Keywords

Return on asset, Statutory auditors going concern judgement, Nigerian Exchange, Information asymmetry, Audit firm size.

Introduction

Every business needs profit for continuous survival. Profit, otherwise known as returns, is considered fundamental to the continuous operation of businesses, hence, a continuous growth in company’s profitability performance is considered pivotal in attracting potential investors and other business stakeholders. To achieve continuous operations of businesses, management invests effort in developing strategies towards increasing business income and or minimising its expenditure (Maverick, 2022).

A significant number of businesses, of different sizes, established in Nigeria were principally established with the aim of maximising profit in order to increase the returns of investors and increase the confidence of stakeholders about the going concern (Nwonyuku, 2016). Nonetheless, profit maximisation is not limited to profit-oriented businesses but further extends to non-profit making organizations, like the non-governmental organizations, professional bodies, and ecclesiastical organizations as this allows them to meet their operating and administrative expenses (Bibu et al., 2013).

Profits, compared to any other line items on the financial statements, are considered ambiguous as they differ from one another, and affect stakeholders differently (Irom et al., 2018). Profit can take a form of gross profit (excess of revenue over cost of sales); operation profit before exceptional items (where exceptional items exists in the financial statement); operating profit before interest and tax; profit before tax; and profit after tax. Differences in the measure of business profits results in a considerable number of profitability performance measures (ratios) depending on the nature of the business. Some of these include operating profit margin, net profit margin, gross profit margin, return on equity, return on asset, amongst others.

As put forward by (Kohlscheen, 2018) the profitability performance of companies in the banking sector is often measured using returns on asset, as it estimates the amount of returns generated from the use of assets. The return on asset (ROA) of banks has been adversely impacted due to the increasing rate of default in bank loans in the hands of borrowers coupled with rising fraud cases, which consequently reduces their earnings in form of interest income and further reduces the return on asset performance (Nwosu, et al., 2020). The rising risk of default, according to (Makri et al., 2014) has been attributed to the presence of information asymmetry between banks and their respective borrowers. This is evident in situations where banks find difficulties in obtaining appropriate and sufficient information with respect to the credit worthiness of its customers prior to the granting of credit facilities.

Moreover, the profitability performance of the non-financial service companies (healthcare, consumer goods, industrial goods) have been adversely affected as a result of the impact of inflationary pressure on the prices of imported material inputs and equipment (Ogungbade et al., 2020). While these companies struggle to increase their returns on asset, there has been a minimal support, in recent times, to these industries from government as a considerable number of them are discouraged from investing in plants, machinery, and equipment. This is evident in increase in tax rates which increases their tax liability as well as the deletion of investment allowances which further reduces their profitability performance (Finance Act, 2023).

Ambiguities in the measure of profitability performance make businesses susceptible to earnings management by management as their performance bonuses are often tied to growth in profitability performance. In order to increase the confidence of shareholders and other business stakeholder about the profitability performance as well as the verification of businesses’ ability to continue as a going concern, independent statutory auditors are therefore engaged in this respect (Anasta, 2019). This study therefore examined the effect of statutory auditors going concern judgement on the profitability performance of companies listed on the NGX.

Research Objective

Principally, this research examined the effect of statutory auditors' going concern judgement on profitability performance of companies listed on the Nigerian Exchange. Further, the specific objective:

• Examined the effect of statutory auditors' going concern judgement on return on assets of companies listed on the Nigerian Exchange; and

• Investigated how audit firm size and information asymmetry moderate the effect of statutory auditors' going concern judgement on return on asset of companies listed on the Nigerian Exchange.

Research Hypotheses

H01:Statutory auditors' going concern judgement does not have significant effect on return on assets of companies listed on the NGX

H02:Audit Firm Size and information asymmetry do not significantly moderate the effect of statutory auditors’ going concern judgment on return on asset of companies listed on the NGX.

Other sections of this research are presented in different sections. Section two focused on the review of literature, section three discussed the methodology of the research, section four captured the results and discussion of findings, while the summary and the conclusion was explained in section five.

