Predict Earnings Management Research Articles

Investigating earnings management practices and the role of the board and committees in emerging markets: Evidence from Malaysian public companies

AbstractThis study was aims to examine the significant elements of the audit and board committee in predicting earnings management (EM) for the period of 2010–2021. The study population comprised total number of 775 listed firms on Bursa Malaysia's main market. The annual audited financial statements and reports of the listed firms, firm's websites, Bloomberg and the Bursa Malaysia website were used as method of data collection. The analytical method used in the current study was descriptive statistic and GLS methods of panel regression. The findings of this study suggested that firms with effective CG mechanisms such as, audit committee size (AUDSIZ), audit committee financial expertise (AUDFEXPT), remuneration and nomination committee (R&NC), supervisory board size (SBS), mitigates accrual, and REM. However, the findings also indicated that gender composition (CGEND) were found to be ineffective in predicting EM.

Do family-controlled and financially healthy firms manage their reported earnings? Evidence from Indonesia

This paper examines whether family-controlled and financially healthy firms practice earnings management. The data collection focuses on non-financial firms listed on the Indonesia Stock Exchange for the fiscal year 2017–2019. Family and financially healthy firms are key predictor variables for predicting earnings management behavior. Jones’s (1991) modified cross-sectional model measures discretionary accruals (the earnings management indicator). This study reveals a negative relationship between family entities and earnings management practices, suggesting that family-controlled firms are more likely to report a higher quality of earnings. This study also documents that family entities with financial difficulties have more incentive to practice earnings management. Additionally, the study indicates that the involvement of a family member in executive positions leads to lower financial reporting quality. Finally, this study reports a nonlinearity association between family share ownership and the magnitude of earnings management. The study’s findings may assist policymakers in considering the costs and benefits associated with various levels of ownership concentration, especially in the hands of family members.

Predicting earnings management through machine learning ensemble classifiers

AbstractIn this paper, we utilize six novel ensemble classifiers to predict earnings management (EM) in both its forms, accrual‐based earnings management (AEM) and real earnings management (REM), and then compare the EM prediction accuracy of wrapper feature selection (FS) and filtering FS techniques in the context of EM. Specifically, we integrate three well‐known filtering FS techniques (information gain [IG], principal component analysis [PCA], and relief [Re]) and three popular wrapper FS techniques (particle swarm optimization [PSO], genetic algorithm [GA], and artificial bee colony [ABC]) with the support vector machine (SVM) to generate our ensemble classifiers. We then assess the performance of each of the six ensemble classifiers to predict AEM and REM based on three criteria: type Ι error, type ΙΙ error, and average accuracy. The results show that the ABC‐SVM ensemble classifier outperforms the others in predicting both AEM and REM. We also find that, overall, wrapper FS ensemble classifiers outperform filtering FS ensemble classifiers in predicting AEM and REM and that it is more difficult for our ensemble classifiers to predict REM than to predict AEM. This paper contributes to the literature on EM prediction by introducing six new ensemble classifiers. It is also the first work (to the best of our knowledge) in the domain of ensemble classifiers' applications (a) to consider both REM and AEM in one context and to show that REM is more difficult to predict than AEM and (b) to compare the performance of wrapper and filtering FS techniques in the EM prediction setting.

Effect of Tax Incentives and Non-Tax Incentives on Earnings Management with Tax Avoidance as a Variable Moderation

Tax incentives and non-tax incentives are both potential motivators for earnings management activity. As a result, the study was conducted to determine the reality of various aspects that could effect profits management. It also conducted tests to demonstrate the impact of tax avoidance on the relationship between the research variables. This research employed secondary data from the Indonesia Stock Exchange for the year 2020, as well as a purposive sampling strategy to select the appropriate firm to serve as the sample. To aid in the testing of the variables, this study used the multiple linear regression model as an analysis tool utilizing IBM SPSS version 25. The findings suggest that tax incentives can be used to detect profits management, as measured by a proxy of tax planning and deferred tax expense. Non-tax incentives, on the other hand, cannot be used to predict earnings management if the proxy is based on the profitability ratio and the amount of managerial ownership. Meanwhile, tax evasion can only amplify the impact of present taxes on earnings management, which includes variables such as tax incentives.

