中文摘要：

利用26个财务变量建立分类回归树模型对会计信息失真进行识别研究，结果表明所建模型对会计信息失真企业的正确识别率达到80％以上，能将第二类错误率控制在20％以下。实证还发现留存收益在总资产中的比率小于2％的公司很容易出现会计信息失真，最后作者利用8年数据对该结果进行检验，表明其识别能力非常出色。

英文摘要：

In this paper, we established a CART model with 26 financial variables, and found that： the CART model can achieve over 80 % correct recognition rate for distortion accounting information and control the second class mistake under 20 %. We also found that companies whose ratio of retained earnings to total assets is less than 2 % are easily involved in delivering a fraudulent financial statement to the public, and this result is proved to be effective with data from 2000 to 2007.