区域金融生态系统运行效率及协调发展研究
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摘要
20世纪80年代以来,世界各地已经发生了几十次的金融危机,无论是发达国家,还是发展中国家都曾受到金融危机的困扰。这些危机的频繁爆发,不仅让各国政府越来越关注金融安全问题,而且也让人们意识到金融安全和金融协调发展是同等重要的,两者之间有着紧密的联系。现代金融发展的新趋势也要求我们既要最大限度地推动金融高效运转,又要兼顾金融安全与金融效率,把金融当前的发展与远期的发展结合起来,实现金融发展与经济社会发展的和谐统一。研究金融生态问题,正是为了预防金融危机发生,提高金融资源配置效率,促进金融生态系统协调、高效地运转,确保国家经济安全,具有深远的理论意义和积极的现实意义。
本文以研究区域金融生态系统运行效率及协调发展这一中心问题为出发点,结合生产率理论、协调发展理论、金融发展理论、可持续发展理论、金融生态理论等理论知识,利用主成分方法和耦合协调度指标比较了我国不同省区、不同时期的金融生态竞争力和协调发展程度；运用非参数DEA方法与Malmquist指数测度和评价了中国29个省区金融生态系统静态和动态运行效率,并使用现代计量方法对影响金融生态系统运行效率差异的诸多因素进行了实证分析,从而为提高金融生态系统运行效率,促进金融生态系统协调、有序地发展提供科学依据。本文与现有金融生态文献最大的区别在于,不是简单介绍金融生态理论,而是围绕区域金融生态系统运行效率及协调发展深入分析,提出相应的政策建议。
首先,阐述了金融生态系统运行效率及协调发展的重要性和现实意义,理清了文章的研究思路,总结和回顾了金融生态系统的理论起源和相关概念。第2章从第三代金融发展理论和金融生态系统理论出发探讨了金融生态系统的理论基础、内涵和研究现状。根据实证研究方向的不同分成金融生态、金融发展与经济增长的关系研究和金融生态系统评价模型两部分,并从金融生态和金融发展的相互作用,金融生态与经济增长的相互作用,不同评价对象,不同评价方法四个方面进行了阐述和总结。
其次,针对区域金融生态主体发展现状进行了统计描述。第3章从金融机构和金融市场两个方面,对我国29个省区的金融生态主体在不同区域,不同时期进行了对比,总结出我国金融生态主体的现状、特点和发展趋势。结果表明：东部地带在大多数指标的绝对规模和增长速度上,都处于领先地位,全国的格局表现出“东—中—西”的形态；在29个省区中,北京、上海、广东三省区优势最明显,在各项指标中稳居前三位,而青海、宁夏、贵州却由于自身金融要素禀赋的不足,长期处于研究对象中的后三位。
再次,对区域金融生态环境和金融生态主体竞争力及两者的协调发展程度进行了评价。第4章构建了本文的区域金融生态系统评价指标体系,该体系包括43项指标,以此详细、精确、科学地考察了两个子系统在我国29个省区竞争力情况,结果表明：成熟型的金融生态环境和金融生态主体主要集中在东部地带,以广东、上海、北京竞争力最强；落后型的金融生态环境和金融生态主体多集中在西部地带,以青海、宁夏、贵州竞争力最差；潜力型的金融生态环境和成长型的金融生态主体则是中部地带各省区主要表现形式。第5章使用耦合协调度指标对金融生态系统协调发展程度进行实证分析,结果表明：1996-2008年间,中国29个省区内的金融生态系统协调情况不仅表现出明显的不平衡性,而且发展趋势也非常迥异,但整体协调程度较好,有8个省区得分是在0.6以上,属于中度协调发展,仅4个省区得分低于0.2,处于严重失调状态。
最后,从静态和动态两方面分别对区域金融生态系统运行效率进行了测度,并对其影响因素进行了定量分析。第6章运用DEA方法和Malmquist指数构建的区域金融生态系统运行效率模型测算了各省区金融生态系统运行效率,结果表明,虽然我国大部分省区的金融生态系统都存在相对无效率现状,但是在系统技术进步效率逐步提高的情况下,29个省区的金融生态系统动态效率提升幅度明显。第7章根据金融生态系统运行效率测度结果与我国29个省区1996-2008年的面板数据,比较了各因素的作用方向和影响程度,结果表明,金融发展水平、对外开放程度、人口受教育水平、经济发展水平等因素很好地解释了区域金融生态系统运行效率的差异性,但在短期和长期模型中,各影响因素的作用效果不尽相同。第8章在此基础上针对我国区域金融生态系统运行的现状及存在的问题,给出了相应的政策建议。
Since 1980s, dozens of financial crises have been recorded throughout the world. These crises not only take place in developed countries, but also in developing countries. Their high frequency of occurrences reminds governments about the impact of the financial risk, moreover, the importance of balancing coordinated development and their corresponding risk. Financial developments usually accompany with market risk. The trend of developing modern financial markets requires considering both operational efficiency and risk accordingly. It means connecting short-term and long-term financial developments as well as making harmonious developments between financial developments and social developments. The purpose of studying financial ecosystem is to prevent financial crisis, improve the allocation efficiency of financial resources, encourage the harmonious and efficient operations of financial ecosystem, and secure national economy. It is of profound theoretical and practical significance.
