• 아태비즈니스연구
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• 제14권3호
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• pp.221-240
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• 2023

Purpose - This paper investigates how business cycle impacts on corporate credit spreads since global financial crisis. Furthermore, it tests how the impact changes by the phase of the cycle. Design/methodology/approach - This study collected dataset from Barclays Global Aggregate Bond Index through the Bloomberg. It conducted multi-regression analysis by projecting business cycle using Hodrick-Prescott filtering and various cyclical variables, while ran dynamic analysis of 5-variable Vector Error Correction Model to confirm the robustness of the test. Findings - First, it proves to be statistically significant that corporate credit spreads have moved countercyclicaly since the crisis. Second, It indicates that the corporate credit spread's countercyclicality to the macroeconomic changes works symmetrically by the phase of the cycle. Third, the VECM supports that business cycle's impact on the spreads maintains more sustainably than other explanatory variable does in the model. Research implications or Originality - It becomes more appealing to accurately measure the real economic impact on corporate credit spreads as the interaction between credit and business cycle deepens. The economic impact on the spreads works symmetrically by boom and bust, which implies that the market stress could impact as another negative driver during the bust. Finally, the business cycle's sustainable impact on the spreads supports the fact that the economic recovery is the key driver for the resilience of credit cycle.

• 수산경영론집
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• 제44권3호
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• pp.77-84
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• 2013

While some steps in laver aquaculture production can be controlled artificially to a certain extent, the culturing process is largely affected by natural factors, such as the characteristics of seawater, climatic and oceanographic conditions, etc. This study aims to find a direct relationship between climatic and oceanographic factors (water temperature, air temperature, salinity, rainfall, sunshine duration and wind speed) and laver aquaculture production in Wando region, the biggest aquaculture production area of laver, located in the southwest coast of Korea using a multiple regression analysis. Despite the small sample size of a dependent variable, the goodness of model fit appeared acceptable. In addition, the R-squared value was 0.951, which means that the variables were very explanatory. Model results indicated that duration of sunshine, temperature, and rainfall during the farming period from the end of September to the end of April would be important factors affecting significantly to the laver aquaculture production.

• 대한수학회논문집
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• 제31권1호
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• pp.185-198
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• 2016

Regression analysis is an analyzing method of regression model to explain the statistical relationship between explanatory variable and response variables. This paper propose a fuzzy regression analysis applying Theils method which is not sensitive to outliers. This method use medians of rate of increment based on randomly chosen pairs of each components of ${\alpha}$-level sets of fuzzy data in order to estimate the coefficients of fuzzy regression model. An example and two simulation results are given to show fuzzy Theils estimator is more robust than the fuzzy least squares estimator.

• Journal of the Korean Data and Information Science Society
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• 제21권1호
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• pp.1-9
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• 2010

본 논문은 분할구 실험에서 반복측정 요인이 처치의 한 요인으로 고려될 때, 실험자료의 분석을 위한 혼합모형과 모형내 미지모수의 추론을 위한 방법을 논의한다. 반복측정 요인으로 공간요인을 고려하고 공간요인의 수준은 분할구에 할당되나 연구자가 임의로 배정할 수 없는 실험환경이 가정된다. 이러한 실험의 특성을 갖는 자료벡터의 확률분포로 복합대칭의 공분산 구조를 갖는 다변량 정규분포를 논의하고 있다. 또한, 가정된 실험환경에 부합하는 적합한 자료의 예를 통하여 제시된 모형의 타당성과 관련모수들의 추론방법을 다루고 있다.

• 품질경영학회지
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• 제24권1호
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• pp.32-43
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• 1996

In this paper we develop nonparametric methods for regression analysis when the response variable is subject to censoring that arises naturally in quality engineering. This development is based on a general missing information principle that enables us to apply, via an iterative scheme, nonparametric regression techniques for complete data to iteratively reconstructed data from a given sample with censored observations. In particular, additive regression models are extended to right-censored data. This nonparametric regression method is applied to a simulated data set and the estimated smooth functions provide insights into the relationship between failure time and explanatory variables in the data.

