本研究以舞弊三角理論為基礎，檢視舞弊性財務報表發生之風險因子，併考量公報中關注的風險因子，建立舞弊性財務報表預測模式。接著檢定公司發生舞弊性財務報表事件揭露之後，有哪些因素及公司特性影響後續影響發生財務困難的機率，透過離散時間涉險模式的運用，不僅考量各因素當期的影響，且更考量了期間的變化。
結果顯示發生詐欺性財務報表之顯著風險因子之代理變數包括，分析師預測誤差(AFE)、負債比率(LEV)、董監事質押比率(PLEDGE)、關係人交易比率(RPT%)、歷史重編次數(RST)，以及委任會計師轉換次數(CPA)，這些變數分別歸類為動機/壓力、環境及態度/合理性三項構面。表示當公司或其董監事承受較大的財務壓力、公司具有較複雜之交易型態、公司管理階層的正直受到質疑時，以及當公司與其審計人員關係惡化時，較易發生詐欺性財務報表。我們以ISA 240、SAS 99及43號審計公報為基礎，所建立一個邏輯性且簡化之舞弊性財務報表風險評估模式，取代冗長主觀的稽核表，相信可提供實務廣泛的運用。
發生詐欺性財務報表公司中，有24%公司在揭露一年內即發生財務困難。離散時間涉險模式較單一期間羅吉斯迴歸分析提供較高之正確分類率，並可避免單一期間羅吉斯迴歸分析所存在選擇性偏誤的問題。在本研究所建立模式中，負債比率(LEV)、總資產淨利率(NITA)、董監事質押比率(PLEDGE)、會計師更換(△CPA)，皆與財務困難之發生具有顯著正相關(p-value <0.05)，模式內除了傳統的財務比率外，亦考量公司治理因素，提高模式的正確分類率。

This research examines risk factors of the fraud triangle, core of all fraud auditing standards, for assessing likelihood of fraudulent financial reporting. And this study applies discrete-time survival analysis (DTSA) to examine the influence of fraudulent statements disclosure on the probability of financial distress not only in the initial period subsequent to disclosure, but future periods as well.
Significant variables, including analyst’s forecast error, debt ratio, directors’ and supervisors’ stock pledged ratio, percentage of sales related party transaction, number of historical restatements, and number of auditor switch, belong to pressure/incentive, opportunity and attitude/rationalization. Results indicate fraudulent reporting positively correlated to one of the following conditions: more financial pressure of a firm or supervisor of a firm, higher percentage of complex transactions of a firm, more questionable integrity of a firm’s managers, or more deterioration in relation between a firm and its auditor. A simple logistic model based on examples of fraud risk factors of ISA 240 and SAS 99 gauges the likelihood of fraudulent financial reporting and can benefit practitioners.
Evidence indicates DTSA is superior to logistic regression and extends a richer depiction of the probability after a first-time fraudulent statement disclosure. After fraudulent statements disclosure, 24% of the reporting firms experienced financial distress in Year 1, with the hazard function declines progressively in subsequent years. This study find total liability to total assets (LEV), net income to total assets (NITA), directors and supervisors’ stock pledged ratio (PLEDGE), and CPA (Certified Public Accountant) change (△CPA) are definitely linked to financial distress probability (p-value <0.05). A DTSA model not only includes financial ratios, but also considers corporate governance variables to produce more accurate classification than those of alternative models.

Chapter 1 Overview
Accounting Research and Development Foundation in Taiwan. 2006. The Auditor’s Responsibility to Consider Fraud in an Audit of Financial Statements: TSAS 43. Taipei, Taiwan.
American Institute of Certified Public Accountants (AICPA). 2002. Consideration of Fraud in a Financial Statement Audit: SAS 99. New York, NY: AICPA.
Anderson, K. L., and T. L. Yohn. 2002. The effect of 10-K restatements on firm value, information asymmetries, and investors’ reliance on earnings. Working paper, Georgetown University, Washington, DC.
Asare, S. K. and A. M. Wright. 2004. The effectiveness of alternative risk assessment and program planning tools in a fraud setting. Contemporary Accounting Research 21(2): 325-352.
Cox, D. 1972. Regression models and life-table. Journal of the Royal Statistical Society 34(2): 187-200.
