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Credit Risk Modeling of Knowledge-based Companies Case Study: Knowledge-based Companies in Science and Technology Parks of Semnan Province
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Ghasem Parvarinezhad *   , Esmaiel Abounoori , ALI Dehghani |
| azad universitymahdishahr branch , ghparvarinezhad@gmail.com |
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Abstract: (790 Views) |
The main purpose of this study is to identify and investigate the factors affecting the credit risk of knowledge-based companies located in Science and Technology Parks of Semnan province and to present an appropriate model. The statistical population of the study includes all 68 knowledge-based companies of Semnan province that have been active in Science and Technology Parks of Semnan province during 2016, 2017 and 2018. For this purpose, the logit Regression Model with a qualitative dependent variable with zero value for non-deferred companies (risk-free) and one for companies with deferred (risky) with 6 explanatory variables including variables of concentration ratio, company history, type of documents, history of borrowing, history of returned checks and profitability were proposed and introduced. The source of data collection of dependent variable and explanatory variables, other than the concentration ratio, is the integrated inquiry system of Central Bank. Also, to calculate the concentration ratio variable, using the microdata of Iran's industrial sector in the years under study, the concentration ratio of 5 firms in terms of employment by two-digit industry codes (ISIC) was estimated by fitting the lognormal parametric model. Then, the structure of the industry was identified and the position of the studied companies in this structure was determined. Finally, with the help of Eviews software, all variables were entered into the model and fitted. According to the results, the variables of concentration ratio, type of collateral and profitability have a significant negative effect on credit risk; That is, by increasing each of these variables, assuming the other variables remain constant, the probability of facility deferral or credit risk decreases. Also, the variables of returned checks history, borrowing history and company history with a positive and significant effect, have the greatest impact on increasing credit risk. Out of 68 knowledge-based companies in Semnan province, 45 companies are in the structure of monopoly competition, 2 companies are in the structure of multilateral monopoly and 21 companies are in the structure of full competition.
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| Keywords: Credit Risk, Logit Regression, Concentration Ratio, Lognormal Pattern, Knowledge-based Companies. |
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Full-Text [PDF 1156 kb]
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Type of Study: Research |
Subject:
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