基于现金流量的高校财务困境预警研究
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摘要
世纪之交的中国高等教育经过三年跨越式发展,就以世界上绝无仅有的速度和方式实现了由精英教育向大众化教育的过渡,举债兴教成为这一特殊历史阶段的产物,几乎所有高校都有银行贷款,不少学校债台高筑负重前行。举债虽然有效解决了扩招引发的基本建设资金需求,然而,随着还贷高峰的到来,一些高校资金捉襟见肘,贷款违约现象时有发生,现金短缺甚至断流成为部分学校的财务特征。不仅如此,世界各国的高等教育实践表明,高校资金供求矛盾将长期存在。高等教育资金运动的单向非补偿性,作为非营利组织对公共资金的依赖,高等教育作为准公共物品的公益性特点,市场运行机制对“象牙塔”的冲击等带来的对高校资金管理的挑战是永久性课题。顺畅的资金流是高校的生命线,资金收支平衡是高校可持续发展的前提,提前预测不可见的财务困境对高校生存和发展意义重大。
针对国内高校财务困境预警研究设计中忽视财务数据的时间序列特征,财务困境界定和判别没有突出高校资金管理特点和预警变量选择缺乏理论依据并缺乏大规模实证的明显不足,本研究旨在整合国内外财务困境预警研究成果,紧密结合高校资金管理特点,基于现金流量对高校财务困境进行等级判别,建立高校财务困境预警模型,为高校全面动态的风险管理提供可靠的依据和指导。
研究内容主要包括：
第一,高校财务困境形成机理分析,通过对困境形成过程的时间性追溯,总结困境形成的影响因素,为警兆的寻找提供客观依据。高等教育的发展受经济、政治和科学技术等方面的影响,我国高校财务困境的形成是内部管理缺陷与外部环境压力共同作用的结果。通过吉林大学财务困境发生始末的个案研究,剖析了财务风险产生、积聚直到危机爆发的全过程,进而勾勒我国高校集体性财务困境形成的阶段性特征和演进路径。
第二,基于现金流量产生的不确定性,对高校财务困境进行概念性界定,总结我国高校财务困境具有“一个根源二个层次三种循环四个症候”等特点。基于困境预警基本理论和文献综述,借鉴IASB/FASB的观点对高校财务报表进行重述,构建了以现金流量特征指标为核心的高校财务困境预警理论模型。
第三,提出现金流量表设计方案,以教育部直属76所高校为例完成了大样本编制,在此基础上,设计了充分体现高校财务风险的六类现金流指标,利用五年时序数据,采用Hill技术设定阈值,按照风险等级将高校划分为无风险级、低风险级、较高风险级和高风险级四类,并对不同类别的财务活动特征进行总结,即实现了对高校财务困境程度的多分类判别。
第四,设计财务困境预警指标体系,采用非配对全样本方式,运用logistic回归方法构建了提前1-3年预警模型,通过因子分析和逻辑回归技术找到了影响高校财务状况的主要因素和财务困境征兆指标,从而实现对高校财务困境的监测和预报。本文以教育部直属高校五年财务数据为样本,采用Logistic回归方法构建的预警模型在困境前一年(t-1年)总体预测准确率达到90.8%；困境前两年(t-2)的预测准确率达到86.8%,困境前三年(t-3)的预测准确率达到69.7%,以较高的精度实现了预警目标。
第五,根据警源分析和困境表征,分别从短期和长期、政府和高校层面提出政策建议,包括重塑政府角色,归位与调适高校的角色；高校要明确目标定位,开拓多元筹资渠道,强化风险管理,改进财务报告体系等。
本文研究得出以下主要结论：
第一,我国高校财务困境具有可测性,财务困境的形成是风险逐渐累积的动态过程,不同阶段体现出不同特征,不同时期的征兆指标存在差异。
第二,实证结果表明,高校财务状况不能简单地用某个指标来表达,也不能理解为举债融资是唯一导致高校出现财务困境的原因,预算管理、支出水平、财政依赖程度、教学投入、收入多样化等共同影响高校财务状况。可以通过监测11个显性指标预测未来财务困境,它们是：生均支出、垫支资金比、负债收入比、捐赠收入额、校办产业投资收益率、资产负债率、负债年增长率、校舍面积增长率、还本付息比率、基本教学支出比和固定资产增长率。其中,“基本教学支出比”、“还本付息比率”对困境具有提前三年预测的显著解释力。“负债收入比”在困境发生前两年里都以最高灵敏度显示困境即将发生,比通常采用的“资产负债率”更加有效,应该成为评价高校及类似非营利性组织财务状况的最主要指标。“校办产业投资收益”和“捐赠收入”虽各校间差异较大,但对缓解短期资金压力效果显著。
第三,现金流量是监控高校财务风险的重要工具,现金流量表有助于信息使用者评价高校资金管理水平,评估流动性、偿债能力和财务弹性,应该成为高校财务风险监控的重要依据,建议高校编制现金流量表。
第四,本文对财务困境的研究从运营活动、投资活动和筹资活动三个维度入手并实证检验了其有效性,这种整合财务报表体系的观点可供企业和非营利组织借鉴。
本文创新之处在于：首先,构建了高校财务困境预警理论模型,提出现金流量短缺作为判别高校财务困境的重要依据,并总结我国高校财务困境特点,开创性地对高校财务报表体系进行重述,揭示财务指标与财务困境的内在关联,为潜在财务风险的辨识提供理论依据。其次,以时序立体数据为基础,构建高校财务困境判别模型。基于现金流量表编制得到的多年时序数据,本文突破前人对财务困境二分类的尴尬界定,将高校财务状况划分为四种风险等级,为全面客观判断一所高校财务健康程度提供了科学依据。对高校时序立体数据的研究有利于提高重要财务趋势特征的信息含量,将高校财务数据连续性变化和累积效果得到较为客观的映射重现。财务困境判别研究为财务综合评价和财务风险防范提供了方法和借鉴,丰富了高校财务管理理论和实践。最后,构建提前一至三年财务困境预警模型,首次采用长达五年跨度的高校样本,突破1：1配对的局限采用全样本实证,发现并验证了具有显著预测能力的11个警兆指标,构建的远期辨识预警系统最早能够在高校发生现金流短缺的前三年提供准确率较高的信号,为控制危机发生换取宝贵冗余时间。高校财务困境的研究丰富了财务管理领域的现有研究成果,充实了非营利性组织财务理论的相关内容。
At the turn of the century, higher education in China has underwent great-leap-forward development in the past three years and has realized the change of elitist education to mass education in its remarkably unique speed and means. Debt financing for higher education has become outcome of this historical stage:almost all universities and colleges turn to banks for loan, and many of them move on with heavy burden. Although debt financing has effectively satisfied the capital demand of infrastructure for enrollment expansion, some colleges and universities' fund are in stretched circumstances and loan default has occurred from time to time with the repayment peak coming and shortage of funds has even become some colleges and universities'financial characteristic. Not only that, higher education practice in other countries has shown the contradiction between supply and demand of capital in universities will long exist. The one-way non-compensatory characteristic of higher education fund movement, reliance on public capital as non-profit organization, being quasi-public goods and market mechanism impact are all challenges to institution fund management, which is a long-lasting task for research. Smooth cash flow is lifeblood for institution, and balance of revenue and expenditure is the premise of institution sustainable development, therefore, foreseeing the invisible financial distress beforehand is significant for college and university survival and development.
In the existing early warning research of university financial distress, they tend to ignore time series character for financial data, not reflect university capital management characteristics in definition of financial distress and be short of theoretical basis as well as large-scale empirical research in early warning variables design. This research integrates the existing research together with the characteristics of higher education institution fund management and does grade judgment of university financial distress based on cash flow in order to establish university financial distress early warning model and to provide reliable basis and guidance for risk management in a dynamic and comprehensive way.
The research mainly includes:
Firstly, mechanism analysis of university financial distress forming process: through the time retrace of distress forming process, the paper analyzes the influence factors which provide objective basis for finding warning signs. High education development is subject to economy, politics, science and technology, therefore financial distress in our universities is attributed to internal management defects and external pressure. In the case research of financial distress in Jilin University, the paper analyzes the whole process of financial risk rising, accumulation till crisis outbreak, which outlines the periodic characteristics and evolution path of collective financial distress in colleges and universities in China.