Cressey, D. R. 1953. Other People’s Money: A Study in the Social Psychology of Embezzlement. Glencoe, IL: Free Press.
Dechow, P. M., R. G. Sloan, and A. P. Sweeney. 1996. Causes and consequences of earnings manipulation: an analysis of firms subject enforcement actions by the SEC. Contemporary Accounting Research 13(1): 1-36.
Eining, M., D. Jones, and J. Loebbecke. 1997. Reliance on decision aids: an examination of auditors’ assessment of management fraud. Auditing: A Journal of Practice and Theory 16(2): 1-19.
Desai, H., C. Hogan, and M. Wilkins. 2006. The reputational penalty for aggressive accounting: earnings restatements and management turnover. The Accounting Review 18(1): 83-112.
Griffin, P .A., J. Grundfest, and M.A. Perino. 2004. Stock price response to news of securities fraud litigation: an analysis sequential and conditional information. Abacus 40(1): 21-48.
Hribar, P. and N. T. Jenkins. 2004. The effect of accounting restatements on earnings revisions and the estimated cost of capital. Review of Accounting Studies 9(2-3): 337-356.
International Federation of Accountants (IFAC). 2002. The Auditors’ Responsibility to Consider Fraud in an Audit of Financial Statements: ISA 240. New York, NY: IFAC.
Louwers, T. J., F. M. Messina, and M.D. Richard. 1999. The auditor’s going-concern disclosure as a self-fulfilling prophecy: a discrete-time survival analysis. Decision Science 30(3): 805-824.
Nieschwietz, R. J., J. J. Jr Schultz, and M. F. Zimbelman. 2000. Empirical research on external auditors’ detection of financial statement fraud. Journal of Accounting Literature 19: 190-246.
Palmrose, Z. V. and S. W. Scholz. 2004. The circumstances and legal consequences of non-gaap reporting: evidence from restatements. Contemporary Accounting Research 21(1): 139-178.
Palmrose, Z-V., V. Richardson, and S. Scholz. 2004. Determinants of market reactions to restatement announcements. Journal of Accounting and Economics 37(1): 59-89.
Shumway, T. 2001. Forecasting bankruptcy more accurately: a simple hazard model. Journal of Business 74(1): 101-124.

Chapter 2
Abbott, L., Y. Park, and S. Parker. 2000. The effects of audit committee activity and independence on corporate fraud. Managerial Finance 26(11): 55-67.
Accounting Research and Development Foundation in Taiwan. 2006. The Auditor’s Responsibility to Consider Fraud in an Audit of Financial Statements: TSAS 43. Taipei, Taiwan.
Albrecht, W. S. and M. B. Romney. 1986. Red-flagging management fraud: a validation. Advances in Accounting 3: 323-334.
American Institute of Certified Public Accountants (AICPA). 2002. Consideration of Fraud in a Financial Statement audit: SAS 99, New York, NY: AICPA.
Apostolou, B., J. Hassell, S. Webber, and G. Sumners. 2001. The relative importance of management fraud risk factors. Behavioral Research in Accounting 13: 1-24.
Asare, S. K. and A. M. Wright. 2004. The effectiveness of alternative risk assessment and program planning tools in a fraud setting. Contemporary Accounting Research 21(2): 325-352.
Association of Certified Fraud Examiners (ACFE). 2008. 2008 Report to the Nation on Occupational Fraud & Abuse. Electronic Version, Retrieved February 20, 2009 from http://www.acfe.com/documents/2008-rttn.pdf.
Barth, M. E., J. A. Elliot, and M. W. Finn. 1999. Market rewards associated with patterns of increasing earnings. Journal of Accounting Research 37(2): 387-413.
Beasley, M. S., J. V. Carcell, D. R. Hermanson, and P. D. Lapides. 2000. Fraudulent financial reporting: consideration of industry traits and corporate governance mechanisms. Accounting Horizons 14(4): 441-454.
Beasley, M. S., J. V. Carcello, and D. R. Hermanson. 1999. Fraudulent Financial Reporting: 1987-1997 An Analysis of U. S. Public Companies, Committee of Sponsoring Organizations of the Treadway Commission. Jersey City, NJ: AICPA.
