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Statutory Payments and Accruals on Financial Performance of Listed Non-Financial Firms in Nigeria
- Dauda John Dzarsa
- Dr. Isaac Lambe
- Assoc. Prof. Orbunde Bemshima
- 2033-2062
- Jul 13, 2024
- Accounting & Finance
Statutory Payments and Accruals on Financial Performance of Listed Non-Financial Firms in Nigeria
Dauda John Dzarsa, Dr. Isaac Lambe, Assoc. Prof. Orbunde Bemshima
Department of Accounting, Faculty of Administration, Bingham University, Nasarawa State
DOI: https://dx.doi.org/10.47772/IJRISS.2024.806154
Received: 03 June 2024; Accepted: 12 June 2024; Published: 13 July 2024
ABSTRACT
The unresolved controversy regarding the effect of statutory payments and accruals on financial performance continues to challenge the success of listed non-financial firms in Nigeria. Despite the critical importance of these factors, there exists a lack of clarity and understanding surrounding their impact on organisational outcomes. Given the foregoing, this study examined the effect of statutory payments and total accruals on financial performance of listed non-financial firms in Nigeria. To achieve these objectives, longitudinal research design was employed and the study used twenty (20) listed non-financial firms that had consistently published their audited annual financial reports from 2008 to 2022, and analyzed the data using panel multiple regression technique with the help of E-view 13 statistical tools. The result of the study revealed that financial statutory payment has a significant effect on financial performance of listed non-financial firms in Nigeria. Conversely, total accrual has insignificant effect on financial performance of listed non-financial firms in Nigeria. Thus, this study concluded that statutory payments serve as a veritable tool or determinant of financial performance. Thus, the study recommended that non-financial firms are to prioritize compliance with financial statutory payments, as demonstrated by the significant influence of such payments on financial performance. This entails adhering to regulatory requirements, tax obligations, and other statutory payments to maintain transparency and credibility with stakeholders.
Keywords: Statutory Payments, Total Accruals, Financial Performance, Return on Assets and Firm Size.
INTRODUCTION
Financial performance evaluation serves as a crucial tool for investors, managers, policymakers, and other stakeholders to gauge the health, sustainability, and growth potential of businesses (Arunkumar, 2015). In today’s globalized economy, characterized by rapid technological advancements, fluctuating market conditions, and evolving regulatory landscapes, the financial performance of companies plays an increasingly pivotal role in shaping economic outcomes. Temile et al., (2021), opined that examining financial performance encompasses a broad spectrum of indicators, including profitability, liquidity, solvency, and efficiency, all of which provide insights into the effectiveness of a company’s operations and management strategies. Moreover, financial performance analysis extends beyond mere numerical figures; it entails understanding the underlying drivers and factors influencing a company’s financial outcomes. These factors can range from internal operational efficiencies to external market dynamics, competitive pressures, regulatory compliance, and macroeconomic trends.
Statutory payments and total accruals influence the financial performance of listed non-financial firms in Nigeria. Statutory payments, encompassing taxes, fees, and regulatory obligations, directly impact a company’s bottom line by reducing its net income (Ohiomegwe, et al., 2022). Compliance with statutory payments is crucial for maintaining good standing with regulatory authorities and avoiding legal repercussions, but the financial burden they impose can detract from profitability (Osiorenoya, 2017). Similarly, total accruals, which represent adjustments made in financial statements to match revenues and expenses with the periods they occur, can affect reported earnings. While accruals are essential for matching revenue and expenses accurately, excessive accruals may signal potential manipulation of financial results or poor management of operational costs. This can erode investors’ confidence and undermine the perceived financial stability of the firm (Uwuigbe, et al., 2019). The interplay between statutory payments and total accruals influences various aspects of financial performance, including profitability, liquidity, and shareholder value. High statutory payments and excessive accruals can reduce profitability margins, strain liquidity by tying up cash flows, and ultimately dampen investors returns.
In essence, the nexus between financial statutory payments and total accruals on the financial performance of listed non-financial firms in Nigeria remains largely unexplored in existing literature. Despite the extensive research on financial performance and related factors, no study has specifically examined the combined impact of financial statutory payments and total accruals on the financial performance of listed non-financial firms in the Nigerian context.
While Bababo and Christopher (2023) investigated the relationship between accruals management and the financial performance of listed manufacturing companies in Nigeria separately, the integration of these factors into a comprehensive analysis is lacking.
Against this backdrop, conducting a study on the financial performance of listed non-financial firms in Nigeria becomes imperative, aiming to uncover trends, challenges, and opportunities within the non-financial sectors of the Nigerian economy. Such research contributes to the body of knowledge in finance, economics, and business management, informing policy formulation, investment strategies, and academic discourse in Nigeria and beyond.
The basic hypothesis underlying this study are stated thus;
Ho1: Financial statutory payments have no significant effect on return on assets of non-financial firms in Nigeria
Ho2: Total accruals have no significant effect on return on assets of non-financial firms in Nigeria.
LITERATURE REVIEW
2.1 Conceptual Framework
2.1.1 Statutory Payment
Statutory payments refer to mandatory financial obligations imposed by law upon employers or individuals in compliance with specific regulations or statutes. These payments are legally required and typically involve contributions to social security, healthcare, or pension schemes to ensure the welfare and financial security of employees or citizens (Faboyede et al., 2021). According to Ahmadu (2016), statutory payments serve as a mechanism for governments to address societal needs and promote social welfare by mandating contributions towards essential services or benefits.
In the context of employment, statutory payments may include contributions towards unemployment insurance, workers’ compensation, or statutory sick pay. These payments are designed to safeguard employees against unforeseen circumstances such as illness, injury, or unemployment, providing financial support and security during times of need. Norziaton and Arfa (2022) opined that, statutory payments may encompass taxes levied on individuals or businesses to fund public services and infrastructure, such as income tax or value-added tax (VAT). The financial implications of statutory payments involve the costs incurred by employers or individuals to fulfill their legal obligations as mandated by government regulations or statutes. These payments represent direct expenses that must be budgeted for and managed within organisational or personal financial frameworks.
Financial statutory payments (FSP) refer to obligatory payments that firms are required to make to the government or regulatory authorities as mandated by law. These payments encompass a variety of financial obligations, including taxes, social security contributions, regulatory fees, and other statutory levies. In the context of corporate financial management, FSPs are critical because they directly impact a company’s financial performance, cash flow management, and overall financial health (Ajiboye & Ibrahim, 2022).
The importance of FSPs lies in their regulatory and legal nature, ensuring that firms comply with national financial regulations and contribute to the public treasury. These payments are not discretionary and must be fulfilled within stipulated timelines to avoid penalties, legal consequences, and reputational damage. For instance, in Nigeria, statutory payments include corporate income taxes, value-added taxes (VAT), pension contributions, and industry-specific levies imposed by regulatory bodies such as the Securities and Exchange Commission (SEC) and the Federal Inland Revenue Service (FIRS).
According to Omoolorun and Abilogun (2017) financial statutory regulations are designed to protect the rights of consumers and ensure that financial institutions and service providers adhere to high ethical standards. These regulations establish a system of accountability and oversight and provide a framework of rules and regulations that must be followed by financial institutions and service providers. Financial statutory regulations also help to protect the integrity of financial markets and promote economic stability. For example, the SEC requires publicly traded companies to make timely and accurate financial disclosures and to adhere to specific reporting requirements. This helps to ensure that investors are able to make informed decisions when investing in securities. Financial statutory regulations are also important for promoting consumer protection. For example, the Consumer Financial Protection Bureau (CFPB) is an independent government agency that has the authority to enforce consumer protection laws. The CFPB enforces laws that protect consumers from unfair, deceptive, and abusive practices in the financial services industry. Additionally, the CFPB works to ensure fair access to credit for consumers and to promote financial education. Financial statutory regulations help to ensure that the financial services industry operates in an ethical, transparent, and fair manner. They also help to protect consumers from fraud and abuse and promote financial stability. Financial statutory regulations are essential to the functioning of the financial sector and the protection of consumers. In Nigeria, the concept of financial statutory is based on the various Acts of Parliament that have been put in place to regulate the financial sector. These Acts are designed to ensure the efficient functioning of the Nigerian financial markets and to protect both investors and financial institutions from fraudulent and other illicit activities (Imagbe et al., 2019). For the purpose of these study financial statutory will be measure this study, financial statutory payment will be measured as the natural log of legal fees.
2.1.1 Total Accrual
Total accrual is an accounting technique used to measure and record the total amount of financial resources used for a period of time Zehri and Chouaibi (2013). Total accrual accounting is also referred to as accrual basis accounting and is a key accounting concept used in financial statement preparation. It is often used in tandem with cash-basis accounting, which records only cash transactions. Dzomira, (2014) opined that total accrual accounting is based on the concept of matching revenue and expenses to the period in which they are incurred. This means that revenue and expenses are recorded when they are generated, not when the cash is received or paid out. This approach is in contrast to the cash-basis accounting method, which records transactions only when cash is received or paid out. According to Yulistyawti et al. (2019), total accrual accounting is used to record all events that affect the financial position of a company, regardless of whether the events involve cash transactions or not. This includes transactions such as accounts receivable, accounts payable, inventory, depreciation, amortization, and other accruals. It is important to recognize the difference between accrual and cash-basis accounting because both types of accounting have different effects on a company’s financial statements.
One of the benefits of total accrual accounting is that it provides a more accurate picture of a company’s financial position (Imagbe et al., 2019). This is because it includes all financial transactions, regardless of whether they involve cash or not. This helps to create a comprehensive view of the company’s financial position and allows for better decision-making. Total accrual accounting is also beneficial because it helps to provide a better understanding of the company’s finacial health. This is because it records all expenses and revenues, even those that may be deferred or capitalized. By recording all of these expenses and revenues, it is easier to identify areas where the company is making a profit or loss. Total accrual accounting is also beneficial because it is more consistent with Generally Accepted Accounting Principles (GAAP). All financial statements prepared using total accrual accounting must be prepared in accordance with GAAP. This helps to ensure that all financial statements are consistent and accurate. Furthermore, total accrual accounting is beneficial because it helps to provide stability to a company’s financial statements. By recording all of the company’s financial transactions, it helps to smooth out the effects of fluctuations in the market. This helps to ensure that the company’s financial statements remain consistent and up-to-date.
Abiloro and Olorunfemi (2021) asserted that total accrual can be used to assess performance by comparing the total income and expenses incurred over a period of time. This comparison allows the organisation to identify trends and patterns in the data which can be used to determine areas of success and failure. For instance, if total income is increasing but total expenses are staying the same, then this could indicate that the organisation is becoming more efficient and/or that the sales team is doing a better job of selling products or services. On the other hand, if total expenses are increasing while total income remains the same, this could indicate that the organisation is not managing its finances effectively. By using total accrual to assess performance, the organisation can develop plans to improve its financial health.
Accruals in accounting pertain to the acknowledgment of revenues and expenses in financial statements at the time they are incurred, irrespective of when the corresponding cash flows take place (Oh & Penman, 2024). Under this accounting principle, revenues are recognised upon being earned, and expenses are recorded upon being incurred, irrespective of the timing of cash inflows or outflows. Accrual accounting differs from cash accounting in that it records transactions when they occur, regardless of when cash is received or paid.