Secondly, based on the uncertainty of cash flow, the paper defines the concept of university financial distress and concludes the "one origin, two gradations, three circulations and four symptoms" in our university distress. In view of basic theory and literature review of distress early warning, the paper reiterates university financial statements with reference to IASB/FASB and constructs university financial distress early warning model taking the characteristic index of cash flow as the core.
Thirdly, the paper conceives university cash flow statements and completes large-sample compilation based upon five-year financial data of76universities directly under the Ministry of Education for the first time. It also designs six cash flow indexes for university financial risk evaluation and utilizes the Hill estimation to divide university financial risks into four categories, i.e. risk-free, low-risk, risky and high-risk. Based on conclusion of financial characteristics for different risk levels, the paper categorizes university financial distress positions.
Fourthly, design of financial distress early warning index:employing non-matching full sample method, applying logistic regression to establish1-3years ahead early warning model, finding financial distress early warning index and main causes impacting university financial position through factor analysis and logistic regression, the paper has realized the supervision and forecast of university financial distress. The model samples selected are76universities directly under the Ministry of Education in2003-2007, and the early warning model's overall forecast accuracy is90.8%in one year before distress (year t-1) based on logistic regression; the forecast accuracy is86.8%in two years before distress (year t-2), and69.7%in three years before distress (year t-3), which realizes high accuracy in early warning model.
Fifthly, in the light of warning source and distress analysis, the paper offers policy advice from aspects of government and university as well as long-term and short-term, i.e. remodeling government role, and homing and adjusting university role; universities should clarify in its goal positioning, broaden multiple financing channels, strengthen risk management and improve financial report system etc.
The paper mainly has following conclusions:
Firstly, university financial distress in China is predictable. Financial distress comes into being during the dynamic process of risk accumulation, and different stage has its characteristics and symptom indexes.
Secondly, according to empirical study, university financial positions cannot be depicted with one single index; debt-financing is not the only reason that leads to university financial distress; budget management, expenditure level, fiscal dependence, teaching input scale and revenue diversity have impact on university financial positions, and altogether there are11dominant indexes for forecast of financial distress. The proportion of teaching spending in basic spending and the proportion of principal and interest amount in total revenue can obviously explain3-year early warning of distress. Debt to income ratio has the highest level of sensitivity in the prior two years before distress, and is more effective than asset-liability ratio in warning of distress, thus it is supposed to be a key financial index in universities and non-profit organizations. University-run industries'equity earnings and donation income is various among different universities, but they do have obvious effect in relieving shortage of capital.
Thirdly, cash flow is an important tool for monitoring university financial risk. Besides, statement of cash flows helps information users to evaluate university capital management, such as asset fluidity, solvency and financial flexibility. Therefore, cash flow is supposed to be an important basis for monitoring university financial distress and cash flow statement is strongly recommended for universities.
Fourthly, this research on financial distress is unfolded from three dimensions as operation, investment and financing. Besides, the paper has tested the validity empirically. This method for integrating financial statements can shed a light on research of corporations and non-profit organization.
The paper is innovative in:firstly, it establishes university financial distress early warning model, proposes that shortage in cash flow can be important basis for differentiating university financial distress, concludes the characteristics of university financial distress in China, reiterates university financial statements in a groundbreaking way and discloses the internal relation between financial index and financial distress, which provides theoretical basis for identification of potential financial risks. Secondly, it constructs university financial distress discriminate model based on time-series data which is deducted from the compiled cash flow statements. The paper breaks through the two-classification of financial distress and sorts out four risk levels for university financial positions, which provides scientific basis for evaluating university financial health in a comprehensive and objective way. The study of university time-series data can add more information in key financial trend and can reproduce the consecutive changes and accumulation effect of university financial data in an objective way. Financial distress discriminate research provides method and guidance for comprehensive financial evaluation and risk control, and it enriches university financial management theory and practice. Lastly, it establishes one-to-three year early warning of financial distress model, and initiates in utilizing five-year university data and full sample which breaks through limits of1:1match. The research finds and testifies the11dominant warning indexes for forecast, and the long-term early warning system constructed can provide accurate signals three years ahead of cash flow shortage in universities, which wins abundant time for crisis control. Higher education financial distress research enriches the existing theory of financial management as well as that of non-profit organization finance.
针对国内高校财务困境预警研究设计中忽视财务数据的时间序列特征,财务困境界定和判别没有突出高校资金管理特点和预警变量选择缺乏理论依据并缺乏大规模实证的明显不足,本研究旨在整合国内外财务困境预警研究成果,紧密结合高校资金管理特点,基于现金流量对高校财务困境进行等级判别,建立高校财务困境预警模型,为高校全面动态的风险管理提供可靠的依据和指导。
研究内容主要包括：
第一,高校财务困境形成机理分析,通过对困境形成过程的时间性追溯,总结困境形成的影响因素,为警兆的寻找提供客观依据。高等教育的发展受经济、政治和科学技术等方面的影响,我国高校财务困境的形成是内部管理缺陷与外部环境压力共同作用的结果。通过吉林大学财务困境发生始末的个案研究,剖析了财务风险产生、积聚直到危机爆发的全过程,进而勾勒我国高校集体性财务困境形成的阶段性特征和演进路径。
第二,基于现金流量产生的不确定性,对高校财务困境进行概念性界定,总结我国高校财务困境具有“一个根源二个层次三种循环四个症候”等特点。基于困境预警基本理论和文献综述,借鉴IASB/FASB的观点对高校财务报表进行重述,构建了以现金流量特征指标为核心的高校财务困境预警理论模型。
第三,提出现金流量表设计方案,以教育部直属76所高校为例完成了大样本编制,在此基础上,设计了充分体现高校财务风险的六类现金流指标,利用五年时序数据,采用Hill技术设定阈值,按照风险等级将高校划分为无风险级、低风险级、较高风险级和高风险级四类,并对不同类别的财务活动特征进行总结,即实现了对高校财务困境程度的多分类判别。
第四,设计财务困境预警指标体系,采用非配对全样本方式,运用logistic回归方法构建了提前1-3年预警模型,通过因子分析和逻辑回归技术找到了影响高校财务状况的主要因素和财务困境征兆指标,从而实现对高校财务困境的监测和预报。本文以教育部直属高校五年财务数据为样本,采用Logistic回归方法构建的预警模型在困境前一年(t-1年)总体预测准确率达到90.8%；困境前两年(t-2)的预测准确率达到86.8%,困境前三年(t-3)的预测准确率达到69.7%,以较高的精度实现了预警目标。
第五,根据警源分析和困境表征,分别从短期和长期、政府和高校层面提出政策建议,包括重塑政府角色,归位与调适高校的角色；高校要明确目标定位,开拓多元筹资渠道,强化风险管理,改进财务报告体系等。
本文研究得出以下主要结论：
第一,我国高校财务困境具有可测性,财务困境的形成是风险逐渐累积的动态过程,不同阶段体现出不同特征,不同时期的征兆指标存在差异。
第二,实证结果表明,高校财务状况不能简单地用某个指标来表达,也不能理解为举债融资是唯一导致高校出现财务困境的原因,预算管理、支出水平、财政依赖程度、教学投入、收入多样化等共同影响高校财务状况。可以通过监测11个显性指标预测未来财务困境,它们是：生均支出、垫支资金比、负债收入比、捐赠收入额、校办产业投资收益率、资产负债率、负债年增长率、校舍面积增长率、还本付息比率、基本教学支出比和固定资产增长率。其中,“基本教学支出比”、“还本付息比率”对困境具有提前三年预测的显著解释力。“负债收入比”在困境发生前两年里都以最高灵敏度显示困境即将发生,比通常采用的“资产负债率”更加有效,应该成为评价高校及类似非营利性组织财务状况的最主要指标。“校办产业投资收益”和“捐赠收入”虽各校间差异较大,但对缓解短期资金压力效果显著。
第三,现金流量是监控高校财务风险的重要工具,现金流量表有助于信息使用者评价高校资金管理水平,评估流动性、偿债能力和财务弹性,应该成为高校财务风险监控的重要依据,建议高校编制现金流量表。
第四,本文对财务困境的研究从运营活动、投资活动和筹资活动三个维度入手并实证检验了其有效性,这种整合财务报表体系的观点可供企业和非营利组织借鉴。
本文创新之处在于：首先,构建了高校财务困境预警理论模型,提出现金流量短缺作为判别高校财务困境的重要依据,并总结我国高校财务困境特点,开创性地对高校财务报表体系进行重述,揭示财务指标与财务困境的内在关联,为潜在财务风险的辨识提供理论依据。其次,以时序立体数据为基础,构建高校财务困境判别模型。基于现金流量表编制得到的多年时序数据,本文突破前人对财务困境二分类的尴尬界定,将高校财务状况划分为四种风险等级,为全面客观判断一所高校财务健康程度提供了科学依据。对高校时序立体数据的研究有利于提高重要财务趋势特征的信息含量,将高校财务数据连续性变化和累积效果得到较为客观的映射重现。财务困境判别研究为财务综合评价和财务风险防范提供了方法和借鉴,丰富了高校财务管理理论和实践。最后,构建提前一至三年财务困境预警模型,首次采用长达五年跨度的高校样本,突破1：1配对的局限采用全样本实证,发现并验证了具有显著预测能力的11个警兆指标,构建的远期辨识预警系统最早能够在高校发生现金流短缺的前三年提供准确率较高的信号,为控制危机发生换取宝贵冗余时间。高校财务困境的研究丰富了财务管理领域的现有研究成果,充实了非营利性组织财务理论的相关内容。
At the turn of the century, higher education in China has underwent great-leap-forward development in the past three years and has realized the change of elitist education to mass education in its remarkably unique speed and means. Debt financing for higher education has become outcome of this historical stage:almost all universities and colleges turn to banks for loan, and many of them move on with heavy burden. Although debt financing has effectively satisfied the capital demand of infrastructure for enrollment expansion, some colleges and universities' fund are in stretched circumstances and loan default has occurred from time to time with the repayment peak coming and shortage of funds has even become some colleges and universities'financial characteristic. Not only that, higher education practice in other countries has shown the contradiction between supply and demand of capital in universities will long exist. The one-way non-compensatory characteristic of higher education fund movement, reliance on public capital as non-profit organization, being quasi-public goods and market mechanism impact are all challenges to institution fund management, which is a long-lasting task for research. Smooth cash flow is lifeblood for institution, and balance of revenue and expenditure is the premise of institution sustainable development, therefore, foreseeing the invisible financial distress beforehand is significant for college and university survival and development.
