摘要
中国是世界茶叶的原产地,是产茶大国。全国有近亿人从事茶叶生产,年茶叶产业产值可达百亿元。但不是茶叶强国。归因是茶叶质量较差,企业竞争力弱,阻碍茶叶企业发展的因素很多,缺少资金是阻碍茶叶企业发展的关键,但是不能忽视的是,总体上茶叶企业的信用不高,通过调查发现近五年来高达43.18%的企业有违约记录,高违约率阻碍了茶叶企业的融资,制约了企业的发展,同时也扰乱了金融市场秩序。因此从银行视角研究茶叶企业整体信用情况、影响茶叶企业信用的因素显得尤为迫切,这不仅仅关系降低银行信贷风险,促进信贷良性发展,也关系着信贷资金能否顺利投入茶叶产业及整个茶叶产业的前景。本研究首先在界定茶叶企业、信用风险、理性人等概念的基础上,选取茶叶企业主特征、茶叶企业自身特性、金融机构因素、非正规融资因素及宏观环境等方面因素对影响福建茶叶企业信用风险的因素进行理论分析和统计描述。从茶叶企业层面通过参与式调查收集数据,建立实证分析模型,应用Probit模型分析影响福建茶叶企业信用风险的的显著因素;实证结果表明:茶叶企业主特征、茶叶企业自身特性、金融机构因素、非正规融资因素及宏观环境中的企业主行业管理年限、企业经营时间、企业性质、企业类型、企业财务状况、企业信用等级、担保形式、非正规融资风险利率、国家金融环境等因素对福建省茶叶企业的信用风险的影响较大。通过计量定性实证出影响福建茶叶企业信用风险的显著因素。依据影响福建茶叶企业信用风险的显著因素,借助层次分析法,依据建立指标全面性、重点性、科学性、针对性、相关性、可操作性、公正性、合法性等原则构建茶叶企业信用风险评价体系。通过构建茶叶企业信用风险评价体系及评分数据,可以看出433家茶叶企业中,有195家茶叶企业的得分在60分以下,这些企业信用程度一般,偿债的能力也一般。经营状况波动非常大,对企业履行相关合同的能力有非常大影响,违约风险很高。因此,可以看出茶叶企业存在较大的信用风险的问题,应该引起高度注意。基于企业的历史数据进行测试和评价,建立茶叶企业信用风险预警模型。采用“绿、黄、橙、红、黑”五种颜色反映风险程度、区分风险因素,五种颜色分别代表“低风险、较低风险、中等风险、较高风险、高风险”,并建立分层次渠道的风险处理机制。其中,绿灯区表示信贷情况安全,低风险。黄灯区表示信贷情况比较安全,但存在发生概率较小的风险。橙灯区表示信贷情况有一定风险,应引起重视。红灯区表示信贷情况存在较大风险,须采取相应措施。黑灯区表示信贷情况存在严重风险,亟须采取紧急措施。最后,提出政府要加大宏观调节力度、茶叶协会应发挥其协调作用、茶叶企业要加强自身信用建设等措施提高企业信用。
China is the world's tea country of origin which is the largest tea-producing country, but not strong country of tea. The main reason the competition of tea enterprises is weak. There many factors to hinder the development of tea enterprises and lack of funding is the key to impede the development of enterprises of tea but the credit of whole tea business is not high which is can not be overlooked. The resent five years of survey data reflect that up to 43.18% of the enterprises have the related contract records, so it is urgent to research the credit of tea enterprises from the respect of bank, it is not only has the relationship between bank credit industry, but also about the entire tea industry's prospects. This study is first based on defining the concept of tea enterprises, credit risk, the concept of rationality, etc, and then does theoretical analysis on the factors affect the Fujian tea company credit risk by selecting the characteristics of tea enterprises owners, tea enterprises, financial institutions, non-formal institutions and macro-environmental factors.The paper collected data and making descriptive statistics analysis and set empirical analysis model through participatory surveys. It does analysis on the corporate credit risk in Fujian tea significant factor though the Probit statistical analysis.And then, we can get the empirical results that characteristics of tea enterprises owners, tea company's own characteristics, financial institutions factors, non-formal financial factors and macroeconomic environment of the years of business owner’management, the time of enterprise operate, business properties, business type, financial status, corporate credit rating, secured forms, informal financing the lending rate, the country's financial and environmental factors take great effect on the Fujian tea business credit risk. Through the measurement of qualitative research analyze Fujian tea significant corporate credit risk factors.Based on the significant factor whict affect the credit risk of Fujian tea enterprises, the paper use the method of AHP to build the principles of corporate credit risk evaluation system according to the principles of comprehensive, focusing on nature, science, relevance, relevance, feasibility, fairness, legitimacy and so on.By rating data, we can see that there are 195 tea companies get the score less 60 in 433 tea companies and credit rating and debt service ability of these companies is in general. And there’s fluctuations in operating