Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6, 1729-1739 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 26 March 2025; Revised: 2 May 2025; Accepted: 4 May 2025; Published: 20 June 2025 * Correspondence: carlos.pinho@uab.pt Earnings management: Is accrual usage abusive? Auditors perception of accounting practices in Angola Pinho, Carlos Santos1*, Santos, Paula Gomes2, Martinho, Carla3 1CAPP Research Centre – ISCSP, Universidade de Lisboa Centro Estudos Globais – Universidade Aberta, Portugal; carlos.pinho@uab.pt (P.C.S.) 2Instituto Superior de Contabilidade e Administração de Lisboa / IPL COMEGI, Portugal; pasantos@iscal.ipl.pt (S.P.G.) 3Instituto Superior de Contabilidade e Administração de Lisboa / IPL ICPOL – ID& I Unit, Portugal; cmartinho@iscal.ipl.pt (M.C.) Abstract: This research explores auditors' perceptions regarding earnings management practices in Angola, with a particular focus on the use of accruals as a mechanism for manipulating financial results. The study also aims to identify the accounting areas most affected by such aggressive practices. A quantitative approach, based on a linear regression model, was adopted through a structured survey conducted in 2024 among auditors from the Big Four firms operating in Angola. The results indicate that accruals are perceived to be used at a significant level as a means of manipulating earnings. Revenue and receivables, personnel expenses, and inventories were identified as the most frequently manipulated areas. The findings also support the emphasis of International Auditing Standard (ISA) 240 on revenue as a key risk area for fraud. The study contributes to a better understanding of financial reporting practices in emerging economies. It provides practical insights for auditors, regulators, and other stakeholders, highlighting the need for focused audit procedures in high-risk areas in Angola. Keywords: Accounting manipulation, Accruals, Earnings management, Emerging economies financial reporting, International Standard on Auditing 240. 1. Introduction The relevance of information produced by financial reporting systems is grounded in stakeholders’ need for reliable financial information. Therefore, accounting frameworks usually highlight several qualitative characteristics, namely, relevance, reliability, and comparability. Fundamentally, the aim is to present a fair and true representation of a reporting entity’s financial position, economic performance, and cash flows. The purpose of worldwide comparability led to the issuance of international accounting standards, such as the ones issued by the International Accounting Standards Board (IASB). IASB standards are considered principle-based, therefore requiring substantial professional judgement and estimates [1]. Given the subjectivity underlying principle-based standards, auditors tend to accept more of the clients' accounting choices when following those types of standards than when they adopt rule-based accounting standards [2]. According to Pinho, et al. [3] in the current economic context, reinforcing the security of financial reporting stakeholders is a growing concern given that, in several contexts, managers use aggressive techniques to achieve desired financial or economic results, potentially resulting in significant benefits to management or heightened shareholder satisfaction through dividend payouts. These techniques can be qualified as accounting standards fraud or earnings management, and the distinction between them is not always simple. The first one violates the accounting standards, while the latter arises when https://orcid.org/0000-0002-5509-2921 https://orcid.org/0000-0003-2192-8855 https://orcid.org/0000-0001-7675-7390 1730 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate management exploits the flexibility permitted within these frameworks to mislead financial statements’ stakeholders [4]. Although the adoption of the IASB standards has been highlighted to significantly depress earnings management practices in some countries [5, 6] the flexibility they provide for managers does not mitigate that problem in others [7, 8]. The increasing regulatory complexity, shaped by globally accepted standards, has facilitated the adoption of accounting treatments for economic and financial events that may sometimes obscure the true and fair view of a company. A significant part of these practices arises from accruals accounting techniques [9]. Literature on earnings management has been mostly centred in developed countries [10]. This paper aims to fill this gap by addressing earnings management practices in Angola, a country that has suffered several financial scandals, which have even led the Financial Action Task Force (FATF) to put the country on the grey list [11]. Moreover, the accounting standards in Angola, the General Angolan Accounting Plan, are based on the international accounting standards issued by the IASB. Therefore, this paper aims to study the auditors' perception of earnings management in Angola, through the abusive usage of accruals. Furthermore, due to the lack of literature on the subject, the study also aims to identify the accounting areas that tend to be more affected by those aggressive practices. To achieve this purpose, a survey was conducted among the Big Four auditors in Angola in 2024. The findings contribute to the knowledge about earnings management practices in an emerging country by providing practical insights for auditors, regulators, and other stakeholders, highlighting the need for a more targeted and risk-based approach in Angola. The paper is divided into five sections, including this introduction. The second one presents the literature review, followed by the materials and methods section. In the fourth section, the main results are presented. Finally, the last section discusses the findings, proposes future research avenues and presents the study limitations. 