Accruals are essential for ensuring a more precise depiction of a company’s financial performance and condition. Accrual accounting ensures that revenues and expenses are recorded in the period they are incurred, resulting in a comprehensive and up-to-date representation of a company’s profitability and financial well-being (Goel, 2016). This empowers investors, creditors, and other stakeholders to make well-informed judgements regarding the company’s operations and future prospects. Accruals have many ramifications from a financial standpoint. Accrual accounting facilitates the alignment of revenues and expenses, leading to more seamless and consistent financial reporting in the long run. Implementing this strategy can mitigate fluctuations in reported earnings and offer a more accurate representation of the underlying business performance. Flynn et al. (2016) affirmed that accruals allow organisation to comply with accounting standards including the matching principle and revenue recognition principle, which are crucial for maintaining the dependability and comparability of financial statements.
Ohiomegwe et al., (2022) stated that, accruals might have ramifications for the management of cash flow and the planning of finances. Although accruals accurately represent economic activity in real-time, they may not always correspond directly to actual cash inflows and outflows. Consequently, organisation must diligently oversee their cash flow to guarantee they possess adequate liquidity to fulfil their responsibilities, even if income and expenses are acknowledged at varying intervals. Accruals are a crucial component of accounting that improves the precision, dependability, and significance of financial reporting. They facilitate organisation in presenting a thorough and timely representation of their financial performance and position, which is crucial for stakeholders to make well-informed decisions regarding the company’s operations and future prospects. For this study, total accruals was computed as net profit minus net cash from operating activities.
2.1.3 Financial Performance
Financial performance refers to the efficiency with which a company utilizes its assets to generate revenue within a specified period, serving as a metric for assessing its overall financial health and growth trajectory (Aniefor & Onatuyeh, 2020). Stakeholders, including trade creditors, bondholders, shareholders, and management, each have distinct interests in monitoring a firm’s financial performance (Ahmadu, 2016). While trade creditors prioritize liquidity, bondholders focus on solvency, shareholders seek returns on investment, and management evaluates market performance. Financial statements, comprising income statements, cash flow statements, and notes to accounts, serve as a primary source of information on a company’s financial performance.
Various factors influence a firm’s financial performance, including liquidity, leverage, firm size, and managerial competence (Adeniyi & Aderobaki, 2021). Profitability and liquidity metrics are particularly crucial for stakeholders in assessing a firm’s past performance and current standing (Ogoun & Owata, 2019). Capital structure is intricately linked with financial performance, with measures such as return on investment (ROI), earning per share (EPS), return on assets (ROA), and return on equity (ROE) providing insights into a company’s financial strength and market position (Zeitun & Tian, 2007). Equity holders and debt holders, as key stakeholders, are keenly interested in a company’s financial performance due to the implications for their investments (Adenugba et al., 2016). Equity holders bear higher risk but stand to benefit from share value appreciation and dividends, while debt holders prioritize timely repayment with interest, leveraging the security of company assets. Financial performance evaluation thus serves as a critical tool for stakeholders in assessing the viability and sustainability of their investments in the company.
2.1.4 Return on Assets
Returns on assets (ROA) stands as a pivotal financial measure utilized for assessing a company’s profitability, quantifying the ratio of net income to total assets (Imagbe et al., 2019). This metric signifies how effective a company leverages its assets to generate profits and is typically presented as a percentage derived by dividing net income by total assets. A higher ROA implies superior profitability, indicating that the company is generating more earnings from its asset base (Tukur & Abubakar, 2014). Investors often consider ROA crucial in evaluating a company’s performance and growth prospects.
In management literature focusing on accounting-based metrics, return on assets serves as a frequently employed performance indicator (Weir & Laing, 2001). It assesses the efficiency of asset utilization and communicates to investors the earnings derived by the company from its capital investments (Bonn et al., 2004). The effective deployment of corporate funds is reflected in the return rate on assets. Since managers bear responsibility for business operations and asset utilization, ROA serves as a metric aiding stakeholders in assessing the efficacy of a company’s corporate governance structure in fostering and safeguarding managerial performance (Epps & Cereola, 2008). Studies conducted by Tukur and Abubakar (2014) and Arumona et al. (2017) have effectively employed asset returns in their analyses.
2.1.5 Firm Size
Firm size denotes the magnitude of a business entity or the extent of its operations (Falope & Ajirole, 2019). It is often associated with economies of scale, where larger firms can achieve competitive advantages by reducing production costs and expanding market share. The ability of larger firms to produce goods at lower costs compared to smaller counterparts is a manifestation of economies of scale. Additionally, firm size encompasses the breadth and depth of a company’s capabilities, including its capacity to deliver value to customers. Akinyomi and Olagunju (2013) define firm size as the scale of operations and activities within a commercial organisation. They highlight the significance of size in competitive strategy, emphasizing the role of economies of scale in cost reduction and market expansion. Numerous studies have established a positive relationship between firm size and profitability, underscoring the importance of size in determining business success.
Researchers such as Jasch (2013) support this view by pointing out that larger enterprises, due to their larger market share, often enjoy higher profitability. The competitive environment in which larger firms operate contributes to their profitability. Empirical research in corporate finance underscores the significance of firm size as a fundamental characteristic, with studies revealing the impact of size on various dependent variables across different contexts.
2.2 Empirical Review
Bababo and Christopher (2023) investigated the relationship between accruals management and the financial performance of listed manufacturing companies in Nigeria. In order to achieve the aim of the research, six specific objectives and hypothesis were proposed. Accruals management was measured by discretionary accruals (DACC) and non-discretionary accruals (NDAC) while financial performance was measured by return on assets (ROA); net profit margin (NPM); and return on capital employed (ROCE). Data for the research covered a period of 11 years from 2010 to 2020 for 20 listed manufacturing companies – thus comprising 220) firm years. Analytical employed for the purpose of the research included descriptive statistics, Pearson correlation and panel least square (PLS) regression method as well as ADF unit root test. Findings of the research revealed that there is a negative non-significant relationship between discretionary accruals and return on assets; net profit margin; and return on capital employed. And non-significant negative relationship between non-discretionary accruals and return on assets; net profit margin; and return on capital employed. From the findings, it was concluded that both discretionary and non-discretionary accruals do not make meaningful contribution to financial performance. It is further concluded that the ability to control/manage the flow of accruals is very important to corporate organisation. The researcher thus recommended that manufacturing companies take more interest in controlling/managing their accruals. This is because accrual in its uncontrolled/unmanaged form (non-discretionary accruals) is clearly shown to be harmful to the organisation. Bababo and Christopher (2023) fail to provide substantial evidence linking accruals management to financial performance, rendering their conclusions about the harmful effects of non-discretionary accruals on listed manufacturing companies in Nigeria unconvincing.
Omah (2022) evaluated the impact of financial statement fraud and financial performance of selected food and beverage companies in Nigeria. The proxies for the independent variable (Financial statement fraud) were improper expense recognition, and incorrect asset valuation. The proxy used for the dependent variable (financial performance) was return on assets (ROA). The specific objectives were to ascertain the effect of improper expense recognition on return on assets (ROA) and also to ascertain the effect of incorrect asset valuation on return on assets (ROA). Descriptive research design was adopted for the study while secondary data were collected from the financial reports of the selected firms and website of security and exchange commission. The analysis of covariance (ANCOVA) was used, and STATA II econometric method was used in the analysis of the data. Altman model and operating expenses ratio was adopted in the analysis of the financial reports to create a dummy variable for the selected firms from 2004-2018 and validation of the parameters were ascertained using various statistical techniques such as t-test, co-efficient of determination (R2), F-statistics and Wald £hi-square. The findings revealed that there is a significant relationship between financial statement fraud and financial performance of selected food and beverage companies in Nigeria. The study recommended that professional accounting bodies and appropriate regulators should ensure proper financial statement fraud management system within the organisation as internal control. Omah (2022) provides a superficial analysis of the impact of financial statement fraud on the financial performance of selected food and beverage companies in Nigeria, relying excessively on statistical techniques without adequately addressing the underlying mechanisms or offering practical insights for mitigating fraud in financial reporting.
Norziaton and Arfa (2022) assessed financial statement fraud and firms profitability: Evidence from Malaysian public listed companies. The main objective of this study is to investigate the primary factors that influence the public listed companies in Malaysia to be involved in financial statement fraud. The sample used in this study comprised 40 financial statement fraud companies matched with another 40 non-financial statement fraud companies listed in Bursa Malaysia from 2003 to 2020. This study used the fraud triangle theory to form the research framework and develop the research hypotheses. Four hypotheses based on the elements of fraud, which are the financial target, external pressure, earnings management, and related-party transaction, have been developed and tested. Pool regression analysis was conducted to examine the relationship between the elements of fraud and financial statement fraud. The results indicated that there is a significant relationship between financial targets, earnings management, related-party transaction and financial statement fraud, thus the hypotheses are accepted. However, there is an insignificant relationship between external pressure and financial statement fraud, hence the hypothesis was rejected. Interestingly, it was found that the fraud companies had poorer earnings quality one year before they committed the financial statement fraud. Overall, this study would assist the auditors as it identifies early warning signals or red flags. The study recommended that information obtained from this study could be used by Bursa Malaysia to develop strong regulations and encourage Malaysian public listed companies to enhance anti-fraud policies. Norziaton and Arfa (2022) fail to account for potential biases in their sample selection and the limitations of using pooled regression analysis, which undermines the reliability of their findings
Yene-Chimy and Forzeh (2021) studied the relationship between accrual accounting practice and financial performance in local governments in Cameroon. Using accountability and efficiency as performance proxies, the study employs a mix of qualitative and quantitative research approaches with a triangulated method of data collection. In a population of 374 councils, 50 councils were sampled and clustered according to their statutory council categories. Both descriptive and inferential statistics were used with a multiple regression analysis on panel data to test the relationship between accrual accounting practice and financial performance within council categories. The findings revealed that about 77% of councils (predominantly rural councils) practicing mild accrual accounting scored a higher financial performance. Meanwhile, 23% of councils (mostly city councils) practicing a moderate and sometimes strong accrual accounting had a lower financial performance. The pooled regression analysis showed a 13 % insignificant but positive correlation between financial performance and accrual accounting practice. These findings where then backed up with inferences drawn from interviews, discussions as well as content study of accounting books. It revealed that councils have the latitude to navigate from mild, moderate, and strong accrual accounting practice as the need arose. Accrual accounting practice should be sequenced in ways that councils can focus on mild accrual accounting practice, and it should move to a higher level of moderate and full accrual accounting only when they can afford the expertise and infrastructural resources needed to yield a significant performance result. The use of data from Cameroon limits the generalizability of Yene-Chimy and Forzeh’s (2021) findings to other contexts, such as Nigeria, where the institutional and economic environments may differ significantly. Additionally, the reliance on pooled regression analysis without adequately addressing potential panel data issues, such as autocorrelation and heteroskedasticity, raises concerns about the robustness of their results.
Olatunji and Juwon (2020) investigated relationship between accrual-based earnings, real-based earnings management and firm’s value of listed manufacturing companies in Nigeria. The study adopted descriptive, panel least square regression technique such as pooled, fixed and random effect with various diagnostic evaluation techniques. The result revealed that accrual-based earnings management measured by abnormal discretionary accrual earnings (ADA) was positively related with the firm’s value captured by the return on equity (ROE) of the quoted manufacturing companies and increased it to the turn of 38.31 per cent. On the other hand, the real-based earnings management measured by abnormal cash flow operation activities (ACF) was discovered to be negatively related with the firm’s value captured by return on equity and thus reduced it by 12.25 per cent. The result of the individually selected quoted manufacturing companies showed that accrual-based earnings management captured by abnormal discretionary accrual earnings (ADA) and real-based earnings management influence the return on equity (ROE) a measured of firm value respectively. While, on the other hand, accrual-based earnings management captured by abnormal discretionary accrual earnings (ADA) and real-based earnings management reduced the return on equity (ROE) a measured of firm value in Nigeria. Hence, this study concluded that the practice of earnings management constructively benefits the manipulator of accounts. It can be emphasized that ease in detecting accrual earnings management can make investors to decide whether a company is worthy of their investment. The study recommended that companies should be encouraged or mandated to improve their financial disclosure practices. Olatunji and Juwon (2020) present contradictory findings and fail to provide clear, actionable insights due to methodological weaknesses and inconsistent interpretations of the impact of earnings management on firm value.
