中国信托公司效率及全要素生产率的测度与影响因素研究

发布时间：2018-01-12 00:24

本文关键词：中国信托公司效率及全要素生产率的测度与影响因素研究　出处：《湖南大学》2012年博士论文　论文类型：学位论文

【摘要】：从1979年10月我国第一家信托投资公司的诞生,到1989年大约有1000家信托投资公司存在于全国各地；从1982年开始的国务院对信托业的数次整顿,到2007年以“一法两规”为基础的信托法律法规体系形成,我国信托业在不断摸索中前行。尽管信托业与银行、保险、证券等其他金融行业相比,发展不够成熟、社会认可度不高、市场影响力较小,但信托业在中国金融体系和经济建设中起着重要的金融中介和桥梁作用,是未来金融业不可忽视的潜在生力军。在此背景下,对我国信托公司效率和生产率进行客观评价,计算信托公司各年度效率值,测度全要素生产率的年度变化,找出效率和生产率的主要影响因素,就显得尤为重要。本文遵循从理论到实践的研究路径,理论上分析信托的内涵和功能,实践上回顾了中国信托业发展的五个阶段,显示出信托业制度变迁的鲜明特征。本文将信托公司效率和生产率具体界定为信托公司技术效率和全要素生产率,技术效率研究的是同一时期相同生产前沿面下不同信托公司的效率差距,是一种相对效率,效率值在0到1之间,是静态分析；全要素生产率则是不同时期不同信托公司生产率的变化,是通过指数来衡量的不同时期的变化值,是动态分析。技术效率和全要素生产率之间有着密切联系,通过Malmquist生产率指数的分解就可以把两者联系起来；研究中通过技术进步由相同生产前沿过渡到不同生产前沿,由静态的技术效率测度过渡到动态的全要素生产率测度,实现了由静态到动态的深入系统研究。全要素生产率的研究可以说是效率研究的更进一步,不仅考虑了不同年份信托公司的效率变化情况,还考虑到了信托行业技术进步情况,从这个层面来看,效率和全要素生产率具有一定的逻辑顺承关系。技术效率的测度。技术效率测度中投入和产出指标的选择最为关键,本文利用KS检验和T检验来确定模型中投入指标为劳动力、资本金和营业费用,产出指标为信托收入和信托公司净利润。一方面,利用DEA测度我国信托公司技术效率并进行分解,发现信托公司技术效率均值较低。另一方面,考虑到信托公司不良资产会影响技术效率,以信托公司不良资产作为“非期望”产出,加入到产出指标当中,利用基于方向性距离函数的DEA模型测度了考虑“非期望”产出的信托公司技术效率。比较两种测度方法,从相同年度信托公司效率排名中发现,考虑非期望产出后,由于不良资产的拖累,部分信托公司效率排名出现一定程度的倒退,比如中泰信托和山东国信。全要素生产率的测度。Malmquist生产率指数和Malmquist-Luenberger生产率指数是生产率研究中较为常用的两种模型。基于Malmquist生产率指数模型,我国信托公司2004～2010年的全要素生产率呈现出不断上升趋势,全要素生产率的增长主要来自于技术变化,技术效率变化的贡献较小。基于Malmquist-Luenberger生产率指数模型,考虑“非期望”产出情况下重新测度了信托公司全要素生产率,并对这两组测度结果进行比较分析,发现在2004-2007年间,Malmquist生产率指数变化均值要稍高于不良资产约束下的Malmquist-Luenberger生产率指数测度结果,说明不良资产会在一定程度上降低信托公司生产率增长水平。但是,2007-2010年间,两种全要素生产率变化曲线逐渐收窄并交织在一起,没有明显趋势,说明不良资产对信托业全要素生产率的影响是逐年下降的,尤其是银监会在颁布《信托公司净资本管理办法》以后,整个信托行业不良资产都有大幅下降。技术效率和全要素生产率的影响因素分析。通过对中国信托公司技术效率和全要素生产率的测度,发现不同信托公司之间存在着显著差异,需要利用回归模型确定导致各信托公司技术效率和全要素生产率波动的长期和实质性因素。一方面,运用面板Tobit模型和系统GMM模型对信托公司技术效率的影响因素进行实证分析,计量结果表明资产周转率、费用率和资本充足率与信托公司综合技术效率负相关,资产收益率和市场份额与信托公司综合技术效率正相关。另一方面,运用随机森林算法从宏观、行业和微观三方面入手,挑选影响全要素生产率的主要因素,并构建面板计量模型,发现资本市场、房地产市场、资产收益率和市场份额四个指标与全要素生产率成正相关关系,公司规模与全要素生产率成负相关关系,产权变量不显著。在上述分析的基础上,从加速形成信托公司核心竞争力、加强信托公司风险控制力、积极推进信托产品和业务创新、深化与金融同业战略合作四个方面提出了相关政策建议,以此提高信托公司效率,促进信托业生产率的不断,确保信托业的长期健康稳定发展。
[Abstract]:From the birth of October 1979 China's first trust and investment companies, in 1989 there were about 1000 trust and investment companies in the country; from the beginning of 1982 the State Council of the trust industry to rectify several times, the trust system of laws and regulations to "one law and two regulations" as the basis for the formation of 2007, China's trust industry constantly groping forward. Although the trust industry and the banking, insurance, securities and other financial industry compared, development is not mature enough, social recognition is not high, the smaller influence market, but the trust industry in China financial system and economic construction plays an important role of financial intermediary and financial industry, is a potential force can not be ignored in the future. Under the background, the objective evaluation of the Chinese trust company's efficiency and productivity, calculated trust each year efficiency value, annual variation of total factor productivity measurement, to find out the efficiency and productivity of the main It is particularly important to influence factors.
This paper follows the research path from theory to practice, analyze the connotation and function of trust theory, practice reviews the five stages of the development of China trust industry, showing the distinct characteristics of the trust system changes. This article will trust company efficiency and productivity is defined as the specific trust company technical efficiency and total factor productivity, technical efficiency research is the efficiency gap between different trust companies under the same period in the same production frontier, is a kind of relative efficiency, efficiency value between 0 to 1, is a static analysis; total factor productivity is the change of different trust productivity in different periods is measured by an index of different periods of change, is a dynamic analysis. There is close relationship between technical efficiency and total factor productivity, through the decomposition of the Malmquist productivity index can be linked; study by technological progress by phase With the transition to the production frontier of different production frontier, from static to transition to measure technical efficiency, total factor productivity measure dynamic, to realize the thorough research of dynamic static. By the research of TFP can be said to be the research efficiency further, not only taking into account the efficiency changes of trust in different years, also taking into account the technical progress of the trust industry, from this perspective, the efficiency and total factor productivity has a logical consequence relation.
