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규모 및 형태별 고급주거시설 가격결정요인의 이질성에 관한 연구
허정 ( Chung Hur ),조경준 ( Kyung June Jo ),김상봉 ( Sang Bong Kim ) 한국부동산분석학회 2012 不動産學硏究 Vol.18 No.4
Recently, need for the mixed-use residential complex which offers luxury housing service has been highly differentiated as demand for mixed-use housing increases in the housing market. Past literature shows a vast lines of quantitative and hedonic variables affecting housing price, however, factors that determine luxury housing price does not exist at all. The study hypothesizes difference on hedonic variables determining luxury housing price and analyzes each price determinant factor by housing size and form. When the data were analyzed with respect to housing size, exclusive residential characteristics were found to be statistically significant for large size. On the other hands, residential characteristics such as number of community were important for small size. When the data were analyzed with respect to housing style, housing expert opinion on security system evaluation was important for mixed-use housing style. For apartment/vila style, a few location characteristics and resident perception such as preference were crucial in determining luxury housing price. Finally, several implications are derived based on heterogeneity of the results.
김상봉 ( Sang Bong Kim ),조경준 ( Kyung June Jo ),( Phi Lip Ji ) 서강대학교 시장경제연구소(구 서강대학교 경제연구소) 2011 시장경제연구 Vol.40 No.1
본 연구는 최근 글로벌 금융위기 자료를 포함하는 2006년~2008년말의 재무변수 자료를 이용해 어떠한 재무변수가 기업부도확률에 영향을 미치는가를 분석하였다. 통합된 자료(pooled data)를 바탕으로 t-검정과 분산분석을 통하여 변수를 선정하였다. 또한 로짓모형을 이용하여 부도예측모형을 구축하였다. 모형의 부도예측력 판단은 AUROC(Area Under Receiver Operator Characteristic)를 사용하였다. 분석결과 정상기업과 부도기업 간에 일반적으로 유의미한 차이가 있다고 알려진 부채비율이 본 연구의 부도예측모형에 포함되지 않았고 자기자본비율, 당좌비율, 총자본경상이익율 등 9개의 재무변수가 부도기업과 정상기업간의 중요한 설명변수가 되었다. AUROC는 0.776으로 나타나 모형의 변별력이 높은 것으로 나타나고 있었다. This paper examines determinants of corporate bankruptcy for Korean firms for the period of 2006 to 2008 immediately after the outbreak of the global financial crisis. We use the t-test and the ANOVA analysis. In addition, we employ a LOGIT model using pooled data and AUROC (Area Under Receiver Operator Characteristic) to determine the predictive power of the model The findings are that the commonly used ratio in bankruptcy models is statistically insignificant and nine variables including capital adequacy ratio, current ratio, quick ratio and others appear to have explanatory power for the probability of bankruptcy.