Isa and Awalludin (2020) investigated detection of fraudulent financial reporting using ratio analysis. The main objective of this analysis was to examine the uses of financial ratios as a tool for detecting fraud in financial reporting. This study examines the annual reports of companies that have been reprimanded by the Securities Commission from 2000 to 2009 for submitting false or misleading information. Ratio-analysis was performed to see if fraudulent financial reporting were predictable or not. The ratios of leverage, profitability, efficiency, and liquidity with have been tested. This study uses trend analysis to figure out changes of more than 10% which may indicate the possibility of financial mismanagement as a change in the ratio of more than 10% annually can be seen as a sign of financial mismanagement. In conclusion, the findings show that signs of fraudulent financial reporting can be detected much earlier. The study recommended that fraudulent financial reporting may be detected even at a much earlier stage if a thorough investigation has been carried out into the submission of each financial statement-related report. Isa and Awalludin (2020) rely on a simplistic and potentially misleading threshold of a 10% change in financial ratios to detect fraudulent financial reporting, which undermines the study’s credibility and practical applicability.
Uwuigbe et al. (2019) looked into the association which exists amid financial statement fraud and governance among business organisations in Nigeria. A population of 122 non-financial companies registered on Nigeria stock exchange was limited to 20 firms employing the rule of thumb based on stratified and simple random technique for a period of 2012-2016. The method of data analysis is panel regression. The dependent variable, fraud in the financial statement was measured using the Beneish M-score model while the independent variable was measured using audit committee independence, board structure. Findings show that an insignificant association exist amid audit committee independence, the composition of the board and financial statement fraud. The research recommended regarding the reduction of the occurrence of financial statement fraud, less emphasis should be placed on audit committee independence, board composition and independent non-executive directors’ effectiveness. The study employed business organisations in Nigeria and was only limited to twenty listed firms. Meanwhile, this present study will consider using seventy-one listed non-financial firms and for the period of fifteen years.
Hussaini et al. (2018) examined the influence of auditor brand name proxied by the Big4 auditors on financial reporting fraud represented by discretionary accruals (DA). The study employ 88 listed companies in Nigeria through 440 firm-year observations for the period of five years from 2012 to 2016. The data for the study are extracted from the annual reports of the listed companies and Thompson Reuters DataStream. The study adopt accruals model to proxy for financial reporting fraud and multiple regression was used to estimate the model of the study. After controlling for monitoring and firm-specific attributes, the study found that non-Big4 auditors are more likely to detect financial fraud as they might have more excellent knowledge of local markets and better relations with their clients. Consistent with the resource dependence theory, the study found that a high proportion of financial experts on the board reduces the extent of financial reporting fraud, thus leading to better financial reporting quality. The study informs regulators and policymakers on the importance of auditor brand name in curtailing financial reporting fraud in the listed companies of Nigeria. The study recommended that high proportion of financial experts is imperative for enriching board monitoring since it leads to better financial reporting quality. Hussaini et al. (2018) present a questionable conclusion that non-Big4 auditors are more effective at detecting financial fraud without adequately addressing potential biases and limitations associated with local market knowledge and auditor-client relationships, which weakens the overall validity of their findings.
2.3 Theoretical Framework
2.3.1 Institutional Theory
Developed by Meyer and Rowan in 1977, institutional theory posits that organisations are influenced by institutional pressures and norms, shaping their behavior, practices, and structures (Meyer & Rowan, 1977). These pressures emanate from external entities such as regulatory bodies, professional associations, and societal expectations, driving organisations to conform to established institutionalized practices to gain legitimacy and survival. In the context of financial statutory payments, total accruals, and financial performance of listed non-financial firms in Nigeria, institutional theory offers valuable insights into how external forces shape corporate behavior and decision-making. Nigerian firms operate within a regulatory environment characterized by legal requirements, taxation policies, and corporate governance standards set by regulatory bodies like the Securities and Exchange Commission (SEC) and the Financial Reporting Council of Nigeria (FRCN). Compliance with these institutional norms regarding financial reporting practices and statutory payments is crucial for maintaining legitimacy and avoiding penalties or reputational damage.
Critics of institutional theory argue that it tends to oversimplify organisational behavior by neglecting internal dynamics and agency-driven actions (DiMaggio & Powell, 1983). Additionally, some scholars suggest that institutional pressures may lead to isomorphism, where organisations conform to institutionalized practices without considering their effectiveness or appropriateness for achieving organisational goals (Meyer & Rowan, 1977).
2.3.2 Legal Compliance and Reputation Theory
Reputation theory was significantly developed by Charles Fombrun in the 1990s, particularly with his seminal work “Reputation: Realizing Value from the Corporate Image” published in 1996. Fombrun emphasized the strategic importance of managing corporate reputation as an intangible asset that can enhance a firm’s financial performance. Legal compliance, as a concept, has long been embedded in regulatory and business practice discourse, but its integration with reputation theory has gained prominence as firms increasingly recognize the intertwined nature of legal adherence and corporate image.
In the context of listed non-financial firms in Nigeria, the application of legal compliance and reputation theory is highly pertinent. Nigerian firms operate in a regulatory environment characterized by stringent statutory payment requirements, such as taxes and other governmental levies. Compliance with these statutory obligations is not only a legal necessity but also a crucial component in shaping the firm’s reputation among stakeholders, including investors, customers, and regulatory bodies. Firms that adhere to these requirements and foster a positive reputation are likely to enjoy enhanced investor confidence, customer loyalty, and operational stability, all of which contribute to better financial performance.
One of the primary strengths of legal compliance and reputation theory is its holistic approach. It recognizes that financial performance is not solely a product of internal management efficiencies but is also significantly influenced by external perceptions and regulatory adherence. This theory underscores the importance of a firm’s external environment and its interactions with regulatory bodies and the public. However, a notable weakness of the theory is its potential oversimplification of the relationship between compliance, reputation, and financial performance. While compliance and a good reputation generally contribute to positive financial outcomes, this relationship can be influenced by various other factors such as market conditions, competitive dynamics, and macroeconomic variables. Moreover, the theory might not adequately account for the costs associated with maintaining compliance and a positive reputation, which can be substantial and may impact short-term financial performance. Critics argue that legal compliance and reputation theory may place excessive emphasis on external perceptions and regulatory adherence, potentially at the expense of innovation and risk-taking. They suggest that a strict focus on compliance and reputation management can lead firms to adopt overly conservative strategies, stifling creativity and limiting growth opportunities. Additionally, the relationship between reputation and financial performance is sometimes seen as correlational rather than causal, with critics highlighting that firms with strong financial performance might have more resources to invest in compliance and reputation management, rather than these factors directly leading to financial success.
Despite its criticisms, legal compliance and reputation theory serves as a robust underpinning framework for examining the financial performance of listed non-financial firms in Nigeria. The theory’s emphasis on the interplay between regulatory adherence and reputation aligns well with the operational realities faced by these firms. In a regulatory environment where non-compliance can lead to severe penalties and reputational damage can result in significant financial losses, understanding and applying this theory can provide valuable insights into strategic management practices that enhance financial outcomes. Moreover, it offers a comprehensive perspective that integrates legal, social, and economic dimensions, making it a versatile tool for analyzing the multifaceted factors influencing financial performance.
METHODOLOGY
A correlational panel research design was employed in this study to gather information about the pre-existing nature of the phenomenon under study and to provide the necessary support to provide and describe the nature of the relationships between variables of the study. The total population for this study consists of all the one hundred and six (106) non-financial companies (firms) listed in the Nigerian Exchange Group as at 31st December, 2022. In order to arrive at the sample size, the purposeful sampling technique were employed. The criterion used is that; a firm must be listed before the year 2008, remain in operation during the period of the study (2008 to 2022) and selections were also made on the basis of the non-financial firms found in the Nigeria Exchange Group stratification of the listed companies.
This is to reduce any problem associated with validity and reliability. A total of twenty (20) non-financial firms was selected for sample selection. The study covers a period of 15 years ranging from 2008-2022. Secondary data was collected for the dependent and independent variables were analyzed using descriptive statistics, correlation analysis, panel regression and post regression diagnostic test on variables using statistical package E-view version 13. The model employed by Olatunji and Juwon (2020) was modified and adapted for the study, as indicated below.
Adapted Model
ROE = β0+ β1ADA + β2ACF + є —————————————- (i)
Modified Model
ROA =α0+ β1FSP + β2TAC + β3FSZ + є —————————————- (ii)
Where;
ROA = Returns on Assets
FSP = Financial Statutory Payments
TAC= Total Accrual
FSZ = Firm Size
α0 = Constant or intercept
β1- β 3 = Regression coefficients.
ε = Stochastic error term.
Apriori Expectation
Variable | A Prior Expectation | Explanation |
Financial Statutory Payments | Positive | Compliance with legal and regulatory obligations is expected to enhance financial performance (measured by ROA). |
Total Accrual | Mixed | Previous studies show conflicting findings: potential negative effects due to earnings management and positive effects due to operating efficiency. |
Firm Size | Positive | Larger firms are anticipated to have better financial performance due to economies of scale, greater market share, and better resource accessibility. |
Source: Research’s Compilation
This table summarizes the anticipated relationships between each variable and Return on Assets (ROA) based on existing literature and theoretical expectations.
Table 1: Definition of Variables
Variable | Type | Measurement | Source |
Return on Assets (ROA) | Dependent | Measured by dividing profit after tax over total assets. | Ogoun & Owota (2019) |
Financial Statutory Payments (FSP) | Independent | Computed as the natural log of legal fees | Okoye & Gbegi (2013) |
Total Accruals (TAC) | Independent | Total Accrual = Net Profit – Net Cash from operating activities | Suhaily & Oloruntoba (2018) |
Firm size (FSZ) | Control | Measure as natural log of total Asset | Omollo, et al., (2018) |
Source: Researcher Computation (2024)
RESULTS AND DISCUSSION
Data Presentation
This section established results of regression analysis on the effect of financial statutory payment and total accruals of listed non-financial firms in Nigeria, using the panel regression analysis technique.
Descriptive Statistics
The study’s data are described using the mean, standard deviation, variance, maximums, minimums, skewness, and kurtosis. Table 4.1 presents the descriptive statistics for the variables of the study below.
