Investigating the Explanatory Power of Accrual Models Using Timing and Matching Properties of Cash Flows

In accounting systems, accrual accounting items are considered as an essential element in achieving the main objectives of financial reporting. However, many researchers believe that there is not enough understanding of the process of emerging accruals. The aim of this study is to understand whether cash-flow changes, serial correlation in cash-flow changes, and operating cash cycle, which capture the timing and matching properties of cash flows add any incremental explanatory power to various accrual models, this issue has been neglected in all models of accruals. In order to answer to the research question by adding timing and matching properties of cash flows as serial correlation indicators to the models for predicting accruals such as: The Jones (1991) model, the McNichols (2002) model that combines the Jones (1991) model with the Ball and Shivakumar (2006) model that considers the asymmetric loss recognition in accruals. In this regard, 121 companies listed on the Tehran Stock Exchange were selected and tested between 1388 and 1397(Iranian calendar). The test results showed that accruals and cash flow changes have a negative and significant relationship, and when the serial correlation of cash flow changes are more negative, this inverse relationship increases. The research results also confirm the existence of a positive relationship between accrual items with revenue changes and the operational cash cycle.The above findings indicate that adding timing and matching properties of cash flows to the Jones (1991), McNichols (2002) and Wing and Shivakomar (2006) models can improves the explanatory power of these models.