In the existing early warning research of university financial distress, they tend to ignore time series character for financial data, not reflect university capital management characteristics in definition of financial distress and be short of theoretical basis as well as large-scale empirical research in early warning variables design. This research integrates the existing research together with the characteristics of higher education institution fund management and does grade judgment of university financial distress based on cash flow in order to establish university financial distress early warning model and to provide reliable basis and guidance for risk management in a dynamic and comprehensive way.
The research mainly includes:
Firstly, mechanism analysis of university financial distress forming process: through the time retrace of distress forming process, the paper analyzes the influence factors which provide objective basis for finding warning signs. High education development is subject to economy, politics, science and technology, therefore financial distress in our universities is attributed to internal management defects and external pressure. In the case research of financial distress in Jilin University, the paper analyzes the whole process of financial risk rising, accumulation till crisis outbreak, which outlines the periodic characteristics and evolution path of collective financial distress in colleges and universities in China.
Secondly, based on the uncertainty of cash flow, the paper defines the concept of university financial distress and concludes the "one origin, two gradations, three circulations and four symptoms" in our university distress. In view of basic theory and literature review of distress early warning, the paper reiterates university financial statements with reference to IASB/FASB and constructs university financial distress early warning model taking the characteristic index of cash flow as the core.
Thirdly, the paper conceives university cash flow statements and completes large-sample compilation based upon five-year financial data of76universities directly under the Ministry of Education for the first time. It also designs six cash flow indexes for university financial risk evaluation and utilizes the Hill estimation to divide university financial risks into four categories, i.e. risk-free, low-risk, risky and high-risk. Based on conclusion of financial characteristics for different risk levels, the paper categorizes university financial distress positions.
Fourthly, design of financial distress early warning index:employing non-matching full sample method, applying logistic regression to establish1-3years ahead early warning model, finding financial distress early warning index and main causes impacting university financial position through factor analysis and logistic regression, the paper has realized the supervision and forecast of university financial distress. The model samples selected are76universities directly under the Ministry of Education in2003-2007, and the early warning model's overall forecast accuracy is90.8%in one year before distress (year t-1) based on logistic regression; the forecast accuracy is86.8%in two years before distress (year t-2), and69.7%in three years before distress (year t-3), which realizes high accuracy in early warning model.
Fifthly, in the light of warning source and distress analysis, the paper offers policy advice from aspects of government and university as well as long-term and short-term, i.e. remodeling government role, and homing and adjusting university role; universities should clarify in its goal positioning, broaden multiple financing channels, strengthen risk management and improve financial report system etc.
The paper mainly has following conclusions:
Firstly, university financial distress in China is predictable. Financial distress comes into being during the dynamic process of risk accumulation, and different stage has its characteristics and symptom indexes.
Secondly, according to empirical study, university financial positions cannot be depicted with one single index; debt-financing is not the only reason that leads to university financial distress; budget management, expenditure level, fiscal dependence, teaching input scale and revenue diversity have impact on university financial positions, and altogether there are11dominant indexes for forecast of financial distress. The proportion of teaching spending in basic spending and the proportion of principal and interest amount in total revenue can obviously explain3-year early warning of distress. Debt to income ratio has the highest level of sensitivity in the prior two years before distress, and is more effective than asset-liability ratio in warning of distress, thus it is supposed to be a key financial index in universities and non-profit organizations. University-run industries'equity earnings and donation income is various among different universities, but they do have obvious effect in relieving shortage of capital.
Thirdly, cash flow is an important tool for monitoring university financial risk. Besides, statement of cash flows helps information users to evaluate university capital management, such as asset fluidity, solvency and financial flexibility. Therefore, cash flow is supposed to be an important basis for monitoring university financial distress and cash flow statement is strongly recommended for universities.
Fourthly, this research on financial distress is unfolded from three dimensions as operation, investment and financing. Besides, the paper has tested the validity empirically. This method for integrating financial statements can shed a light on research of corporations and non-profit organization.
The paper is innovative in:firstly, it establishes university financial distress early warning model, proposes that shortage in cash flow can be important basis for differentiating university financial distress, concludes the characteristics of university financial distress in China, reiterates university financial statements in a groundbreaking way and discloses the internal relation between financial index and financial distress, which provides theoretical basis for identification of potential financial risks. Secondly, it constructs university financial distress discriminate model based on time-series data which is deducted from the compiled cash flow statements. The paper breaks through the two-classification of financial distress and sorts out four risk levels for university financial positions, which provides scientific basis for evaluating university financial health in a comprehensive and objective way. The study of university time-series data can add more information in key financial trend and can reproduce the consecutive changes and accumulation effect of university financial data in an objective way. Financial distress discriminate research provides method and guidance for comprehensive financial evaluation and risk control, and it enriches university financial management theory and practice. Lastly, it establishes one-to-three year early warning of financial distress model, and initiates in utilizing five-year university data and full sample which breaks through limits of1:1match. The research finds and testifies the11dominant warning indexes for forecast, and the long-term early warning system constructed can provide accurate signals three years ahead of cash flow shortage in universities, which wins abundant time for crisis control. Higher education financial distress research enriches the existing theory of financial management as well as that of non-profit organization finance.