Table 2: Descriptive Statistics
ROA | FSP | TAC | FSZ | |
Mean | 0.201483 | 5.867059 | 17390695 | 7.152297 |
Median | 0.200700 | 5.866180 | 1940324. | 7.048500 |
Maximum | 0.987700 | 7.858850 | 5.180808 | 9.578000 |
Minimum | -3.913000 | 3.684127 | -5240846. | 4.027000 |
Std. Dev. | 0.405063 | 0.735515 | 59748904 | 0.965036 |
Skewness | -3.604995 | -0.011361 | 6.315900 | -0.069816 |
Kurtosis | 37.66239 | 3.173607 | 46.63529 | 2.998907 |
Jarque-Bera | 15668.31 | 0.381921 | 25709.03 | 0.243727 |
Probability | 0.000000 | 0.826165 | 0.000000 | 0.885269 |
Sum | 60.44477 | 1754.251 | 5.206509 | 2145.689 |
Sum Sq. Dev. | 49.05876 | 161.2126 | 1.067888 | 278.4573 |
Observations | 300 | 300 | 300 | 300 |
Source: E-views 13 Output (2024)
Table 2 presents a summary of the descriptive statistics for the variables incorporated in the model. The table indicates that the average return on assets (ROA) is 0.201483, with a standard deviation of 0.405063. The minimum observed ROA value is -3.913000, while the maximum value is 0.987700. The relatively narrow range between the minimum and maximum values suggests a stable performance, as supported by the standard deviation indicating that the data are closely distributed around the mean value.
Financial statutory payment is another attribute metric, as shown in table 2 above, with a mean value of 5.86, a standard deviation of 0.73, and a minimum and maximum value of 3.68 and 7.85, respectively. The standard deviation is statistically different from the mean and the range between the minimum and maximum values is limited, the financial statutory payment appears to have decrease marginally throughout the research period. The data also shows that for the time period, the total accrual (TAC) was 17390695, with a standard deviation of 59748904 and lowest and highest values of -5248904 and 5.180808, respectively. This suggests that the total accrual grew dramatically over the research period. Moreover, the average level of firm size is 7.152297, with a standard deviation of 0.965036. The minimum and maximum values for firm size are 4.027000 and 9.578000, respectively.
The analysis was also fortified by the value of the skewness and kurtosis of all the variables involved in the model. All the distributions are both negatively and positivity skewed. Variables with value of kurtosis less than three are called platykurtic (fat or short-tailed) only firm size qualified for this during the study period. On the other hand, variables whose kurtosis value is greater than three are called leptokurtic (slim or long tailed) and all the variables qualified for this during the study period except for firm size. Jarque-Bera test shows that the residuals are not normally distributed as indicated by the probability values less than 5% in the case of ROA and TAC, while in the case of FSP and FZS the residuals are normally distributed. In summary, the descriptive statistics revealed that ROA and TAC data sets are not normally distributed. This is so because the probability values of the variables are less than 5%.
Correlation Analysis
Table 3 below shows the results of the association between the independent and dependent variables of listed non-financial firms in Nigeria. It contains the Pearson pairwise correlation coefficients of the variables under study. The correlation matrix is presented in Table 4.2 below.
An acceptable correlation is typically considered significant if the absolute value of the correlation coefficient is at least 0.3, indicating a moderate relationship, while a high correlation would generally be above 0.7.
Table 3: Correlation Matrix
Correlation | ||||
Probability | ROA | FSP | TAC | FSZ |
ROA | 1.000000 | |||
—– | ||||
FSP | -0.142497 | 1.000000 | ||
0.0138 | —– | |||
TAC | -0.071271 | 0.503746 | 1.000000 | |
0.2199 | 0.0000 | —– | ||
FSZ | 0.045087 | -0.134835 | 0.007504 | 1.000000 |
0.4381 | 0.0199 | 0.8974 | —– |
Source: E-views 13 Output (2024)
The correlation results presented in Table 3 illustrate the relationship between the dependent variable, Return on Assets (ROA), and the independent variables: Financial Statutory Payments (FSP), Total Accrual (TAC), and Firm Size (FSZ). Financial Statutory Payments exhibit a negative and weak correlation (-0.142497) with ROA, indicating that higher levels of statutory payments are associated with lower returns on assets. Similarly, Total Accrual demonstrates a negative and weak correlation (-0.071271) with ROA, suggesting that greater accruals are associated with lower returns on assets, albeit to a lesser extent. In contrast, Firm Size displays a positive and weak correlation (0.045087) with ROA, indicating that larger firms tend to have slightly higher returns on assets. Overall, these correlation results suggest that financial statutory payments and total accruals may exert negative influences on ROA, while firm size may have a modest positive impact, although the relationships are relatively weak in magnitude. Moreover, the analysis reveals that the associations between and within the variables under study are weak, indicating the absence of significant multicollinearity.
Multicollinearity Test (VIF)
To ensure the robustness of the measurements, multicollinearity tests were conducted using the Variance Inflation Factor (VIF) as the evaluation criterion. Multicollinearity arises when one or more independent variables exert a significant influence on others, violating the assumptions of the linear regression model and potentially compromising the validity of the analysis outcomes. Conducting multicollinearity tests is essential to determine if there is a strong inter-correlation among independent variables that could lead to erroneous results.
Table 4: Multicollinearity Test (VIF)
Coefficient | Uncentered | Centered | |
Variable | Variance | VIF | VIF |
C | 158.23367 | 9.02627 | NA |
FSP | 591.53893 | 7.95491 | 1.926372 |
TAC | 637.94632 | 9.64993 | 1.987645 |
FSZ | 88.974334 | 9.39419 | 1.988245 |
Source: E-View 13 Output (2024)
*Decision rule: uncentered VIF less than 10 indicates the absence of multi-collinearity, while VIF intermediate over 10 is a sign of multi-collinearity. As noted above, the law of multicollinearity test rule uses a variance inflation factor that VIF centered below indicates a lack of multi-collinearity, while VIF intermediate over 10 indicates the presence of multi-collinearity. Table 4 above shows the absence of multicollinearity between independent variables, as all independent variables (FSP, TAC and FSZ) have less than 10 VIF centres.
Heteroskedasticity
In order to validate the panel regression results, the Heteroskedasticity test was conducted as a robustness check. Heteroskedasticity happens when the standard errors of a variable, monitored over a specific amount of time, are non-constant. Heteroskedasticity is a violation of the assumptions for linear regression modeling, and so it can impact the validity of the result from any analysis while heteroskedasticity does not cause bias in the coefficient estimates, it does make them less precise; lower precision increases the likelihood that the coefficient estimates are further from the correct population value.
Hypothesis
Ho: There is no heteroskedasticity problem in the model (Residuals are homoskedastic)
Hi: There is heteroskedasticity problem in the model
Decision Rule:
Reject H0 if the Prob. value is less than 0.05 (5% level of significant). Otherwise, do not reject H0.
Table 5: Heteroskedasticity Test
Value | df | Probability | |
Likelihood ratio | 101.6732 | 20 | 0.0711 |
LR test summary: | |||
Value | Df | ||
Restricted LogL | -178.7938 | 296 | |
Unrestricted LogL | -948.8374 | 296 |
Source: E-views 13 Output (2024)
Based on the above rule of thumb, the Heteroskedasticity Test, Prob. value is 0.0711, greater than 0.05; thus, the study affirmed that the regression model is free from Heteroskedasticity problem
Hausman Test
The Hausman test is a test for model specification in panel data analysis and this test is employed to choose between fixed effects model and the random effects model. Due to the panel nature of the data set utilized in this study, the test basically checked if the error terms were correlated with the regressors. Thus, the decision rule for the Hausman specification test is stated thus; at 5% Level of significance:
Decision Rule:
Reject H0 if the Prob > F is less than 0.05. Otherwise, do not reject H0.
Hypothesis
H0: Random effect is most appropriate for the Panel Regression analysis
H1: Fixed effect is not appropriate for the Panel Regression analysis
Table 6: Hausman Test
Test Summary | Chi-Sq. Statistic | Chi-Sq. d.f. | Prob. |
Cross-section random | 1.418968 | 3 | 0.7011 |
Source: E-views 13 Output (2024)
The result of the Hausman test appended in table 5 above does not provide sufficient evidence to reject this null hypothesis at 5% level of significance as can be seen that the probability value (0.7011) of the test is greater than the critical value of 0.05. Therefore, the study upholds that difference in coefficients is not systematic and hence, the random effect model is the most appropriate models for the study. It is imperative therefore, to proceed to another test which is the Langranger Multiplier test, which will indicate the appropriateness or otherwise of using the pooled effect model or the random effect model.
Breusch-Pagan and Lagranger Multiplier Test
In panel data analysis, the Lagranger multiplier test is used to select between pooled and random effects models.
Hypothesis
H0: Pooled effect is not appropriate for the Panel Regression analysis
H1: Random effect is most appropriate for the Panel Regression analysis
Decision Rule: if the p-value is less than 0.05 the decision rule is to reject the null hypothesis which states that pooled effect is most appropriate for the Panel Regression analysis (meaning that the preferred model is random effects). Similarly, if the p-value is greater than 0.05 the decision rule is to accept the null hypothesis which states that pooled effect is most appropriate for the Panel Regression analysis (meaning that the random effect model is to be rejected).
Table 7: Breusch-Pagan and Lagranger Multiplier Test
Test | Statistic | d.f. | Prob. |
Breusch-Pagan LM | 266.1187 | 190 | 0.0002 |
Source: E-View 13 Output (2024)
Based on the probability value of the Breusch-Pagan Langranger Multiplier Test at probability value of 0.0002, the null hypothesis is rejected, thus random effect is most appropriate when compared to pooled effect.
Test of Research Hypotheses
In panel regression analysis, the ultimate goal is the estimation of the relationship between dependent and independent variables. This goal can be achieved through the estimation of the coefficients of each independent variable in the model. The sign of coefficients of independent variables indicates their relationship with dependent variable, while the magnitude of the coefficients implies the responses of dependent variables to independent variables.
Decision Rule: The decision rule for accepting or rejecting the null hypothesis for any of these tests was based on the Probability Value (PV) and the Probability (F-statistic). If the PV is less than 5% or 0.05 (that is, if PV < 0.05), it implies that the regressor in question is statistically significant at 5% level; and if the PV is more than 5% or 0.05 (that is, if PV > 0.05), it is categorized as not significant at that level. This implies that the level of significance for the study is at 5% (for the two-tailed test). Thus, the decision rule for accepting or rejecting the null hypothesis is based on both the Probability Value (PV) and the Probability (F-statistic)”.
Table 9: Panel Regression Result (Random Effect)
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | 0.691748 | 0.340728 | 2.030204 | 0.0432 |
FSP | -0.071454 | 0.040210 | -2.777013 | 0.0466 |
TAC | -1.715310 | 4.768210 | -0.359068 | 0.7198 |
FSZ | 0.009465 | 0.030623 | 0.309078 | 0.7575 |
Effects Specification | ||||
S.D. | Rho | |||
Cross-section random | 0.156156 | 0.1454 | ||
Idiosyncratic random | 0.378572 | 0.8546 | ||
Weighted Statistics | ||||
R-squared | 0.417076 | Mean dependent var | 0.107540 | |
Adjusted R-squared | 0.397046 | S.D. dependent var | 0.378903 | |
S.E. of regression | 0.377564 | Sum squared resid | 41.91104 | |
F-statistic | 1.702518 | Durbin-Watson stat | 1.889295 | |
Prob(F-statistic) | 0.166580 |
Source: E-View 13 Output (2024)
The table 9 established that, a unit increase in financial statutory payment (FSP) and Total Accrual (TAC) on the average holding other independent variables constant will lead to a -0.071454 and -1.715310 unit decrease in return on assets (ROA) of the listed non-financial firms in Nigeria. Besides, a unit increase in firm size (FSZ) and on the average holding other independent variables constant will lead to a 0.009465 unit increase in performance (ROA) of the listed non-financial firms in Nigeria respectively. However, based on the probability value, financial statutory payment (FSP) was negatively but statistically significant in explaining the variation in the return on assets (ROA) of the listed non-financial firms in Nigeria; total accruals (TAC) was negatively and statistically insignificant in explaining the variation in the return on assets (ROA) of the listed non-financial firms in Nigeria; Firm Size (FSZ) was positively and statistically insignificant in explaining the variation in the return on assets (ROA) of the listed non-financial firms in Nigeria.
