引入企业社会责任的我国房地产上市公司财务风险研究

发布时间：2018-02-16 00:16

本文关键词： 房地产上市公司财务风险社会责任因子分析 Logistic模型　出处：《湖南科技大学》2013年硕士论文　论文类型：学位论文

【摘要】：随着国民经济的不断发展，市场竞争的日益激烈，我国房地产行业上市公司面临的风险也不断增多，财务风险首当其冲。因为企业一旦陷入财务危机就会使公司承受巨大的经济损失甚至影响到企业的生存与发展。此外对于公司的投资人、供应商、员工、银行，政府等众多利益相关者来说都存在至关重要的影响，这就对房地产企业履行企业应有的社会责任提出了新的挑战。基于此，本文通过引入企业社会责任构建财务指标体系框架来探讨我国房地产上市公司财务风险。如果想要高准确地预测企业的财务状况，，就需要考虑很多相关的因素。因为企业的日常运营管理与履行社会责任之间的联系越来越紧密，本文在传统的财务指标的基础上加入企业社会责任指标构建财务风险Logistic回归模型。以我国房地产行业上市公司2006~2012年间34家被特别处理（ST）的公司作为研究样本公司，采用同行业当年资产规模相近的标准，并且以1:1的配比方式选取了财务状况健康的34家房地产上市公司作为其配比样本，随后根据所选取的指标收集并整理了这34家ST公司被特别处理前一年及前两年的数据，然后通过SPSS18.0统计软件对样本数据进行了单样本T检验、因子分析以及Logistic多元回归分析法，构建了4个财务风险Logistic回归模型，并分别用来比较房地产上市公司财务危机发生前1年（T-1年）、前2年（T-2年）中仅加入传统的财务指标的模型与结合了房地产企业社会责任指标的模型的财务危机预测能力。研究结果表明，加入了房地产企业社会责任指标后所构建的财务风险Logistic回归模型比仅用传统财务指标构建的模型拥有更高的预测能力，而且不论是在财务危机发生的前一年（T-1）还是前两年（T-2），都比仅依靠传统的财务指标所构建的Logistic模型具有更强的预测能力。
[Abstract]:With the continuous development of the national economy and the increasingly fierce market competition, the risks faced by listed companies in the real estate industry in China are also increasing. Financial risks bear the brunt. Once an enterprise is caught in a financial crisis, it will make the company suffer enormous economic losses and even affect the survival and development of the enterprise. In addition, for the investors, suppliers, employees and banks of the company, Many stakeholders, such as the government, have a crucial impact, which poses a new challenge for real estate companies to fulfill their due social responsibility. This paper discusses the financial risk of listed real estate companies in China by introducing corporate social responsibility into the framework of financial index system. If you want to predict the financial situation of an enterprise with a high degree of accuracy, a number of relevant factors need to be taken into account. Based on the traditional financial indicators, this paper builds a Logistic regression model of financial risk by adding corporate social responsibility indicators. Taking 34 listed companies in the real estate industry in China from 2006 to 2012 as the research sample companies, Adopting the standard of similar asset size in the same industry in the same year, and selecting 34 listed real estate companies with a healthy financial position as their matching samples by using the 1: 1 formula. Then according to the selected indicators, the data of the 34 St companies were collected and sorted out in the year before and in the first two years, and then the single sample T test, factor analysis and Logistic multiple regression analysis were carried out through SPSS18.0 statistical software. Four Logistic regression models of financial risk are constructed. It is used to compare the financial crisis prediction ability of real estate listed companies one year before the occurrence of financial crisis, one year before the first two years, the first two years, T-2) only to add the traditional financial indicators model and real estate corporate social responsibility indicators combined with the model of financial crisis prediction ability. The results show that the Logistic regression model of financial risk constructed by adding the social responsibility index of real estate enterprises has higher predictive power than the model constructed with only traditional financial indicators. Both T-1 and T-2 are more powerful than the Logistic model based on traditional financial indicators.
【学位授予单位】：湖南科技大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F275;F299.233.4

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