Review of Literature

Conceptual Review

Statutory Auditors’ Going Concern Judgement

Going concern is one of the bases employed by management in the preparation and presentation of the financial statements of a reporting entity. Therefore, the presentation of financial statements requires that this basis should be applied, if and only if management is reasonably certain that the entity will continue to exist into the foreseeable future. On the contrary, where management have the intention of liquidating or significantly reducing its business scale, the going concern basis is therefore considered not applicable, therefore, IAS 1 requires that management prepares its financial statement using an alternative basis, which is sometimes referred to as the break-up value basis, or liquidation basis (IFRS Foundation, 2021; Triani, et al., 2017).

Enyi (2018) expounded the concept of going concern, as used in several financial accounting perspectives, as the ability of businesses to continue their operations beyond the current and the next reporting period. It further explicates the ability of a reporting entity to use its available assets to meet its contractual obligations and execute its planned operations either through liquidation or unfavourable conditions beyond the foreseeable future.

In accounting system, the budget reports are prepared under the going concern, with the understanding that the element is a going concern and will continue with its tasks for years to come. Except when the executives intend to exchange the substance or stop activities, or have no other practical option, universally useful fiscal summaries are organized using the going concern premise of bookkeeping. Unique reason fiscal summaries may be prepared in accordance with a financial detailing system for which the going concern premise of accounting is critical. When the going concern of accounting is appropriate, resources and liabilities are recorded on the premise that the substance will actually want to comprehend its resources and release its liabilities in the normal course of the business (ISA 570 [Revised] ‘Going Concern’).

To Measure statutory auditors’ going concern, Credit payment, (CRPM), Operating cashflow (OPCF), Customer retentions (CSRT) and regulatory and capital requirement s (RSCR) are used as proxies. CRPM relates to the settlement or non settlement of a loan or debt obligation. In the context of this this study, it focuses on the instances (if any) when the listed companies on NGX pay on due date or or otherwise fail. OPCF is an index of how an organisation generates cash to cover its operations. CSRT is the extent and frequency to which an organisations customer base reduces, and it could be an indication of the quality of the Organisation’s products, services, and key operations. Finally, RSCR looks at how an organisation is compliant to the regulatory provisions and capital structure requirement of the industry in which they operate.

Profitability Performance

The determination of companies’ profitability depends on their capacity to use their resources efficiently and effectively to generate income (Taouab & Issor, 2019). Profitability performance is also an indicator put into cosideration by investors to appraise possible returns a company is able to generate. Positive rate of return attracts more investors which translates to more capital inflow. On the other hand, poor profitability performance implies on the overall, poor performance of a company which requires more capital to mitigate the risk involved (Ben, 2014). For this study, profitability performance of listed companies is assessed based on statutory auditors going concern judgement. To measure profitability performance, in line with (Irom et al., 2018), Returns on Assets (ROA) is adopted for the measurement. ROA gauges how well a corporation can turn a profit by making use of its resources. As it offers information on how well a company is employing its assets to generate revenues, ROA is a crucial metric for investors, creditors, and other stakeholders (Hargrave, 2022).

An increasing ROA over time suggests increased profitability, whereas a dropping ROA may be an indication of subpar investments, excessive spending, or ineffective operations. This implies that when a company's ROA rises over time, it means that it is extracting more profits from each dollar of assets it owns. A declining ROA, on the other hand, indicates that a company has made poor investments, is overspending, and may be in trouble. Higher profitability and a greater ROA can result from increased operational efficiency, such as streamlining procedures, improved cost management, and productivity enhancements (Chen et al., 2023). On the other hand, operational inefficiencies might cause a lower ROA. A greater ROA reflects efficiency and excellent resource management since it shows that a corporation is getting more profit out of every dollar of assets it owns (Hagel & Brown, 2013). When assessing the performance and financial health of a single organization, the indicator has to be significant (Kotane & Kuzmina-Merlino, 2012).