引文
1国内也有一些学者将高校列入非营利组织类,如熊筱燕等(2004)
2本部分内容已独立发表于《上海管理科学》2011年第一期,题目为：美国高校财务困境预警研究述评。
1[美]布鲁斯·约翰斯通著,陈运超、沈红译,高等教育财政与管理：世界改革现状报告,高等教育研究1999年第6期。
1 Gavin, M, Hausmann R.The roots of banking crises:the Macroeconomic context.Banking Crises in Latin America. Blatimore, Md.:Johns Hopkins Press,1996,P27-28
1我国高等教育毛入学率在上世纪80年代末90年代初期一直维持在平均3.5%的水平,邓小平南巡讲话后,1993年跃升到4.68%,此后以年均增长近1%速度于1998年提高到9.76%。引自：谢作栩.中国高等教育大众化发展道路的研究[M].福州：福建教育出版社,2001：252
1关于召开征集解决学校财务困难建议座谈会的通知.吉大校财字(2007]9号.2007.3.19
1别敦容,杨德广.中国高等教育改革与发展30年.上海教育出版社.2009.2.P2
1财政部,国家教育委员会关于印发《高等学校财务制度》的通知.财务与会计,1997.8
1吕长江,周现华.上市公司财务困境预测方法的比较研究.吉林大学社会科学学报,2005(11)：99
1 Sinkey J F (Jr). A multivariate statistical analysis of the characteristics of problem banks [J]. The Journal of Finance,1975, (30).
2审计署：全国1164所地方所属高校负债2634亿.济南日报,2011年07月04日
1 OECD.On the Edge:Securing a Sustainable Future for Higher Education [EB/OL]. http://www.oecd.org/dataoecd/20/24/38309943.pdf.2007-09-17.
2王正青.部分OECD国家高校财务危机与治理[J].教育发展研究,2007,(12A)：66-67
3赵善庆.破解高校还贷风险问题的建议[J].山西财政税务专科学校学报,2008,(2)：62
4国家中长期教育改革和发展规划纲要(2010—2020年)
5孙洁.企业财务危机预警的智能决策方法研究[D].哈尔滨：哈尔滨工业大学博士论文,2007
6林文修.演化式类神经网络为基底的企业危机诊断模型：智慧资本之应用[D],台湾：“国立中央大学”博士论文,2000
7吴世农,卢贤义.我国上市公司财务困境的预测模型研究[J].经济研究.2001.(6)：46
8 P.J.Fitzpartrick. A Comparison of Ratios of Successful Industrial Enterprises with Those of Failed Finns[J]. Certified Public Accountant.1932,10:598-605,11:656-662, 12:727-731
9吴世农,黄世忠.企业破产的分析定性指标和预测模型[J].中国经济问题.1986,(6)：15-22
10 W.Beaver. Financial Ratios as Predictors of Failure[J].Journal of Accounting Research.1966,4(Supplement):71-111
11陈肇荣.运用财务比率预测企业危机之实证研究[D].台湾：“国立”政治大学博士论文,1983
12 Lau, A. Hing-Ling, A Five-State Financial Distress Prediction Model[J], Journal of Accounting Research, Spring 1987:127-38.
13 E.I.Altman.Financial Ratios Discriminant Analysis and the Prediction of Corporate Bankruptcy [J] Journal of Finance.1968,23(4):589-609.
14 E.B.Deakin.A Discriminant Analysis of Prediction of Business Failure[J]. Journal of Accounting Research.1972,(spring):167-169
15 Blum, M., Failing Company Discriminant Analysis[J], Journal of Accounting Research, Spring 1974,1-25.
16 Foster, G., Financial Statement Analysis, Englewood Cliffs[M]. New Jersey: Prentice-Hall Inc.,1978.
17谷祺,刘淑莲.财务危机企业投资行为分析与对策[J].会计研究.1999.(10)：28-31
18吕长江,徐丽莉,周琳.上市公司财务困境与财务破产的比较分析[J].经济研究.2004,(8)：64-73
19 J.A.Ohlson.Financial Ratios and Probabilistic Prediction of Bankruptcy[J]. Journal of Accounting Research.1980,18:109-131
20 Rose,P.and GA.Giroux.Predicting Corporate Bankruptcy:An Analytical and Empirical Evaluation[J],Review of Business and Economic Research, Spring 1984:1-12
21周首华,杨济华,王平.论财务危机的预警分析——F分数模式[J].会计研究.1996,8：8-11
22张鸣,程涛.上市公司财务预警实证研究的动态视角,财经研究[J],2005(1)
23章之旺.现金流量信息含量与财务困境预测[J],现代财经,2004(8)：26
24韩东平,田艳丽,王悦鑫.基于现金流测量标准的财务预警实证研究[J],财会通讯(学术版),2006(12)：
25李洪伟.基于IFAHP的中国上市公司财务危机预警研究[D].哈尔滨：哈尔滨工业大学硕士论文,2008
26刘庆华.基于现金流量的企业财务预警系统研究[D].成都：西南财经大学博士论文,2006
27鲁顺.基于现金流量的上市公司财务危机预测研究[D].武汉：武汉理工大学硕士论文,2008
28李维安.公司治理评价与指数研究[M].高等教育出版社,2005：44-55
29姜秀华,孙铮.治理弱化与财务危机：一个预测模型[J],南开管理评论,2001(5)：19-25
30杨兵,柯佑鹏.非财务指标影响上市公司财务危机预测能力的实证研究[J].财 会通讯(学术版),2005,(11)
31杨轶.财务预警研究中非财务指标选择综述与评价[J],财会通讯(综合)2008(6)：100-101
32 William H. Beaver; Maureen F. McNichols; Jung-Wu Rhie. Have Financial Statements Become Less Informative?Evidence from the Ability of Financial Ratios to Predict Bankruptcy. www.ssrn.com, Working Paper.2006
33 Ohlson, J.S.. Financial Ratios and the Probabilistic Prediction of Bankruptcy [J]. Journal of Accounting Research 1980, (19), (Spring):109-131.
34 Hadley,J.,R.Mullner,and J.Feder.The Financially Distressed Hospital[J].New England Journal of Medicine 307(11 November 1982):1283-87
35 Kwon,I.,S.R.Safranski,and W.R.Walker.Causes of Financial Difficulty in Catholic Hospitals[J]. Health Care Management Review 13,no 1.Winter 1988:29-37
36 Martin, J, and Parson, R. Financially Distressed Hospitals:Associated Factors. Policy Brief 40, American Hospital Association, Office of Public Policy Analysis, 25,November,1981
37 Kelly, J, and O'Brien, J. Characteristics of Financially Distressed Hospitals. HCHSR Hospital Cost and Utilization Research Prect:Research Note 3, Rockville,MD:Public Health Service, June,1983
38 John M. Trussel, Patricia A. Patrick.An Empirical Analysis of Financial Distress in Pennsylvania Ho spitals[J] Journal of Health Care Finance.2009,36(1):31-60
39 Tuckman, H., and Chang, C. A Methodology for Measuring the Financial Vulnerability of Charitable Nonprofit Organizations [J]. Nonprofit and Voluntary Sector Quarterly,1991,65,445-460.
40 Janet S.Greenlee, John M.Trussel.Predicting the Financial Vulnerability of Charitable Organizations[J].Nonprofit Managemen& Leadership, Vol,11, no.2. winter2000
41 John Trussel, Janet S. Greenlee, and Tbomas Brady.Predictive Financial Vulnerability in Charitable Organizations [J].The CPA Journal. June 2002
42 Chabotar,K.J.Financial ratio annlysis comes to nonprofits[J].The Journal of Higher Education,1989,60(2),188-209
43 McCue, M. The Use of Cash Flow to Analyze Financial Distress in California Hospitals[J], Hospital & Health Services Administration,1991,36 (2):223-241.
44 Xiaohu Wang, Lynda Dennis. Measuring Financial Condition:A Study of U.S. States[J].Public Budgeting & Finance, Vol.27, No.2:1-21, Summer 2007
45 Cheit,E.F.,& Ford,F.The new depression in higher education:A study of financial conditions at 41 colleges and universities[M].1971,New York:McGraw-Hill.
46 Gilmartin,K.J. Development of financial indicators of the viability of higher education institutions[R].1984,Palo Alto,CA:American Institutes for Research in Behavioral Services.
47 Peters,M.F.A multivariate analysis of predictive measures of fiscal distress among selected,private,four-year colleges and universities [D].1994,UMI No.9516385:56
48 Lee,R.A.Financial and staffing ratio analysis:predicting fiscal distress in school districts. Journal of Higher Education [J],1983(58):181-204
49 Sharp,William L.,Lair,Wiliferd R.An early warning system for schools:an examination of Illinois' financial watch list.Conference paper of the American Education Finance Association,March 17-20,1994
50 Marshall, Mary Jo.The relationship between budgeted and actual revenues and expenses as predictors of financial distress in Illinois elementary-school districts[D].Northern Illinois University.1998
51 Brubaker, P.Financial health indicators for institutions of higher learning:A literature review and synthesis[R].1979, SAGE Tech.Rep.No.13
52 Lupton,A.H.Auginblick,J.,&Heyison,J. The state of higher education. Change[J], 1976,8(8),21-36
53 Collier,D.J.&Patrick,C.A multivariate approach to the analysis of institutional financial condition[M],1978.Boulder,Co:National Cente for Higher Education Management Systems.
