Chinese corporate distress prediction using LASSO: The role of earnings management |
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| Affiliation: | 1. Department of International Business, Tunghai University, Taiwan; Department of International Business, National Taiwan University, Taiwan;2. Finance Discipline, College of Management, Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taiwan;3. Accounting Discipline, College of Management, Yuan Ze University, Taiwan;1. Finance Department, EDHEC Business School, 24 Avenue Gustave Delory, CS 50411, 59057 Roubaix Cedex 1, France;2. Accounting and Finance Division, Leeds University Business School, Moorland Rd, Leeds LS2 9JT, UK;1. Department of Economics and Statistics, University of Salerno, Via Giovanni Paolo II, 132 84084 Fisciano, SA, Italy;2. Department of Management and Information Technology, University of Salerno, Via Giovanni Paolo II, 132 84084 Fisciano, SA, Italy |
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| Abstract: | Motivated by recently increasing accounting manipulation cases and deteriorating economic condition in China, we investigate the importance of a set of earnings management predictors and develop up-to-date distress prediction model with earnings management consideration for the Chinese market. Employing annual firm-level data from January 2014 to December 2018, we find that real earnings management (REM) is robustly selected out as a key distress predictor via the variable selection technique LASSO. Our results consistently show that REM could improve early warning of distressed companies with a slight sacrifice of accuracy in predicting healthy companies. After considering the cost of misclassification, it is confirmed that REM contains incremental information about a forthcoming corporate distress risk. Meanwhile, our results also detect an interesting finding that in China, aggressive real earnings management signals the lower probability of corporate distress, indicating distressed firms have lower capacity to conduct REM. |
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