Furthermore, the R2 value is 0.47; it indicates the prediction capability of the independent variables. This indicates that 41% changes in the financial statutory payment and total accruals were explained by the changes in the return on assets (ROA) of the listed non-financial firms in Nigeria. Also, that about 59% other factors that could bring about changes in the model were not included. Furthermore, the value of 41% of the R2 shows an optimum relationship between the financial statutory payment, total accruals and financial performance of listed non-financial firms in Nigeria.
More so, the study established that the HO1 which stated that financial statutory payment has no significant effect on return on assets (ROA) of the listed non-financial firms in Nigeria is rejected; this is because the p-value of 0.0466 is less than 0.05. Conversely, the HO2 which stated that total accrual has no significant effect on return on assets (ROA) of the listed non-financial firms in Nigeria is accepted; this is because the p-value of 0.7198 is greater than 0.05. Thus, the study affirmed that financial statutory payment serves as essential tool that can influence financial performance of listed non-financial firms in Nigeria. This is because; the Prob. (F-statistic) is 0.166580, greater than 0.05. Also, the Durbin-Watson stat of 1.8 shows that the regression model is free from auto-correlation.
DISCUSSION OF FINDING
The findings of the study reveal important insights into the relationship between financial statutory payments, total accruals, and the financial performance of listed non-financial firms in Nigeria. Firstly, the rejection of Hypothesis one (HO1) suggests that financial statutory payments have a significant effect on return on assets (ROA) for these firms. This implies that adherence to statutory payment obligations plays a crucial role in influencing financial performance. The significance of this finding underscores the importance of regulatory compliance and financial transparency in enhancing the overall performance of non-financial firms in Nigeria. It suggests that firms that prioritize meeting their statutory payment obligations are likely to achieve better financial outcomes, possibly through improved stakeholder trust and reduced regulatory risks. This study is in tandem with the study of Olatunji and Juwon (2020) which state that adherence to statutory financial obligations and transparent financial practices positively impact firm performance. Their study indicated that such compliance enhances stakeholder trust and reduces regulatory risks, ultimately contributing to better financial outcomes for firms.
Conversely, the acceptance of Hypothesis two (HO2) indicates that total accruals do not have a significant effect on return on assets (ROA) for listed non-financial firms in Nigeria. While accruals are commonly used as a measure of earnings management and operational efficiency, the non-significant relationship with financial performance in this context suggests that the impact of accruals on ROA may be limited or influenced by other factors. These findings disagree with the findings of Uwuigbe et al., (2019) and Norziation and Arfa (2022). Overall, the study’s findings have significant implications for accounting practices in Nigeria. The confirmation of the influence of financial statutory payments on financial performance highlights the importance of robust financial reporting practices and compliance with regulatory requirements. It emphasizes the need for firms to prioritize transparency and accountability in financial management to enhance their competitiveness and sustainability in the Nigerian market (Uwuigbe et al., (2019). Additionally, the non-significant relationship between total accruals and financial performance suggests that while accruals may be useful for internal decision-making, they may not directly impact financial performance in the context of listed non-financial firms in Nigeria. This underscores the importance of adopting a nuanced approach to financial analysis and decision-making, considering multiple factors beyond accruals alone.
CONCLUSION AND RECOMMENDATION
The findings of this study shed light on the relationship between financial statutory payments, total accruals, and the financial performance of listed non-financial firms in Nigeria. The results indicate that financial statutory payments significantly influence financial performance, highlighting the importance of regulatory compliance and transparency in enhancing financial performance. Conversely, total accruals do not exhibit a significant effect on financial performance, suggesting that their impact on financial performance may be limited in this context. These findings underscore the importance of robust financial reporting practices and adherence to regulatory requirements for improving the financial performance of non-financial firms in Nigeria.
Based on the study’s findings, the following recommendations are proposed to enhance the efficient financial performance of listed non-financial firms on the Nigeria Exchange Group;
- Firstly, it is crucial for firms to prioritize compliance with financial statutory payments, as demonstrated by the significant influence of such payments on financial performance. This entails adhering to regulatory requirements, tax obligations, and other statutory payments to maintain transparency and credibility with stakeholders.
- Secondly, while total accruals may not directly impact financial performance in this context, firms should still focus on prudent financial management practices to minimize unnecessary accruals and ensure accurate representation of financial performance. This includes regular monitoring of accrual levels, adopting conservative accounting policies, and maintaining transparency in financial reporting.
These actions are essential for promoting trust among stakeholders and optimizing the financial health and sustainability of listed non-financial firms.
REFERENCES
- Abiloro, T. A., & Olorunfemi, D. Y. (2021). Assessing performance through total accrual: An analysis of income and expenses. Financial Review, 45(2), 217-229.
- Adeniyi, S. I. & Aderobaki, V. A. (2021). The effect of debt level, long term debt and debt – equity level on financial performance of list agricultural firms on the Nigeria stock exchange. Journal of Contemporary Issues in Accounting, 1(1), 17-28.
- Adenugba, A. A., Ige, A. A. & Kesinro, O. R. (2016). Financial leverage and firm’s value: A study of selected firms in Nigeria. European Journal of Research and Reflection in Management Sciences, 4(1), 14-32.
- Ahmadu, M. S. (2016). Effects of financial leverage on firms’ performance. Journal of Accounting and Finance, 15(6), 57-65
- Ajiboye, F. A., & Ibrahim, A. (2022). Financial statutory payments and their impact on corporate financial management. Journal of Financial Markets, 24(2), 85-102.
- Akinyomi, O. J. & Olagunju, G. (2013). Effect of capital structure on firm performance: Evidence from Nigeria manufacturing industry. International Journal of Innovation research and studies, 2(9), 1-13.
- Aniefor, S. J. & Onatuyeh, A. E. (2020). Effect of debt financing on the corporate performance: A study of listed consumer goods firms in Nigeria. International Journal of Academic Accounting, Finance & Management Research. 3(5), 26-34.
- Arumona, J. O., Erin, O., Eriki, E. & Jacob, A. (2017) studied the impact of Enterprise Risk Management ERM) on financial performance in the emerging market with special focus on the Nigerian financial sector. International Journal of Management, Accounting and Economics, 4(9), 54-63.
- Arunkumar, K. (2015). How to Detect Fraud in Corporate financial statement. Journal of Accounting Research. 4(1), 71 – 127.
- Bababo, A. O., & Christopher, E. C. (2023). Accruals Management and the Financial Performance of Listed Manufacturing Companies in Nigeria. International Journal of Business & Management. 7(12), 105-113.
- DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organisational fields. American Sociological Review, 48(2), 147-160.
- Dzomira, S. (2014). The concept of matching revenue and expenses in total accrual accounting. Global Finance Journal, 29(4), 133-150.
- Epps, R. W., & Cereola, S. J. (2008). Do institutional shareholder services (ISS) corporate governance ratings reflect a company’s operating performance? Critical Perspectives on Accounting, 19, 1138-48.
- Faboyede, S. O., Enyi, P. & Dick O. M. (2021). The accountability in the financial statements of Nigerian banks. Academy of Accounting and Financial Studies Journal, 25(4), 1-17.
- Falope, O. L. & Ajirole, O. T. (2019) Working capital management and corporate profitability: Evidence from panel data analysis of selected quoted companies in Nigeria, Research Journal of Business Management, 3(2), 73 – 84.
- Flynn, M. S., Moretti, D., & Cavanagh, J. (2016). Implementing accrual accounting in the public sector. International Monetary Fund.
- Goel, D. S. (2016). The earnings management motivation: Accrual accounting vs. cash accounting. Australasian Accounting, Business and Finance Journal, 10(3), 48-66.
- Hussaini, B., Noor, A. A. & Hasnah, S. (2018). The influence of auditor brand name proxied by the Big4 auditors on financial reporting fraud represented by discretionary accruals Journal of Advanced Research in Business and Management Studies. 11, (1), 84-94.
- Imagbe, V. U., Abiloro, T. O., & Saheed, G. A. (2019). Fraud diamond and financial crimes in Nigerian banking industries. International Journal of Academic Research in Accounting, Finance and Management Sciences, 9(4), 294-303.
- Isa, N. F., Awalludin, N. R. (2020). Detection of Fraudulent Financial Reporting using Ratio Analysis. The Asian Journal of Professional and Business Studies, 1(1), 53-67.
- Jasch, C. (2013). The use of environmental management accounting (ECD) for identifying environmental costs. Journal of Cleaner Production, 11(3), 2-15.
- Meyer, J. W., & Rowan, B. (1977). Institutionalized organisations: Formal structure as myth and ceremony. American Journal of Sociology, 83(2), 340-363.
- Norziaton, I. K. & Arfa, A. M. H. (2022). Financial statement fraud: Evidence from Malaysian public listed companies. Jurnal Intelek 17, (1), 34-44.
- Ogoun, S. & Owota, G. P. (2019). The effect of audit committee characteristics, as a sub-system of the corporate governance framework, on fraudulent financial reporting. The International Journal of Business & Management. 7(12), 105-113.
- Oh, H. I., & Penman, S. (2024). The Accruals–Cash Flow Relation and the Evaluation of Accrual Accounting. Abacus, 60(1), 23-48.
- Ohiomegwe, I., Augustine, A. & Obiagele, G. I. (2022). Corporate governance and fraudulent financial reporting in Nigerian quoted banks. International Journal of Innovative Research in Accounting and Sustainability, 7(1), 17-30.
- Okoye, E. I. & Gbegi, D. O. (2013). The impact of fraud and related financial crimes on growth and development of Nigerian economy. Kuwait Chapter of Arabian Journal of Business and Management Review, 2 (7), 23-27.
- Olatunji, O. C., & Juwon, A. M. (2020). Accrual Earnings Management, Real Earnings Economica, 39(3), 119-140.
- Omollo, E. A., Munga, D., Njoroge, P., & Waweru, K. (2018). Measurement of firm size as the natural log of total assets. Journal of Investment Strategies, 14(3), 45-62.
- Omoolorun, A. J., & Abilogun, T. O. (2017). Fraud free financial report: A conceptual review. International Journal of Academic Research in Accounting, Finance and Management Sciences, 7(4), 83-94.
- Osiorenoya, P. S. (2017). The impact of financial reporting on financial performance of quoted companies in Nigeria. A Dissertation Submitted in Partial Fulfillment of the Requirements for the Award of the Degree of Master of Science (M.Sc.) Management.
- Suhaily, H. & Rashidah, A. I. (2014). Determinants of fraudulent financial reporting: Evidence from Malaysia. Jurnal Pengurusan 4(2), 103 – 117.
- Temile, S. O. Enaruna, D. V., Dadang, P. J. & Biatna, D. T. (2021). The manipulation of accounting figures and the financial performance of listed firms in Nigeria. European Journal of Accounting, Finance and Investment. 7(10), 12-31.
- Tukur, G., & Abubakar, B. (2014). Corporate board diversity and financial performance of insurance companies in Nigeria: An application of panel data approach. Asian Economic and Financial Review, 4(2) 12-19.
- Uwuigbe, O. R., Olorunshe, U., Ozordi, E., Asiriuwa, O., Asaolu, T. & Erin, O. (2019). The association which exists amid financial statement fraud and governance among business organisations in Nigeria. Earth and Environmental Science 331 (9), 20 – 55.