conditions is very large which has a enormous influence on the ability of enterprises to fulfill the contract, and the risk of default is very high.Therefore, we can see that there is a big credit risk of tea companies, it should have aroused great attention.The paper do testing and evaluation based on historical data to establish credit risk early warning model of tea enterprises. And takes up the five colors of yellow, orange, red, black, to reflect the degree of risk and distinguish risk factors. The five colors represents the" low-risk, low risk, medium risk, high risk, high-risk ". Then the paper establish the sub-levels channels management mechanisms.Among them, the green light district said that credit conditions are safe, low-risk. Yellow light district shows credit conditions relatively safe, but there is a smaller probability of risk. Orange light district saids that credit conditions have a certain risk, attention should be paid.Red-light district credit conditions shows that there is a big risk to take corresponding measures. Black light District shows that there are serious risks of credit conditions and urgent measures should be urgent taken. Finally, the paper put some advices from the respect of government to strengthen macro-regulation efforts, tea associations should play its coordinating role, tea enterprises should strengthen their own credit-building measures to improve enterprise credit.
引文
杨江帆,管曦等茶叶经济管理学中国农业出版社,2004
孙鹏,施海球,倪立芬.基于AHP的施工企业信用标准体系研究[J].研究探索,2003,(7) :41.
陈中华.层次分析法在中小企业信用评价中的应用研究[D].苏州.苏州大学, 2006
全国重点产茶县产业现状分析[R].中国茶叶行业发展报告,2009:1.
欧兵.企业借款陷阱与商业银行贷款风险防范[J].南方金融,2003,(6): 58.
施锡铨,邹新月.典型判别分析在企业信用风险评估中的应用[J].财经研究,2001,(10): 53.
The Editors. Credit Risk and Credit Derivatives [J] , Reviewof DerivativesResearch,1998(2):95
Fotios Pasiouras , Chrysovalantis Gaganis. The impact of bank regulations,supervision,market structure,and bank characteristics on individual bank [J],Rev Quant Finan Acc,2006(27):404
SIMON KWAN, ROBERT A.EISENBEIS. Bank Risk,Capitalization,and Operating Effciency [J], Journal of Financial Services Research,1997(12):119
Klaus Düllmann, Agnieszka Sosinska. Credit default swap prices as risk indicators of listed German banks [J], Fin Mkts Portfolio Mgmt,2007(21):269
Duffie,D , Singleton,K.J , Duffie,D. Book Review [J], Princeton University Press,2003(12):6
Ling Chu,Robert Mathieu,Sean Robb. Bank capitalization and lending behavior after the introduction of the Basle Accord [J], Rev Quant Finan Acc,2007(28):148
James H.Rauch,Jill M.Hendrickson. Does Bank Consolidation Hurt the Small Business Borrower? [J],Small Business Economics,2004(23):220
Enrico Geretto,Rubens Pauluzzo. The Structure of the Chinese Banking System and Credit Access Problems for SMEs [J],Transit Stud Rev,2008(15):567
Angelo Zago,Paola Dongili. Credit quality and technical efficiency in banking[J], Empir Econ,2009(12):10
Paul H.Kupiec. Capital Allocation for Portfolio Credit Risk [J], Published online,2007(15):103
Yoshifumi Muroi. Pricing contingent claims with credit risk:Asymptotic expansion approach [J],Finance Stochast,2005(9):415
陈乃醒.中国中小企业发展与预测(第一版)[M].北京:经济管理出版社,2002,244-248.
Allen N,Berger&Leora F,Klapper&Rima Turk-Ariss. Bank Competition and Financial Stability [J],Financ Serv Res,2009(35):99
Robert A.Eisenbeis,W.Scott Frame,Larry D.Wall. Fannie Mae and Freddie Mac and An Evaluation of the Policy Options for Reducing Those Risks [J],Financ Serv Res,2007(31):82
MICHAEL H.ANDERSON. Asset Liquidity,Moral Hazard,and Bank Loan Rescheduling [J] , Review of Quantitative Finance and Accounting ,1999(13):227
余建国.中国中小企业融资(第一版)[M].北京:中国计划出版社,2002,257-355.
