Forecast Accuracy Considering Accruals Earnings Volatility (Case Study of Iran and Iraq): A Spatial Econometric Approach

This study investigates how the quality of financial disclosure, influenced by accruals, impacts earnings volatility and the accuracy of earnings forecasts in banks from Iran and Iraq. We utilized a hybrid spatial panel model, analyzed through R and RStudio, to evaluate data from 22 Iranian banks and 44 Iraqi banks over the period of 2017 to 2022, taking into account spatial dependence. The results show that higher quality of disclosure leads to improved accuracy in earnings forecasts. Conversely, volatility in accruals—both short- and long-term—has a negative effect on forecast accuracy, indicating potential earnings management. Furthermore, our analysis reveals that larger and more established banks tend to have greater forecast accuracy, while higher book-to-market ratios and increased financial leverage are associated with lower accuracy. The strong spatial dependence observed among the banks emphasizes the necessity of considering spatial effects to avoid biased and inconsistent findings. Overall, this research underscores the importance of transparent and timely information disclosure in enhancing earnings forecast accuracy, providing valuable insights for investors, analysts, and regulators in the Iranian and Iraqi banking sectors. However, caution is advised when applying these findings to other contexts.

Forecast Accuracy Considering Accruals Earnings Volatility (Case Study of Iran and Iraq): A Spatial Econometric Approach Keywords:

Accruals Earnings Volatility , Disclosure Quality , earnings forecast accuracy , Hybrid Panel , Spatial Effects