- Weir, C., & Laing, D. (2001). Financial variables impact on common stock systematic risk. International Journal of Scientific Research and Innovative Technology, 4(10), 52-67
- Yene-Chimy A.S. & Forzeh F.M. (2021). Accrual Accounting Practice and Financial Performance in Local Governments of Cameroon. European Scientific Journal, 17(23), 269.
- Yulistyawti, A. K., Suardikha, S. M., & Sudana, P. I. (2019). The analysis of the factor that causes fraudulent financial reporting with fraud diamond. Jurnal Akuntansin Dan Auditing Indonesia, 23(1), 1-10.
- Zehri, F., & Chouaibi, J. (2013). Total accrual accounting: Measuring and recording financial resources. Journal of Finance and Management, 33(1), 45-58.
- Zeitun, R. & Tian, G. (2007). Capital structure and corporate performance: evidence from Jordan. Australian Accounting and Finance Journal, 1(4), 40-67.
APPENDIX
Data Presentation
FIRM | ID | YEAR | ROA | FSP | TAC | FSZ |
11 Plc | 1 | 2008 | 0.042 | 5.453 | 0,136,524 | 5.431 |
11 Plc | 1 | 2009 | 0.213 | 5.590 | 8,211,048 | 6.519 |
11 Plc | 1 | 2010 | 0.231 | 5.635 | 9,940,155 | 6.026 |
11 Plc | 1 | 2011 | 0.234 | 6.376 | 10,737,302 | 6.622 |
11 Plc | 1 | 2012 | 0.205 | 6.415 | 10,991,054 | 7.431 |
11 Plc | 1 | 2013 | 0.319 | 6.513 | 15,704,295 | 7.526 |
11 Plc | 1 | 2014 | 0.129 | 6.290 | 15,273,383 | 7.610 |
11 Plc | 1 | 2015 | 0.090 | 6.319 | 16,593,619 | 7.692 |
11 Plc | 1 | 2016 | 0.132 | 6.245 | 16,640,488 | 7.733 |
11 Plc | 1 | 2017 | 0.101 | 6.253 | 12,980,124 | 7.790 |
11 Plc | 1 | 2018 | 0.132 | 5.533 | 544,573 | 7.873 |
11 Plc | 1 | 2019 | 0.117 | 5.626 | 494,238 | 7.849 |
11 Plc | 1 | 2020 | 0.097 | 5.624 | 538,914 | 7.960 |
11 Plc | 1 | 2021 | 0.073 | 5.624 | 589,717 | 7.969 |
11 Plc | 1 | 2022 | 0.080 | 5.635 | 594,900 | 7.640 |
Academy Press Plc | 2 | 2008 | 0.518 | 5.631 | 514,604 | 4.028 |
Academy Press Plc | 2 | 2009 | 0.086 | 5.586 | 379,907 | 5.839 |
Academy Press Plc | 2 | 2010 | 0.067 | 5.461 | 514,152 | 6.032 |
Academy Press Plc | 2 | 2011 | 0.080 | 5.510 | 485,838 | 6.116 |
Academy Press Plc | 2 | 2012 | 0.026 | 5.492 | 509,567 | 6.374 |
Academy Press Plc | 2 | 2013 | -0.026 | 5.337 | 1,430,355 | 6.451 |
Academy Press Plc | 2 | 2014 | 0.030 | 5.600 | 516,659 | 6.550 |
Academy Press Plc | 2 | 2015 | 0.018 | 5.328 | 298,054 | 6.579 |
Academy Press Plc | 2 | 2016 | -0.016 | 5.141 | (96,865) | 6.572 |
Academy Press Plc | 2 | 2017 | 0.298 | 5.553 | (399,400) | 6.547 |
Academy Press Plc | 2 | 2018 | 0.450 | 5.420 | (821,915) | 6.474 |
Academy Press Plc | 2 | 2019 | 0.296 | 5.954 | (122,448) | 6.437 |
Academy Press Plc | 2 | 2020 | 0.195 | 4.988 | 144,814 | 6.425 |
Academy Press Plc | 2 | 2021 | 0.291 | 4.845 | 130,317 | 6.418 |
Academy Press Plc | 2 | 2022 | 0.090 | 4.900 | 133,493 | 6.721 |
Afromedia Plc | 3 | 2008 | 0.155 | 5.090 | 226,520 | 5.022 |
Afromedia Plc | 3 | 2009 | 0.253 | 5.117 | 215,953 | 5.682 |
Afromedia Plc | 3 | 2010 | 0.296 | 5.117 | 279,470 | 5.018 |
Afromedia Plc | 3 | 2011 | 0.200 | 5.196 | 307,693 | 5.036 |
Afromedia Plc | 3 | 2012 | 0.178 | 5.261 | 333,724 | 6.944 |
Afromedia Plc | 3 | 2013 | 0.175 | 5.370 | 342,607 | 6.639 |
Afromedia Plc | 3 | 2014 | 0.228 | 4.862 | 340,104 | 6.623 |
Afromedia Plc | 3 | 2015 | 0.362 | 4.872 | 336,297 | 6.557 |
Afromedia Plc | 3 | 2016 | 0.321 | 4.796 | 306,883 | 6.362 |
Afromedia Plc | 3 | 2017 | 0.296 | 5.394 | 267,546 | 6.333 |
Afromedia Plc | 3 | 2018 | 0.245 | 6.644 | 8,726,240 | 6.264 |
Afromedia Plc | 3 | 2019 | 0.059 | 6.144 | 10,145,132 | 6.333 |
Afromedia Plc | 3 | 2020 | 0.073 | 6.158 | 12,627,606 | 6.324 |
Afromedia Plc | 3 | 2021 | 0.057 | 6.250 | 18,464,929 | 6.320 |
Afromedia Plc | 3 | 2022 | 0.090 | 6.384 | 18,361,430 | 6.592 |
Aluminium Extrusion Indus | 4 | 2008 | 0.029 | 6.412 | 20,583,914 | 5.027 |
Aluminium Extrusion Indus | 4 | 2009 | 0.047 | 6.387 | 24,115,939 | 5.217 |
Aluminium Extrusion Indus | 4 | 2010 | -0.069 | 6.414 | 11,329,033 | 5.519 |
Aluminium Extrusion Indus | 4 | 2011 | 0.005 | 6.381 | 11,281,717 | 5.878 |
Aluminium Extrusion Indus | 4 | 2012 | -0.161 | 6.254 | 12,130,548 | 6.089 |
Aluminium Extrusion Indus | 4 | 2013 | 0.062 | 5.821 | 1,320,692 | 6.206 |
Aluminium Extrusion Indus | 4 | 2014 | -0.225 | 5.865 | 1,747,807 | 6.227 |
Aluminium Extrusion Indus | 4 | 2015 | 0.128 | 6.010 | 1,617,678 | 6.244 |
Aluminium Extrusion Indus | 4 | 2016 | 0.080 | 6.035 | 1,480,418 | 6.265 |
Aluminium Extrusion Indus | 4 | 2017 | 0.177 | 5.990 | 1,633,583 | 6.582 |
Aluminium Extrusion Indus | 4 | 2018 | 0.244 | 5.964 | 1,211,481 | 6.354 |
Aluminium Extrusion Indus | 4 | 2019 | 0.274 | 5.970 | 1,617,983 | 6.398 |
Aluminium Extrusion Indus | 4 | 2020 | 0.315 | 5.892 | 1,373,412 | 6.394 |
Aluminium Extrusion Indus | 4 | 2021 | 0.300 | 5.904 | 1,711,212 | 6.409 |
Aluminium Extrusion Indus | 4 | 2022 | 0.263 | 5.889 | 1,223,268 | 6.620 |
Ardova Plc (Forte Oil) | 5 | 2008 | 0.240 | 5.512 | 1,130,470 | 5.203 |
Ardova Plc (Forte Oil) | 5 | 2009 | 0.143 | 5.537 | 1,162,592 | 5.093 |
Ardova Plc (Forte Oil) | 5 | 2010 | -0.185 | 5.618 | 1,172,160 | 5.938 |
Ardova Plc (Forte Oil) | 5 | 2011 | 0.086 | 5.659 | 1,186,780 | 6.546 |
Ardova Plc (Forte Oil) | 5 | 2012 | -0.105 | 5.634 | 898,537 | 7.655 |
Ardova Plc (Forte Oil) | 5 | 2013 | 0.124 | 5.655 | 850,004 | 7.629 |
Ardova Plc (Forte Oil) | 5 | 2014 | 0.036 | 5.616 | 1,098,099 | 8.020 |
Ardova Plc (Forte Oil) | 5 | 2015 | 0.066 | 5.663 | 1,444,051 | 8.144 |
Ardova Plc (Forte Oil) | 5 | 2016 | 0.200 | 5.740 | 1,404,757 | 8.085 |
Ardova Plc (Forte Oil) | 5 | 2017 | 0.220 | 5.663 | 1,514,371 | 8.148 |
Ardova Plc (Forte Oil) | 5 | 2018 | 0.122 | 4.607 | 969,205 | 8.168 |
Ardova Plc (Forte Oil) | 5 | 2019 | 0.128 | 4.726 | 977,052 | 8.151 |
Ardova Plc (Forte Oil) | 5 | 2020 | 0.323 | 5.639 | 1,068,562 | 7.672 |
Ardova Plc (Forte Oil) | 5 | 2021 | 0.471 | 5.687 | 1,346,870 | 7.812 |
Ardova Plc (Forte Oil) | 5 | 2022 | 0.396 | 5.797 | 1,378,568 | 8.193 |
Associated Bus Company | 6 | 2008 | 0.638 | 5.753 | 1,111,631 | 5.092 |
Associated Bus Company | 6 | 2009 | 0.260 | 5.770 | 1,273,077 | 6.111 |
Associated Bus Company | 6 | 2010 | 0.180 | 5.668 | 1,480,361 | 6.409 |
Associated Bus Company | 6 | 2011 | 0.264 | 5.769 | 1,664,324 | 6.501 |
Associated Bus Company | 6 | 2012 | 0.201 | 5.856 | 1,419,078 | 6.705 |
Associated Bus Company | 6 | 2013 | 0.264 | 6.237 | 3,420,872 | 6.698 |
Associated Bus Company | 6 | 2014 | 0.233 | 6.285 | 3,120,701 | 6.751 |
Associated Bus Company | 6 | 2015 | 0.024 | 6.346 | 3,225,915 | 6.809 |
Associated Bus Company | 6 | 2016 | 0.251 | 6.351 | 4,448,652 | 6.777 |
Associated Bus Company | 6 | 2017 | 0.017 | 6.393 | 3,705,877 | 6.636 |
Associated Bus Company | 6 | 2018 | 0.008 | 6.440 | 3,945,815 | 6.650 |
Associated Bus Company | 6 | 2019 | -0.119 | 6.316 | 5,247,863 | 6.660 |
Associated Bus Company | 6 | 2020 | -0.118 | 6.498 | 6,380,639 | 6.711 |
Associated Bus Company | 6 | 2021 | -0.068 | 6.478 | 7,810,998 | 6.769 |
Associated Bus Company | 6 | 2022 | -0.059 | 6.500 | 5,903,982 | 6.872 |
B.O.C Gases Nig | 7 | 2008 | -0.034 | 6.717 | 11,159,197 | 4.027 |