Predicting Earnings Management from Qualitative Disclosures

While analysts, customers, and lenders rely on financial disclosures to make decisions regarding a company, executives often manage the disclosed earnings. Detecting such practices is thus a concern for company stakeholders and regulators. Qualitative disclosures are an additional source of information about a company's financial situation, but executives likely attempt to hide their earnings management activity in these disclosures, as well. We use supervised machine learning models to predict earnings management by property and casualty insurers from the Management’s Discussion and Analysis filings. For this, we utilize a new algorithm that interprets textual data conditional on the reported financial situation of the company. We show that the qualitative disclosures can predict earnings management, revealing that executives are unable to remove all subliminal messages from them. The results demonstrate that qualitative disclosures can be useful for learning about the accounting choices of companies.

Dependency Analysis Between Various Profit Measures and Corporate Total Assets for Visegrad Group’s Business Entities

Abstract Background and Purpose: Models of identifying and predicting earnings management in companies by using accruals are in general based on the dependence between total assets of companies and various profit measures. In this paper, we focused on an initial dependency analysis between these business indicators in the Visegrad group’s business entities. We explore the mentioned relationships, verify, and quantify the strength of the dependencies between earnings levels of companies (in terms of economic evaluation of the return on business capital in absolute terms) and the value of their total assets (i.e. business capital tied in the assets without its further classification and analysis). Methodology: We use descriptive statistics as well as a correlation analysis based on the real business data on almost 300 thousand companies in the V4 countries from the Amadeus database, covering the period from 2013 to 2017. Finally, we use a comparative analysis to identify disproportion among the results that were found out for each of the analysed countries. Results: The analysis showed that Slovak companies have the average values of profit measures and total assets comparable to Hungarian companies. Czech and Polish companies have several times higher average values of profit measures and also of total assets than Slovak and Hungarian companies. The analysis of the development of the profit measures and the total assets of the companies over the years showed significant differences across the four countries during the period covered by this study. Conclusion: The analysis of relationships between total assets of the companies and their profit measures showed that the strength of these dependencies among countries is very similar, and over the years, these results did not change. The results of this study can be further used in the creation of the earnings management model in enterprises, both in Slovakia and in other V4 countries.

Use of benchmarks in predicting earnings management?

AbstractThis study conducts multiple approaches to identify whether earnings benchmarks are an indicator for earnings management within the Australian market. We investigate firms reporting small positive earnings and small positive earnings changes, referred to as benchmark beaters. Accrual quality models, earnings distributions and earnings persistence measures are applied to identify whether benchmark beating firms are manipulating earnings. Our findings suggest that the small positive earnings benchmark attracts earnings managers. However, we do not identify any evidence to indicate that the positive earnings change benchmark is a signal for earnings management.

Predicting earnings management: A nonlinear approach

This study compares conventional linear and nonlinear accrual models to evaluate their ability to predict earnings management when applied to firm experiencing different performance levels. Linear models, which ignore the nonlinear relation between performance and accruals, result in measurement errors and, in turn, biased inferences. Using financial restatement as a proxy for earnings management, I show that a nonlinear expense-related model is best-specified and enhances the reliability of inferences in earnings management issues. The results echo the increasing cost- or expense-related earnings management after July 2002. When firms engage in downward earnings management after the passage of the SOX Act, the other models are also statistically reliable.

Evidences of Financial Shenanigans from Past and Techniques to Predict Earnings Management and Solvency Position: A Case Study of IOCL

This study tries to give the evidences of companies which manipulate their earnings through financial shenanigans. Financial shenanigans are the gimmicks used to misrepresent the financial statement through wrong accounting practices and cleverly changing the accounting policies to show a better financial health of companies when actually they do not have sound financial health. This study specifically gives evidence of companies which were using aggressive accounting practice to cheat the investors and other stakeholders. This study also states the measures to be taken by investors or analysts while analysing the financial statement. This study has also given a case study of Indian Oil Corporation as an illustrative purpose. In this study some advanced models like M score and Z score are used to predict possibility of earnings management and financial distress of companies. This study finds empirical evidence that companies are cleverly manipulate the accounting GAAPs to misrepresent the company’s position and fulfil the expectation of the stakeholders. This study specifically analyses the warnings signs to be checked with a case study of IOCL. Though this study we conclude that up to a certain extent we can predict the financial distress of companies and take measures accordingly to save us from financial loss. The findings of the study also suggest the companies to use these techniques to know about their real position and take appropriate decisions to save company from collapse. The main purpose of the study to apply the advance measures of financial statement analysis in Indian context as there are very few studies have been done and some area are still remain as grey area like study of the Indian corporate which are likely to be earnings management through wrong accounting practices.

