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Article

Can the Presence of Big 4 Auditors in IPO Prospectus Reduce Failure Risk?

Department of Accounting, College of Business Administration, Taif University, Taif 21944, Saudi Arabia
J. Risk Financial Manag. 2024, 17(6), 234; https://doi.org/10.3390/jrfm17060234
Submission received: 4 May 2024 / Revised: 28 May 2024 / Accepted: 3 June 2024 / Published: 5 June 2024
(This article belongs to the Special Issue Judgment and Decision-Making Research in Auditing)

Abstract

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This paper addresses a void in the research on auditing and initial public offering (IPO) failure by investigating the impact of the Big 4 auditing firms on the likelihood of an IPO failure. This research is the first comprehensive analysis of more than 33,000 global IPOs that either failed or were successful between 1995 and 2019 across a wide range of nations with vastly different regulatory, cultural, and economic settings. A cross-sectional probit regression model is utilized to investigate the influence of hiring the Big 4 auditing firms on IPO failure, building upon prior studies on IPO failure. We found strong evidence that IPO failure rates were diminished by up to 67% when one of the Big 4 auditing firms was involved in auditing the IPO prospectus. For IPO founders, hiring Big 4 auditors before an IPO is a quality signaling strategy that minimizes the risk of a failed IPO by reducing information asymmetry among IPO participants. Our findings provide useful policy implications. Hiring one of the Big 4 auditing firms before an IPO is a reassuring signaling strategy for founders, since it decreases information asymmetry among IPO investors and so lowers the risk of the IPO failing. Primary market investors now have access to credible evidence indicating that backing IPOs from companies that use the Big 4 auditing firms increases the likelihood of such IPOs being listed on stock exchanges and yields positive returns. This is the first time, as far as the academicians are aware, that conclusive evidence has been found of a strong inverse association between the presence of Big 4 audits and failure risk for IPO firms. Our research could be helpful to primary market regulators since it shows how crucial it is to encourage Big 4 audits in IPO companies. The quality work of the Big 4 auditors does lower the risk of failure in the IPO market, which might help owners of small private equities to list their firms on the IPO market, boosting economic growth.