54 Gomberg,I.L.,&Atelsek,F.J.Trends in financial indicators of colleges and universities.Washington,DC:American Council on Education.1981
55 Bolda,P.J.M.&Bruce A.A measurement of financial viability among private colleges[R]. Motreal,Canda.1983,Educational Research Association Rep No.104
56 Curry,C.T.A determination of the perceived utility of financial indicators within the state system of higher education of Pennsylvania. [D],1998,UMI No.9837573:23
57 Schipper,K.An analysis of the financial condition of private college[D].1977, Chicago,IL:University of Chicago.
58 Lomax,V.M.An examination of the determinants of the financial viability of small,private,four-year colleges and universities [D].1984,UMI No.8512231:46
59 Roden,J.K.& Moore,W.Uaing financial ratios analysis to describe the relative fiscal health of selected publicly funded institutions of higher education in New York state[D].UMI No.9120720:52
60 Talboys,W.M..Using financial rations in the analysis of four private universities in the southwest United States:A case study[D].1995,UMI No.9615638:57
61 Richard A. Lee. Examining Financial and Non-Financial Indicators for Predicting Private Higher Education Viability [D], Northcentral University,2008
62王德春,张树庆.高校财务风险与防范对策[J],山东农业大学学报(社科版),2003年第2期：8-11
63胡信生,拓东玲,王希文.高校财务风险的类型及其防范[J],教育财会研究,2004,6：27-30
64杨周复,施建军.大学财务综合评价研究[M].北京：中国人民大学出版社,2002：196
65许道银.试论高校财务危机预警系统[J].徐州师范大学学报(自然科学版).2003年第21卷第4期：19-22
66林莉.中国高校贷款问题研究[D],厦门大学博士学位论文,2006
67刘跃,王玲.西部高校财务预警与财务风险防范研究[J].财会通讯,2006(2)
68张克友.高校财务风险预警系统研究[J],企业经济,2007.6：187-189
69雷振华.高校财务风险预警指标体系的构建研究[J].财会通讯(学术版),2007(2)：118
70米新英,刘泽琴.高校财务预警系统的研究.北华航天工业学院学报[J],2008(10)：41
71雷中英,严守德.基于G1法的高校财务风险预警指标体系权重确定[J].价值工程,2010(1)：38
72齐向丽.高等院校财务风险评估与防范[D],天津大学硕士论文,2003
73郑鸣,黄光晓.我国高校财务困境预测研究[J],经济纵横,2008.5：79-81
74窦伟.修正的z值风险模型—高校财务风险预警指标体系探析[J],河南财政税务高等专科学校学报,2007.2：32-34
75周雪,顾晓敏.动态现金流量模型在高校财务风险预警中的运用[J],财会月刊(综合)2009.1：85-87
76林立妍.陕西省属高校财务风险综合评价与预警研究[D].西安理工大学硕士论文.2008年
77王开田.公司财务危机预警系统研究[J].河北经贸大学学报.2001(3)：30
78张亚杰.我国制造业上市公司财务状况评价及预测研究[D1.中国矿业大学博士论文.2010年
79李秉成.企业财务困境研究一上市公司财务困境实证分析[M].中国财政经济出版社,2008：56-80
80庞皓,黎实,贾彦东.金融安全的预警机制与风险控制研究[M].科学出版社,2009：61
81别敦容,杨德广.中国高等教育改革与发展30年[M].上海教育出版社.2009：2
82李武好.中国经济发展中财政政策与货币政策[M].经济科学出版社.2002：63
83何忠洲.负债30亿的吉林大学[N].中国新闻周刊,2007.4.9
84王娜,孙雷.教育部：政府要加大投资力度学校要着重化解风险[N].21世纪经济报道,2007.3.28
85蔡俊兰.中国高等教育规模与经济发展相关的实证分析[J].高教探索,2008(3)：49-52
86李亚勃.我国普通高等教育招生规模研究——基于中美比较的视角[J].教育发展研究,2006(1)
87刘宇.我国高校财务困境成因与预警研究[D].南开大学企业管理博士论文,2009
88鲍威.扩招后中国高等院校贷款融资行为的实证研究[J].北大教育经济研究,2007年6月第五卷第2期：12
89鲍威.扩招后中国高等院校贷款融资行为与财务运作特征[C].2009年中国教育经济学学术年会论文集,2009.12
90叶平.关于进行高等教育规模增长速度预警研究的探讨[J].高等教育研究, 1996(6)：47
91李岚清.李岚清教育访谈录[M].北京：人民教育出版社,2003：119
92谢作栩.中国高等教育大众化发展道路的研究[M].福州：福建教育出版社,2001：252
93王胜今.我国高等教育大众化十年盘点与省思[J].高等教育研究.2009,(4)：56
94张友堂.财务预警系统管理研究[M].北京：中国人民大学出版社,2004.
95马志远.中国财政性教育经费占GDP 4%的可行性分析—国际比较的视角[J].教育研究,2011,(3)：24
96孔喜梅.高等教育经费短缺现状及解决途径[J].郑州大学学报(哲学社会科学版).2006(7)：184
97王良驹,试论高校理财环境的阶段性特征与应对[J],财会研究.2009,(15)
98徐明稚.对我国高等教育投入的思考与建议[J].教育发展研究.2009,(7)
99曾月明,朱杏龙,葛文雷.高校财务风险的涵义及形成机理探究[J].南京财经大学学报,2009.3：59-60
100华清君.当前高等学校财务危机的理性思考[J].黑龙江高教研究,2004.10：86-87
101马新平.我国教育经费来源结构分析与国际比较[J].商业时代,2010,(27)：110
102邬大光.高校贷款的理性思考和解决方略[J].教育研究,2007(4)：18-25
103王远伟.中国高等教育财政经费来源的变迁[J].清华大学教育研究,2006(5)
104教育部财务司.高校经济活动案例选编[M].北京：高等教育出版社,2001
105冯晓华.浅谈高校资金管理存在的问题和对策[J].会计之友,2008.9
106林毅夫,李志赟.政策性负担、道德风险与预算软约束[J].经济研究,2004,(2)
107庞晓波,黄卫挺.高校预算软约束的制度成因及其治理[J].中国高教研究,2009(1)：46-49
108李秉成.企业财务困境研究-上市公司财务困境实证分析[M].中国财政经济出版社,2004.8：60
109姜晓璐,张丹,徐明稚.基于共生理论下高校财务风险的演变机理研究[J].中国高教研究.2009.11：30
110魏海苓,孙远雷.论现代产权制度下的我国公立高校产权改革[J].现代大学教 育.2005,(4)：54-57
111 Segal Ilya R.Monopoly, Soft Budget Constraint[J].Rand Journal of Economics, 1998,(3):11
112林毅夫,李志赞.政策性负担,道德风险与预算软约束[J].经济研究,2004,(2)
113曹淑江.高等学校的软预算约束与财务自主权[J].高等教育研究,2005,(10)
114刘淑华,王福友.预算软约束：高校群体性负债的深度分析[J].教育发展研究,2010.5：12-16
115韦英妹,罗艳洪.高校贷款及其风险的控制与化解[J].中国农业会计,2008.11：12-14
116刘淑华,王福友.预算软约束：高校群体性负债的深度分析[J].教育发展研究2010,(5)：12-16
117阿什比著,滕大春,滕大生泽.科技发达时代的大学教育[M].1983：62
118董云川.论大学行政权力的泛化[J].高等教育研究.2000,(2)：60
119赵建军.我国高等学校财务治理问题研究(教育部财务司)[J].教育财会研究.2008(5)：9
120张凡.把握高校会计改革方向提升专员办服务品牌-财政部驻湖北专员办在鄂部属高校资产财务管理工作座谈会综述[J].财政监督,2010(14)：25
121孟昭德.论新时期大学财务工作的主要任务[J].事业会计,2005,(2)：31
122肯尼斯·汉克尔,尤西·李凡特著,张凯等译.现金流量与证券分析[M].北京：华夏出版社2001,第2版
123 Copland. Valuation:Measuring and managing the value of companies [M].John Wily&sons.1990
124汤姆·科普兰,蒂姆·科勒.价值评估[M],中国大百科全书出版社,1998
125汤谷良,朱蕾.自由现金流量与财务运行体系[J].会计研究,2002
126 Argenti,John.Corporate Collapse:The Causes and Symptoms[M],McGraw Hill,NY,1976.
127 Subhash Sharma & Vijay Wahajan. Early Warning Indicators of Business Failure [J], Journal of Marketing,vol.44(Fall 1980).80-89
128 Ho,Thomas S,and Anthony Saunders.The Determinants of Bank Interest Margins:Theory and Empirical Evidence[J].Journal of Financial and Quantitative Analysis,1981,16(4):581-600.