Beasley, M. 1996. An empirical analysis of the relation between the board of director composition and financial statement fraud. The Accounting Review 71(4): 443-465.
Bell, T. B. and J. V. Carcello. 2000. A decision aid for assessing the likelihood of fraudulent financial reporting. Auditing: A Journal of Practice & Theory 19(1): 169-184.
Bell, T. B., S. Szykowny, and J. J. Willingham. 1991. Assessing the likelihood of fraudulent reporting: a cascaded logic approach. Working Paper, KPMG Peat Marwick.
Black, E. L. 1998. Life-cycle impacts on the incremental value-relevance of earnings and cash flow measures. The Journal of Financial Statement Analysis 4(1): 40-56.
Blocher, E., and J. C. Cooper. 1988. A study of auditors’ analytical review performance. Auditing: A Journal of Practice and Theory 7(2): 1-28.
Blocher, E. 1992. The Role of Analytical Procedures in Detecting Management Fraud. Montvale, NJ: Institute of Management Accountants.
Bonner, S. E., Z-V. Palmrose, and S. M. Young. 1998. Fraud type and auditor litigation: an analysis of SEC accounting and auditing enforcement releases. The Accounting Review 73(4): 503-532.
Bratton, W. 2002. Enron and the dark side of shareholder value. Tulane Law Review 76: 1275-1361.
Calderon, T. G. and B. P. Green. 1994. Analysts’ forecasts as an exogenous risk indicator in analytical auditing. Advances in Accounting 12: 281-300.
Claessens, S., S. Djankov, and L. H. P. Lang. 2000. The separation of ownership and control in East Asian corporation. Journal of Financial Economics 58(1-2): 81-112.
Collins, D. W., M. Pincus, and H. Xie. 1999. Equity valuation and negative earnings: the role of book value of equity. The Accounting Review 74: 29-61.
Cottrell, D. M. and W. S. Albrecht. 1994. Recognizing the symptoms of employee fraud. Health Care Financial Management May: 19-25.
Cox, D., M. La Caze, and M. Levine. 2005. Integrity. Zalta, E. N. (ed.) 2005. The Stanford Encyclopedia of Philosophy. Fall 2005 Edition. URL = <http://plato.stanford.edu/archives/fall2005/entries/ integrity/>. (last viewed 7 March 2009).
Crask, M. R. and W. D. Jr. Perreault. 1977. Validation of discriminant analysis in marketing research. Journal of Marketing Research 14(1): 60-68.
Cressey, D. R. 1953. Other People’s Money: A Study in the Social Psychology of Embezzlement. Glencoe, IL: Free Press.
Deakin, S. and S. J. Konzelmann, 2004. Learning from Enron. Corporate Governance – An International Review 12(2): 134–142.
Dechow, P. M., R. G. Sloan, and A. P. Sweeney. 1996. Causes and consequences of earnings manipulation: an analysis of firms subject enforcement actions by the SEC. Contemporary Accounting Research 13(1): 1-36.
Degeorge, F., J. Patel, and R. Zeckhauser. 1999. Earnings management to exceed thresholds. Journal of Business 72(1): 1-33.
Duke, J. C. and H. C. Hunt III. 1990. An empirical examination of debt covenant restrictions and accounting-related debt proxies. Journal of Accounting & Economics 12(1-3): 45-63.
Eining, M., D. Jones, and J. Loebbecke. 1997. Reliance on decision aids: an examination of auditors’ assessment of management fraud. Auditing: A Journal of Practice and Theory 16(2): 1-19.
General Accounting Office. 2002. Financial Statement Restatements: Trends, Market Impacts, Regulatory Responses, and Remaining Challenges. GAO-03-138.
Greene, W. 1999. Econometric Analysis. Macmillan, New York.
Hansen, J. V., J. B. McDonald, W. F. Messier, Jr., and T. B. Bell. 1996. A generalized qualitative-response model and the analysis of management fraud. Management Science 42: 1022-1032.
Hayn, C. 1995. The information content of losses. Journal of Accounting and Economics 20(2): 125-153.
Heiman-Hoffman, V. B., K. P. Morgan, and J. M. Patton. 1996. The warning signs of fraudulent financial reporting. Journal of Accountancy 182(4): 75-81.