B.O.C Gases Nig | 7 | 2009 | -0.041 | 6.689 | 11,097,299 | 5.918 |
B.O.C Gases Nig | 7 | 2010 | 0.956 | 6.727 | 13,100,096 | 5.317 |
B.O.C Gases Nig | 7 | 2011 | 0.333 | 6.711 | 7,930,457 | 6.052 |
B.O.C Gases Nig | 7 | 2012 | 0.663 | 6.739 | 8,930,227 | 6.350 |
B.O.C Gases Nig | 7 | 2013 | -0.621 | 6.756 | 6,860,403 | 6.423 |
B.O.C Gases Nig | 7 | 2014 | -0.609 | 6.702 | 7,435,134 | 6.460 |
B.O.C Gases Nig | 7 | 2015 | -3.913 | 6.726 | 7,956,066 | 6.534 |
B.O.C Gases Nig | 7 | 2016 | 0.246 | 6.735 | 8,325,598 | 6.507 |
B.O.C Gases Nig | 7 | 2017 | -0.769 | 6.765 | 5,899,045 | 6.560 |
B.O.C Gases Nig | 7 | 2018 | -0.202 | 6.253 | 1,393,772 | 6.628 |
B.O.C Gases Nig | 7 | 2019 | -0.142 | 6.175 | 1,387,195 | 6.652 |
B.O.C Gases Nig | 7 | 2020 | 0.356 | 5.996 | 1,209,653 | 6.702 |
B.O.C Gases Nig | 7 | 2021 | 0.264 | 5.751 | 1,318,286 | 6.734 |
B.O.C Gases Nig | 7 | 2022 | 0.150 | 5.774 | 1,337,933 | 7.045 |
Berger Paints Nig | 8 | 2008 | 0.230 | 5.687 | 1,591,229 | 6.023 |
Berger Paints Nig | 8 | 2009 | -0.459 | 6.290 | 1,503,168 | 6.251 |
Berger Paints Nig | 8 | 2010 | 0.123 | 6.251 | 1,107,704 | 6.304 |
Berger Paints Nig | 8 | 2011 | 0.137 | 6.011 | 1,056,119 | 6.393 |
Berger Paints Nig | 8 | 2012 | 0.304 | 5.693 | (357,937) | 6.427 |
Berger Paints Nig | 8 | 2013 | 0.686 | 5.542 | (378,007) | 6.463 |
Berger Paints Nig | 8 | 2014 | 0.842 | 5.632 | (466,382) | 6.549 |
Berger Paints Nig | 8 | 2015 | 0.465 | 5.579 | 25,935 | 6.561 |
Berger Paints Nig | 8 | 2016 | 0.788 | 5.828 | 639,932 | 6.591 |
Berger Paints Nig | 8 | 2017 | 0.425 | 5.900 | 999,698 | 6.613 |
Berger Paints Nig | 8 | 2018 | 0.709 | 5.940 | 1,067,053 | 6.635 |
Berger Paints Nig | 8 | 2019 | 0.988 | 6.010 | 1,386,621 | 6.657 |
Berger Paints Nig | 8 | 2020 | 0.566 | 6.000 | 1,191,092 | 6.705 |
Berger Paints Nig | 8 | 2021 | 0.031 | 5.942 | 64,282,380 | 6.697 |
Berger Paints Nig | 8 | 2022 | 0.858 | 6.020 | 1,940,324 | 6.781 |
Beta Glass Company | 9 | 2008 | 0.263 | 5.710 | 686,786 | 6.092 |
Beta Glass Company | 9 | 2009 | 0.784 | 5.572 | 2,301,735 | 6.637 |
Beta Glass Company | 9 | 2010 | 0.090 | 5.641 | 1,849,786 | 6.032 |
Beta Glass Company | 9 | 2011 | 0.905 | 5.519 | 1,550,360 | 7.281 |
Beta Glass Company | 9 | 2012 | 0.619 | 5.738 | 388,957 | 7.256 |
Beta Glass Company | 9 | 2013 | 0.159 | 5.513 | 693,457 | 7.351 |
Beta Glass Company | 9 | 2014 | 0.562 | 5.561 | 742,993 | 7.434 |
Beta Glass Company | 9 | 2015 | 0.535 | 5.586 | 785,534 | 7.430 |
Beta Glass Company | 9 | 2016 | 0.905 | 5.706 | 1,008,344 | 7.434 |
Beta Glass Company | 9 | 2017 | 0.332 | 5.669 | 759,515 | 7.521 |
Beta Glass Company | 9 | 2018 | 0.343 | 5.889 | 2,524,383 | 7.582 |
Beta Glass Company | 9 | 2019 | 0.824 | 5.970 | 3,016,977 | 7.664 |
Beta Glass Company | 9 | 2020 | 0.383 | 5.955 | 3,029,670 | 7.717 |
Beta Glass Company | 9 | 2021 | 0.290 | 6.007 | 2,638,601 | 7.732 |
Beta Glass Company | 9 | 2022 | 0.392 | 6.033 | 2,069,430 | 7.892 |
Cadbury Nig | 10 | 2008 | 0.754 | 6.030 | 3,851,343 | 6.027 |
Cadbury Nig | 10 | 2009 | 0.808 | 5.914 | 3,425,629 | 6.843 |
Cadbury Nig | 10 | 2010 | 0.956 | 5.860 | 1,815,066 | 6.682 |
Cadbury Nig | 10 | 2011 | 0.333 | 5.897 | 527,284 | 6.834 |
Cadbury Nig | 10 | 2012 | 0.666 | 5.898 | 641,863 | 7.527 |
Cadbury Nig | 10 | 2013 | 0.621 | 5.603 | 1,541,240 | 7.604 |
Cadbury Nig | 10 | 2014 | 0.093 | 5.574 | 2,599,498 | 7.635 |
Cadbury Nig | 10 | 2015 | -0.913 | 5.653 | 3,155,104 | 7.460 |
Cadbury Nig | 10 | 2016 | 0.246 | 5.772 | 3,597,686 | 7.454 |
Cadbury Nig | 10 | 2017 | -0.791 | 5.781 | 3,587,965 | 7.453 |
Cadbury Nig | 10 | 2018 | 0.202 | 5.764 | 3,312,483 | 7.454 |
Cadbury Nig | 10 | 2019 | 0.123 | 5.741 | 3,249,965 | 7.440 |
Cadbury Nig | 10 | 2020 | 0.566 | 5.734 | 3,729,973 | 7.459 |
Cadbury Nig | 10 | 2021 | 0.031 | 5.862 | 3,972,962 | 7.521 |
Cadbury Nig | 10 | 2022 | 0.858 | 6.009 | 3,742,192 | 7.610 |
Champion Breweries | 11 | 2008 | 0.263 | 5.881 | 1,941,233 | 6.574 |
Champion Breweries | 11 | 2009 | 0.784 | 5.886 | 2,636,675 | 6.792 |
Champion Breweries | 11 | 2010 | 0.090 | 5.877 | 9,772,810 | 6.039 |
Champion Breweries | 11 | 2011 | 0.905 | 5.854 | 5,918,891 | 6.033 |
Champion Breweries | 11 | 2012 | 0.619 | 5.882 | 5,983,199 | 6.843 |
Champion Breweries | 11 | 2013 | 0.159 | 5.897 | 6,360,638 | 6.832 |
Champion Breweries | 11 | 2014 | 0.562 | 6.089 | 16,509,895 | 6.961 |
Champion Breweries | 11 | 2015 | 0.535 | 6.158 | 10,712,240 | 6.982 |
Champion Breweries | 11 | 2016 | 0.905 | 6.226 | 11,714,967 | 7.014 |
Champion Breweries | 11 | 2017 | 0.332 | 6.139 | 12,962,902 | 6.998 |
Champion Breweries | 11 | 2018 | 0.343 | 6.319 | 15,017,327 | 7.004 |
Champion Breweries | 11 | 2019 | 0.824 | 6.346 | 16,163,716 | 7.021 |
Champion Breweries | 11 | 2020 | 0.639 | 6.335 | 17,038,518 | 7.041 |
Champion Breweries | 11 | 2021 | 0.222 | 6.342 | 13,789,472 | 7.056 |
Champion Breweries | 11 | 2022 | 0.267 | 6.339 | 11,537,758 | 7.893 |
Chellarams | 12 | 2008 | 0.259 | 6.359 | 14,140,549 | 6.043 |
Chellarams | 12 | 2009 | 0.326 | 6.305 | 13,049,372 | 6.632 |
Chellarams | 12 | 2010 | 0.109 | 6.256 | 12,770,903 | 6.503 |
Chellarams | 12 | 2011 | 0.233 | 6.320 | 13,439,254 | 7.010 |
Chellarams | 12 | 2012 | 0.024 | 6.346 | 9,818,385 | 7.037 |
Chellarams | 12 | 2013 | 0.251 | 4.672 | 364,055 | 7.169 |
Chellarams | 12 | 2014 | 0.017 | 4.766 | 473,693 | 7.188 |
Chellarams | 12 | 2015 | 0.008 | 4.809 | 602,695 | 7.225 |
Chellarams | 12 | 2016 | 0.436 | 4.940 | 824,623 | 7.265 |
Chellarams | 12 | 2017 | 0.235 | 5.009 | 85,187 | 7.141 |
Chellarams | 12 | 2018 | 0.120 | 5.087 | 691,940 | 7.126 |
Chellarams | 12 | 2019 | 0.543 | 4.996 | 450,153 | 7.120 |
Chellarams | 12 | 2020 | 0.234 | 5.333 | 483,092 | 7.102 |
Chellarams | 12 | 2021 | 0.119 | 5.595 | 1,417,701 | 6.980 |
Chellarams | 12 | 2022 | 0.118 | 5.506 | (5,240,846) | 6.356 |
Chemical & Allied Product | 13 | 2008 | 0.068 | 5.103 | 452,708 | 5.382 |
Chemical & Allied Product | 13 | 2009 | 0.059 | 4.973 | 390,527 | 6.002 |
Chemical & Allied Product | 13 | 2010 | 0.034 | 5.081 | 53,656 | 6.049 |
Chemical & Allied Product | 13 | 2011 | 0.041 | 5.129 | 651,535 | 6.392 |
Chemical & Allied Product | 13 | 2012 | 0.956 | 5.191 | 639,008 | 6.487 |
Chemical & Allied Product | 13 | 2013 | 0.333 | 5.255 | 33,352 | 6.459 |
Chemical & Allied Product | 13 | 2014 | 0.663 | 5.359 | 1,005,646 | 6.482 |
Chemical & Allied Product | 13 | 2015 | -0.621 | 5.460 | 1,520,689 | 6.489 |
Chemical & Allied Product | 13 | 2016 | -0.609 | 5.599 | 1,644,787 | 6.533 |
Chemical & Allied Product | 13 | 2017 | -0.913 | 5.571 | 1,441,969 | 6.692 |
Chemical & Allied Product | 13 | 2018 | 0.246 | 6.874 | 143,698,035 | 6.700 |
Chemical & Allied Product | 13 | 2019 | -0.769 | 7.046 | 180,149,728 | 6.800 |
Chemical & Allied Product | 13 | 2020 | 0.183 | 7.184 | 243,660,152 | 6.830 |
Chemical & Allied Product | 13 | 2021 | 0.115 | 7.306 | 248,581,163 | 6.931 |
Chemical & Allied Product | 13 | 2022 | 0.053 | 7.486 | 289,917,000 | 7.321 |
Conoil | 14 | 2008 | 0.013 | 7.660 | 291,287,000 | 6.043 |