129 Scott, J. The Probability of Bankruptcy:A Comparision of Empirical Predictions and Theoretical Models[J]. Journal od Banking and Finance,1981, (5):317-344.
130中国注册会计师协会.会计[M].中国财政经济出版社,2011：247-255
131财政部.国家教育委员会关于印发《高等学校财务制度》的通知.财务与会计,1997.8
132 Berg A,Borensztein E.et al. Anticipating balance of payments crises-the role of early warning systems.Occasional Paper,1999
133唐旭,张伟.论建立中国金融危机预警系统[J].经济学动态,2002(6)
134朱莲美IASB/FASB"关于财务报表列报的初步观点”讨论稿之评价[J].财会月刊,2010(7)下：16
135斯蒂芬.H.佩因曼著,刘力,陆正飞译.财务报表分析与证券定价[M].中国财政经济出版社,2005：306-320
136丁绍凡,王丽洁.高等学校现金流量表编制探析[J],教育财会研究.2005(4)
137徐明稚.高校编制现金流量表初探[J].财务与会计,2009(21)：28-30
138安红,廖文萍.高校现金流量表的编制与运用[J].会计之友,2010(22)：65-66
139宋加山,李勇.极值理论中阈值选取的Hill估计方法改进[J].中国科学技术大学学报,2008(9)：1104-1106
140 Reiss R, Thomas M. Statistical Analysis of Extreme Values:From Insurance, Finance, Hydrology and Other Fields[M]. Basel:Birkhauser Verlag,2001.
141杜强,贾丽艳SPSS统计分析从入门到精通[M].人民邮电出版社,2009：150-189
142詹建平.上市公司多分类财务预测模型及其应用研究[D].首都经济贸易大学硕士论文,2008
143 Miller,B.E.Mastering cause and effect ratio analysis[M].Business Credit, 1993:24-27
144李珊.基于财务状况多分类的财务困境预警模型研究[D].浙江大学,2009
145姜秀华,任强,孙铮.上市公司财务危机预警模型研究[J].预测,2002(3)：56-61
146黄德华.财务数据对我国上市公司协议收购事件的解释[D].上海财经大学博士论文,2001：33-45
147张万朋.美国高校债务问题的控制与防范[J],教育发展研究,2009.7：20
148陈晓宇,冯倩倩.我国高校的捐赠收入及捐赠人行为研究[J].北京大学教育评论.2011(1)：80-90
149 Craig R.Hansel.The Lowa school financial solverncy ratio as a predictive measure of financial health for Lowa K-12 public school[D].Northcentral University,2005
150席酉民,李怀祖,郭菊娥.我国大学治理面临的问题及改善思路[J].西安交通大学学报(社会科学版).2005(3)：78-83
151徐明稚.大学管理和大学发展[J].中国高等教育,2010(6)：4-7
152应益华.高校推行注册会计师审计制度的探讨[J].财会研究,2006(6)：40
2本部分内容已独立发表于《上海管理科学》2011年第一期,题目为：美国高校财务困境预警研究述评。
1[美]布鲁斯·约翰斯通著,陈运超、沈红译,高等教育财政与管理：世界改革现状报告,高等教育研究1999年第6期。
1 Gavin, M, Hausmann R.The roots of banking crises:the Macroeconomic context.Banking Crises in Latin America. Blatimore, Md.:Johns Hopkins Press,1996,P27-28
1我国高等教育毛入学率在上世纪80年代末90年代初期一直维持在平均3.5%的水平,邓小平南巡讲话后,1993年跃升到4.68%,此后以年均增长近1%速度于1998年提高到9.76%。引自：谢作栩.中国高等教育大众化发展道路的研究[M].福州：福建教育出版社,2001：252
1关于召开征集解决学校财务困难建议座谈会的通知.吉大校财字(2007]9号.2007.3.19
1别敦容,杨德广.中国高等教育改革与发展30年.上海教育出版社.2009.2.P2
1财政部,国家教育委员会关于印发《高等学校财务制度》的通知.财务与会计,1997.8
1吕长江,周现华.上市公司财务困境预测方法的比较研究.吉林大学社会科学学报,2005(11)：99
1 Sinkey J F (Jr). A multivariate statistical analysis of the characteristics of problem banks [J]. The Journal of Finance,1975, (30).
2审计署：全国1164所地方所属高校负债2634亿.济南日报,2011年07月04日
1 OECD.On the Edge:Securing a Sustainable Future for Higher Education [EB/OL]. http://www.oecd.org/dataoecd/20/24/38309943.pdf.2007-09-17.
2王正青.部分OECD国家高校财务危机与治理[J].教育发展研究,2007,(12A)：66-67
3赵善庆.破解高校还贷风险问题的建议[J].山西财政税务专科学校学报,2008,(2)：62
4国家中长期教育改革和发展规划纲要(2010—2020年)
5孙洁.企业财务危机预警的智能决策方法研究[D].哈尔滨：哈尔滨工业大学博士论文,2007
6林文修.演化式类神经网络为基底的企业危机诊断模型：智慧资本之应用[D],台湾：“国立中央大学”博士论文,2000
7吴世农,卢贤义.我国上市公司财务困境的预测模型研究[J].经济研究.2001.(6)：46
8 P.J.Fitzpartrick. A Comparison of Ratios of Successful Industrial Enterprises with Those of Failed Finns[J]. Certified Public Accountant.1932,10:598-605,11:656-662, 12:727-731
9吴世农,黄世忠.企业破产的分析定性指标和预测模型[J].中国经济问题.1986,(6)：15-22
10 W.Beaver. Financial Ratios as Predictors of Failure[J].Journal of Accounting Research.1966,4(Supplement):71-111
11陈肇荣.运用财务比率预测企业危机之实证研究[D].台湾：“国立”政治大学博士论文,1983
12 Lau, A. Hing-Ling, A Five-State Financial Distress Prediction Model[J], Journal of Accounting Research, Spring 1987:127-38.
13 E.I.Altman.Financial Ratios Discriminant Analysis and the Prediction of Corporate Bankruptcy [J] Journal of Finance.1968,23(4):589-609.