Return on Assets (ROA) is used to measure the effectiveness of the company in generating profits by exploiting its assets; it is also a tool to measure the rate of return on total assets after interest expenses and taxes (Heikal et al., 2014). Using ROA as a diagnostic tool, auditors can determine where a company is underperforming and evaluate the viability of its business plan and underlying assumptions (Hargrave, 2022). The chance of a corporation failing may increase by a falling or persistently low ROA, which may be a sign of potential financial trouble, inefficiencies, or bad investment choices (McClure, 2021). Auditor monitoring and analysis of ROA enables early risk identification and mitigation, which helps to effectively increase business profit (Kaplan & Mikes, 2012).

Auditors can spot potential risks and vulnerabilities that could cause a company to collapse by evaluating its ROA (Hargrave, 2022). The chance of a business survival is constrained by inefficiencies, poor financial management, or a lack of competitiveness, all of which can be indicated by a sliding or persistently low ROA (McClure, 2021). In addition to other financial ratios and indications, auditors can use ROA to analyse a company's financial health, determine whether its business strategy is realistic, and pinpoint areas in need of improvement (Maverick, 2022).

Theoretical Framework: Inspired Confidence Theory

The theory of inspired confidence was propounded by Professor Theodore Limperg in 1920s. While management may be bias in the process of providing financial information to users through financial statements, auditors are saddled with the responsibility of providing independent opinion on the financial information through statutory audit exercise, for the purpose of augmenting investors’ confidence about the financial performance and position, as well as cash flows of the reporting entity. (Limperg, 1932) further emphasized that auditors should make possible efforts to meet the expectations of the users of financial statements without disappointing them.

The theory assumed that if society lost trust in audit opinion, the moral usefulness of audit would cease, because audit provides benefits to financial statement users. In order to fulfil his obligation to examine business practices and provide a credible opinion on the financial statements, the auditor should maintain appropriate business practices to maintain his independence from the firm being audited.

This theory expects that auditors should not inspire the confidence of the public in the audit report, more than his findings and examination. It assumes that audit technologies would assist auditors in doing everything possible to meet expectation of the users, however, a comment made by Gijs Bak, the chairman of the International Auditing Practices Committee (IAPC) of the International Federation of Accountants (IFAC) identified that such confidence could be impaired (through limited assurance) whenever there is a limitation in the scope of audit engagement being performed, which is often traced to insufficient and inappropriate audit evidence(s) (Limperg, 1985). Integrating the theory into this study therefore guide auditors on the need to obtain all appropriate and sufficient information, as audit evidence, to enhance shareholder’s confidence on the financial statements provided by management.

The theory was criticised by (Carmichael, 2004) who argued that theory of inspired confidence does not prescribe definite rules about the behaviour of the auditor in each case, but that it is a principle-based approach. The researchers said that the Public Company Accounting Oversight Board (PCAOB) and the social responsibility of auditors 2004 focused on the role of the PCAOB and its performance.

The theory supported the supply and demand for audit services (Ittonen, 2010). The accountability relationship is realized through the preparation of financial statements; therefore, where stakeholders are unable to monitor any material misstatement or bias in financial statements, necessitates the demand for independent and reliable audit, towards augmenting public confidence. As the general function of audit is derived from the need for independent examination and an expert opinion based on findings; due to the trust society places in an independent auditors' opinion; the supply of audit services should satisfy the public confidence that arises from the audit and fulfil community expectations. As a result, the auditor must conduct the audit in such a way that any external stakeholder's expectations are not jeopardized. As a result, as audit procedures advance, auditors should strive to meet the public's reasonable expectations (Hayes et al., 1999).

Other researchers who supported the theory of inspired confidence include (Flint, 1988) and (Limperg Institute, 1985). The findings of (Limperg institute, 1985) explained that the theory of inspired confidence connects the community needs for reliability of financial information to the ability of audit techniques to meet these needs and it stressed the development of the need of the community and the techniques of auditing in the course of time. The researchers submitted that the changes in the need of the community and the changes in the auditing techniques result in the auditor’s function.

The inspired confidence theory is considered relevant because it provides periodic financial statements and keeps in mind management's information, which may be biased and misleading due to the use of inaccurate transactions, necessitating the development of a mechanism to ensure the reliability of the information. As a result, an auditor is called upon to perform the necessary audit procedures and render an independent opinion on the reports. The theory also provided a link between the ability of the practitioners to meet the needs of users and extending tenure.