Conoil | 14 | 2009 | 0.031 | 7.699 | 454,292,000 | 6.873 |
Conoil | 14 | 2010 | 0.074 | 7.758 | 517,902,000 | 7.245 |
Conoil | 14 | 2011 | 0.249 | 7.798 | 511,682,000 | 7.691 |
Conoil | 14 | 2012 | 0.267 | 7.859 | #VALUE! | 7.791 |
Conoil | 14 | 2013 | 0.290 | 6.344 | 13,597,719 | 7.920 |
Conoil | 14 | 2014 | 0.322 | 6.387 | 23,228,510 | 7.916 |
Conoil | 14 | 2015 | 0.430 | 6.554 | 24,598,474 | 7.937 |
Conoil | 14 | 2016 | 0.402 | 6.760 | 18,628,010 | 7.841 |
Conoil | 14 | 2017 | 0.445 | 6.663 | 20,728,480 | 7.844 |
Conoil | 14 | 2018 | 0.364 | 6.719 | 22,988,581 | 7.798 |
Conoil | 14 | 2019 | 0.258 | 6.793 | 50,988,094 | 7.785 |
Conoil | 14 | 2020 | 0.494 | 6.840 | 39,685,360 | 7.803 |
Conoil | 14 | 2021 | 0.293 | 6.428 | 38,285,230 | 7.689 |
Conoil | 14 | 2022 | 0.886 | 6.503 | 53,746,448 | 8.932 |
Dangote Cement | 15 | 2008 | 0.654 | 5.613 | 2,440,166 | 7.039 |
Dangote Cement | 15 | 2009 | 0.373 | 5.611 | 3,045,273 | 8.374 |
Dangote Cement | 15 | 2010 | 0.558 | 5.672 | 2,884,448 | 8.032 |
Dangote Cement | 15 | 2011 | 0.511 | 5.740 | 1,291,455 | 8.472 |
Dangote Cement | 15 | 2012 | 0.055 | 5.781 | 3,080,000 | 8.721 |
Dangote Cement | 15 | 2013 | -0.300 | 5.866 | 8,568,372 | 8.828 |
Dangote Cement | 15 | 2014 | 0.175 | 5.743 | 6,337,277 | 8.926 |
Dangote Cement | 15 | 2015 | 0.209 | 5.902 | 4,642,446 | 8.993 |
Dangote Cement | 15 | 2016 | 0.203 | 5.947 | 4,950,207 | 9.046 |
Dangote Cement | 15 | 2017 | 0.158 | 6.004 | 5,507,893 | 9.184 |
Dangote Cement | 15 | 2018 | 0.052 | 5.496 | 756,243 | 9.222 |
Dangote Cement | 15 | 2019 | 0.143 | 5.655 | 938,832 | 9.229 |
Dangote Cement | 15 | 2020 | 0.093 | 5.685 | 1,044,316 | 9.241 |
Dangote Cement | 15 | 2021 | 0.365 | 5.712 | 1,543,468 | 9.306 |
Dangote Cement | 15 | 2022 | -0.098 | 5.779 | 2,472,339 | 9.578 |
Flour Mills of Nigeria | 16 | 2008 | -0.240 | 5.926 | 2,903,919 | 6.058 |
Flour Mills of Nigeria | 16 | 2009 | 0.969 | 5.940 | 1,716,948 | 7.053 |
Flour Mills of Nigeria | 16 | 2010 | 0.051 | 6.009 | 1,624,634 | 7.043 |
Flour Mills of Nigeria | 16 | 2011 | 0.682 | 6.027 | 2,025,603 | 8.032 |
Flour Mills of Nigeria | 16 | 2012 | 0.357 | 5.976 | 1,146,203 | 8.213 |
Flour Mills of Nigeria | 16 | 2013 | 0.691 | 4.300 | 89,257 | 8.367 |
Flour Mills of Nigeria | 16 | 2014 | 0.340 | 4.267 | 71,078 | 8.448 |
Flour Mills of Nigeria | 16 | 2015 | 0.456 | 4.309 | 81,121 | 8.473 |
Flour Mills of Nigeria | 16 | 2016 | 0.409 | 4.301 | 60,547 | 8.535 |
Flour Mills of Nigeria | 16 | 2017 | 0.343 | 4.291 | 65,252 | 8.538 |
Flour Mills of Nigeria | 16 | 2018 | 0.307 | 4.353 | 48,281 | 8.684 |
Flour Mills of Nigeria | 16 | 2019 | 0.577 | 4.290 | 36,477 | 8.611 |
Flour Mills of Nigeria | 16 | 2020 | 0.327 | 4.241 | 42,425 | 8.620 |
Flour Mills of Nigeria | 16 | 2021 | 0.272 | 4.215 | 25,008 | 8.636 |
Flour Mills of Nigeria | 16 | 2022 | 0.747 | 4.351 | 98,807 | 8.026 |
Glaxosmithkline Nig | 17 | 2008 | 0.825 | 5.954 | 4,053,438 | 7.048 |
Glaxosmithkline Nig | 17 | 2009 | 0.195 | 5.874 | 4,073,993 | 5.392 |
Glaxosmithkline Nig | 17 | 2010 | 0.139 | 5.834 | 5,113,933 | 7.083 |
Glaxosmithkline Nig | 17 | 2011 | 0.603 | 5.812 | 5,439,589 | 7.049 |
Glaxosmithkline Nig | 17 | 2012 | 0.269 | 5.786 | 4,351,864 | 7.254 |
Glaxosmithkline Nig | 17 | 2013 | 0.173 | 5.734 | 4,055,363 | 7.338 |
Glaxosmithkline Nig | 17 | 2014 | 0.300 | 5.781 | 7,155,167 | 7.419 |
Glaxosmithkline Nig | 17 | 2015 | 0.145 | 5.872 | 6,319,684 | 7.447 |
Glaxosmithkline Nig | 17 | 2016 | 0.080 | 6.012 | 5,875,557 | 7.496 |
Glaxosmithkline Nig | 17 | 2017 | 0.063 | 6.185 | 8,581,340 | 7.450 |
Glaxosmithkline Nig | 17 | 2018 | 0.064 | 6.943 | 40,185,298 | 7.423 |
Glaxosmithkline Nig | 17 | 2019 | 0.335 | 7.003 | 39,565,812 | 7.196 |
Glaxosmithkline Nig | 17 | 2020 | 0.143 | 7.183 | 38,010,122 | 7.272 |
Glaxosmithkline Nig | 17 | 2021 | 0.168 | 7.147 | 43,656,993 | 7.375 |
Glaxosmithkline Nig | 17 | 2022 | -0.183 | 7.116 | 35,366,960 | 7.693 |
Guinness Nig | 18 | 2008 | -0.279 | 7.251 | 37,624,722 | 6.048 |
Guinness Nig | 18 | 2009 | 0.024 | 7.265 | 66,689,068 | 6.038 |
Guinness Nig | 18 | 2010 | -0.179 | 7.316 | 68,775,057 | 7.832 |
Guinness Nig | 18 | 2011 | 0.321 | 7.404 | 53,347,557 | 7.736 |
Guinness Nig | 18 | 2012 | -0.080 | #NUM! | 65,787,177 | 7.965 |
Guinness Nig | 18 | 2013 | -0.489 | 4.984 | 4,479 | 8.025 |
Guinness Nig | 18 | 2014 | -0.001 | 4.902 | (253,402) | 8.083 |
Guinness Nig | 18 | 2015 | 0.842 | 4.899 | (95,183) | 8.122 |
Guinness Nig | 18 | 2016 | 0.188 | 4.393 | (261,409) | 8.087 |
Guinness Nig | 18 | 2017 | 0.087 | 4.549 | (59,333) | 8.137 |
Guinness Nig | 18 | 2018 | 0.257 | 4.624 | (58,208) | 8.164 |
Guinness Nig | 18 | 2019 | 0.133 | 4.548 | (250,962) | 8.185 |
Guinness Nig | 18 | 2020 | 0.157 | 4.987 | (213,666) | 8.206 |
Guinness Nig | 18 | 2021 | 0.202 | 5.067 | (546,151) | 8.159 |
Guinness Nig | 18 | 2022 | -0.110 | 4.683 | (297,172) | 8.937 |
Lafarge Cement Wapco Nig | 19 | 2008 | 0.028 | 6.192 | 8,987,868 | 7.261 |
Lafarge Cement Wapco Nig | 19 | 2009 | 0.842 | 6.316 | 10,227,698 | 7.392 |
Lafarge Cement Wapco Nig | 19 | 2010 | -0.783 | 6.359 | 11,602,050 | 7.942 |
Lafarge Cement Wapco Nig | 19 | 2011 | 0.688 | 6.460 | 10,735,015 | 8.016 |
Lafarge Cement Wapco Nig | 19 | 2012 | -0.436 | 6.188 | 10,326,243 | 8.183 |
Lafarge Cement Wapco Nig | 19 | 2013 | -0.404 | 6.239 | 8,966,411 | 8.182 |
Lafarge Cement Wapco Nig | 19 | 2014 | 0.484 | 6.225 | 4,479,568 | 8.207 |
Lafarge Cement Wapco Nig | 19 | 2015 | -0.304 | 6.218 | 6,756,778 | 8.486 |
Lafarge Cement Wapco Nig | 19 | 2016 | 0.239 | 6.048 | 6,052,300 | 8.656 |
Lafarge Cement Wapco Nig | 19 | 2017 | -0.064 | 6.202 | 5,914,756 | 8.701 |
Lafarge Cement Wapco Nig | 19 | 2018 | 0.086 | 4.795 | 160,451 | 8.762 |
Lafarge Cement Wapco Nig | 19 | 2019 | 0.250 | 4.676 | 129,553 | 8.733 |
Lafarge Cement Wapco Nig | 19 | 2020 | 0.321 | 4.724 | 142,389 | 8.696 |
Lafarge Cement Wapco Nig | 19 | 2021 | 0.415 | 4.722 | 137,901 | 8.705 |
Lafarge Cement Wapco Nig | 19 | 2022 | 0.104 | 4.765 | 149,343 | 8.944 |
Total Nigeria | 20 | 2008 | 0.286 | 4.810 | 166,152 | 6.840 |
Total Nigeria | 20 | 2009 | 0.162 | 4.855 | 255,336 | 6.048 |
Total Nigeria | 20 | 2010 | 0.021 | 4.857 | (114,676) | 7.632 |
Total Nigeria | 20 | 2011 | 0.007 | 4.809 | (178,842) | 7.696 |
Total Nigeria | 20 | 2012 | 0.017 | 3.684 | 1 | 7.769 |
Total Nigeria | 20 | 2013 | 0.009 | 6.852 | 55,043,605 | 7.881 |
Total Nigeria | 20 | 2014 | -0.047 | 6.916 | 55,183,201 | 7.900 |
Total Nigeria | 20 | 2015 | 0.216 | 6.965 | 6,078,434 | 7.980 |
Total Nigeria | 20 | 2016 | -0.057 | 6.979 | 51,333,214 | 7.922 |
Total Nigeria | 20 | 2017 | 0.104 | 7.105 | 55,891,520 | 8.136 |
Total Nigeria | 20 | 2018 | 0.120 | 7.091 | 41,810,413 | 8.033 |
Total Nigeria | 20 | 2019 | 0.097 | 7.062 | 48,315,304 | 8.122 |
Total Nigeria | 20 | 2020 | 0.021 | 6.982 | 48,625,405 | 8.126 |
Total Nigeria | 20 | 2021 | 0.063 | 6.943 | 40,129,228 | 8.157 |
Total Nigeria | 20 | 2022 | 0.426 | 7.018 | 33,330,061 | 8.823 |
Source: Author’s Compilation from Annual Report (2008-2022).