14 E.B.Deakin.A Discriminant Analysis of Prediction of Business Failure[J]. Journal of Accounting Research.1972,(spring):167-169
15 Blum, M., Failing Company Discriminant Analysis[J], Journal of Accounting Research, Spring 1974,1-25.
16 Foster, G., Financial Statement Analysis, Englewood Cliffs[M]. New Jersey: Prentice-Hall Inc.,1978.
17谷祺,刘淑莲.财务危机企业投资行为分析与对策[J].会计研究.1999.(10)：28-31
18吕长江,徐丽莉,周琳.上市公司财务困境与财务破产的比较分析[J].经济研究.2004,(8)：64-73
19 J.A.Ohlson.Financial Ratios and Probabilistic Prediction of Bankruptcy[J]. Journal of Accounting Research.1980,18:109-131
20 Rose,P.and GA.Giroux.Predicting Corporate Bankruptcy:An Analytical and Empirical Evaluation[J],Review of Business and Economic Research, Spring 1984:1-12
21周首华,杨济华,王平.论财务危机的预警分析——F分数模式[J].会计研究.1996,8：8-11
22张鸣,程涛.上市公司财务预警实证研究的动态视角,财经研究[J],2005(1)
23章之旺.现金流量信息含量与财务困境预测[J],现代财经,2004(8)：26
24韩东平,田艳丽,王悦鑫.基于现金流测量标准的财务预警实证研究[J],财会通讯(学术版),2006(12)：
25李洪伟.基于IFAHP的中国上市公司财务危机预警研究[D].哈尔滨：哈尔滨工业大学硕士论文,2008
26刘庆华.基于现金流量的企业财务预警系统研究[D].成都：西南财经大学博士论文,2006
27鲁顺.基于现金流量的上市公司财务危机预测研究[D].武汉：武汉理工大学硕士论文,2008
28李维安.公司治理评价与指数研究[M].高等教育出版社,2005：44-55
29姜秀华,孙铮.治理弱化与财务危机：一个预测模型[J],南开管理评论,2001(5)：19-25
30杨兵,柯佑鹏.非财务指标影响上市公司财务危机预测能力的实证研究[J].财 会通讯(学术版),2005,(11)
31杨轶.财务预警研究中非财务指标选择综述与评价[J],财会通讯(综合)2008(6)：100-101
32 William H. Beaver; Maureen F. McNichols; Jung-Wu Rhie. Have Financial Statements Become Less Informative?Evidence from the Ability of Financial Ratios to Predict Bankruptcy. www.ssrn.com, Working Paper.2006
33 Ohlson, J.S.. Financial Ratios and the Probabilistic Prediction of Bankruptcy [J]. Journal of Accounting Research 1980, (19), (Spring):109-131.
34 Hadley,J.,R.Mullner,and J.Feder.The Financially Distressed Hospital[J].New England Journal of Medicine 307(11 November 1982):1283-87
35 Kwon,I.,S.R.Safranski,and W.R.Walker.Causes of Financial Difficulty in Catholic Hospitals[J]. Health Care Management Review 13,no 1.Winter 1988:29-37
36 Martin, J, and Parson, R. Financially Distressed Hospitals:Associated Factors. Policy Brief 40, American Hospital Association, Office of Public Policy Analysis, 25,November,1981
37 Kelly, J, and O'Brien, J. Characteristics of Financially Distressed Hospitals. HCHSR Hospital Cost and Utilization Research Prect:Research Note 3, Rockville,MD:Public Health Service, June,1983
38 John M. Trussel, Patricia A. Patrick.An Empirical Analysis of Financial Distress in Pennsylvania Ho spitals[J] Journal of Health Care Finance.2009,36(1):31-60
39 Tuckman, H., and Chang, C. A Methodology for Measuring the Financial Vulnerability of Charitable Nonprofit Organizations [J]. Nonprofit and Voluntary Sector Quarterly,1991,65,445-460.
40 Janet S.Greenlee, John M.Trussel.Predicting the Financial Vulnerability of Charitable Organizations[J].Nonprofit Managemen& Leadership, Vol,11, no.2. winter2000
41 John Trussel, Janet S. Greenlee, and Tbomas Brady.Predictive Financial Vulnerability in Charitable Organizations [J].The CPA Journal. June 2002
42 Chabotar,K.J.Financial ratio annlysis comes to nonprofits[J].The Journal of Higher Education,1989,60(2),188-209
43 McCue, M. The Use of Cash Flow to Analyze Financial Distress in California Hospitals[J], Hospital & Health Services Administration,1991,36 (2):223-241.
44 Xiaohu Wang, Lynda Dennis. Measuring Financial Condition:A Study of U.S. States[J].Public Budgeting & Finance, Vol.27, No.2:1-21, Summer 2007
45 Cheit,E.F.,& Ford,F.The new depression in higher education:A study of financial conditions at 41 colleges and universities[M].1971,New York:McGraw-Hill.
46 Gilmartin,K.J. Development of financial indicators of the viability of higher education institutions[R].1984,Palo Alto,CA:American Institutes for Research in Behavioral Services.
47 Peters,M.F.A multivariate analysis of predictive measures of fiscal distress among selected,private,four-year colleges and universities [D].1994,UMI No.9516385:56
48 Lee,R.A.Financial and staffing ratio analysis:predicting fiscal distress in school districts. Journal of Higher Education [J],1983(58):181-204
49 Sharp,William L.,Lair,Wiliferd R.An early warning system for schools:an examination of Illinois' financial watch list.Conference paper of the American Education Finance Association,March 17-20,1994
50 Marshall, Mary Jo.The relationship between budgeted and actual revenues and expenses as predictors of financial distress in Illinois elementary-school districts[D].Northern Illinois University.1998
51 Brubaker, P.Financial health indicators for institutions of higher learning:A literature review and synthesis[R].1979, SAGE Tech.Rep.No.13
52 Lupton,A.H.Auginblick,J.,&Heyison,J. The state of higher education. Change[J], 1976,8(8),21-36
53 Collier,D.J.&Patrick,C.A multivariate approach to the analysis of institutional financial condition[M],1978.Boulder,Co:National Cente for Higher Education Management Systems.
54 Gomberg,I.L.,&Atelsek,F.J.Trends in financial indicators of colleges and universities.Washington,DC:American Council on Education.1981
55 Bolda,P.J.M.&Bruce A.A measurement of financial viability among private colleges[R]. Motreal,Canda.1983,Educational Research Association Rep No.104
56 Curry,C.T.A determination of the perceived utility of financial indicators within the state system of higher education of Pennsylvania. [D],1998,UMI No.9837573:23
57 Schipper,K.An analysis of the financial condition of private college[D].1977, Chicago,IL:University of Chicago.
58 Lomax,V.M.An examination of the determinants of the financial viability of small,private,four-year colleges and universities [D].1984,UMI No.8512231:46
59 Roden,J.K.& Moore,W.Uaing financial ratios analysis to describe the relative fiscal health of selected publicly funded institutions of higher education in New York state[D].UMI No.9120720:52
60 Talboys,W.M..Using financial rations in the analysis of four private universities in the southwest United States:A case study[D].1995,UMI No.9615638:57
61 Richard A. Lee. Examining Financial and Non-Financial Indicators for Predicting Private Higher Education Viability [D], Northcentral University,2008
62王德春,张树庆.高校财务风险与防范对策[J],山东农业大学学报(社科版),2003年第2期：8-11
63胡信生,拓东玲,王希文.高校财务风险的类型及其防范[J],教育财会研究,2004,6：27-30
64杨周复,施建军.大学财务综合评价研究[M].北京：中国人民大学出版社,2002：196
65许道银.试论高校财务危机预警系统[J].徐州师范大学学报(自然科学版).2003年第21卷第4期：19-22
66林莉.中国高校贷款问题研究[D],厦门大学博士学位论文,2006
67刘跃,王玲.西部高校财务预警与财务风险防范研究[J].财会通讯,2006(2)
68张克友.高校财务风险预警系统研究[J],企业经济,2007.6：187-189
69雷振华.高校财务风险预警指标体系的构建研究[J].财会通讯(学术版),2007(2)：118
70米新英,刘泽琴.高校财务预警系统的研究.北华航天工业学院学报[J],2008(10)：41
71雷中英,严守德.基于G1法的高校财务风险预警指标体系权重确定[J].价值工程,2010(1)：38
72齐向丽.高等院校财务风险评估与防范[D],天津大学硕士论文,2003
73郑鸣,黄光晓.我国高校财务困境预测研究[J],经济纵横,2008.5：79-81
74窦伟.修正的z值风险模型—高校财务风险预警指标体系探析[J],河南财政税务高等专科学校学报,2007.2：32-34
75周雪,顾晓敏.动态现金流量模型在高校财务风险预警中的运用[J],财会月刊(综合)2009.1：85-87
76林立妍.陕西省属高校财务风险综合评价与预警研究[D].西安理工大学硕士论文.2008年
77王开田.公司财务危机预警系统研究[J].河北经贸大学学报.2001(3)：30
78张亚杰.我国制造业上市公司财务状况评价及预测研究[D1.中国矿业大学博士论文.2010年
79李秉成.企业财务困境研究一上市公司财务困境实证分析[M].中国财政经济出版社,2008：56-80
80庞皓,黎实,贾彦东.金融安全的预警机制与风险控制研究[M].科学出版社,2009：61
81别敦容,杨德广.中国高等教育改革与发展30年[M].上海教育出版社.2009：2
82李武好.中国经济发展中财政政策与货币政策[M].经济科学出版社.2002：63
83何忠洲.负债30亿的吉林大学[N].中国新闻周刊,2007.4.9
84王娜,孙雷.教育部：政府要加大投资力度学校要着重化解风险[N].21世纪经济报道,2007.3.28
85蔡俊兰.中国高等教育规模与经济发展相关的实证分析[J].高教探索,2008(3)：49-52
86李亚勃.我国普通高等教育招生规模研究——基于中美比较的视角[J].教育发展研究,2006(1)
87刘宇.我国高校财务困境成因与预警研究[D].南开大学企业管理博士论文,2009
88鲍威.扩招后中国高等院校贷款融资行为的实证研究[J].北大教育经济研究,2007年6月第五卷第2期：12
89鲍威.扩招后中国高等院校贷款融资行为与财务运作特征[C].2009年中国教育经济学学术年会论文集,2009.12
90叶平.关于进行高等教育规模增长速度预警研究的探讨[J].高等教育研究, 1996(6)：47
91李岚清.李岚清教育访谈录[M].北京：人民教育出版社,2003：119
92谢作栩.中国高等教育大众化发展道路的研究[M].福州：福建教育出版社,2001：252
93王胜今.我国高等教育大众化十年盘点与省思[J].高等教育研究.2009,(4)：56
94张友堂.财务预警系统管理研究[M].北京：中国人民大学出版社,2004.