陈晓红.中小企业融资创新与信用担保(第一版)[M].北京:中国人民大学出版社,2003,174-229.
李荣.论中小企业信用缺失对融资的影响[J].商业研究,2003,(11):14-16.
张水英.集群中小企业的融资优势[J].企业改革与管理,2005,(8):9-10.
聂高辉.中小企业融资的理智选择一金融租赁[J].金融与经济,2005,(3):24-25.
宋祺,胡小钟.国内外企业信用评价体系比较与创新研究[J].湖北行政学院学报,2007,(3):110.
刘萍.论企业信用体系的建立与运行[J].企业管理,2007,(1):57.
魏瑞兴.中小企业融资管理中出现的问题及对策[J].山西财经大学学报,2009,(11):102.
盖地.中国企业信用制度研究的新成果———《企业信用制度论》评价[J].石家庄经济学院学报,2007,(6):41.
黄志豪.中小企业信贷违约行为研究.暨南大学[D]博士论文2006
Dimitrios Askounis,Ioannis Psarras. On the Appraisal of Consumer Credit Banking Products within the Asset Quality Frame:A Multiple Criteria Application [J],International Journal,2007(2):255
DANIEL ROSCH. CORRELATIONS AND BUSINESS CYCLES OF CREDIT RISK:EVIDENCE FROM BANKRUPTCIES IN GERMANY [J],Swiss Society for Financial Market Research,2003(17): 309
Risk Metrics Group.Credit Metrics.technical document[R/OL],[1997]http://www.riskmetrics corn/research
Michael Cmuhy,A Comparative Analysis of Current Credit Risk Models[J],Journal of Banking and Finace,2000(24):59-117
李磊宁张凯.KMV模型的修正及在我国上市公司信用风险度量中的应用[J].金融纵横,2007(13):81-87
杨雨.个人信用风险计量:双边抗体人工免疫概率模型[J].系统工程理论与实践.2009(29)
Hanley J A,The meaning and use of area under a receiver operating characteristic curve(ROC)[J], Radiogy,1982,143(1):29
于立勇.基于Logistic回归分析的违约概率预测研究[J].财经研究,2004(30)
谢爱荣.多层次灰色评价法在中小企业信用评价中的应用[J].成都大学学报,2007(2):160-163
张云起.基于BP神经网络的客户信用评价和管理[J].中国知网,2009
陈良维.决策树在农户贷款中的应用研究[J].计算机工程与应用,2008(44):242-248
李兴法.信用风险理论、模型及应用研究[J].东北财经大学博士学位论文,2007
梁琪.企业信用风险的主成分判别模型及其实证研究[J].财经研究,2003(29):52-55
陈祥槐倪建平.企业信用及其制度模式探讨[J].工业企业管理,2003,(2):34-37.
周春喜.企业信用等级综合评价指标体系及其评价[J].科技进步与对策,2003,(4):124-126.
范伯乃朱文斌.中小企业信用评价指标的理论遴选与实证分析[J].科研管理,2003,(6):83-88.
毛定祥.基于多元统计分析和模糊综合评判的企业财务信用综合评价[J].上海大学学报,2000,(3):38 - 42.
李小燕卢闯等.企业信用评价模型、信用等级与业绩相关性研究[J].中国软科学,2003,(5):81-85.
中国信用信息网. http://www.creditinfo.com.cn/chinese/index.asp
张铁铸周红.上市公司提供商业信用的影响因素研究[J].财贸研究,2009(3):12-30
白曜新.中小企业融资难问题研究[J].合作科技与经济,2008,(4):115.
刘斌.中小企业融资难问题研究[J].北京金融,2005,(8):18.
王碎元,柯晓微.中小企业融资难的原因与对策[J].温州学刊,2006,(2):46.
黄惠琴,杨晓丽.中小企业融资现状及对策[J].社会经纬,2009,(2):36.
吴蕊.中小企业融资文献综述[J].经济论坛,2007,(21):100.
RAYMOND C.CHIANG.Residential Mortgage Lending and Borrower Risk:The Relationship Between Mortgage Spreads and Individual Characteristics [J].Journal of Real Estate Finance and Economics,2002,(25):6
雷雨,徐群,张世文.民营企业融资策略分析[J].现代商贸工业,2009,(22):150.