1. Introduction

The association between hiring well-known audit firms, such as the Big 4 (Deloitte, PricewaterhouseCoopers, Ernst & Young, and KPMG), and initial public offering (IPO) firms has attracted considerable academic attention due to notable auditing scandals linked to IPOs (El-Rajabi and Gunasekaran 2006; De Franco et al. 2011; Ke et al. 2015; Sun et al. 2015; Meckfessel and Sellers 2017; Alhadab and Clacher 2018; Chen et al. 2022). Choosing one of the Big 4 audit firms is a crucial decision for companies aiming to become publicly traded (Feng et al. 2019). Audit firms are responsible for providing unbiased confirmation of the truthfulness and dependability of financial statements (De Franco et al. 2011). This helps to build investor confidence and maintain the integrity of the IPO process.
The frequency of auditing scandals related to IPOs has caused uncertainties regarding the efficacy of audits conducted by prominent firms such as the Big 4 (Fuerman 2006; Chen 2016; Chen et al. 2022). Enron, an energy company, experienced a significant downfall in 2001 due to the revelation of its involvement in extensive accounting fraud. Arthur Andersen, one of the Big 5 accounting firms at the time, audited the company’s IPO (Huang and Li 2009). Tyco International faced allegations of accounting fraud in relation to its IPO in 2002 (The New York Times 2002). The CEO and CFO of the company were found guilty of theft and fraud involving securities. Additionally, the auditing firm PwC agreed to a settlement of USD 225 million to resolve lawsuits associated with the case (The Financial Times 2007). Adelphia Communications’ bankruptcy in 2002 was linked to accounting fraud (Gilson and Villalonga 2007). The owner and directors of the company faced convictions of conspiracy and securities fraud. Deloitte & Touche, the auditing firm, paid USD 167.5 million to settle lawsuits associated with the case (CFO Magazine 2007). Satyam Computer Services, a prominent Indian IT firm, acknowledged significant accounting fraud in 2009 (Bhasin 2013). The CEO and founder of the company, Ramalinga Raju, received a seven-year prison sentence, while the auditing firm PwC received a penalty of USD 6 million from Indian regulators (Reuters 2015a). In 2015, Toshiba, a Japanese multinational conglomerate, faced an accounting scandal in which it was discovered that the company had inflated its profits by USD 1.2 billion over multiple years (Reuters 2015b). Ernst & Young ShinNihon audited the company’s IPO (Reuters Staff 2015). Recently, Deliveroo’s IPO in 2021 faced substantial investor criticism due to concerns regarding the firm’s hiring procedures and valuation (Insider 2021). PwC, the company’s auditor, faced criticism regarding its involvement in the IPO.
Audit scandals related to IPOs have undermined confidence in the reliability and precision of financial reporting, leading investors to exercise greater caution and skepticism when considering involvement in IPOs (Chen et al. 2005; Habib et al. 2014; Lau and Ooi 2016; Petra and Spieler 2020). The heightened skepticism has resulted in a more cautious approach toward IPO investments, as investors now require more thorough due diligence and stricter oversight (Warganegara and Indriastari 2009; Beatty et al. 2013). The discovery of financial irregularities, fraudulent activities, and material misstatements in notable IPOs highlights the necessity for additional investigation into the correlation between the engagement of Big 4 audit firms and the withdrawal of IPOs. In this study, we argue that the existence of a positive association may suggest that investors perceive a lack of confidence in the Big 4 auditing firms, leading to a higher rate of IPO withdrawals when companies engage these firms for auditing services. In contrast, a negative correlation may indicate that regardless of the frequency of the auditing scandals, investors continue to view the involvement of the Big 4 auditing firm as a signal of quality. IPO research has explored the presence of Big 4 auditors on the IPO market with a large focus on the underpricing phenomena at the time of an IPO, despite the numerous benefits that may emerge from selecting Big 4 auditing firms for the IPO market (Albring et al. 2007; Chang et al. 2008; Wang and Song 2021; Jamaani and Alidarous 2022). Little is revealed about the significance of the Big 4 auditors to the survivability of IPO enterprises on the worldwide IPO market, although IPO failure is much more critical to IPO companies’ survivability than underpricing.
According to Jamaani and Alidarous (2022), IPO businesses that use Big 4 audit firms reduce IPO underpricing. IPO underpricing is the gap between the offer price accepted by issuers and the initial closing price of the IPO share on the first trading day, which IPO issuers provide to investors (Jamaani and Alidarous 2019; Álvarez-Otero 2022). This wealth transfer is supposed to compensate for the information asymmetry between issuers and investors in the IPO process (Jamaani and Ahmed 2020; Jamaani and Alidarous 2021; Abrahamson 2024). A company’s capacity to survive is more affected by IPO withdrawal than underpricing (Lin et al. 2010; Helbing 2019). IPO withdrawal risk refers to the possibility of an IPO being canceled before its complete execution (Dunbar and Foerster 2008). IPO underpricing temporarily transfers wealth from issuers to investors (Habib and Ljungqvist 2001). However, Mumtaz and Yoshino (2021) found that many underpriced IPOs do well over time. Thus, this event may counterbalance IPO issuers’ temporary wealth loss due to underpricing. Withdrawal requires accounting, underwriting, and legal costs and is seldom reversible (Reiff and Tykvová 2021). Withdrawing an IPO may affect a company’s financial liquidity, financing options, market value, and bankruptcy risk (Busaba et al. 2001). These effects mostly result from the company’s credibility being eroded (Qing 2011).
Thus, studies on Big 4 auditors’ impact on failure threat at the offering time are scarce. This study aims to fill a gap in the existing literature on accounting and IPO failure by examining the influence of the Big 4 auditing firms on the probability of an IPO failure. Signaling theory suggests that signals may reveal unseen owners’ qualities, lowering the prevalent asymmetric information amongst investors and issuers and diminishing IPO failure threat (Helbing 2019; Helbing et al. 2019). IPO investors depend on signals from IPO businesses to make investment decisions, and academic research indicates that employing Big 4 auditing firms may offer an attractive signaling role to build legitimacy in the face of market newness liability (Choi et al. 2008; Zimmerman et al. 2021). In particular, Big 4 auditors at an IPO could signify a business’s excellent auditing quality and satisfactory financial information (Feng et al. 2019). The research argues that Big 4 auditors can bring many benefits to IPO firms (Jamaani and Alidarous 2022). PO businesses with Big 4 auditors may provide higher-quality IPO audit services, as they may have a greater understanding of a broader variety of accounting difficulties due to their extensive expertise with audits of public and private companies (Gao et al. 2011). The Big 4 auditors possess extensive worldwide connections, substantial advising practices, and a high number of previous policy experts (Elemes and Chen 2022). This insight might enable them to identify required audit modifications more accurately and to predict and react to local SEC accounting comments (Defond et al. 2018). Big 4 auditors also demand substantial IPO audit fee premiums, allowing them to devote more resources to IPO audits than non-Big 4 auditors (Jacob et al. 2019). Additionally, the Big 4 auditing firms have more to lose in a lawsuit because of their large financial resources and extensive investment in establishing their reputation (Khurana and Raman 2004). As a result of their bigger scale, Big 4 auditing firms are also able to recruit and maintain better quality human resources, which is widely believed to contribute to their superior expertise (Fitriyani and Mahmud 2017). Prior studies involving publicly traded corporations have consistently shown that audits conducted by one of the “Big 4” accounting firms are of a better quality than those conducted by any of the “other” firms (Albring et al. 2007; De Franco et al. 2011; Defond et al. 2018).