2. Literature Review The continued corporate financial scandals suggest that management may influence the reported accounting results, which may not truly represent the companies’ economic performance [12]. Thus, the literature highlights that financial reporting often suffers from material misrepresentations, which can mislead stakeholders and distort decision-making [10, 13, 14]. According to Dos Santos [9] earnings manipulation occurs when managers deliberately alter the content and interpretations stemming from financial reporting. Supporting this view, Aerts, et al. [15] consider that earnings management involves intentional interference by managers in preparing financial statements, thereby distorting stakeholder perceptions to fulfil specific interests or goals. Thereby, earnings management, such as discretionary accruals, is a matter of concern for investors and regulators, as it diminishes the reliability of financial reporting [16]. Discretionary accruals are widely recognised as indicators of earnings management [16]. According to Casciello, et al. [17] discretionary accruals are “accounting items which are documented inside financial statements according to the accrual basis principle, despite the absence of any financial manifestation. Because of their discretionary identification, they could be manipulated by managers according to a particular legal or illegal policy of reporting. Discretionary accruals represent that part of total accruals which mainly impact on earnings quality”. Therefore, earnings quality is assessed by the absolute value of the irregular component of discretionary accruals, with higher values implying lower earnings quality and, consequently, more aggressive earnings management [16]. A strong control system is essential to limit the management’s ability to manage profits [18] as it is negatively related to the level of discretionary accruals [19]. Ramos [20] concluded that these aggressive practices can assume several forms, namely earnings smoothing, big bath, bum up and cookie jar reserves. However, the great disagreement among most 1731 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate authors when it comes to results’ manipulation has to do with the legality of this interference (Ramos, 2012). According to Dechow and Schrand [21] and Dechow, et al. [22] even if earnings management does not constitute a violation of legal limits, it significantly affects the quality of results, and a greater practice of earnings management leads to a lower quality of earnings and, therefore, to a decrease in stakeholder confidence. For Healy and Wahlen [13] earnings management can be motivated by different reasons, such as personal objectives of managers, contractual issues, tax issues, political costs, or capital market, which may contribute to the distortion of the financial reporting, significantly affecting stakeholders' decisions, as the published report does not provide a true and fairly view of the financial and economic position of the reporting entity. Shuto [23] studied the Japanese listed companies and compared discretionary accounting policy choices with managers' remuneration, concluding that the use of discretionary accruals increases their remuneration and that, normally, during periods when they do not receive bonuses, managers tend to decrease their accounting results. Managers of listed companies more often adopt "big bath" practices, making it appear that the company has performed worse in the current period than it actually has, allowing them to smooth out their earnings for various periods [23]. According to Ball and Shivakumar [24] listed companies tend to incorporate more negative transitory components in their results than non-listed ones. On the contrary, i.e., when results tend to be above the maximum bonus limit set, managers tend to reduce them and create bubbles of potential gains that can be used in future periods, since an additional increase in results is not, as a rule, synonymous with a higher compensation [23]. In addition to these practices, it is observed that when the criteria that define or do not define the attribution of bonuses are based on the performance of the previous year, managers usually tend not to raise the reference standards [25, 26]. Richardson and Waegelein [27] say that companies that have a policy of compensating their managers based on long-term performance plans are associated with lower levels of earnings management practices, compared to companies that operate only at the level of short-term bonus plans. The literature also stresses that larger companies have greater incentives to practice earnings management to reduce the risks associated with greater public exposure and possible external