Determining the Effective Organizational Characteristics on the Inventory Valuation Methods: Multinomial Logistic Regression Approach in an Emerging Economy

Subject Areas : Tectonostratigraphy

Arash Arianpoor ¹ , Zaid Salman ²

1 - Department of Accounting, Attar Institute of Higher Education, Mashhad, Iran
2 - Department of Accounting, Imam Reza International University, Mashhad, Iran

Received: 2023-06-18 Accepted : 2023-08-18 Published : 2023-07-01

Keywords: Inventory valuation methods, Weighted Average Cost (WAC), First-In-First-Out (FIFO), Firm’ s characteristics, Inventory,

Abstract :

This study investigates the effective characteristics of the company on the choice type of inventory valuation methods and evaluates the probabilities of using these methods for companies listed on the Iraq Stock Exchange. 35 companies' data during 8 years from 2014 to 2021 was examined. In this research, inventory accounting methods are defined as dependent variables. FIFO, WAC, and moving average methods are the most commonly used measure for evaluating inventories by most Iraqi industrial companies. Considering that the dependent variable type is a multi-level qualitative, the Multinomial Logistic Regression (MLR) was used. According to the results of Multinomial Logistic Regression and simple method, the working capital, ROA, and current ratio have a significant effect on the choice of FIFO and WAC valuation methods, while the industry type has only a significant effect on the choice of WAC valuation method. According to the results of the Bootstrap method, ROA and current ratio have a significant effect on the choice of FIFO and WAC valuation methods, while the working capital and Industry type, have a significant effect on the choice of WAC valuation method. Analysis based on robustness checks and the t+1 test confirmed these results. In addition, the results show that companies are more likely to use the WAC method than other methods.