This research hypothesizes that Big 4 auditing companies might act as a signal of IPO quality and reduce IPO failure, based on the vast evidence that Big 4 firms could improve the quality of IPO prospectuses (Albring et al. 2007; De Franco et al. 2011; Defond et al. 2018; Jamaani and Alidarous 2022). According to a study conducted by Helbing et al. (2019), the average failure rate for IPOs on most stock exchanges was about 15% between 1980 and 2017. This eventually resulted in losses of several billion USD because of missed listing fees suffered by founders, lost investment possibilities for participating investors, and lost prospects for economic growth as a direct result of the IPO failure (Qing 2011).
Significant academic interest has been directed toward the correlation between the engagement of the Big 4 auditing firms and IPO firms, owing to the notable auditing scandals associated with IPOs (El-Rajabi and Gunasekaran 2006; De Franco et al. 2011; Ke et al. 2015; Sun et al. 2015; Meckfessel and Sellers 2017; Alhadab and Clacher 2018; Chen et al. 2022). Companies that aspire to attain public listing must make a critical decision when selecting one of the Big 4 audit firms (Feng et al. 2019). The primary duty of audit firms is to furnish impartial verification regarding the accuracy and reliability of financial statements (De Franco et al. 2011). This contributes to investor confidence and preserves the IPO procedure’s integrity. Uncertainties have been cast on the effectiveness of audits performed by renowned firms, including the Big 4, due to the prevalence of auditing controversies associated with IPOs (Fuerman 2006; Chen 2016; Chen et al. 2022). Investors are now more hesitant and skeptical of participating in IPOs due to audit controversies associated with them that have eroded faith in the accuracy and dependability of financial reporting (Chen et al. 2005; Habib et al. 2014; Lau and Ooi 2016; Petra and Spieler 2020). Despite the numerous benefits that may result from selecting Big 4 auditing firms for the IPO market, IPO research has examined the presence of Big 4 auditors on the IPO market with a particular emphasis on underpricing phenomena at the time of an IPO (Albring et al. 2007; Chang et al. 2008; Wang and Song 2021; Jamaani and Alidarous 2022). The importance of the Big 4 auditors to the survival of IPO companies on the global IPO market is not extensively discussed, despite the fact that IPO failure poses a far greater threat to the IPO companies’ survival than underpricing. Thus, research on the impact of Big 4 auditors on the risk of failure at the time of offering is scant. A void in the extant literature regarding accounting and IPO failure is sought to be filled by this study, which investigates the impact of the Big 4 auditing firms on the likelihood of an IPO failing.
The following critical question is whether or not Big 4 auditors’ presence at the time of an IPO could act as a signal of the quality of the IPO business, hence reducing the threat of failure. Stated differently, we seek to address the following research question: Can the presence of Big 4 auditors in IPO prospectus reduce IPO failure risk?
We conduct the first worldwide study on the Big 4 auditors’ impact on IPO failure utilizing more than 33,000 completed and failed IPOs in 22 marketplaces with various legal and cultural backgrounds from 1995 to 2019. This study extends the remarkable work of Firth and Liau-Tan (1998), Busaba et al. (2001), Chang et al. (2008), De Franco et al. (2011), and Reiff and Tykvová (2021). All these researchers ignored the Big 4 auditing firms’ signaling roles in IPO failure. We find considerable evidence that the Big 4 auditors’ participation in IPO prospectuses as a quality signal decreases information asymmetry in the IPO market, lowering the risk of IPO failure globally. The Big 4 auditors decrease asymmetric information amongst IPO players and lower the risk of IPO failure by up to 67% by sending comforting signals to the IPO market. Due to their significant auditing experience, Big 4 auditors audit IPOs better. This enables them to recognize audit modifications and react to stock market authorities’ financial reporting concerns. Because they charge more, the Big 4 auditing firms can focus on IPO audits. Big 4 auditors may participate in the IPO market because of IPO lawsuits and reputation concerns. IPO auditors have tremendous incentives to avoid litigation since many countries have laws protecting investors from lawsuits. Auditing IPOs may increase an auditor’s reputation owing to large profit margins, the potential of a long-term connection with the IPO firm, and client visibility. Consequently, engaging the Big 4 auditing firms as IPO quality signals reduces the occurrence of IPO failures.
The results of our research have important ramifications for new businesses, investors, researchers, and policymakers. As indicated previously, Helbing et al. (2019) discovered that the average failure rate for IPOs on the majority of stock markets between 1980 and 2017 was approximately 15%. Founders lose listing fees, investors lose investment opportunities, and economic progress is lost due to the failed investment. Hiring one of the Big 4 auditing firms before an IPO is a reassuring signaling strategy for founders, since it decreases information asymmetry among IPO investors and so lowers the risk of the IPO failing. On the contrary, primary market investors now have access to credible evidence indicating that backing IPOs from companies that use the Big 4 auditing firms increases the likelihood of such IPOs being listed on stock exchanges and yields positive returns. This is because money invested in IPOs that are widely predicted to fail is often returned to investors at some point. Maintaining invested cash in an IPO company that may be removed from the market due to failure is a waste of money for investors. This is the first time, as far as the academicians are aware, that conclusive evidence has been found of a strong inverse association between the presence of Big 4 audits and failure risk for IPO firms.
Our research could be helpful to primary market regulators since it shows how crucial it is to encourage Big 4 audits in IPO companies. The quality work of the Big 4 auditors does help to lower the risk of failure in the IPO market, which might help owners of small private equities to list their firms on the IPO market, boosting economic growth.
This paper continues as follows. Section 2 discusses related literature, while Section 3 provides theory and hypothesis-building. Section 4 discusses statistics and methodology. Section 5 discusses the findings. Section 6 covers sensitivity testing. Section 7 concludes the research.

