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    산업별 신용위험 결정요인 분석: 거시변수와 산업간 부실 전이효과를 중심으로 = The determinants of Industry Credit Risk: focusing on Macro Variables & Spillover Effect

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    https://www.riss.kr/link?id=A102133301

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    Firm`s credit risk is governed in large part by the industrial environment, which in turn is affected by the macroeconomic conditions. This paper studies the nature of these links by applying the principal component analysis. In addition, it analyzes whether there exist spillover effects of failure rates across vertically integrated industries. The regression results show that variables such as unemployment, credit spread, and Euro are positively correlated with failure rates. On the other hand, variables such as the KOSPI, housing price, manufacturing and service output, and construction are negatively correlated with the failure rates of a majority of industries. The stronger korean won seems to increase the failure rate of the manufacturing sector, while it has the opposite effect for the service sector. Among variables that proxy the financial conditions, term structure of the interest rates and the credit spread produce statistically significant results. Using the full information maximum likelihood approach on 21 industries, this study also finds that there exist significant spillover effects of failure rates across 15 industries.
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    Firm`s credit risk is governed in large part by the industrial environment, which in turn is affected by the macroeconomic conditions. This paper studies the nature of these links by applying the principal component analysis. In addition, it analyzes ...

    Firm`s credit risk is governed in large part by the industrial environment, which in turn is affected by the macroeconomic conditions. This paper studies the nature of these links by applying the principal component analysis. In addition, it analyzes whether there exist spillover effects of failure rates across vertically integrated industries. The regression results show that variables such as unemployment, credit spread, and Euro are positively correlated with failure rates. On the other hand, variables such as the KOSPI, housing price, manufacturing and service output, and construction are negatively correlated with the failure rates of a majority of industries. The stronger korean won seems to increase the failure rate of the manufacturing sector, while it has the opposite effect for the service sector. Among variables that proxy the financial conditions, term structure of the interest rates and the credit spread produce statistically significant results. Using the full information maximum likelihood approach on 21 industries, this study also finds that there exist significant spillover effects of failure rates across 15 industries.

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