intervention [28]. According to Sweeney [29] entities with more restrictive financing contracts or with restricted renegotiation capacity have an increased tendency to adopt earnings management practices, as a way to avoid possible penalties or defaults. He also highlights that the flexibility inherent in accounting and financial reporting standards tends to encourage the adoption of such practices. It is important to underline that creditors increasingly tend to exercise control over the financial reports of debtor companies, which mainly aims at restricting performance management practices [30]. Increasingly, creditors resort to and require that the entities’ financial reports be validated by competent and independent financial auditors to increase their credibility Pinho, et al. [31]. Pinho, et al. [3] reinforce that the credibility of the financial report produced by companies is increasingly a vehicle for the proper functioning of the markets, with the financial sector and capital markets being particularly sensitive to the adequacy of the financial report produced, with several financial scandals known worldwide that have occurred due to distorted financial information by companies. The sector of activity is also a factor that influences the adoption of earnings management practices Grace and Leverty [32]; Healy and Wahlen [13] and Michelson, et al. [33]. Datta, et al. [34] reinforce that the most competitive industries are associated with a higher level of results management practices. Thus, sectors that face greater market competition may be better able to manage their results to strategically limit the information disclosed and to ensure a competitive advantage over competitors. This can even have a sectoral contamination effect, that is, companies tend to adopt such practices if they are aware that competing companies manipulate accounting reporting [35]. 1732 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate According to Dechow and Schrand [21] entities tend to manipulate the taxable profit component, since they manage the timing of the recognition of results and, in this way, reduce the taxes payable in the current financial year. Those authors conclude that if the indicators show that the tax rate in the subsequent period is lower, managers tend to transfer results from the current period to the next period and thus reduce the tax burden, enjoying immediate tax savings. It is widely investigated that aggressive practices are used by financial reporting professionals and, also, the main intents of such practices, as discussed above. But in fact, there is quite less evidence of the accounting areas that tend to be more affected by those aggressive practices. Therefore, this research aims to identify those significantly affected accounting areas, as developed in the following steps of this research. The next section presents the materials and methods followed in this research. 3. Materials and Methods The objective of this article is to identify to what extent earnings management techniques are used specifically in Angola and in what areas such usage tends to be more frequent. To obtain statistical evidence about the above-mentioned objective, a survey was prepared and sent to auditors who work in Big Four auditing companies in Angola. According to the 2022 Audit Analytics report, it is observed that Big Four auditing companies absorb the greater part of the financial auditing market and that their partners and staff's perception of this issue incorporates a profound and relevant experience in this area. As a result of the survey carried out, 160 valid responses have been obtained and are thus subject to this empirical study. Some responses showed that responders did not show a significant experience related to accrual matters, and therefore, such answers were not considered valid for this study. The sample size is adequate for the universe under study in Angola, having in mind a total of around 1.200 audit partners and staff operating in Big Four audit firms in this region, according to the reports available in corporate reports. Equation 1 was followed for calculating the minimum sample size for a 95% confidence level for such a study. 𝑛 = 𝑝 𝑥 𝑞 𝐷2 𝑍𝑎 2 + 𝑝 𝑥 𝑞 𝑁 (1) Being: • n, the sample size; • Zα/2, the critical value that corresponds to the desired degree of confidence (1.96); • p, the proportion of the population that verifies the characteristic under study (92.9%); • q, the proportion of the population that does not verify the characteristic under study, i.e. (1-p = 7.1%); and • D, the margin of error or maximum estimation error that identifies the maximum difference between the sample mean (X) and the true population mean (5%). For the data collected, it was calculated a relevant sample of 90 answers. Thus, the sample size obtained of 160 valid responses is adequate for the study. The survey intended to assess the auditors' opinions on the usage of discretionary accruals based on a five-level Likert scale. According to Reis, et al. [36] the instrument used is adequate to evaluate the opinion or acceptance degree of a certain issue under evaluation. Furthermore, respondents had to identify in what accounting areas such abusive techniques were used. The survey is intended to assess in what accounting areas such usage is to be considered more frequent, with the intent to identify critical areas that are more affected by such practices. For this purpose, a linear regression model was applied through SPSS 30, where this use constitutes the dependent variable, whose inclusion of variables followed the Stepwise methodology. It is also important to highlight that the Durbin-Watson test was applied to evaluate possible correlations between the variables used in the model [37]. 