2. Related Literature Review

2.1. Literature Review on IPO Failure Risk

IPO research concentrated on variables that influence the possibility of an IPO failure owing to issuer-investor information asymmetry. Dunbar (1998) investigated issuer and issue criteria in 236 failed and 520 completed IPOs between 1979 and 1982 in the US to identify IPO failure. The research examines the association between registration volume and IPO failure threat. The researchers included owners and offerors, a corporate governance intermediary, market post-filing, and market at filing features as potential IPO failure factors (Dunbar 1998; Busaba et al. 2001; Dunbar and Foerster 2008; Helbing 2019; Reiff and Tykvová 2021).
Between 1999 and 2004, Boeh and Southam (2011) examined 1071 completed and 584 failed IPOs in the US, where the author found that reputable underwriters could cause IPO companies to cancel their offering to protect their image. Researchers indicated the reverse to be evident for an IPO backed by underwriting banks with a poor market reputation, which had to be pulled as a result of poor reputational capital. Qing (2011) found no association between prestigious underwriters and IPO failure in 2284 completed and 594 failed IPOs from 1996 to 2005 in the US. Helbing et al. (2019) found similar results to Qing after examining 2474 completed and 334 failed IPOs in Denmark, the UK, France, Norway, Italy, Germany, Sweden, and Spain from 2001 to 2015. Boeh and Southam (2011) observed that venture capitalist-backed IPOs fail more. The researchers indicated that venture capital firms funded by IPOs may reject weak IPOs if they discover another funding source.
Reiff and Tykvová (2021) used 2500 completed and 938 failed IPOs in the US IPO market from 1997 to 2014 to show that venture capital support and improved corporate governance might signal quality and reduce the likelihood of an IPO failure. Helbing et al. (2019) found that systemic risk increases when a company’s CEO is also the board chairman, increasing the chance of an IPO failure. Dual CEOs do not affect IPO failure, according to Reiff and Tykvová (2021). Generally, studies suggest that the likelihood of IPO failure is connected to the issue of information asymmetries between IPO players, which itself is likely to be impacted by IPO features.

2.2. Literature Review on IPO Audit Service Quality

The IPO auditor’s principal responsibility is to offer an opinion on the financial statements contained in the IPO prospectus (Albring et al. 2007; Sundarasen et al. 2021). The auditor uses auditing processes to check that the financial information disclosed is compliant with recognized accounting principles and accurately represents the firm’s economics (Razafindrambinina and Kwan 2013). Previous literature explored earnings quality surrounding IPOs and proposes that auditor monitoring could impact managers’ pre-IPO financial reporting strategies (Ball and Shivakumar 2008; Hirst et al. 2008)1. IPO auditors help firms meet local SEC reporting rules (Defond et al. 2018). Before submitting the draft IPO prospectus to the SEC, the auditor offers technical financial reporting advice, direction on preparing the financial statements, and other disclosures to guarantee correctness, thoroughness, and integrity (Albring et al. 2007). The SEC often gives clarifications and revisions to the corporation after its first evaluation. Executives and corporate counsel normally write each comment’s response and a revised prospectus (Li and Liu 2017). