Investigating the Relationship between Predicted Financial Distress and Earnings management Approaches Based on Structural Equations

  The main objective of this paper is to investigate the relationship between predicted financial distress and earnings management approaches. We predict financial distress for 312 stock market listed and out-listed companies from 2006 to 2015 using C5 decision tree model. Then the relationship between financial distress prediction and earnings management approaches was observed using multivariate linear regression model (structural equation modeling approach). The results showed that there is a significantly negative relationship between predicted financial distress and the first actual activity earnings management index, while there was a significantly positive relationship between the predicted financial distress and the second actual activity earnings management index and the accrual earnings management index. We concluded that distressed companies in comparison with other companies will be able to manipulate their earnings significantly by increasing operating cash flows and accrual items and also by decreasing costs. It was also found that earnings management tools are influenced by the type of industry and the predicted financial distress and earnings management tools affected each other through the cause and effect relationship.