UCLA

This study investigates the role of earnings quality (EQ) in the prediction of financial distress. Specifically, I predict and find that EQ is positively associated with the informativeness of both accounting- and price-based distress predictors, and negatively associated with distress risk, itself. These results hold across several EQ measures and various distress prediction models, and are driven by both components of EQ measures - that related to firm fundamentals and that related to managerial discretion. Furthermore, I find that incorporating the impact of EQ improves prediction models' out-of-sample performance, especially when the forecast horizon is longer than one year. These results contribute to the literature by documenting that EQ impacts the prediction of financial distress, the most crucial input in the lending process.