Empirical Studies in Financial Accounting

Abstract Abstract

This study examines the effect of classification shifting–based earnings management on the risk of stock price crash. Classification shifting increases operating profit by reallocating operating expenses to non-operating items without altering net income, making it a low-cost tool for concealing negative performance news and thereby increasing crash risk. The sample consists of 129 listed companies over the period 2012–2023 (with additional data from 2007 for classification-shifting calculations). Crash risk is measured using negative return skewness and down-to-up volatility. The findings show that classification shifting has a significant negative relationship with crash risk in both measures, indicating a higher probability of crash when such shifting is used more extensively. Moreover, a larger gap between operating profit and net income weakens this negative relationship. Cash flow volatility and information asymmetry exhibit a positive effect on crash risk only under the negative skewness measure and weaken the main relationship, whereas financial leverage shows no significant effect.

Keywords: Reclassification-based earnings management, stock price crash risk, information asymmetry, cash flow volatility.



Introduction

Earnings management is used by managers to influence financial reports, creating a favorable short-term image but increasing long-term stock price crash risk. A less examined method is classification shifting, where operating expenses are moved to non-operating items to inflate operating income without affecting net income, making it difficult for investors to detect. First highlighted by McVay (2006), this method is influential because investors generally rely more on operating income than on net income.

Research shows that overstated operating earnings mislead investors and can raise crash risk. In Iran, although classification shifting has been introduced in prior studies, its effect on stock price crash risk has received limited attention. Weak auditor oversight, low implementation cost, and the lack of clear classification standards allow firms to improve the appearance of financial performance by reallocating income-statement items.This study investigates how classification shifting affects stock price crash risk among firms listed on the Tehran Stock Exchange and examines moderating factors such as information asymmetry, cash flow volatility, and capital structure. It presents the theoretical background, research models, and empirical results.



Methods & Material

The present study examines the relationship between earnings management through classification shifting and stock price crash risk, with the moderating role of information asymmetry, cash flow volatility, and capital structure. Accordingly, this research is descriptive–correlational in nature. In terms of purpose, it is an applied study. The required data include items from financial statements and the accompanying notes available in the “Rahavard Novin” comprehensive database and the comprehensive corporate information database on the official website of the Tehran Stock Exchange, which were extracted as needed. The collected data were organized using Excel in the form of data files, after which the relevant variables were calculated and ultimately analyzed using EViews software.

The statistical population of the study consists of all companies listed on the Tehran Stock Exchange during the years 2012 to 2023and the research sample includes 129 companies.



Findings

The results showed that classification shifting has a negative and significant relationship with stock price crash risk, meaning that greater use of this method increases the likelihood of a crash. Moreover, an increase in the gap between operating income and net income weakens the strength of this relationship. Cash flow volatility and information asymmetry have a positive effect on crash risk only when using the negative skewness measure, thereby weakening the main relationship, whereas capital structure (financial leverage) had no significant role.



Conclusion & Results

This study investigates the relationship between earnings management through classification shifting and stock price crash risk in the Iranian capital market, considering the moderating roles of cash flow volatility, capital structure, and information asymmetry. The results indicate that, unlike international studies, classification shifting in Iran has a negative and significant effect on crash risk, as managers primarily use it to smooth earnings and present a stable performance, rather than to hide bad news. The gap between operating and net income weakens this negative effect, as lower earnings quality reduces the credibility of reclassification signals. Cash flow volatility increases uncertainty and weakens the stabilizing effect of classification shifting, raising crash risk, whereas financial leverage shows no significant impact. Information asymmetry has a direct positive effect on crash risk but does not significantly moderate the relationship between classification shifting and crash risk. Overall, in the Iranian market, classification shifting functions as a stabilizing tool, smoothing earnings, reducing informational uncertainty, and lowering stock price crash risk, while cash flow volatility and low earnings quality can weaken its effectiveness.