Hoogs, B., T. Kiehl, C. Lacomb, and D. Senturk. 2007. A genetic algorithm approach to detecting temporal patterns indicative of financial statement fraud. Intelligent Systems in Accounting Finance and Management 15(1/2): 41-56.
Hosmer, D. W., and S. Lemeshow. 2000. Applied Logistic Regression. Second edition, New York, NY: John Wiley and Sons, Inc.
Hsu, Po-Yen. 2003. An empirical analysis of the potential factors of financial statement fraud. Master dissertation, National Taiwan University. (in Chinese)
Huang, Yu-Kai. 2006. The detecting model of financial fraud. Master dissertation, National Chengchi University. (in Chinese)
International Federation of Accountants (IFAC). 2002. The Auditors’ Responsibility to Consider Fraud in an Audit of Financial Statements: ISA 240. New York, NY: IFAC.
Jensen, M. C. 1993. The modern industrial revolution, exit, and the failure of internal control systems. Journal of Finance 48(3): 831-880.
Kaminski, K., T. Wetzel, and L. Guan. 2004. Can financial ratios detect fraudulent financial reporting? Managerial Auditing Journal 19(1): 15-28.
Kasznik, R. and M. McNichols. 2002. Does meeting earnings expectations matter? Evidence from analyst forecast revisions and share prices. Journal of Accounting Research 40(3): 727-759.
Kirkos, E., C. Spathis, and Y. Manolopoulos. 2007. Data mining techniques for the detection of fraudulent financial statements. Expert Systems with Applications 32(4): 995-1003.
Krishnan, J. and J. Krishnan. 1997. Litigation risk and auditor resignations. The Accounting Review 72(4): 539-560.
Krishnan, J. 2005. Audit committee quality and internal control: an empirical analysis. The Accounting Review 20(5): 649-675.
La Porta, R., F. Lopez-de-Silanes, and A. Shleifer. 1999. Corporate ownership around the world. Journal of Finance 54(2): 471-517.
La Porta, R., F. Lopez-de-Silanes, A. Shleifer, and R.W. Vishny. 2002. Investor protection and corporate valuation. Journal of Finance 57(3): 1147-1171.
Lee, T. S. and Y. H. Yeh. 2004. Corporate governance and financial distress: evidence from Taiwan. Corporate Governance – An International Review 12(3): 378-388.
Lin, Sin-Jin. 2007. The study of detecting financial statement fraud – using data mining. Master dissertation, Chinese Culture University. (in Chinese)
Lipe, R. C., L. Bryant, and S. K. Widener. 1998. Do nonlinearity, firm-specific coefficients, and losses represent distinct factors in the relation between stock returns and accounting earnings? Journal of Accounting and Economics 25(2): 195-214.
Loebbecke, J. K., M. M. Eining, and J. J. Willingham. 1989. Auditors’ experience with material irregularities: frequency, nature, and detectability. Auditing: A Journal of Practice & Theory 9(1): 1-28.
Lopez, T. J. and L. Rees. 2002. The effect of beating and missing analysts’ forecasts on the information content of unexpected earnings. Journal of Accounting, Auditing, and Finance 17(2): 155-184.
Ma, Hsiu-Ru. 2006. The responsibility of cpa to detect financial fraud- about TSAS No. 34. Accounting Research Monthly 253(12): 44-61. (in Chinese)
McFadden, D. 1974. Conditional Logit Analysis of Qualitative Choice Behavior. in Zarembka P. (ed), Frontiers in Econometrics, Academic Press, New York, 105-142.
Menard, S. 1995. Applied Logistic Regression Analysis. Thousand Oaks, CA: SAGE Publications.
Moyes, G. D. and I. Hasan. 1996. An empirical analysis of fraud detection likelihood. Managerial Auditing Journal 11(3): 41-47.
Neter, J., W. Wasserman, and M. H. Kunter. 1990. Applied Linear Statistical Models. 3rd ed. Chicago: Irwin.
Nieschwitz, R. J., J. J. Schultz, and M. F. Zimbelman. 2000. Empirical research on external auditors’ detection of financial statement fraud. Journal of Accounting Literature 19: 190-246.
O’Reilly, V. M., P. J. McDonnell, B. N. Winograd, J. S. Gerson, and H. R. Jaenicke, eds. 1998. Montgomery’s Auditing. 12th ed. New York. NY: John Wiley & Sons.