Empirical Review

Given that return on assets serves as one of the financial metrics for measuring the profitability performance of businesses. Some of the studies that has considered examining statutory auditors’ going concern without ROA as a measure of profitability performance include (Averio, 2020); (Pratama & Meutia, 2018); (Rahma & Sukirman, 2018); (Triani et al., 2017); and (Widoretno, 2019) among others. However, only a few numbers of studies in the literature have examined the nexus between statutory auditor’s going concern judgement and return on asset.

Sukirman, Sari, Rachmadani, and Wijaya, (2022) examined the role of auditor switching on going concern audit opinion acceptance, by sampling 28 listed manufacturing companies on the Indonesia Stock Exchange (IDX) between 2012-2016. The study found that the acceptance of audit opinions does not influence return on asset, being a proxy for profitability. They added that auditors will not only consider the entity’s profitability performance, but also considers the operational, legal, and financial factors. In the same Indonesia, (Saragih, et al., 2017) employed purposive sampling technique, to examine the effect of profitability, liquidity and quality of auditors’ audit opinion going concern in eight (8) food and drink listed companies, in Indonesia Stock Exchange (IDX) (within the consumer goods sector) between 2012 and 2015. The study proxy profitability ratio, using returns on asset, and found that returns on asset insignificantly affects going concern opinion.

An empirical analysis on the effect of profitability and liquidity on audit opinions between 2009 and 2015 by (Ryu, et al., 2019) found that returns on asset impacts on auditors’ going concern opinion. This finding expounds that statutory auditor tends to issues more going concern opinion, when their companies make less returns (profits). The result from the logistic regression is considered to be fairly consistent with the univariate test, which indicates that companies that significantly improve on its profitability performance (proxy by ROA) are susceptible to receiving an unqualified audit opinion subsequent to receiving a going concern opinion in prior year. (Widoretno, 2019) explained the factors which influence the acceptance of auditor’s going concern opinion, using logistic regression analysis. The findings revealed that profitability negatively affect the issuance of going concern audit opinion. Also, company’s size and audit lag insignificantly affect the issuance of going concern audit opinion.

While analysing going concern prediction using data mining techniques, (Koh & Low, 2004) suggested several going concern prediction models, between 1980 and 1987, which are based on certain statistical models (logistic, decision tree, and neural network models) by observing 165 firms with going concern and 165 firms without going concern status. The study therefore analysed the effect of six financial ratios (net income/total assets [otherwise known as ROA], total liabilities-total assets, quick asset/current liabilities, market value of equity/total assets, interest payment to profit before interest and tax, and retained earnings/total assets) on statutory auditors going concern, using the aforementioned statistical going concern prediction model. Hence, findings from the study, using logistic regression analysis, expounds that ROA highly (significantly) and directly (positively) predicts an entity’s ability to continue as a going concern. The decision tree model equally identified ROA as one of the most important variables that impacts entity’s going concern. However, using the neural network model, the study found that ROA does not significantly impacts on the going concern opinion.

Despite the fact that ROA has been used severally, as a measure of profitability in the literature, when compared with other profitability ratios, only few of these studies examined the effect of ROA on statutory auditors’ going concern opinion. More so, many of these studies that considered the effect of return on asset on auditors’ going concern opinion employed ROA as independent variable, while going concern opinion as dependent variable (Averio, 2020); (Koh & Low, 2004); (Pratama & Meutia, 2018); (Rahma & Sukirman, 2018); (Ryu, et al., 2019); (Triani et al., 2017); and (Saragih, et al., 2017); (Sukirman, Sari, Rachmadani, & Wijaya, 2022); and (Widoretno, 2019). Also, most of these researchers employed purposive sampling technique, decision tree, neural network model, and logistic regression model; however, many of these studies are yet to employ panel regression analysis in analysing the effect of statutory auditors going concern judgment (using the indicators of going concerns as defirned by ISA 570 (Revised)) on return on assets of companies listed on the Nigerian Exchange.