Starting from the study of China financial ecosystem's operational efficiency and coordinated development, while associating with productivity theory, coordinated development theory, financial development theory, sustainable development theory, financial ecology theory, and some other related theories, this paper adopts the principle component analysis and coupled coordination degree index to analyze the status of China financial ecosystem competitiveness and coordinated development in different provinces and time periods. This paper also use the nonparametric Data Envelopment Analysis (DEA) method and malmquist index to measure both static and dynamic operational efficiency of China financial ecosystems for 29 provinces. Modern econometric instruments are also utilized to find the factors which result in the differences in the performance of financial ecosystem. This kind of instruments provide basis for encouraging the orderly and coordinated developments of financial ecosystem. Different from existing literatures which simply introduce the financial ecosystem theory itself, this paper make contribution to provide in-depth analysis and policy advices for the operational efficiency and coordinated developments of regional financial ecosystem.
Firstly, the importance and practical significance of financial ecosystem's operational efficiency and coordinated developments are explained. Related theories and histories are also reviewed. Chapter 2 begins with the third generation of financial development theory and financial ecosystem theory. The theoretical basis, concepts and research status are presented. With different research scopes, the research subject could be classified as the relationship among financial ecology, financial development and economic development, as well as the evaluation model of financial ecosystem. The analytical results are concluded from 4 sectors, namely the interaction relationship between financial ecology and financial development, the interaction relationship between financial ecology and economic development, different judgment subjects and different judgment methods.
Secondly, the body of China financial ecosystem is statistically described. Chapter 3 analyzes body of China financial ecosystems for 29 provinces, from the prospectors of both financial institutions and financial markets while in different regions and time periods. Results suggest that the east takes the leading position in most indicators, including scale and developing speed. East, Middle and West are separated by these indicators and Beijing, Shanghai and Guangzhou have dominant advantages and take the top three places. On the other hand, Qinghai, Ningxia and Guizhou are the last three ones due to their weakness in factor endowments.
Moreover, the competitiveness and the degree of development of regional financial ecological environment and financial ecological body have been assessed. Chapter 4 builds the index system for regional financial ecosystem. The indicators include 43 sub-indices so that it could measure the features of competitiveness of 29 provinces in detailed, accurate and scientific manners. Result shows that most mature financial ecological environment and financial ecological body are gathered in eastern regions. Beijing, Shanghai and Guangzhou are the top tiers. On the other hand, inferior ones are usually located in western regions. Qinghai, Ningxia and Guizhou are at the bottom. Middle regions appear to have more potential in future growth. Chapter 5 adopts coupled coordination degree index and analyzes the degree of coordinated developments in financial ecosystem. We find that during the periods from 1996 to 2008, the coordination of 29 financial ecosystems are not only unbalanced but also keep in different developing paths. Yet the overall situation is in good condition,8 of them gain the points above 0.6 which means moderate coordinated development. Only 4 provinces have the points below 0.2 and in serious deviation from coordinated state.
Finally, the operational efficiency of dynamic and static regional financial ecosystem is measured and the influencing factors are quantized. Chapter 6 uses DEA method and malmquist index based models to estimate the operational efficiency of the regional financial ecosystem. Results suggest that even through most of the provinces do not have operational efficient financial ecosystem, but according with the acceleration in technical change of system, the situation is improving in all the regions and especially in recent years. Chapter 7 combines the above results with panel data set for 29 provinces from 1996 to 2008 and finds the strength and direction of impacts. Results indicate that factors as the level of financial developments, the degree of opening-up, the level of education and the status of economic developments could explain the difference in operational efficiency of regional financial ecosystem well. But the factors play a different role in short-term and long term models. On the base of the above findings, Chapter 8 analyzes the current circumstance and problems in China financial ecosystem's operational environment and coordinated development, as well as giving corresponding political suggestions.
