Research and Development Spending in Bankruptcy Prediction: Examining an Adjusted Ohlson O-score Model

Abstract: This thesis investigates whether bankruptcy prediction applying the Ohlson O-score model can be enhanced by modifying accounting variables associated with research and development (R&D) spending. To examine this, we study the expected risk of bankruptcy and R&D intensity among listed firms in the United States from 1990 to 2019. Through statistical tests, we determine whether accounting-based bankruptcy prediction can be improved through an adjustment for conservative R&D accounting. The findings of our study indicate that R&D intensive firms are more likely to be classified with the highest expected risk of bankruptcy and that the prediction accuracy of the Ohlson O-score model is enhanced through adjusting for conservative R&D accounting.