何明亮.破解中小企业“融资难”问题之管见[J].银企信用,2009,(10):51.
任永平梅强.中小企业信用评价指标体系探讨[J].现代企业管理,2001,(4):52-55.
孙智英.信用问题的经济学分析[M].广州:中国城市出版社,2002 :172-182.
赵昕李莉等.基于AHP、GEM综合算法的个人信用评价体系[J].农村金融研究,2002,(4):21-24.
刘晓星.个人消费信用评级及贷款决策研究[J].消费经济,2003,(6):43-45.
管晓勇陈红.中小企业信用影响因素:理论与实证[J].中共浙江省委党校校报,2008,(3):111-117
陈述云.对企业信用评级内容的理论界定[J].经济问题探索,2000,(1):22-23
雷晓敏等.中小企业家信用评价模型指标构建分析[J].财经问题研究,2008 (1):119-125
高海波.关于违约率与经济周期的关系的研究[J].吉林大学硕士论文,2006
杨智恒.信用七大结构要素分析[J].生产力研究,2007,(7):10-12
Rotter, J.B., 1967, A New Scale for The Measuremen to fInterpersonal Trust,Journal of Personality, 1967,(35):651-665.
方洪全曾勇.运用多元判别法评估企业信用风险的实例[J].预测,2004,(4):65-70
李水平.信贷企业信用评价中的非财务因素分析[J].湖南税务高等专科学校学报,2007,(91):38-42
王富全.影响个人信用因素的实证分析[J].金融与经济,2008,(10):9-12
白保中朱世武.基于Log istic模型的单个信用资产违约概率预测[J].广东金融学院学报,2008,(23)57-62
Davidson, R. , and MacKinnon, J. G. , 1984:“Convenient specification tests for logit and p robitmodels”, Journal of Econometrics, Elsevier, Vol. 25 (3).
Efron, B., 1975:“The efficiency of logistic regression compared to normal discrimnant analysis”, Journal of the American StatisticalAssociation, Vol. 70, No. 352 p892 - 898.
MASAAKI KIJIMA,YUKIO MUROMACHI.Credit Events and the Valuation of Credit Derivatives of Basket Type [J].Review of Derivatives Research,2000,(4):55.
J.GALINDO.Credit Risk Assessment Using Statistical and Machine Learning:Basic Methodology and Risk Modeling Applications [J].Review of Derivatives Research,2000,(15):110.
MARCELLO BOFONDI,FRANCESCA LOTTI.Innovation in the Retail Banking Industry:the Diffusion of Credit Scoring [J].Review of Industrial Organization,2006,(28):345.
许静怡.中小企业银行贷款融资的信用评级[J].山东财政学院学报(双月刊) ,2008,(5):53.
门玉峰.企业信用风险防范对策[J].黑龙江对外经贸,2007,(11):109.
李毅.对我国中小企业划分标准的研究[J].决策管理,2008,(17):4.
顾光青.破解中小企业融资难题:经验与启迪———中小企业金融服务国际研讨会综述[J].上海经济研究,2008,(9):124-125.
王俊波.货币政策调整与中小企业融资问题研究[J].经济研究导刊,2009,(8):152.
王春峰,万海晖,张维.商业银行信用风险评估及其实证研究[J].管理科学学报,1998,(1):68
朱富强.主流经济学中的“经济人”:内涵演变及其缺陷审视[J].财经研究,2009,(4):75-76
李小燕,钱建豪.我国中小企业信用风险评估实证研究[J].中国软科学,2005,(9).121.
高媛,卞直巍.关于中小企业信用评级体系[J].长春工业大学学报,2003,(4):44.
陈元燮.建立信用评级指标体系的几个理论问题[J].财经问题研究,2008,(8):5.
张红波.略论企业信用状况评价指标体系的构建[J].湘潭师范学院学报(社会科学版),2004,(2):54.
王新红,陈燕杰,仲伟周.我国中小企业信用风险评价指标体系构建[J].西北师大学报(社会科学版),2009,(4):130.
东方茶文化传播网.中国茶叶行业企业信用等级评价管理办法[EB/OL]. (2008-9-05)[2010-3-10] http://www.cnteaw.com/ArticleContent.asp?ID=2328
李燕.中国茶叶流通协会全面开展行业信用评价体系工作[J].茶世界,2008,(7).29.