本文以研究区域金融生态系统运行效率及协调发展这一中心问题为出发点,结合生产率理论、协调发展理论、金融发展理论、可持续发展理论、金融生态理论等理论知识,利用主成分方法和耦合协调度指标比较了我国不同省区、不同时期的金融生态竞争力和协调发展程度；运用非参数DEA方法与Malmquist指数测度和评价了中国29个省区金融生态系统静态和动态运行效率,并使用现代计量方法对影响金融生态系统运行效率差异的诸多因素进行了实证分析,从而为提高金融生态系统运行效率,促进金融生态系统协调、有序地发展提供科学依据。本文与现有金融生态文献最大的区别在于,不是简单介绍金融生态理论,而是围绕区域金融生态系统运行效率及协调发展深入分析,提出相应的政策建议。
首先,阐述了金融生态系统运行效率及协调发展的重要性和现实意义,理清了文章的研究思路,总结和回顾了金融生态系统的理论起源和相关概念。第2章从第三代金融发展理论和金融生态系统理论出发探讨了金融生态系统的理论基础、内涵和研究现状。根据实证研究方向的不同分成金融生态、金融发展与经济增长的关系研究和金融生态系统评价模型两部分,并从金融生态和金融发展的相互作用,金融生态与经济增长的相互作用,不同评价对象,不同评价方法四个方面进行了阐述和总结。
其次,针对区域金融生态主体发展现状进行了统计描述。第3章从金融机构和金融市场两个方面,对我国29个省区的金融生态主体在不同区域,不同时期进行了对比,总结出我国金融生态主体的现状、特点和发展趋势。结果表明：东部地带在大多数指标的绝对规模和增长速度上,都处于领先地位,全国的格局表现出“东—中—西”的形态；在29个省区中,北京、上海、广东三省区优势最明显,在各项指标中稳居前三位,而青海、宁夏、贵州却由于自身金融要素禀赋的不足,长期处于研究对象中的后三位。
再次,对区域金融生态环境和金融生态主体竞争力及两者的协调发展程度进行了评价。第4章构建了本文的区域金融生态系统评价指标体系,该体系包括43项指标,以此详细、精确、科学地考察了两个子系统在我国29个省区竞争力情况,结果表明：成熟型的金融生态环境和金融生态主体主要集中在东部地带,以广东、上海、北京竞争力最强；落后型的金融生态环境和金融生态主体多集中在西部地带,以青海、宁夏、贵州竞争力最差；潜力型的金融生态环境和成长型的金融生态主体则是中部地带各省区主要表现形式。第5章使用耦合协调度指标对金融生态系统协调发展程度进行实证分析,结果表明：1996-2008年间,中国29个省区内的金融生态系统协调情况不仅表现出明显的不平衡性,而且发展趋势也非常迥异,但整体协调程度较好,有8个省区得分是在0.6以上,属于中度协调发展,仅4个省区得分低于0.2,处于严重失调状态。
最后,从静态和动态两方面分别对区域金融生态系统运行效率进行了测度,并对其影响因素进行了定量分析。第6章运用DEA方法和Malmquist指数构建的区域金融生态系统运行效率模型测算了各省区金融生态系统运行效率,结果表明,虽然我国大部分省区的金融生态系统都存在相对无效率现状,但是在系统技术进步效率逐步提高的情况下,29个省区的金融生态系统动态效率提升幅度明显。第7章根据金融生态系统运行效率测度结果与我国29个省区1996-2008年的面板数据,比较了各因素的作用方向和影响程度,结果表明,金融发展水平、对外开放程度、人口受教育水平、经济发展水平等因素很好地解释了区域金融生态系统运行效率的差异性,但在短期和长期模型中,各影响因素的作用效果不尽相同。第8章在此基础上针对我国区域金融生态系统运行的现状及存在的问题,给出了相应的政策建议。
Since 1980s, dozens of financial crises have been recorded throughout the world. These crises not only take place in developed countries, but also in developing countries. Their high frequency of occurrences reminds governments about the impact of the financial risk, moreover, the importance of balancing coordinated development and their corresponding risk. Financial developments usually accompany with market risk. The trend of developing modern financial markets requires considering both operational efficiency and risk accordingly. It means connecting short-term and long-term financial developments as well as making harmonious developments between financial developments and social developments. The purpose of studying financial ecosystem is to prevent financial crisis, improve the allocation efficiency of financial resources, encourage the harmonious and efficient operations of financial ecosystem, and secure national economy. It is of profound theoretical and practical significance.