• 대한가정학회지
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• 제42권5호
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• pp.107-126
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• 2004

As the information society matures, an analysis on possible outputs of internet usage is needed. Thus, this study was peformed in order to understand the utility cognition and negative outputs of internet users. The method used in this study was a web-based questionnaire that was administered to the internet users. Five hundred married men and women were analyzed with a factor and a multiple regression analysis. Results were as follows: First, many kinds of internet usages - information searching, internet shopping, electronic mail, instant messaging, and decision-making dependent on internet information - were differentiated with age. Second, the altitude about the internet was an important explanatory variable in the types of internet usage. Third, negative outputs of internet usage were great in terms of information resource management and unbalanced scheduling in daily time spent. Fourth, utility cognition was affected by qualitative elements on internet usage more than the quantitative ones.

• Journal of applied mathematics & informatics
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• 제32권3_4호
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• pp.343-357
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• 2014

In many non-life insurance applications past data are given in a form known as the run-off triangle. Smoothing such data using parametric crisp regression models has long served as the basis of estimating future claim amounts and the reserves set aside to protect the insurer from future losses. In this article a fuzzy counterpart of the Hoerl curve, a well-known claim reserving regression model, is proposed to analyze the past claim data and to determine the reserves. The fuzzy Hoerl curve is more flexible and general than the one considered in the previous fuzzy literature in that it includes a categorical variable with multiple explanatory variables, which requires the development of the fuzzy analysis of covariance, or fuzzy ANCOVA. Using an actual insurance run-off claim data we show that the suggested fuzzy Hoerl curve based on the fuzzy ANCOVA gives reasonable claim reserves without stringent assumptions needed for the traditional regression approach in claim reserving.

• 지역연구
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• 제14권2호
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• pp.35-50
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• 1998

This paper examines the determinants of imbalanced regional development in Korea during the period of 1985-1995. The review of previous analytical techniques have been used to analyze the determinants of disparities in regional development of disparities in regional development, but few has applied the regression technique which reduces a bias due to heterogeneity across region. The results of the study show that Kmenta model with per capita GRDP as dependent variable can reduce the heterogeneity bias in regional development and can minimize the statical errors in estimation and interpretation of the coefficients of the explanatory variables. According to the results of Kmenta model, urban infrastructure such as roads, information and communication facilities are major causes of regional disparity over the period of 1985-1995. The results of the study also indicate that local government should devote their policy efforts to identify and utilize the unique soci-economic characteristics of each locality in the process of regional development.

• 한국산학기술학회논문지
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• 제8권6호
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• pp.1625-1633
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• 2007

본 논문은 자본조달방식이 경영성과에 미치는 영향을 코스닥등록 벤처기업을 대상으로 실증적 검정을 하였다. 연구결과 설명변수 단기차입방식, 장기차입방식, 사채발행방식, 주식발행방식은 기업의 경영성과 변수 성장성, 수익성, 유동성에 유의한 영향을 미치고 있는 것으로 나타났으며, 자본조달 순서이론(POT)과 정태적 상충관계이론은 일부지지 되는 결과를 얻었다. 그리고 토지건물투자는 경영성과에 유의한 영향을 미치고 있는 것으로 분석되었다.

• 기술혁신연구
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• 제12권3호
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• pp.97-109
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• 2004

According to "structure-conduct-performance" paradigm in IO, market structure (concentration) determines conduct (R&D investments), and conduct yields market performance (ratio of price to marginal cost). Previous empirical studies on Schumpeter Mark I, II assumed that the explanatory variable (market structure) and the disturbance are uncorrelated in the R&D equation. In this situation, Ordinary Least Squares (OLS) estimates of the structural parameters are inconsistent, because the endogeneous variables (R&D and market structure) can be determined simultaneously. So, in this study, full information (or system methods) estimation is used to test Schumpeter hypothesis since joint estimation can as well bring efficiency gains in the seemingly uncorrelated regressions (SUR) setting.