Methodology

Ex-post facto research design, as widely been used in the literature (Data et al., 2017); (Hafidz et al., 2020); (Hasyim & Nuraeni, 2022), this study therefore employed the ex-post facto research design also known as causal-comparative research to examine the effect of statutory auditors going concern judgement on the profitability performance of companies listed on the Nigerian Exchange Group between 2006 and 2021, thus covering a period of 16 years.

The study observed the 87 of 155 companies listed on the NGX within the Consumer goods industry; financial services sector; healthcare sector; and Industrial Goods sector. The 87 companies were selected on the basis that they exhibited zombie status as at the financial reporting period ending December 31, 2021.

For the purpose of testing the formulated hypotheses, this study employed the multiple regression estimation techniques. Correlation analysis was conducted to ensure that there is no unhealthy relationship amongst the independent variables while multiple regression analysis was carried to investigate the predictive nature of the models. In order to ascertain the appropriateness of the chosen estimation technique between the fixed effect, random effect and pooled-panel ordinary least square regression, the study conducted Hausman test. Further, the Testparm as well as Breusch-pagan Langrangian Multiplier (LM) test were carried to validate the appropriateness of the results produced from the Hausman test.

The study carried out diagnostic (post-estimation) tests to validate the fitness of the research models. These tests include the heteroscedasticity test, serial correlation test and cross-sectional dependence test. The heteroscedasticity was used to check for variations of the residuals of the models in order to ascertain whether the residuals of the model are unstable over time. The coefficients and residuals were further diagnosed for serial correlation problem using Wooldridge test.

Research Hypotheses

H01: Statutory auditors' going concern judgement does not have significant effect on return on assets of companies listed on the NGX

H02: Audit Firm Size and information asymmetry do not significantly moderate the effect of statutory auditors’ going concern judgment on return on asset of companies listed on the NGX.

Multiple Linear Regression Model

The multiple regression model employed in this study was adopted from the empirical model of Emeke, Olaoye and Ogundajo (2021) as thus:

According to the study, the variables were represented as thus, accordingly: ROA = Return on assets; SD = Social Disclosure; ED = Environmental Disclosure; FS = Firm size and AGE = Age of firm; β1 – Β4= Coefficient of explanatory variables; βo = Constant; ɛ = error term; i is the number of the sampled firms and t is the time frame of the study.

Where (Emeke, et al., 2021) examined the effect of social and environmental disclosure on return on asset, this study therefore modifies the model by examining the effect of statutory auditors going concern judgement on returns on asset of companies listed on the NGX. The adopted model is modified as thus:

ROA, CRPM, OPCF, CSRT, RSCR, AFSZ, and ASYM represent Return on Asset, Credit Payment, Operating Cash Flows; Customer Retention; Regulatory, Statutory, and Capital Requirements Compliance; Audit Firm Size; and Information Asymmetry, respectively.ROA, CRPM, OPCF, CSRT, RSCR, AFSZ, and ASYM represent Return on Asset, Credit Payment, Operating Cash Flows; Customer Retention; Regulatory, Statutory, and Capital Requirements Compliance; Audit Firm Size; and Information Asymmetry, respectively see Table 1.

Table 1 Multicollinearity Test Result
Variables	ROA	CRPM	OPCF	CSRT	RSCR	AFSZ	ASYM	VIF	1/VIF
ROA	1
CRPM	-0.188	1						1.32	0.759
OPCF	0.165	0.024	1					1.05	0.952
CSRT	-0.051	-0.295	-0.132	1				1.37	0.731
RSCR	-0.049	-0.086	-0.053	0.016	1			1.09	0.914
AFSZ	0.092	0.231	0.131	-0.186	-0.037	1		1.35	0.742
ASYM	-0.071	0.302	0.102	0.202	0.179	0.41	1	1.63	0.615
								Mean = 1.30

The regression model represented in equation 1 explicate the effect of statutory auditors going concern judgement and return on asset in companies listed on the NGX, while the regression model specified in equation 2 resulted from the modification of equation 1 above by adjusting for the moderating effect of statutory auditors going concern judgement and return on asset using Audit Firm Size; and Information Asymmetry.