Owusu-Ansah, S., G. D. Moyes, P. B. Oyelere, and D. Hay. 2002. An empirical analysis of the likelihood of detecting fraud in New Zealand. Managerial Auditing Journal 17(4): 192-204.
Palmrose, Z. V. and S. W. Scholz. 2004. The circumstances and legal consequences of Non-GAAP reporting: evidence from restatements. Contemporary Accounting Research 21(1): 139-178.
Persons, O. 1995. Using financial statement data to identify factors associated with fraudulent financial reporting. Journal of Applied Business Research 11(3): 38-46.
Pincus, K. V. 1989. The efficacy of a red flags questionnaire for assessing the possibility of fraud. Accounting, Organizations, and Society 14 (1-2): 153-163.
Press, E. G. and J. B. Weintrop. 1990. Accounting-based constraints in public and private debt agreements: their association with leverage and impact on accounting choice. Journal of Accounting and Economics 12(1-3): 65-95.
Ramos, M. 2003. Auditors’ responsibility for fraud detection. Journal of Accountancy 195(1): 28-36.
Shu, S. 2000. Auditor resignations: clientele effects and legal liability. Journal of Accounting and Economics 29(2): 173-205.
Skousen, C. J. and C. J. Wright. 2006. Contemporaneous risk factors and the prediction of financial statement fraud. Working paper, University of Texas at Arlinton.
Sorenson, J. E., H. D. Grove, and F.H. Selto. 1983. Detecting management fraud: an empirical approach. Symposium on Auditing Research 5: 73-116.
Stice, J. D. 1991. Using financial and market information to identify pre-engagement factors associated with lawsuits against auditors. The Accounting Review 66(3): 516-533.
Swartz, M., and S. Watkins. 2003. Power Failure: The Inside Story of the Collapse of Enron. New York: Doubleday.
Tukey, J. W. 1958. Bias and confidence in not-quite large samples. Annals of Mathematical Statistics 29(2): 614.
Wang, Yu-Hsiang. 2006. A study on the correlation between internal control risk and fraud of tse and otc listed companies, Master dissertation, National Chung Hsing University. (in Chinese)
Wilks, T. J. and M. F. Zimbelman. 2004. Decomposition of fraud-risk assessments and auditors’ sensitivity to fraud cues. Contemporary Accounting Research 21(3): 719-745.
Young, B. 2005. Related-party transactions: why they matter and what is disclosed. The Corporate Governance Advisor 13(4): 1-7.
Zmijewski, M. E. 1984. Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research 22 (Supplement): 59-82.

Chapter 3
Allison, P. 1982. Discrete-time methods for the analysis of event histories. Sociological Methodology 13: 61-98.
Altman, E. I. 1968. Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy. Journal of Finance 23(4): 589-609.
Altman, I. and D. A. Taylor. 1973. Social Penetration: The Development of Interpersonal Relationship. New York, NY: Rinehart & Winston.
Altman, E. I., G. G. Haldeman, and P. Narayanan. 1977. Zeta analysis: a new model to identify the bankruptcy risk of corporations. Journal of Banking and Finance 1: 29-54.
Altman, E. 1993. Corporate Financial Distress and Bankruptcy: A Complete Guide to Predicting & Avoiding Distress and Profiting from Bankruptcy. New York, NY: Wiley.
Anderson, K. L. and T. L. Yohn. 2002. The effect of 10-k restatements on firm value, information asymmetries, and investors’ reliance on earnings. Working paper, Georgetown University, Washington, DC.
Beasley, M. 1996. An empirical analysis of the relation between the board of director composition and financial statement fraud. The Accounting Review 71(4): 443-465.
Beaver, W. 1966. Financial ratios as predictors of failure, empirical research in accounting: selected studies. Journal of Accounting Research 4(3): 71-111.
Beck, N., J. Katz, and R. Tucker. 1998. Taking time seriously: time-series-cross-section analysis with a binary dependent variable. American Journal of Political Science 42(4): 1260-1288.
Berg, D. 2007. Bankruptcy prediction by generalized additive models. Applied Stochastic Models in Business and Industry 23: 129-143.
