فصلنامه مطالعات تجربی حسابداری مالی
پیاپی 75 (پاییز 1401)

Development of Earnings quality measures, especially Accruals quality measures, has been a critical line of research over more than three decades. Literature indicates that linear-regression-based measures are subject to (suffer from) significant estimation error in non-discretionary accruals estimation. Therefore, recent research used machine learning algorithms including multilayer perceptron and radial basis neural networks, in order to address the issue. However, being founded on Blackbox approach limits future development and applicability of these methods. So, to address the limitations, we have used Group Method of Handling Data (GMDH) approach, as a Whitebox approach, in order to estimate the accruals. Findings using data from 299 Tehran Securities Exchange listed companies during 1385 to 1397 suggests that GMDH-based models perform superior to regression models and multilayer perceptron neural networks in terms of estimation error measured by mean squared error. Moreover, Cash flow approach in total accruals calculation leads to less estimation error compared to balance sheet approach. As a result, the model developed in this article can be used by market participants such as regulators, analyst and auditors in order to detect probable financial reporting misstatements.

Today, information competition space, as an external importance mechanism, affects the company's management system and stable performance and government ownership in both complementary and destructive aspects can affect this impact. The purpose of this study is to investigate the effect of government ownership on the relationship between information competition and Earning persistenceof companies listed on the Tehran Stock Exchange.The statistical sample of the research includes 103 companies listed on the Tehran Stock Exchange for the period 2013 to 2020. In terms of purpose, the present study is an applied research using a post-event approach. For panel data, fixed-effect and random-effect models were used to estimate the research model using Eviews-8 software. The research results showed that information competition based on political relations and centralized institutional ownership increases Earning persistence and the interactive effect of government ownership with information competition further increases Earning persistence. That is, Government ownership and information competition are two complementary factors in achieving the goals of stakeholders.

This research has been conducted with the aim of experimental test of the effect of political relations on the amount of investment of companies and its efficiency in the period of 2012 to 2019 of companies listed in the Tehran Stock Exchange. The method of data collection is archival and reference to databases and the method of data analysis is multivariate regression model using panel data model and fixed effects method. The results show that the relationship between political relations and the amount of investment as well as investment efficiency is positive and significant. These results indicate that companies with political connections have more investment than other companies and investment efficiency is higher in companies with political connections. According to the research findings, it can be seen that companies with political connections invest more and more efficiently than other companies due to their government benefits and privileges, as well as the ease of attracting financial resources.

Financial statement comparability improves the quality of financial information and the information environment, and enabling users to identify similarities and differences between different companies, and evaluating the performance of managers and supervising them. So, it is expected that increasing the comparability of financial statements will limit the opportunism of managers. In this regard, in this study, the relationship between comparability of companies and debt maturity has been investigated. The data of the present study were collected using the financial information of 125 companies listed on the Tehran Stock Exchange in the period 2013 to 2019 (882 observation). To analyze the data, a multivariate linear regression model of the generalized least squares type by utilizing combined data was used. The results showed that there is a negative and significant relationship between the comparability of financial statements and the maturity of the company's debt. Therefore, it can be concluded that the Financial statement comparability plays an important role in aligning incentives in the company and by reducing information asymmetry and potential agency costs, can substitute for the use of short-term debt by serving as a corporate governance mechanism.

Audit task complexity, as one of the important and effective factors on the auditors' judgment and decision-making, is one of the controversial concepts in the audit field, which, due to its multidimensional nature, has led to many researches in the audit field. Despite the provision of individual indicators to measure audit task complexity in these studies, explaining a multidimensional model to measure of this fundamental concept in auditing is a problem that requires to research. It is expected that the explanation of such an index can lead to a better understanding of this concept and its dimensions and help auditors in planning audit task as well as ways to increase the quality of judgment and decision making. Accordingly, the current research purpose is to explain a model to measure for audit task complexity concept. For this purpose, information related to 128 companies in Tehran Stock Exchange during 2010-2019 was collected and tested through Partial Least Squares Structural Equation Modeling. Findings based on Constructive-Constructive measurement model and second-order Confirmatory Factor analysis showed that twenty-one factors effect on audit task complexity. Also, the results showed that audit task complexity is influenced by three dimensions of input, processing and output complexity. These findings, in addition to explaining the concept of audit task complexity, have helped to understand the effective factors and dimensions of this concept and can be useful in auditor's tasks planning and policy making and provide a more powerful tool to increase audit judgment quality.

We intended to provide a comprehensive overview of behavioral accounting research. For this purpose, 371 articles published in two specialized journals of behavioral accounting - "Behavioral Research in Accounting" and "Advances in Accounting Behavioral Research"- have been analyzed. These journals are indexed on the Scopus database and are among the specialist journals ranked by the Australian Business Deans Council. Co-word analysis and social network analysis have been used as the main method. Our analysis shows that emerging issues in recent years in the field of behavioral research have focused on "auditing", "corporate governance", "fraud" and "ethics". Findings show that the article "Online instrument delivery and participant recruitment services: Emerging opportunities for behavioral accounting research" with 167 citations is the most cited behavioral research article. Wicky Arnold is the top author in terms of number of articles with 12 articles. The United States is the top country in the world with 179 articles and 2,210 citations, and the two top universities in the world with 15 articles are the Virginia Commonwealth University and the University of Central Florida. This paper is the first study that conduct a bibliometric analysis of behavioral accounting research focusing on two specialized journals of behavioral accounting.

The two approaches are more prominent in the accounting literature, accrual-based earnings management and manipulating the actual activities however, the present study is considered the third type of earnings management model, namely a classification shifting. The purpose of this study is to investigate the effect of constraints on earnings management strategies on the application of shifting strategy in earnings classification in the Iranian capital market. The research sample consisted of 114 firms from 2013 to 2021 (1026 observation). Logistic regression models have been used to test research hypothesis. The results of the study show that financial health, institutional shareholders, audit firm size and market share have a negative and significant effect on the classification shifting. Also, the operating cycle has a positive and significant effect on the c classification shifting; and its tenure does not have a significant effect on the classification shifting. Additional tests indicated large companies have a greater incentive to do classification shifting (a form of earnings management) compared to small companies, because they have greater political costs.