Analysis of Data and Discussion of Results

Using correlation matrix to discover the existence of multicollinearity among the explanatory variables, the results in absolute values showed that the least value is 0.00 while the highest is 0.83, all the degree of association are less than the benchmark of 0.8. Baltagi (2015) revealed that multicollinearity problem does not exists among the explanatory variables Also, the result of the Variance inflation factor negated the result of the correlation matrix which proved that all the series in the distribution are unhealthily correlated, as VIF showed a mean value of 1.30 which is relatively lower than the threshold of 5 or 10 (James et al. 2013); and also the inverse VIF for all the series are less than 1, which is the threshold. Therefore, this study concluded that multicollinearity problem does not exist among the explanatory variables of the models.

The probability of the Hausman tests which were conducted to know which of the estimating technique between Fixed- Effect and Random-Effect would be more appropriate considering the null hypothesis of the Hausman test in support of fixed-effect, however, the result of the tests with probability values of 0.03 and 0.01 being less than 0.05 (5%) chosen significant level negates null hypothesis of Hausman test and proved that fixed effect is better than random effect in estimating both models. Testparm test was conducted as a confirmatory test for fixed effect in Hausman and the probability of 0.053 and 0.153 contradict the result of the Hausman tests and showed the inappropriateness of fixed-effect, thus, Pooled OLS is preferred for both models.

In order to ascertain that the models (Models One and Two) are free from any econometric problem, the three diagnostic tests applicable to panel-data analysis were carried out, which includes the heteroscedasticity test, serial correlation test and cross-sectional dependence test. The heteroscedasticity, checking for variations of the residuals of the model; with the probability values of 0.000 and 0.000 respectively showed that the model is heteroscedastic, implying that the residuals of the model are unstable over time, thus the study did reject the null hypothesis which states that the variance of the residuals of the model are invariant over time. Also, the two models’ coefficients and residuals were checked for serial correlation problem using Wooldridge test for autocorrelation in panel data and with the probability values of 0.263 and 0.762, proved that the coefficients and the residual of the model are uncorrelated and thus, there are absence of serial correlation problem in the Models One and Two. Due to the presence of heteroscedasticity problem in the models; Model One and Model Two were estimated using Pooled Ordinary Least Square Regression Analysis with Robust standard errors and the results presented in Table 2.

Table 2 Regression Analysis
	Model 1				Model 2
	Pooled OLS Regression with Robust Standard Errors				Pooled OLS Regression with Robust Standard Errors
Variable	Coeff	Std. Err	T-Stat	Prob	Coeff	Std. Err	T-Stat	Prob
Constant	10.495	1.172	8.95	0	10.463	4.199	2.49	0.013
CRPM	-0.08	0.014	-5.9	0	-0.078	0.024	-3.23	0.001
OPCF	0.14	0.032	4.43	0	0.12	0.027	4.44	0
CSRT	-0.056	0.016	-3.46	0.001	-0.025	0.017	-1.44	0
RSCR	-0.995	0.726	-1.37	0.171	-0.958	0.878	-1.09	0.276
AFSZ					2.716	0.945	2.87	0.004
ASYM					-0.169	0.327	-0.52	0.606
Adj. R2	0.0799				0.0776
F-Stat	F(4, 911) = 14.35 (0.00)				F(6, 880) = 17.39 (0.00)
Hausman Test	chi2(4) = 10.45 (0.03)				chi2(6) = 16.88 (0.01)
Testparm Test	F(15, 816) = 1.72 (0.053)				F(15, 790) = 1.37 (0.153)
Heteroscedasticity Test	chi2(1) = 153.67 (0.00)				chi2(1) = 178.34 (0.000)
Serial Correlation Test	F(1, 73) = 1.274 (0.263)				F(1, 69) = 0.092 (0.762)

As depicted in Table 2, the regression results estimated for evaluating the effect of the constructs of statutory auditors' going concern judgement on the return on assets of Nigerian listed companies; judging from the probability values of the t-statistics which were used in determining the significance of the effect while the coefficients (in values and signs) were used in determining the extent of the effect as well as the nature of the effect; revealed that CRPM has significant negative effect on ROA (β = -0.080, ρ = 0.000); OPCF exerted significant positive effect on ROA (β = 0.140, ρ = 0.000); CSRT negatively and significantly influence ROA (β = -0.056, ρ = 0.001); while RSCR has negative but insignificant effect on ROA (β = -0.995, ρ = 0.171).