95马志远.中国财政性教育经费占GDP 4%的可行性分析—国际比较的视角[J].教育研究,2011,(3)：24
96孔喜梅.高等教育经费短缺现状及解决途径[J].郑州大学学报(哲学社会科学版).2006(7)：184
97王良驹,试论高校理财环境的阶段性特征与应对[J],财会研究.2009,(15)
98徐明稚.对我国高等教育投入的思考与建议[J].教育发展研究.2009,(7)
99曾月明,朱杏龙,葛文雷.高校财务风险的涵义及形成机理探究[J].南京财经大学学报,2009.3：59-60
100华清君.当前高等学校财务危机的理性思考[J].黑龙江高教研究,2004.10：86-87
101马新平.我国教育经费来源结构分析与国际比较[J].商业时代,2010,(27)：110
102邬大光.高校贷款的理性思考和解决方略[J].教育研究,2007(4)：18-25
103王远伟.中国高等教育财政经费来源的变迁[J].清华大学教育研究,2006(5)
104教育部财务司.高校经济活动案例选编[M].北京：高等教育出版社,2001
105冯晓华.浅谈高校资金管理存在的问题和对策[J].会计之友,2008.9
106林毅夫,李志赟.政策性负担、道德风险与预算软约束[J].经济研究,2004,(2)
107庞晓波,黄卫挺.高校预算软约束的制度成因及其治理[J].中国高教研究,2009(1)：46-49
108李秉成.企业财务困境研究-上市公司财务困境实证分析[M].中国财政经济出版社,2004.8：60
109姜晓璐,张丹,徐明稚.基于共生理论下高校财务风险的演变机理研究[J].中国高教研究.2009.11：30
110魏海苓,孙远雷.论现代产权制度下的我国公立高校产权改革[J].现代大学教 育.2005,(4)：54-57
111 Segal Ilya R.Monopoly, Soft Budget Constraint[J].Rand Journal of Economics, 1998,(3):11
112林毅夫,李志赞.政策性负担,道德风险与预算软约束[J].经济研究,2004,(2)
113曹淑江.高等学校的软预算约束与财务自主权[J].高等教育研究,2005,(10)
114刘淑华,王福友.预算软约束：高校群体性负债的深度分析[J].教育发展研究,2010.5：12-16
115韦英妹,罗艳洪.高校贷款及其风险的控制与化解[J].中国农业会计,2008.11：12-14
116刘淑华,王福友.预算软约束：高校群体性负债的深度分析[J].教育发展研究2010,(5)：12-16
117阿什比著,滕大春,滕大生泽.科技发达时代的大学教育[M].1983：62
118董云川.论大学行政权力的泛化[J].高等教育研究.2000,(2)：60
119赵建军.我国高等学校财务治理问题研究(教育部财务司)[J].教育财会研究.2008(5)：9
120张凡.把握高校会计改革方向提升专员办服务品牌-财政部驻湖北专员办在鄂部属高校资产财务管理工作座谈会综述[J].财政监督,2010(14)：25
121孟昭德.论新时期大学财务工作的主要任务[J].事业会计,2005,(2)：31
122肯尼斯·汉克尔,尤西·李凡特著,张凯等译.现金流量与证券分析[M].北京：华夏出版社2001,第2版
123 Copland. Valuation:Measuring and managing the value of companies [M].John Wily&sons.1990
124汤姆·科普兰,蒂姆·科勒.价值评估[M],中国大百科全书出版社,1998
125汤谷良,朱蕾.自由现金流量与财务运行体系[J].会计研究,2002
126 Argenti,John.Corporate Collapse:The Causes and Symptoms[M],McGraw Hill,NY,1976.
127 Subhash Sharma & Vijay Wahajan. Early Warning Indicators of Business Failure [J], Journal of Marketing,vol.44(Fall 1980).80-89
128 Ho,Thomas S,and Anthony Saunders.The Determinants of Bank Interest Margins:Theory and Empirical Evidence[J].Journal of Financial and Quantitative Analysis,1981,16(4):581-600.
129 Scott, J. The Probability of Bankruptcy:A Comparision of Empirical Predictions and Theoretical Models[J]. Journal od Banking and Finance,1981, (5):317-344.
130中国注册会计师协会.会计[M].中国财政经济出版社,2011：247-255
131财政部.国家教育委员会关于印发《高等学校财务制度》的通知.财务与会计,1997.8
132 Berg A,Borensztein E.et al. Anticipating balance of payments crises-the role of early warning systems.Occasional Paper,1999
133唐旭,张伟.论建立中国金融危机预警系统[J].经济学动态,2002(6)
134朱莲美IASB/FASB"关于财务报表列报的初步观点”讨论稿之评价[J].财会月刊,2010(7)下：16
135斯蒂芬.H.佩因曼著,刘力,陆正飞译.财务报表分析与证券定价[M].中国财政经济出版社,2005：306-320
136丁绍凡,王丽洁.高等学校现金流量表编制探析[J],教育财会研究.2005(4)
137徐明稚.高校编制现金流量表初探[J].财务与会计,2009(21)：28-30
138安红,廖文萍.高校现金流量表的编制与运用[J].会计之友,2010(22)：65-66
139宋加山,李勇.极值理论中阈值选取的Hill估计方法改进[J].中国科学技术大学学报,2008(9)：1104-1106
140 Reiss R, Thomas M. Statistical Analysis of Extreme Values:From Insurance, Finance, Hydrology and Other Fields[M]. Basel:Birkhauser Verlag,2001.
141杜强,贾丽艳SPSS统计分析从入门到精通[M].人民邮电出版社,2009：150-189
142詹建平.上市公司多分类财务预测模型及其应用研究[D].首都经济贸易大学硕士论文,2008
143 Miller,B.E.Mastering cause and effect ratio analysis[M].Business Credit, 1993:24-27
144李珊.基于财务状况多分类的财务困境预警模型研究[D].浙江大学,2009
145姜秀华,任强,孙铮.上市公司财务危机预警模型研究[J].预测,2002(3)：56-61
146黄德华.财务数据对我国上市公司协议收购事件的解释[D].上海财经大学博士论文,2001：33-45
147张万朋.美国高校债务问题的控制与防范[J],教育发展研究,2009.7：20
148陈晓宇,冯倩倩.我国高校的捐赠收入及捐赠人行为研究[J].北京大学教育评论.2011(1)：80-90
149 Craig R.Hansel.The Lowa school financial solverncy ratio as a predictive measure of financial health for Lowa K-12 public school[D].Northcentral University,2005
150席酉民,李怀祖,郭菊娥.我国大学治理面临的问题及改善思路[J].西安交通大学学报(社会科学版).2005(3)：78-83
151徐明稚.大学管理和大学发展[J].中国高等教育,2010(6)：4-7
152应益华.高校推行注册会计师审计制度的探讨[J].财会研究,2006(6)：40