1733 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate 4. Results Regarding the respondents’ experience, the results are presented in Table 1. Table 1. Respondents' experience. Professional Experience Absolute Frequency Percentage Less than 5 years 43 27% From 5 to 10 years 63 39% From 11 to 15 years 25 16% More than 15 years 18 11% No Answer 11 7% Table 1 shows that most of the respondents (66%) have relevant experience regarding auditing activities (above 5 years), which supports the fact that the respondents have adequate skills to appreciate the problem of this research. Concerning the first objective of this paper, the respondents’ perceptions about discretionary accrual usage are presented in Table 2, with 1 being a very low level and 5 being a very frequent level. Table 2. How frequently are discretionary accruals used. Level of Usage Absolute Frequency Percentage 1 – very low frequency (≤ 20% of companies) 4 2.5% 2 – low frequency (> 20% and ≤ 40% of companies) 61 38.1% 3 – average frequency (> 40% and ≤ 60% of companies) 38 23.75% 4 – high frequency (> 60% and ≤ 80% of companies) 38 23.75% 5 – very high frequency (> 80% of companies) 19 11.9% From Table 2, it can be observed that the average level of companies tends to manipulate results using aggressive techniques based on accruals to manipulate earnings. This does not mean that such is done on a yearly consistent basis, nor that such manipulation reaches material amounts. Nevertheless, it is a significant result, somewhat in line with the observation that aggressive methods tend to be used in a growing tendency. Therefore, these observations allow us to conclude that a significant proportion of companies that report in Angola have used or are considering using accruals as a method to manipulate earnings, which is a significant conclusion. As mentioned, the present research also aims to identify which of the independent variables: (i) Net cash and deposits; (ii) Purchases, Supplies and Payables; (iii) Inventories; (iv) Revenues and Receivables; (v) Non-financial investments; (vi) Financial Investments; (vii) Financial Liabilities and (viii) Personnel Expenses — have greater explanatory power over the practice of using accruals as a form of manipulation of earnings. The designation used to characterise the variables under study was as follows: • Net cash and deposits – NC&D; • Purchases, Supplies, and Payables -PS&P; • Inventories - I; • Revenue and Receivables – R&R; • Non-Financial Investments - NFI; • Financial Investments - FI; • Financial Liabilities - FL; • Personnel Expenses - PE; The Stepwise method was used to evaluate the inclusion of variables in the regression models. It is an iterative procedure whose objective is to find an optimal subset of explanatory variables, eliminating 1734 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate those that do not contribute significantly to the model [38]. The results of the regression models estimated according to this method can be seen in Table 3. Table 3. Variables Inserted/Removed. Model Inserted variables Removed variables Method 1 R&R . Stepwise (Criteria: Probability of F to be inserted <= 0.05, Probability of F to be removed >= 0.10). 2 PE . Stepwise (Criteria: Probability of F to be inserted <= 0.05, Probability of F to be removed >= 0.10). 3 I . Stepwise (Criteria: Probability of F to be inserted <= 0.05, Probability of F to be removed >= 0.10). 4 NFI . Stepwise (Criteria: Probability of F to be inserted <= 0.05, Probability of F to be removed >= 0.10). 5 FI . Stepwise (Criteria: Probability of F to be inserted <= 0.05, Probability of F to be removed >= 0.10). Note: a. Dependent Variable: Accruals usage to manipulate results. Therefore, it can be concluded that the variables that most contribute to justify the abusive use of accruals are, in descending order, R&R - revenue and receivables, followed by PE - personnel expenses, I - inventories, NFI - non-financial investments and FI - financial investments. Nevertheless, the influence of both Financial Investments and Non-Financial investments is quite insignificant compared with the above-mentioned three variables, as can be seen in Table 4. Table 4. Model summaryf. Mod. R R2 R2 adjustment. Estimate E-p Change Statistics Durbin- Watson Change from R2 Change F df1 df2 Sig. Change F 1 0.493ª 0.243 0.238 0.945 0.243 50.664 1 158 <0.001 2 0.663b 0.439 0.432 0.816 0.197 55.046 1 157 <0.001 3 0.715c 0.511 0.501 0.765 0.071 22.739 1 156 <0.001 4 0.733d 0.537 0.525 0.746 0.026 8.793 1 155 0.004 5 0.749e 0.562 0.547 0.729 0.025 8.632 1 154 0.004 2.178 Note: a. Predictors: (Constant), Revenue, receivables b. Predictors: (Constant), Revenue and receivables, Personnel costs c. Predictors: (Constant), Revenue and receivables, Personnel costs, Inventories d. Predictors: (Constant), Revenue and receivables, Personnel costs, Inventories, Non-financial