The magnitude of the effect is determined by the value of the coefficients, and this showed that CRPM, CSRT, and RSCR with the coefficient values of -0.08, -0.056, and -0.995 means that a percentage increase in CRPM, CSRT, and RSCR would yield 0.08, 0.056 and 0.995 percent decrease in ROA; while OPCF with the coefficient value of 0.140 implies that a percentage change in OPCF would improve ROA by 0.14 percent.

The result of the F-statistics of 14.35 with the degree of freedom of (4, 911) and probability value of 0.000 indicating that the four measures of independent variable jointly and significantly affect ROA of listed companies in Nigeria. In addition, the value of the coefficient of multiple determination (Adjusted R²) of 0.0799 means that the combined changes in the explanatory variables could only explain 7.99% variations in the explained variable (ROA) while the remaining changes in ROA of 92.01% is as a result of other factors not captured in the model.

Considering the value of the F-statistics of 14.35 with the degree of freedom of (4, 911) and having a probability value of 0.000 that is less than 5% (0.05), being the chosen significant level of the study, this study therefore decides that the null hypothesis for model One which states that “Statutory auditors' going concern judgement does not have significant effect on return on assets of companies listed on the NGX” be rejected while accepting the alternate hypothesis and concluded that “Statutory auditors' going concern judgement have significant effect on return on assets of companies listed on the NGX”.

Model 2 included the moderating variables of AFSZ and ASYM in model one. Pooled panel OLS with Robust Standard Errors, was employed in the estimation of Model two in order to moderate the effect of Statutory Auditor’s going concern judgement on ROA. The result from the estimation of model 2 revealed that CRPM had a significant negative effect on ROA (β = -0.078, ρ = 0.001); OPCF exerted significant positive effect on ROA (β = 0.120, ρ = 0.000); CSRT negatively and significantly influence ROA (β = -0.025, ρ = 0.000); while RSCR has negative but insignificant effect on ROA (β = -0.958, ρ = 0.276); AFSZ with a positive significant effect on ROA (β = 2.716, ρ = 0.004) and ASYM with a negative but insignificant effect on ROA (β = -0.169, ρ = 0.606).

The magnitude of the effect is determined by the value of the coefficients, and this showed that CRPM, CSRT, and RSCR with the coefficient values of -0.078, -0.025 and -0.958 means that a percentage increase in CRPM, CSRT, and RSCR would yield 0.078, 0.025 and 0.958 percent decrease in ROA; while OPCF with the coefficient value of 0.120 implies that a percentage increase in OPCF would increase ROA by 0.12 percent. Table 2 further expounded that while AFSZ positively and significantly moderates the effect of Statutory auditors going concern judgement on ROA (β = 2.716, ρ =0.004); ASYM, on the contrary, negatively and insignificantly moderates the effect of Statutory auditors going concern judgement on ROA (β = -0.169, ρ = 0.606).

The result of the F-statistics of 17.39 with the degree of freedom of (6, 880) and probability value of 0.00 indicating that the AFSZ and ASYM jointly and significantly moderates the effect of Statutory Auditors going concern judgement on the ROA of listed companies in Nigeria. In addition, the value of the coefficient of multiple determination (Adjusted R²) of 0.0776 means that the combined changes in the explanatory and moderating variables could only explain 7.76% variations in the explained variable (ROA) while the remaining changes in ROA of 92.24% is as a result of other factors not captured in the model.

Considering the value of the F-statistics of 17.39 with the degree of freedom of (6, 880) and having a probability value of 0.000 that is less than 5% (0.05), being the chosen significant level of the study, this study therefore decides that the null hypothesis for model two which states that “Audit Firm Size and information asymmetry do not significantly moderate the effect of statutory auditors’ going concern judgment on return on asset of companies listed on the NGX” be rejected while accepting the alternate hypothesis and concluded that Audit Firm Size and information asymmetry significantly moderate the effect of statutory auditors’ going concern judgment on return on asset of companies listed on the NGX.