Predicting earnings management based on adjusted earnings per share (EPS)

This paper investigates the usefulness of accounting information in forecasting earnings management. For this purpose, the firms listed in the Tehran Stock Exchange (TSE) that engage in adjusting the annual earnings per share (EPS) were recruited as the sample. It was found that the contracting incentive (debt contracts) and capital market pressures (net income and operating earnings growth) are two incentives for adjusting of EPS by the management. According to the conceptual framework, information in accrual of an item was expected to play a key factor in detecting the firms with adjusted EPS. This was however not confirmed in this study. Furthermore, the firms with higher ratios of price earning (P/E) and book-to-market (B/M) appear to have more tendencies for adjusting of EPS under the capital market pressures was rejected. Finally, it could be totally said that the firms with further earnings growth and higher leverage seem to be more inclined to adjust their EPS. This can be exploited as a clue to predicting of earnings management in the firms. Key words: Earnings management, adjusted earnings per share (EPS), accruals, capital market pressures, contracting incentive.

Analyst vs. Market Forecasts of Earnings Management to Avoid Small Losses

Abstract: Burgstahler and Eames (2003) present evidence that analysts commonly anticipate earnings management to avoid small losses, but often incorrectly predict its occurrence. Here we consider whether the market's behavior mimics that of analysts. Our results suggest that analysts exhibit more forecast optimism in their zero earnings forecasts than in their other small earnings forecast levels, and markets exhibit less relative optimism at this point. At the 271–360 day forecast horizon, we find a reduction in the earnings response coefficient at analysts’ zero earnings forecasts and interpret this as reflecting less optimism in market earnings forecasts than in analyst forecasts when analysts forecast zero earnings. This evidence is consistent with the market not following analysts in erroneously predicting earnings management to avoid small losses. We do not find similar evidence for shorter forecast horizons, suggesting that market and analyst forecasts converge towards the end of the year. Finding differences in market and analyst earnings forecasts in this loss avoidance environment raises the possibility of differences in a variety of earnings management and other environments, and sends a general note of caution in using analyst forecasts issued early in the year to proxy market expectations.

Empirical Investigation of the Ability of Sensitivity of Stock Prices to Earnings News in Predicting Earnings Management and Management Forecast Errors

This paper presents an evidence that a firm’s Sensitivity of Stock Price to Earnings News (SSPEN), as measured by surplus stock demand over its supply, affects on incentives to manage earnings and, in turn, Management Forecast Errors (MFE). In particular, we find a tendency for firms rated a Sell (Buy) to engage more (less) frequently in extreme, income-decreasing Earnings Management (EM), indicating that they have relatively stronger (weaker) incentives to create accounting reserves especially in the form of earnings baths than other firms. In contrast, firms rated a Buy (Sell) are more (less) likely to engage in earnings management that leaves reported earnings equal to or slightly higher than management forecasts. The result of empirical evidence from Iranian firms in Tehran Stock Exchange (TSE) showing the existence of a meaningful relationship between SSPEN and EM. Generally, SSPEN can be used to predict EM and Forecast Errors (FEs).

Non‐audit service fees, auditor characteristics and earnings restatements

PurposeThe objective of the study is to provide empirical evidence of the impact of non‐audit services (NAS) as well as other auditor characteristics on auditor independence by testing the relationship of NAS fees to the occurrence of financial statement restatements.Design/methodology/approachThe authors tested whether firms that restate their financial statements have higher levels of total service fees or higher levels of NAS fees than non‐restatement firms. The testing also includes an examination of the relationship between the audit firm size and the audit firm industry specialization to financial statement restatements.FindingsThe study found only limited evidence to support the concept that firms with higher NAS fees are more likely to restate earnings, thereby casting doubt on the public perception that NAS impairs auditor independence and the legislative approval of Section 201 of the Sarbanes‐Oxley Act prohibiting external auditors from providing certain NAS to audit clients as necessary to preserve auditor independence. The study did find stronger evidence that the level of total fees paid to the audit firm is significant in the predictability of a restatement. In addition, the study also found stronger and more conclusive evidence of a negative association to audit firm industry specialization and a strong positive association to Big 5 audit firms.Practical implicationsResults demonstrate the necessity of regulations concerning NAS and conflict of interest.Originality/valueThis paper is an original contribution that demonstrates the importance of auditor characteristics over audit fees in predicting earnings management.

