursing students who have low critical thinking disposition score to increase critical thinking disposition. And instructors can actively use S-PBL to enhance critical thinking disposition as well as self-efficacy in class.

• Journal of the Korean Regional Science Association
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• v.38 no.2
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• pp.3-20
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• 2022

The purpose of this study is to explore the heterogeneity of compensating wage differentials for outdoor workers, under the threat of climate change and heatwave, by region and by wage quantile. This study conducted Oaxaca-Blinder decomposition, multiple regression analysis by region, and unconditional quantile regression analysis using the Korean Working Conditions Survey, which provides individual-level information on the working environment and worker's characteristics. The implications derived from the results of the study are as follows: For most variables, the endowment effect and the price effect were greater for indoor workers, while experience and gender played a role in narrowing the wage gap; The compensating wage differentials for outdoor workers were confirmed to be 2.4% nationwide, depending on the region however, the compensating wage differentials varied from 5 times of national average to nothing statistically significant; The higher the wage quantile, the greater the compensating wage differentials for outdoor workers, and statistically significant monetary compensation was not identified for some low-level outdoor workers. This study is meaningful as an early study that revealed the heterogeneity of compensating wage differentials for outdoor workers and suggested further research on the topic.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.2
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• pp.94-104
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• 2015

Population and urban development along the coast is growing in South Korea, and particularly sea level rise is likely to increase the vulnerability of coastal areas. This study aims to investigate the sea level rise through Mann-Kendall(MK) test, ordinary linear regression(OR) and quantile regression analysis(QRA) with sea level data at the 20 tide stations along the coast of Korean Peninsula. First, statistically significant long-term trends were analysed using a non-parametric MK test and the test indicated statistically significant trends for 18 and 10 stations at the 5% significance level in the annual mean value of sea level and the annual maximum value of sea level, respectively. The QRA method showed better performance in terms of characterizing the degree of trend. QRA showed that an average annual rise in mean sea level is about 1-6 mm/year, and an average rise in maximum sea level is about 1-20 mm. It was found that upward convergent and upward divergent were a representative change given the nine-category distributional changes. We expect that in future work we will address nonstationarities with respect to sea level that were identified above, and develop a nonstationary frequency analysis with climate change scenarios.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.426-433
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• 2016

This study investigates the effects of entrepreneurship and corporate social responsibility (CSR) on firm performance. I use the conditional quantile regression as well as the ordinary least square (OLS) with 300 samples, only medium and small size companies. I found firstly, entrepreneurship affected overall positively firm performance in the all quantile levels. Secondly, CSR also have a positive impact on firm performance in the overall all quantile levels. By these results, I recommend that entrepreneurship and CSR should a positive impact on the firm performance for the small and medium business companies.

• Journal of the Korean Geographical Society
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• v.49 no.5
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• pp.690-704
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• 2014

Single family houses are the traditional & typical type of house in human history. But there had been little attention to single family houses in Korea so that there was little studies on single family houses. This study aimed to analyse price determinants of single family houses in Seoul, using Quantile Regression Analysis(QRA). Because single family houses has large levels of price, quantile regression analysis is more proper than Ordinary Least Square(OLS). The Results of analysis showed that, land coverage ratio, zoning, passed years, basement floor, hight of land, shape of land were important factors to single family houses price. The scale of effect of land coverage ratio to single family houses price was different to price levels of single family houses. And basement floor affected more negative effects to middle price, location and zoning had positive effects to high price single family houses. The degree of influence of determinants of single family houses price was deferent by region, KangBuk and KangNam. In KangNam, land coverage ratio and accessibilities were more important in low price single family houses, green zone and more far way is affected positive effects on single family houses price. In Kangbuk, land coverage ratio affects similar effects on single family houses price.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7820-7830
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• 2015

Korean households' demand for food consumed away from home is on the steady increase. The ratio of eating-out expenditure of the household income, however, tends to decrease recently irrespective of income groups. This paper, therefore, aims to analyse the food-away-from-home expenditures of salary and wage earners' households by income decile group. The eating-out expenditure is modelled as a function of household income and then estimated using econometric methods such as regression, rolling regression, impulse response, and variance decomposition of forecast error. The regression results indicate that the higher the income decile group is, the lower the income elasticity of eating-out expenditure is, and the high income groups enjoy seasonal eating-out, the low groups do not. The coefficients of dynamic rolling regression are much smaller than those of static one, meaning that households tend to decrease the eating-out expenditure of their income. The impulse response analysis suggests that the eating-out expenditure increase of higher income groups lasts long relative to that of lower income groups. The variance decomposition, also, shows that household income plays much more important role in determining eating-out expenditure at the higher income groups than at the lower income groups.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.753-762
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• 2020

With an increasing interest in integrating artificial intelligence (AI) into interview processes, the Republic of Korea (ROK) army is trying to lead and analyze AI-powered interview platform. This study is to analyze the AI interview data using a unified non-crossing multiple quantile tree (UNQRT) model. Compared to the UNQRT, the existing models, such as quantile regression and quantile regression tree model (QRT), are inadequate for the analysis of AI interview data. Specially, the linearity assumption of the quantile regression is overly strong for the aforementioned application. While the QRT model seems to be applicable by relaxing the linearity assumption, it suffers from crossing problems among estimated quantile functions and leads to an uninterpretable model. The UNQRT circumvents the crossing problem of quantile functions by simultaneously estimating multiple quantile functions with a non-crossing constraint and is robust from extreme quantiles. Furthermore, the single tree construction from the UNQRT leads to an interpretable model compared to the QRT model. In this study, by using the UNQRT, we explored the relationship between the results of the Army AI interview system and the existing personnel data to derive meaningful results.

• Korean Journal of Social Welfare Studies
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• v.47 no.3
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• pp.35-60
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• 2016

This study analyzes the unequal distributional effect of threesome of family policy(child benefit, childcare services and parental leave) focusing on family income, mother's status in labor market in Korea. To measure the unequal distributional effect of family policies, this study used the quantile analysis. The results of this study are as follows. First, in terms of childcare service and parental leave, there is some difference of the rate of use by family income and mother's status in labor market. Second, total public fund for childcare services, child benefits and parental leave are high in fourth income quintile, and mothers work regularly. Third, public fund is high in fourth income quintile, dual earners, mothers work regularly, the family has many number of child, and is high educational level of parents. Finally, the results of quantile regression show the biggest factors of unequal distribution of family policy are mother's stable work and it deepens the inequalities and differences. Based on these results, this article suggests that more equal right to access and use family policy regardless of the type of employment, adequate minimum income through income transfer, and universal application of the policy.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1095-1106
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• 2016

The quantile regression method proposed by Koenker et al. (1978) focuses on conditional quantiles given by independent variables, and analyzes the relationship between response variable and independent variables at the given quantile. Considering the linear programming used for the estimation of quantile regression coefficients, the model fitting job might be difficult when large data are introduced for analysis. Therefore, dimension reduction (or variable selection) could be a good solution for the quantile regression of large data sets. Regression tree methods are applied to a variable selection for quantile regression in this paper. Real data of Korea Baseball Organization (KBO) players are analyzed following the variable selection approach based on the regression tree. Analysis result shows that a few important variables are selected, which are also meaningful for the given quantiles of salary data of the baseball players.