investments e. Predictors: (Constant), Revenue and receivables, Personnel costs, Inventories, Non-financial investments, Financial Investments f. Dependent Variable: Accrual usage to manipulate results Table 4, shows the evolution of the model with the inclusion of each variable. For example, the variable Revenue and Receivables explain 24.3% of the variations in the misuse of accruals, and the five independent variables accepted by Stepwise, together, explain 54.7%. The Durbin-Watson test is a statistic used to detect the presence of autocorrelation in the residuals of a linear regression model [37]. Autocorrelation occurs when the residuals (random errors) of a model are correlated, which violates one of the basic premises of linear regression: the independence of errors. This violation can lead to inefficient coefficient estimates and incorrect statistical inferences. The Durbin-Watson statistic ranges between 0 and 4 and is interpreted as follows [39]: • d ≈ 2: Indicates absence of autocorrelation in the residuals. • d < 2: Suggests the presence of positive autocorrelation (positive residuals tend to be followed by positive residuals, and negative residuals by negative residuals). 1735 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate • d > 2: Suggests the presence of negative autocorrelation (positive residuals tend to be followed by negative residuals, and vice versa). To determine whether autocorrelation is statistically significant, the value of d is compared with tabulated critical values (available in Durbin-Watson tables), which depend on the sample size (n), the number of independent variables (k), and the level of significance. The critical values for n = 160 and k = 5, at level  = 0.05 are • dI (lower critical value): 1.654 • dS (upper Critical Value): 1.748 These critical values define two regions: Rejection region for positive autocorrelation: If d < dI, the null hypothesis of absence of autocorrelation is rejected. 1. Rejection region for negative autocorrelation: If d > 4−dI, the null hypothesis is rejected. 2. Indecision zone: If dI ≤ d ≤ dS or 4−dS ≤ d ≤ 4−dI, the test is inconclusive. Because in this case, d = 2.178, i.e., dS < d < 4−dS (1.748 < d < 2.252), we can conclude that there is no evidence of autocorrelation. To evaluate the overall significance of the adjusted linear regression model, i.e., to verify whether the explanatory (independent) variables help to predict the dependent variable in a statistically significant way, an ANOVA (Analysis of Variance) test was performed [40]. Results are shown in Table 5. Table 5. ANOVAa. Model Sum of Squares Df Medium Square Z p 5 Regression 104.695 5 20.939 39.445 <0.001f Residue 81.749 154 0.531 Total 186.444 159 Note: a. Dependent Variable: Accruals usage to manipulate results b. Predictors: (Constant), Revenue and receivables c. Predictors: (Constant), Revenue and receivables, Personnel costs d. Predictors: (Constant), Revenue and receivables, Personnel costs, Inventories e. Predictors: (Constant), Revenue and receivables, Personnel costs, Inventories, Non-financial investments f. Predictors: (Constant), Revenue and receivables, Personnel costs, Inventories, Non-financial investments, Financial Investments According to the ANOVA (Table 5), the model selected by Stepwise is globally significant (p < 0.001). The results of the tests on the regression coefficients are presented in Table 6. Table 6. Coefficients. CnP1 CP3 t p 95,0% IC4 for B Correlations Collinearity statistics B EP2 Beta LI5 LS6 Zero- order Partial Part Tolerance VIF 2.043 0.104 19.58 <0.001 1.837 2.249 1.185 0.124 0.517 9.58 <0.001 0.940 1.430 0.493 0.610 0.509 0.972 1.029 1.072 0.130 0.452 8.28 <0.001 0.814 1.329 0.420 0.553 0.439 0.943 1.061 0.698 0.123 0.318 5.69 <0.001 0.456 .941 0.339 0.417 0.304 0.909 1.100 0.601 0.204 0.162 2.94 0.004 0.197 1.005 -0.011 0.230 0.157 0.934 1.070 0.494 0.168 0.163 2.94 0.004 0.162 0.827 0.064 0.230 0.157 0.920 1.087 Note: 1: Non-standard coefficients; 2: Standard Error; 3: Standardized coefficients; 4: Confidence interval; 5: Lower limit; 6: Upper limit. All the independent variables admitted by the Stepwise method are naturally important to justify the variations in the abusive usage of Accruals, which is corroborated by the results of the tests (p < 0.001 and p = 0.004) to the regression coefficients (Table 6). The presence of multicollinearity is undesirable in linear regression models, which occurs when two or more independent variables in a regression model are highly correlated, which can cause problems in 1736 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate estimating the model's coefficients. One of the most common methods for detecting multicollinearity is the Variance Inflation Factor (VIF) [41]. The VIF measures how much the variance of a regression coefficient is increased due to multicollinearity. It is calculated for each independent variable in the model. A high VIF indicates that the variable is highly correlated with other variables in the model. The VIF is calculated as follows: VIFi=1/(1−Ri2), where Ri2 is the coefficient of determination of the regression of the variable i concerning the other independent variables. If: VIF = 1: There is no multicollinearity; 1 < VIF < 5: Moderate multicollinearity, but generally not of concern; VIF ≥ 5: High