Abstract On the basis of Pecking Order Theory, when firms need resources
they usually rely on debts since capital is considered expensive due to
information asymmetry. Moral hazard is a kind of information
asymmetry; therefore, it is expected that it has relationship with
capital structure. The purpose of this study is to investigate the impact
of moral hazard on capital structure. In order to conduct the research
132 firms were selected from listed firms in Tehran Stock Exchange
between years 2006_2012.research hypothesis was tested using
structural equation model. The results show that moral hazard has
significant negative impact on capital structure, and the negative effect
of moral hazard on capital structure is moderated by control variables

Abstract The company's ability to identify potential funding sources both internal and external, are the main factors of growth and development. The main objective of companies is to maximize shareholder wealth and the company's capital structure is one of the factors contributing to this, that involve financial resources commensurate with the risk and return.
On the other hand, several studies have shown that due to the problems of the traditional theory of capital structure, one of the most important factors, affecting the issues of financing in companies, is financial flexibility. This study examines the impact of financial flexibility on capital structure decisions. For this purpose, the companies listed in Tehran Stock Exchange, 108companies were selected and financial data for the years 1382 to 1392 were studied. The results indicate that current period financial flexibility has a significant and positive relationship with capital structure. The results also suggest that for companies that have negative marginal value of cash, financial flexibility in capital structure decisions, is a priority.

Abstract Ability of companies to identify potential internal and external financing resources is an important factor fortheir growth and improvement. Main objectiveof companies is to maximize their shareholders' wealth, and capital structure is one of the effective factors for this purpose which requires optimal use of financial resources to create proper returns regarding risk taken by companies. Based on data derived from a sample of 157 companies listed on Tehran Stock Exchange (TSE) from 1383 to 1389, this study examined relationship between company characteristics and capital structure.Approach of this study is descriptive-correlative, and panel data statistical method was used to test the hypotheses. Test results showthatsize, tangibleassets, andbusiness risk of the company have a significant positive relationshipwithcapital structure; and growth opportunities of the company has a significant negative relationship with it. However, the results do not show any meaningful relationship between age and industry of the company and capital structure

Abstract Choosing between debt financing and capital financing influenced by internal and external factors impacting companies' capital structure. The main goal of determining capital structure is to recognize the combination of financial resources to maximize stockholders' wealth. Because of the qualitative aspects of capital formation in high-tech companies, there has been huge investments in these companies which doesn’t seem to be a rational behavior in the investment community; Therefore it seems necessary to compare high-tech and traditional company’s capital structure.
In this paper, in order to investigate the capital structure of high-tech and traditional companies and also comparing linear and non-linear models, companies are divided into two groups, high-tech and traditional companies. We collected year-company data of 378 companies during 2004- 2009 for the analysis using multiple regression and artificial neural network.
The findings of this study indicate that liability ratio and financial leverage decisions in two above mentioned companies are different. The capital structure criterion in both industries has significantly different and non-linear models of capital structure in comparison with linear ones are more powerful in prediction

Abstract Decision making about capital structure and determining its effectiveness is increasingly important subject in managing of firms. In addition, earnings management is one of the effective factors on capital structure in corporate governance subjects. This study aimed to investigate the impact of earnings management, Profitability ratios and firm size on the capital structure of listed companies of Tehran Stock Exchange (TSE) in the period of 1382-1386.  A sample of 125 companies of TSE was taken for research study. For the analysis of data, multiple regression model approach was applied. Gearing ratio was taken as dependent variable whereas absolute discretionary accruals, ROA, ROE, and Size were used as independent variables. The results indicate that absolute discretionary accruals have insignificant effect on dependent variable. According to the results, Size, and   ROE have positive Impact on the capital structure of the listed companies in Tehran stock exchange.

Abstract This article explores the changes and effects of capital structure on the production of products.  For this purpose we test hypotheses with simple and logistic multi-regression analysis. This research use data related to 341 corporations that were listed in Tehran Stock Exchange from 1378 to 1387. The findings of the research are follows: A significant statistic relation was seen between the components of capital  structure  (The only exceptions were registered  capital) and companies'  capacity  in  getting  access  to  the  predicted  products. Between change in short-term liabilities, allowance for labors' work and retained   earnings   in capital structure and actualization of predicted products are observes a statistically significant relation. In addition, components of capital structure and changes in them can predict ability of manufacturing amount that predicted in first of fiscal year. Lastly the results show that with over use components of capital structure and changes in them one can predict through 95.9 percent increase or decrease in products manufacturing.

Abstract The firms' capital structure plays an important role in investment decision making. The main goal of this paper is review the relationship between capital structure and profitability measures in Tehran Stock Exchange. Therefore 189 sample firms that their required data for a nine years period (1375-1383) was available are selected. Then the relation between profitability ratios and capital structure is reviewed. Four industries of sample statistic, that had more firms, are selected to examine the hypotheses too. The panel data regression is used to examine the hypotheses. Signification of the models is examined by T and F statistics.