Starting from the study of China financial ecosystem's operational efficiency and coordinated development, while associating with productivity theory, coordinated development theory, financial development theory, sustainable development theory, financial ecology theory, and some other related theories, this paper adopts the principle component analysis and coupled coordination degree index to analyze the status of China financial ecosystem competitiveness and coordinated development in different provinces and time periods. This paper also use the nonparametric Data Envelopment Analysis (DEA) method and malmquist index to measure both static and dynamic operational efficiency of China financial ecosystems for 29 provinces. Modern econometric instruments are also utilized to find the factors which result in the differences in the performance of financial ecosystem. This kind of instruments provide basis for encouraging the orderly and coordinated developments of financial ecosystem. Different from existing literatures which simply introduce the financial ecosystem theory itself, this paper make contribution to provide in-depth analysis and policy advices for the operational efficiency and coordinated developments of regional financial ecosystem.
Firstly, the importance and practical significance of financial ecosystem's operational efficiency and coordinated developments are explained. Related theories and histories are also reviewed. Chapter 2 begins with the third generation of financial development theory and financial ecosystem theory. The theoretical basis, concepts and research status are presented. With different research scopes, the research subject could be classified as the relationship among financial ecology, financial development and economic development, as well as the evaluation model of financial ecosystem. The analytical results are concluded from 4 sectors, namely the interaction relationship between financial ecology and financial development, the interaction relationship between financial ecology and economic development, different judgment subjects and different judgment methods.
Secondly, the body of China financial ecosystem is statistically described. Chapter 3 analyzes body of China financial ecosystems for 29 provinces, from the prospectors of both financial institutions and financial markets while in different regions and time periods. Results suggest that the east takes the leading position in most indicators, including scale and developing speed. East, Middle and West are separated by these indicators and Beijing, Shanghai and Guangzhou have dominant advantages and take the top three places. On the other hand, Qinghai, Ningxia and Guizhou are the last three ones due to their weakness in factor endowments.
Moreover, the competitiveness and the degree of development of regional financial ecological environment and financial ecological body have been assessed. Chapter 4 builds the index system for regional financial ecosystem. The indicators include 43 sub-indices so that it could measure the features of competitiveness of 29 provinces in detailed, accurate and scientific manners. Result shows that most mature financial ecological environment and financial ecological body are gathered in eastern regions. Beijing, Shanghai and Guangzhou are the top tiers. On the other hand, inferior ones are usually located in western regions. Qinghai, Ningxia and Guizhou are at the bottom. Middle regions appear to have more potential in future growth. Chapter 5 adopts coupled coordination degree index and analyzes the degree of coordinated developments in financial ecosystem. We find that during the periods from 1996 to 2008, the coordination of 29 financial ecosystems are not only unbalanced but also keep in different developing paths. Yet the overall situation is in good condition,8 of them gain the points above 0.6 which means moderate coordinated development. Only 4 provinces have the points below 0.2 and in serious deviation from coordinated state.
Finally, the operational efficiency of dynamic and static regional financial ecosystem is measured and the influencing factors are quantized. Chapter 6 uses DEA method and malmquist index based models to estimate the operational efficiency of the regional financial ecosystem. Results suggest that even through most of the provinces do not have operational efficient financial ecosystem, but according with the acceleration in technical change of system, the situation is improving in all the regions and especially in recent years. Chapter 7 combines the above results with panel data set for 29 provinces from 1996 to 2008 and finds the strength and direction of impacts. Results indicate that factors as the level of financial developments, the degree of opening-up, the level of education and the status of economic developments could explain the difference in operational efficiency of regional financial ecosystem well. But the factors play a different role in short-term and long term models. On the base of the above findings, Chapter 8 analyzes the current circumstance and problems in China financial ecosystem's operational environment and coordinated development, as well as giving corresponding political suggestions.
引文
①距离函数的具体介绍可以参见李双杰(2010)所著的《效率与生产率度量方法及应用》一书。
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