multicollinearity, indicating that the variable may be causing problems in the model. The VIF is a useful tool for identifying multicollinearity in regression models. As the VIF values (Table 6) are all practically equal to 1, this indicates that multicollinearity is not affecting the reliability of the coefficient estimates. The Condition Index is a measure used to assess the presence and severity of multicollinearity in regression models. It is derived from the covariance matrix or variance-covariance matrix of the independent variables. The Condition Index helps to identify whether the independent variables are highly correlated, which can compromise the stability of the regression coefficients. Values are shown in Table 7. Table 7. Diagnosis of collinearity. Anything. Autovalor Condition Index Variance Ratios (Constant) Revenue and receivables Personnel costs Inventories Non-financial investments Financial Investments 1 2.635 1.000 0.04 0.05 0.04 0.04 0.01 0.02 2 1.064 1.574 0.00 0.01 0.07 0.03 0.42 0.20 3 0.907 1.705 0.00 0.01 0.01 0.09 0.29 0.44 4 0.710 1.927 0.00 0.50 0.40 0.00 0.02 0.01 5 0.471 2.365 0.00 0.25 0.30 0.49 0.13 0.16 6 0.213 3.520 0.96 0.19 0.17 0.34 0.13 0.18 Note: a Dependent Variable: Accruals usage to manipulate results. As presented in Table 7, the condition indexes are less than 10, thus ensuring an overall measure of low or absent multicollinearity. Therefore, the estimated regression model can be validated, which allows the identification of the variables that most contribute to explaining the abusive usage of accruals. The next section presents the discussion and the conclusion of this research. 5. Discussion and Conclusions This study aimed to investigate the perceptions of auditors regarding earnings management practices in Angola, with a particular focus on the use of accruals. In line with prior literature (e.g., [4, 9]) the findings confirm that accrual-based accounting choices continue to be a relevant avenue for financial result manipulation. The overall average to a high level of accruals usage to potentially manipulate earnings highlights a concerning trend. This trend is consistent with the international literature, which points to a growing tendency toward the use of aggressive accounting practices, particularly under principle-based standards such as those issued by the IASB [2, 7]. The findings provide empirical evidence that accruals are deliberately employed by some companies in Angola to manage reported earnings. The tendency to use accruals may be constrained not necessarily by regulation but by a lack of professional capacity and training in the Angolan context [9]. A significant contribution of this research is the identification of specific accounting areas that are more prone to aggressive practices. Namely, revenue and receivables, personnel expenses, and inventories emerged as the most commonly manipulated elements. This is particularly relevant for 1737 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate auditors and financial reporting inspectors, as well as for other stakeholders, as it aligns with International Auditing Standard 240 (paragraph 32), which highlights revenue recognition as an area of high fraud risk. The findings thus have direct practical implications for audit planning and risk assessment in Angola, encouraging a more targeted and risk-based approach. In conclusion, this study contributes to the understanding of earnings management practices in Angola by providing empirical evidence on the perceived use of accruals for earnings manipulation and identifying specific accounting areas more vulnerable to such practices. These findings are relevant for regulators, auditors, and other stakeholders striving to improve the reliability and transparency of financial reporting in Angola. Strengthening professional training and reinforcing audit scrutiny, particularly in high-risk areas, may serve as effective deterrents to aggressive accounting behaviour, thereby enhancing financial reporting quality and stakeholder confidence in emerging markets. The study also responds to a gap in the literature [10] who underline the scarcity of research on earnings management in developing and emerging economies. By focusing on Angola, a country that has faced significant financial transparency challenges and remains under the scrutiny of international bodies such as the Financial Action Task Force (FATF) [11] this paper sheds light on the particular vulnerabilities of emerging markets to earnings manipulation. While the findings are significant, the study has some limitations. Firstly, it relies on the perceptions of a specific group, auditors from the Big Four, which may not fully capture the diversity of views across the broader accounting and corporate governance community in Angola. Secondly, as the study was based on survey data, there may be an element of subjectivity in the responses, particularly on a sensitive topic such as earnings manipulation. Further investigations on this issue could be carried out in other geographic realities. Moreover, it would also be relevant to investigate the reasons behind the aggressive accounting practices to manipulate earnings. Further investigation could also try to identify what practices are carried out by financial reporting professionals, and also the impact on the overall quality of the financial and economic information provided. Institutional Review Board Statement: For ethical purposes, the survey identified the objective and the researchers and obtained the written consent of each participant, following the ethical guidelines approved by Universidade Aberta and ISCAL/Instituto Politécnico de Lisboa. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Copyright: © 2025 by the authors. This open-access article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). References [1] P. J. Coram and L. Wang, "The effect of disclosing key audit matters and accounting standard precision on the audit expectation gap," International Journal of Auditing, vol. 25, no. 2, pp. 270-282, 2021. https://doi.org/10.1111/ijau.12203 [2] I. Pinto and A. I. Morais, "What matters in disclosures of key audit matters: Evidence from Europe," Journal of International Financial Management & Accounting, vol. 30, no. 2, pp. 145-162, 2019. https://doi.org/10.1111/jifm.12095 [3] C. Pinho, P. G. Santos, and C. Martinho, "Analytical procedures–are they useful for auditing purposes? An iberian peninsula approach," International Journal of Economics and Finance Studies, vol. 14, no. 03, pp. 302-321, 2022. https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1111/ijau.12203 https://doi.org/10.1111/jifm.12095 1738 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate [4] P. M. Dechow and D. J. Skinner, "Earnings management: Reconciling the views of accounting academics, practitioners, and regulators," Accounting Horizons, vol. 14, no. 2, pp. 235-250, 2000. https://doi.org/10.2308/acch.2000.14.2.235 [5] S. Kousay, "The impact of IFRS adoption on earnings management-results from Canada," Journal of Economics and Business, vol. 2, no. 3, pp. 540-554, 2019. [6] A. M. M. Amer, A. Azimli, and M. W. Adedokun, "Can IFRS adoption mitigate earnings management in an emerging market?," Heliyon, vol. 10, no. 19, p. e38226, 2024. https://doi.org/10.1016/j.heliyon.2024.e38226 [7] M. Bryce, M. J. Ali, and P. R. Mather, "Accounting quality in the pre-/post-IFRS adoption periods and the impact on audit committee effectiveness—Evidence from Australia," Pacific-Basin Finance Journal, vol. 35, pp. 163-181, 2015. https://doi.org/10.1016/j.pacfin.2014.12.002 [8] T. Malofeeva, "The impact of IFRS adoption on earnings management in Russia," European Research Studies Journal, vol. 21, no. 2, pp. 147-164, 2018. [9] F. P. Dos Santos, "Use of accruals as a measure of manipulation of corporate results in Angola: Exploratory study," Master's Thesis, Universidade Aberta (Portugal, 2017. [10] G. Ahmad, M. Subhan, F. Hayat, and M. A. S. Al-Faryan, "Unravelling the truth: A bibliometric analysis of earnings management practices," Cogent Business & Management, vol. 10, no. 1, p. 2194088, 2023. https://doi.org/10.1080/23311975.2023.2194088 [11] Financial Action Task Force (FATF), Black and grey lists. Paris, France: FATF, 2024. [12] M. Boulhaga, A. Bouri, and H. Elbardan, "The effect of internal control quality on real and accrual-based earnings management: Evidence from France," Journal of Management Control, vol. 33, no. 4, pp. 545-567, 2022. https://doi.org/10.1007/s00187-022-00348-5 [13] P. M. Healy and J. M. Wahlen, "A review of the earnings management literature and its implications for standard setting," Accounting Horizons, vol. 13, no. 4, pp. 365-383, 1999. https://doi.org/10.2308/acch.1999.13.4.365 [14] Y. Shahwan, A. Abuhussein, and R. Binsaddig, "Earnings management, company value, corporate governance, evidence from non-financial companies," International Journal of Economics and Finance Studies, vol. 16, no. 3, pp. 109- 138, 2024. [15] W. Aerts, P. Cheng, and A. Tarca, "Management's earnings justification and earnings management under different institutional regimes," Corporate Governance: An International Review, vol. 21, no. 1, pp. 93-115, 2013. https://doi.org/10.1111/corg.12014 [16] Y. Jamadar, T. S. Ong, A. A. Abdullah, and F. Kamarudin, "Earnings and discretionary accruals," Managerial and Decision Economics, vol. 43, no. 2, pp. 431-439, 2022. https://doi.org/10.1002/mde.3391 [17] R. Casciello, A. Caldarelli, and M. Maffei, Earnings management and mergers and acquisitions: Empirical evidence from Italian-listed companies. In J. Oliveira, G. Azevedo, & A. Ferreira (Eds.), International financial reporting standards and new directions in earnings management. IGI Global. https://doi.org/10.4018/978-1-5225-7817-8.ch004, 2019. [18] J. T. Doyle, W. Ge, and S. McVay, "Accruals quality and internal control over financial reporting," The Accounting Review, vol. 82, no. 5, pp. 1141-1170, 2007. https://doi.org/10.2308/accr.2007.82.5.1141 [19] M. S. Nuhu, Z. Ahmad, and L. Y. Zhee, "Nexus among disclosure quality, discretionary accruals and real earnings management practices: An empirical analysis of Malaysian public firms," Journal of Corporate Accounting & Finance, vol. 35, no. 4, pp. 121-138, 2024. https://doi.org/10.1002/jcaf.22720 [20] L. Ramos, "Earnings management in the context of the European public business sector," Master’s Dissertation, University of Aveiro, Department of Economics, Management and Industrial Engineering. University of Aveiro Repository, 2012. [21] P. M. Dechow and C. M. Schrand, Earnings quality. Charlottesville, VA: Research Foundation of CFA Institute, 