Blum, M. 1974. Failing company discriminant analysis. Journal of Accounting Research 12(1): 1-25.
Brown, C. C. 1975. On the use of indicator variables for studying the time dependence of parameters in a response-time model. Biometrics 31(4): 863-872.
Byar, D. P. and N. Mantel. 1975. Some interrelationships among the regression coefficient estimates arising in a class of models appropriate to response-time data. Biometrics 31(4): 943-947.
Chen, Chien-Pin. 2003. Study of including corporate governance variable in to financial crisis prediction model: application logistic model. Master dissertation, Tamkang University. (in Chinese)
Chen, H. L. 2002. Financial statement credibility and auditing quality with the financial statement restatement side – one of the financial transparency estimate. Money Watching and Credit Rating 37: 77-86. (in Chinese)
Chow, G. C. 1960. Tests of equality between sets of coefficients in two linear regressions. Econometrica 28: 591-605.
Claessens, S., S. Djankov, and L. H. P. Lang. 2000. The separation of ownership and control in East Asian corporation. Journal of Financial Economics 58(1-2): 81-112.
Collins, R. A. and R. D. Green. 1982. Statistical method for bankruptcy forecast. Journal of Economics and Business 34: 348-354.
Cox, D. 1972. Regression models and life-table. Journal of the Royal Statistical Society 34(2): 187-200.
Crask, M. R. and W. D. Jr. Perreault.1977. Validation of discriminant analysis in marketing research,” Journal of Marketing Research 14(1): 60-68.
Dechow, P. M., R. G. Sloan, and A. P. Sweeney. 1996. Causes and consequences of earnings manipulation: an analysis of firms subject enforcement actions by the SEC. Contemporary Accounting Research 13(1): 1-36.
General Accounting Office. 2002. Financial Statement Restatements: Trends, Market Impacts, Regulatory Responses, and Remaining Challenges. GAO-03-138.
Gombola, M. J., M. E. J. Haskins, E. Keta, and D. Williams. 1987. Cash flow in bankruptcy prediction. Financial Management 16(4): 55-65.
Griffin, P .A., J. Grundfest, and M.A. Perino. 2004. Stock price response to news of securities fraud litigation: an analysis sequential and conditional information. Abacus 40(1): 21-48.
Hillegeist, S., D. Cram, E. Keating, and K. Lundstedt. 2004. Assessing the probability of bankruptcy. Review of Accounting Studies 9(1): 5–34.
Hribar, P. and N. T. Jenkins. 2004. The effect of accounting restatements on earnings revisions and the estimated cost of capital. Review of Accounting Studies 9(2-3): 337-356.
Jensen, M. C. 1993. The modern industrial revolution, exit, and the failure of internal control systems. Journal of Finance 48(3): 831-880.
Kiefer, N. M. 1988. Economic duration data and hazard functions. Journal of Economic Literature 26(2): 646-679.
Krishnan, J. and J. Krishnan. 1997. Litigation risk and auditor resignations. The Accounting Review 72(4): 539-560.
La Porta, R., F. Lopez-de-Silanes, and A. Shleifer. 1999. Corporate ownership around the world. Journal of Finance, 54(2), 471-517.
Lancaster, T. 1990. The Econometric Analysis of Transition Data. New York: Cambridge University Press.
Lee, T. S. and Y. H. Yeh. 2004. Corporate governance and financial distress: evidence from Taiwan. Corporate Governance – An International Review 12(3): 378-388.
Lo, A.W. 1986. Logit versus discriminant analysis — a specification test and application to corporate bankruptcies. Journal Econometrics 31(2): 151-178.
Loebbecke, J. K., M. M. Eining, and J. J. Willingham. 1989. Auditors’ experience with material irregularities: frequency, nature, and detectability. Auditing: A Journal of Practice & Theory 9(1): 1-28.
Louwers, T. J., F. M. Messina, and M.D. Richard. 1999. The auditor’s going-concern disclosure as a self-fulfilling prophecy: a discrete-time survival analysis. Decision Science 30(3): 805-824.
Mantel, N. and B. Hankey. 1978. A logistic regression analysis of response-time data where the hazard function is time dependent. Communications in Statistics—Theory and Methods A7: 333-347.