Discussion of Findings

Returns on asset have been commonly used in extant literature in the evaluation of the profitability performance of listed companies. As a matter of fact, ROA has been considered appropriate in evaluating the profitability performance of companies in different categories (Boyte-White, 2022). This study therefore considered how the statutory auditors going concern judgement proxies affect the ROA of companies listed on the NGX. Further, for the purpose of this study, the proxies for estimating the statutory auditors’ going concern judgement were extracted from the three indicators specified in the ISA 570 (Revised). These include the Credit payment (CRPM), Operating cashflow (OPCF), Customer retention (CSRT), and Regulatory, Statutory, and Capital Requirements Compliance (RSCR).

Theoretically, the results imply that shareholders and investors of many businesses are considered profit-oriented. Therefore, in practice, the performance of ROA of significantly attracts the interest of investors as it revealed the likelihood of maximising returns from investment as well as enhancing the equity performance of listed companies. On the contrary, the risk of going concern is high where there is a considerable decline in the profitability performance of listed companies as investors and other stakeholders tends to refrain from investing their resources in such business.

In order to empirically determine the effect of statutory auditors' going concern judgement on the return on assets of companies listed on the NGX; and further assessed how audit firm size and information asymmetry would moderate the effects of statutory auditors’ going concern judgement on return on asset of companies listed on the NGX, the study employed the pooled panel OLS analysis with robust standard errors on models one and two. Where model one examined how statutory auditors going concern judgement affected the ROA of companies listed on the NGX, model two further examined model one by employing both information asymmetry and audit firm size to adjust for the moderating effect of statutory auditors going concern judgement on the return on asset in companies listed on the NGX.

Particularly, both models showed that Credit payment, Customer retention, and Regulatory, Statutory, and Capital Requirement negatively affects the returns on asset of companies listed on the NGX, while the Operating cashflow positively affects their ROA in this respect. Therefore, the empirically findings derived from both models therefore revealed that the results of model one is consistent with model two as statutory auditors going concern judgement, with and without moderating variables significantly affects the returns on asset of companies listed on the NGX. This finding is in tandem with the findings of (Widoretno, 2019); and (Sukirman, et al., 2022). However, (Ryu, et al., 2019); and (Koh & Low, 2004) are found inconsistent with this study’s findings. The study also found that the inclusion of audit firm size and information asymmetry moderated the effect of statutory auditors’ going concern judgement on ROA in listed companies in Nigerian exchange which consequently reduced the magnitude of the effect.

Conclusion and Recommendations

This study mainly examined the effect of statutory auditor’s going concern judgement and return on asset in companies listed on the Nigerian exchange. The study used the pooled panel OLS regression analysis to test the hypothesis, and the findings revealed that statutory auditors going concern judgement had a negative and significant effect on returns on assets of companies listed on the NGX. On the basis of this finding, this study therefore concluded that statutory auditors going concern judgement is a significant factor influencing return on asset of companies listed on the NGX.

The study further assessed how audit firm size and information asymmetry would moderate the effects of statutory auditors’ going concern judgement on return on asset of companies listed on the NGX. The study also employed the pooled OLS regression to evaluate the stated hypothesis, and the findings also showed that audit firm size and asymmetric information moderate the effect of statutory auditor’s going concern judgement on the ROA of companies listed on the NGX.

Contribution to Future research

Sequel to the empirical results and findings obtained from this study, the study further suggests that future studies should consider examining the effect of statutory auditors going concern judgement on other business performance measures other than profitability performance, some of which include:

• Investigating the effect of statutory auditors going concern judgement on liquidity performance of companies listed on the Nigeria Exchange Group (NGX), as liquidity constitute one of the major forces impacting the going concern of businesses;

• Examining the effect of statutory auditors going concern judgement on the leverage performance of businesses listed on the NGX.

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Received: 26-Dec-2023, Manuscript No. IJE-24-14328; Editor assigned: 29-Dec-2023, Pre QC No. IJE-24-14328 (PQ); Reviewed: 12-Jan-2024, QC No. IJE-24-14328; Revised: 17-Jan-2024,, Manuscript No. IJE-24-14328 (R); Published: 23-Jan-2024