2004. [22] P. M. Dechow, R. G. Sloan, and A. P. Sweeney, "Detecting earnings management," Accounting Review, vol. 70, no. 2, pp. 193-225, 2011. [23] A. Shuto, "Executive compensation and earnings management: Empirical evidence from Japan," Journal of International Accounting, Auditing and Taxation, vol. 16, no. 1, pp. 1-26, 2007. https://doi.org/10.1016/j.intaccaudtax.2007.01.004 [24] R. Ball and L. Shivakumar, "The role of accruals in asymmetrically timely gain and loss recognition," Journal of Accounting Research, vol. 44, no. 2, pp. 207-242, 2006. https://doi.org/10.1111/j.1475-679X.2006.00198.x [25] O. D. Moses, "Income smoothing and incentives: Empirical tests using accounting changes," Accounting Review, pp. 358-377, 1987. [26] K. J. Murphy, "Performance standards in incentive contracts," Journal of Accounting and Economics, vol. 30, no. 3, pp. 245-278, 2000. https://doi.org/10.1016/S0165-4101(01)00013-1 [27] V. J. Richardson and J. F. Waegelein, "The influence of long-term performance plans on earnings management and firm performance," Review of Quantitative Finance and Accounting, vol. 18, pp. 161-183, 2002. https://doi.org/10.1023/A:1014517102230 [28] R. Azevedo, "Study of earnings management practices in listed and unlisted European companies," Doctoral Dissertation, Instituto Superior de Economia e Gestão). Instituto Superior de Economia e Gestão, 2014. https://doi.org/10.2308/acch.2000.14.2.235 https://doi.org/10.1016/j.heliyon.2024.e38226 https://doi.org/10.1016/j.pacfin.2014.12.002 https://doi.org/10.1080/23311975.2023.2194088 https://doi.org/10.1007/s00187-022-00348-5 https://doi.org/10.2308/acch.1999.13.4.365 https://doi.org/10.1111/corg.12014 https://doi.org/10.1002/mde.3391 https://doi.org/10.4018/978-1-5225-7817-8.ch004 https://doi.org/10.2308/accr.2007.82.5.1141 https://doi.org/10.1002/jcaf.22720 https://doi.org/10.1016/j.intaccaudtax.2007.01.004 https://doi.org/10.1111/j.1475-679X.2006.00198.x https://doi.org/10.1016/S0165-4101(01)00013-1 https://doi.org/10.1023/A:1014517102230 1739 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 6: 1729-1739, 2025 DOI: 10.55214/25768484.v9i6.8236 © 2025 by the authors; licensee Learning Gate [29] A. P. Sweeney, "Debt-covenant violations and managers' accounting responses," Journal of Accounting and Economics, vol. 17, no. 3, pp. 281-308, 1994. https://doi.org/10.1016/0165-4101(94)90030-2 [30] K. Zhong, D. W. Gribbin, and X. Zheng, "The effect of monitoring by outside blockholders on earnings management," Quarterly Journal of Business and Economics, vol. 46, no. 1, pp. 37-60, 2007. [31] C. Pinho, P. Gomes dos Santos, and A. E. P. F. B. Martins, "Why auditors increasingly rely on analytical procedures: An empirical approach in Portugal," International Journal of Professional Business Review, vol. 8, no. 10, p. e03691, 2023. https://doi.org/10.26668/businessreview/2023.v8i10.3691 [32] M. F. Grace and J. T. Leverty, "Political cost incentives for managing the property‐liability insurer loss reserve," Journal of Accounting Research, vol. 48, no. 1, pp. 21-49, 2010. https://doi.org/10.1111/j.1475-679X.2009.00358.x [33] H. Michelson, C. Bolund, B. Nilsson, and Y. Brandberg, "Health-related quality of life measured by the EORTC QLQ-C30: reference values from a large sample of the Swedish population," Acta Oncologica, vol. 39, no. 4, pp. 477- 484, 2000. https://doi.org/10.1080/028418600750013384 [34] S. Datta, M. Iskandar-Datta, and V. Singh, "Product market power, industry structure, and corporate earnings management," Journal of Banking & Finance, vol. 37, no. 8, pp. 3273-3285, 2013. https://doi.org/10.1016/j.jbankfin.2013.03.012 [35] M. Bagnoli and S. G. Watts, "The effect of relative performance evaluation on earnings management: A game- theoretic approach," Journal of Accounting and Public Policy, vol. 19, no. 4-5, pp. 377-397, 2000. https://doi.org/10.1016/S0278-4254(00)00005-3 [36] E. Reis, P. Melo, R. Andrade, and T. Calapez, Applied statistics. Lisboa, Portugal: Edições Sílabo, 2019. [37] M. M. Ali, "An approximation to the null distribution and power of the Durbin—Watson statistic," Biometrika, vol. 71, no. 2, pp. 253-261, 1984. https://doi.org/10.1093/biomet/71.2.253 [38] C.-K. Ing and T. L. Lai, "A stepwise regression method and consistent model selection for high-dimensional sparse linear models," Statistica Sinica, pp. 1473-1513, 2011. [39] N. E. Savin and K. J. White, "The Durbin-Watson test for serial correlation with extreme sample sizes or many regressors," Econometrica: Journal of the Econometric Society, vol. 18, no. 2, pp. 1989-1996, 1977. [40] G. A. F. Seber and A. J. Lee, Linear regression analysis, 2nd ed. Hoboken, NJ: Wiley, 2003. [41] M. R. Lavery, P. Acharya, S. A. Sivo, and L. Xu, "Number of predictors and multicollinearity: What are their effects on error and bias in regression?," Communications in Statistics-Simulation and Computation, vol. 48, no. 1, pp. 27-38, 2019. https://doi.org/10.1080/03610918.2017.1371750 https://doi.org/10.1016/0165-4101(94)90030-2 https://doi.org/10.26668/businessreview/2023.v8i10.3691 https://doi.org/10.1111/j.1475-679X.2009.00358.x https://doi.org/10.1080/028418600750013384 https://doi.org/10.1016/j.jbankfin.2013.03.012 https://doi.org/10.1016/S0278-4254(00)00005-3 https://doi.org/10.1093/biomet/71.2.253 https://doi.org/10.1080/03610918.2017.1371750