Martin, D. 1977. Early warning of banking failure. The Journal of Banking and Finance 1: 249-276.
McFadden, D. 1974. Conditional Logit Analysis of Qualitative Choice Behavior. in Zarembka P. (ed). Frontiers in Econometrics, New York, NY: Academic Press.
Meyer, P. A. and H. W. Pifer. 1970. Prediction of bank failures. Journal of Finance 25: 853-868.
Myers, M. H., B. F. Hankey, and N. Mantel. 1973. A logistic-exponential model for use with response-time data involving regressor variables. Biometrics 29(2): 257-269.
Ohlson, J. 1980. Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research 18(1): 109-131.
Palmrose, Z. V. and S. W. Scholz. 2004. The circumstances and legal consequences of Non-GAAP reporting: evidence from restatements. Contemporary Accounting Research 21(1): 139-178.
Palmrose, Z-V., V. Richardson, and S. Scholz. 2004. Determinants of market reactions to restatement announcements. Journal of Accounting and Economics 37(1): 59-89.
Shu, S. 2000. Auditor resignations: clientele effects and legal liability. Journal of Accounting and Economics 29(2): 173-205.
Shumway, T. 2001. Forecasting bankruptcy more accurately: a simple hazard model. Journal of Business 74(1): 101-124.
Smith, R. F. and A. H. Winkor. 1930. A test analysis of unsuccessful industrial companies. University of Illinois of Bureau of Business Research Bulletin 31.
Sorenson, J. E., H. D. Grove, and F.H. Selto. 1983. Detecting management fraud: an empirical approach. Symposium on Auditing Research 5: 73-116.
Stice, J. D. 1991. Using financial and market information to identify pre-engagement factors associated with lawsuits against auditors. The Accounting Review 66(3): 516-533.
Tam, K. and M. Kiang. 1992. Managerial applications of neural networks: the case of bank failure predictions. Management Science 38(7): 926-947.
Theodossiou, P., E. Kahya, G.C. Philippatos, and R. Saidi. 1996. Financial distress corporate acquisitions: further empirical evidence. Journal of Business Finance and Accounting 23(5-6): 699-719.
Thompson, W. A. Jr. 1977. On the treatment of grouped observations in life studies,. Biometrics 33(3): 463-470.
Tukey, J. W. 1958. Bias and confidence in not-quite large samples. Annals of Mathematical Statistics 29(2): 614.
Wang, Wu-Chang, 2005. Financial distress score, corporate governance and stock price performance. Master dissertation, National Chung Hsing University. (in Chinese)
Wu, TsingZai C. and Wan-Ting Hsieh. 2004. Using discrete-time hazard models to forecast financially distressed firms delisted from the Taiwan Stock Exchange and the TAISDAQ. The International Journal of Accounting Studies 39: 56-88. (in Chinese)
Zhang, G., M.Y. Hu, and B. E. Patuwo. 1999. Artificial neural networks in bankruptcy prediction: general framework and cross-validation analysis. European Journal of Operational Research 116: 16–32.
Zmijewski, M. E. 1984. Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research 22 (Supplement): 59-82.

Chapter 4
Anderson, K. L. and T. L. Yohn. 2002. The effect of 10-k restatements on firm value, information asymmetries, and investors’ reliance on earnings. Working paper, Georgetown University, Washington, DC.
Griffin, P .A., J. Grundfest, and M.A. Perino. 2004. Stock price response to news of securities fraud litigation: an analysis sequential and conditional information. Abacus 40(1): 21-48.
Loebbecke, J. K., M. M. Eining, and J. J. Willingham. 1989. Auditors’ experience with material irregularities: frequency, nature, and detectability. Auditing: A Journal of Practice & Theory 9(1): 1-28.
Palmrose, Z. V. and S. W. Scholz. 2004. The circumstances and legal consequences of Non-GAAP reporting: evidence from restatements. Contemporary Accounting Research 21(1): 139-178.
Palmrose, Z-V., V. Richardson, and S. Scholz. 2004. Determinants of market reactions to restatement announcements. Journal of Accounting and Economics 37(1): 59-89.
Sorenson, J. E., H. D. Grove, and F.H. Selto. 1983. Detecting management fraud: an empirical approach. Symposium on Auditing Research 5: 73-116.