| Project/Area Number |
12630141
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Business administration
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| Research Institution | Kyoto Sangyo University |
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Principal Investigator |
YASUNAGA Toshihiro Kyoto Sangyo University, Faculty of Business Administration, Professor, 経営学部, 教授 (80230233)
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| Co-Investigator(Kenkyū-buntansha) |
INORI Michinori Kyoto Sangyo University, Faculty of Business Administration, Professor, 経営学部, 教授 (40340434)
SHIBA Takao Kyoto Sangyo University, Faculty of Business Administration, Professor, 経営学部, 教授 (00135641)
MIYASITA Hiroshi Kyoto Sangyo University, Faculty of Business Administration, Professor, 経営学部, 教授 (80166173)
HINATSU Kazuo Kyoto Sangyo University, Faculty of Business Administration, Professor, 経営情報学部, 教授 (20258180)
KAKINO Kingo Kyoto Sangyo University, Faculty of Economics, Professor, 経済学部, 教授 (50097680)
今口 忠政 慶応義塾大学, 商学部, 教授 (40102941)
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| Project Period (FY) |
2000 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥2,500,000 (Direct Cost: ¥2,500,000)
Fiscal Year 2002: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2001: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2000: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | going concern model / decline / turn around / ranking order of bonds / assets liabilities ratio / bankruptcy / 倒産予測 / 債権格付 / オーダード・プロバビリティモデル / マルタイ・ロジットモデル / 企業の存続可能性モデル / 債権格付情報 / 企業の衰退 / 企業の倒産 / オーダード・プロビット・モデル |
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| Research Abstract |
It is very important to predict a possibility of going concern of the firms. This study is to build a model which is able to forecast the bankruptcy and decline of the enterprises. We have researched proceeding studies on the going concern and turn-around of the firms.
Sometimes, we visited the ranking company and discussed about a possibility of building a forecasting model of going concern. We got R&I's "ranking data base on bond" of non-life insurance firms, and tried to forecast the ranking of them. To analyze what kind of the factor make up and down the ranking bonds, we made ranking data convert to ranking order. Both a probit model and a logit model were employed, and they yielded interesting results. We believe our model will be unique enough because such models have not been found.
Explaining ranking order change, we found significant factor, reserve per assets, total operating assets, balance of reserve, disposed income, assets-liability ratio, operating profit and loss.
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