ANALISIS AKTIVA PAJAK TANGGUHAN DAN AKRUAL SEBAGAI PREDIKTOR MANAJEMEN LABA: KAJIAN EMPIRIS PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BEJ

Pernyataan Standar Akuntansi Keuangan (PSAK) No 46 about income tax accounting in Indonesia, allows for management to judge deferred tax assets valuation annually in the financial statements. This regulation can give management an opportunity to use the deferred tax assets account to manage earnings. The probability of earnings management can be predicted by many variables. How a manager manages earnings in this study are by controlling accrual, and deferred tax assets valuation allowance under PSAK No 46. This research is purposed to investigate whether discretionary accrual modified Jones Model and deferred tax assets valuation allowance can be used to predict earnings management to prevent loss. Data used in this research are collected from audited-annual financial statements of manufacturing firms listed in the Jakarta Stock Exchange 2003-2005 The sampling method is purposive sampling. There are 66 samples to be analyzed by logistic regression. The results show that discretionary accruals can be used to predict earnings management, and the other hand, the deferred tax assets valuation allowance can not. The limitation and the research implication are also discussed.

Can Stock Recommendations Predict Earnings Management and Analysts' Earnings Forecast Errors?

Can Stock Recommendations Predict Earnings Management and Analysts' Earnings Forecast Errors?

Predicting Earnings Management: The Case of Earnings Restatements

This paper examines the usefulness of accounting information in predicting earnings management. We investigate a comprehensive sample of firms from 1971-2000 that restated annual earnings. We find that firms restating earnings have high market expectations for future earnings growth and have higher levels of outstanding debt. We also find that a primary motivation for the earnings manipulation is the desire to attract external financing at a lower cost. Furthermore, our evidence suggests that restating firms have been attempting to maintain a string of consecutive positive earnings growth and consecutive positive quarterly earnings surprises. Together, our evidence is consistent with capital market pressures acting as a motivating factor for companies to adopt aggressive accounting policies. Finally, we document that information in accruals, specifically, operating and investing accruals, are key indicators of the earnings manipulation that lead to the restatement. Collectively, the evidence suggests that market participants can gain substantial value from a careful consideration of information in financial statements.

Can Stock Recommendations Predict Earnings Management and Analysts’ Earnings Forecast Errors?

In this article we present evidence that a firm's stock price sensitivity to earnings news, as measured by outstanding stock recommendation, affects its incentives to manage earnings and, in turn, affects analysts’ex post forecast errors. In particular, we find a tendency for firms rated a Sell (Buy) to engage more (less) frequently in extreme, income–decreasing earnings management, indicating that they have relatively stronger (weaker) incentives to create accounting reserves especially in the form of earnings baths than other firms. In contrast, firms rated a Buy (Sell) are more (less) likely to engage in earnings management that leaves reported earnings equal to or slightly higher than analysts’ forecasts. Our empirical results provide direct evidence of purported, but heretofore, weakly documented equity market incentives for firms to manage earnings. They are also consistent with a growing body of literature that finds analysts either cannot anticipate or are not motivated to anticipate completely in their forecasts firms’ efforts to manage earnings.

Can Stock Recommendations Predict Earnings Management and Analysts' Earnings Forecast Errors?

We investigate whether the direction and magnitude of earnings management by a firm is affected by analysts' current perception of its equity investment potential (i.e., its perceived ability to generate positive abnormal returns). We argue that firms whose investment potential is perceived to be high (low) by analysts have strong (weak) incentives to meet earnings expectations. Accordingly, firms whose investment potential is perceived to be high are expected to manage earnings towards expectations (to ratify analysts beliefs), whereas firms whose investment potential is perceived to be low are expected to manage earnings away from expectations (to create the greatest possible amount of accounting slack for the future). Relying on analysts' Buy, Hold and Sell recommendations as proxies for firms' perceived investment potential and analysts' earnings forecasts to measure earnings expectations, we find evidence that strongly supports these hypotheses. Specifically, we find that after being rated a Sell, firms engage more frequently in extreme income-decreasing earnings management than other firms, indicating strong incentives to take earnings baths to create accounting slack. This earnings management behavior is associated with extreme bad news earnings surprises. In contrast, after being rated a Buy, firms engage in more frequent (but not more extreme) income-increasing earnings management than other firms. This behavior is associated with a high incidence of reported earnings that meet or slightly exceed the target of analysts' earnings forecasts. Our findings provide evidence of widespread earnings management in response to equity market incentives. They also suggest that some portion of apparent optimism in analysts' forecasts previously documented may be attributable to actions taken by managers subsequent to the issuance of forecasts rather than incentives to bias forecasts often ascribed to analysts.