The measure of technical efficiency. The key for input and output indicators to measure technical efficiency, selection, this paper uses KS test and T test to determine the model input index for labor, capital and operating expenses, net profit for the output indicators of income trust and trust companies. On the one hand, the technical efficiency of China Trust Company DEA measure and decomposed, found the mean technical efficiency of trust is low. On the other hand, taking into account the trust of non-performing assets will affect the technical efficiency, as a "non expected" output to the trust company of bad assets, added to the output index, using DEA model to measure the directional distance function based on the consideration of "trust company technical efficiency non expected" output. Two kinds of measuring methods, found from the same year efficiency ranking of trust company, considered undesirableoutputs, because of the bad assets on the part of the trust The company's efficiency ranking has fallen to a certain extent, such as the Sino Thai trust and the Shandong state letter.
Measure the total factor productivity of.Malmquist productivity index and Malmquist-Luenberger index are two kinds of popular model of productivity research. Malmquist productivity index based on the model of trust companies in China from 2004 to 2010 the total factor productivity shows a rising trend, the TFP growth mainly from technical change, technical efficiency change little contribution. Malmquist-Luenberger productivity index based on the model, considering the non expected output case to re measure the trust TFP, and the two group measure results were compared, found in the 2004-2007 years, mean change of Malmquist productivity index is slightly higher than the Malmquist-Luenberger productivity index to measure the non-performing assets under the constraints that non-performing assets will be reduce the level of productivity growth in the trust company to a certain extent. Is 2007-2010, two years, the total factor productivity curve gradually narrowed and intertwined, no obvious trend, illustrates the influence of non-performing assets of the trust industry total factor productivity is declining, especially in the CBRC promulgated "measures for the administration of net capital of trust companies" after the non-performing assets of the trust industry has dropped significantly.
Analysis of the factors affecting technical efficiency and total factor productivity. Through measure of technical efficiency and total factor productivity Chinese trust company, found that there are significant differences between different companies, using the regression model to determine the technical efficiency and lead to the trust company to long-term and substantial factor productivity fluctuations. On the one hand, the use of factors effect of panel Tobit model and GMM model system on the technical efficiency of the trust company to carry on the empirical analysis, the results show that the asset turnover ratio, expense ratio and capital adequacy ratio and trust company comprehensive technical efficiency are negatively related to asset returns and market share and trust is positively related to the comprehensive technical efficiency. On the other hand, using the random forest algorithm from the macro aspect, the three industry and the main factors affecting the selection of micro start, total factor productivity, and construct a panel econometric model, the capital The four indicators of market, real estate market, asset return and market share are positively correlated with total factor productivity. The size of the company is negatively correlated with total factor productivity, and the property rights variables are not significant.
On the basis of the above analysis, from accelerating the formation of core competitiveness of trust companies, trust companies to strengthen risk control, and actively promote trust products and business innovation, deepening and the four aspects of financial strategic cooperation puts forward relevant policy suggestions, in order to improve the efficiency of trust, promote the trust industry productivity, ensure the long-term healthy and stable development in the trust industry.

【学位授予单位】：湖南大学
【学位级别】：博士
【学位授予年份】：2012
【分类号】：F224;F832.49

【参考文献】