凌佳.当前生产型企业财务管理存在的问题及对策[J].商场现代化,2009,(5).237.
李智敏.企业信用风险体系因素探析[J].业务技术,2008,(12).40.
李桦.企业性质和企业文化的差异[J].企业活力,2009,(11).72.
雷晓敏,宋家顺.中小企业家信用评价指标体系研究[J].科技促进发展,2009,(10). 300.
于洋.我国中小企业融资难因素分析[J].金融税务,2008,(10).30.
王树娟.信息不对称与中小企业融资困难问题[J].金融经济,2008,(11).135.
张优勤.金融危机下再谈中小企业融资难问题[J].商场现代化,2009,(3).189.
韩平,席酉民.企业违约风险因素分析与模糊综合评价[J].西安交通大学学报(社会科学版),2000,(3).26-27.
蒋伏心,周春平.交易成本、非正规金融与中小企业融资[J].世界经济与政治论坛,2009,(2).25.
张娜.非正规金融与中小企业融资[J].中小企业融资,2008,(1).28.
左臣明.非正规金融与中小企业融资[J].山东工商学院学报,2005,(6).28.
王姝,杨万荣.商业银行信用风险预警模型探究[J].合作经济与科,2009,(10) :33.
邹小凡,余君,钱英.企业信用评估指标体系与评价方法研究[J].数理统计与管理,2005,(1) :40.
肖丽容,杨全成,付敏.关于中小企业融资风险的对策研究[J].长江大学学报(自然科学版),2009,(3) :96-97.
沈蕾.论商业银行中小企业信贷风险预警体系构建[J].黄冈师范学院学报,2008,(4) :21.
朱建军.层次分析法的若干问题研究及应用[D].沈阳.东北大学, 2005
吴岩.基于AHP的中小企业信用体系的建立[J].中小企业研究,2007,(9).135.
梁晓娟.后危机时代中小企业信用评价体系和方法的构建[J].问题探讨,2009,(1).41.
赵介箴.浅议中小企业信用评价指标体系的建立和构成[J].甘肃科技,2006,(9) :33.
蔡文浩.层次分析法在企业信用风险评估中的应用[J].经济师,2008,(10) :217.
刘堃,巴曙松,任亮.中国信用风险模型及实证研究——基于企业关联关系和信贷行为的视角[J].财经研究,2009,(7) :19.
沈俊,孙强.我国民营企业融资风险预警管理研究[J].武汉理工大学学报·信息与管理工程版,2004,(3) :70.
王桂荣,赵艳丽.关于建立企业融资风险预警系统的思考[J].现代管理科学,2004,(8) :102.
秦江波,于冬梅.信贷风险预警指标体系的构建[J].商业研究,2009,(3) :151-152.
张一童.次贷危机影响下我国商业银行信用风险管理研究[J].现代商贸工业,2009,(5) :123.
徐蔼婷.德尔菲法的应用及其难点[J].统计科普,2006,(9) :58-59.
黄成斌.德尔菲法[J].工程质量,2008,(7) :3.
吴青.信用风险的度量与控制[M].对外经济贸易大学出版,2008:20-21.
隋剑雄,林琪.试论我国商业银行信贷风险预警系统的建立[J].金融论坛,2004,(8) :48.
马九杰,郭宇辉,朱勇.县域中小企业贷款违约行为与信用风险实证分析[J].管理世界,2004,(5) :59.
王瑾.中小企业融资障碍及对策研究[J].理论科学,2009,(5) :218.
李红梅.浅谈中小企业融资问题[J].商业现代化,2009,(11) :12.
李月华.论中小企业信用风险的事前控制[J].企业经济,2008,(2) :38.
杜智勇.企业信用风险的形成机理与防范策略[J].企业经济,2004,(10) :43.
杨元泽.中国中小企业信贷风险评估研究[J].金融论坛,2009,(3) :72-73.
中国茶叶流通协会.中国茶叶流通协会将全面开展行业信用评价体[EB/OL]. (2008-7-24)[2010-3-10] http://www.cnteaw.com/ArticleContent.asp?id=2083
闫芳.浅析企业的信用风险及其管理[J].现代商业,2007,(7) :67.
王燕.浅议企业信用风险的管理和防范[J].经营谋略·金融资本,2008,(7) :73.
王桂荣,赵艳丽.企业信用危机的预警[J].企业改革与管理,2007,(12) :18.