Early Warning Research Of Higher Education Financial Distress Based On Cash Flow

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.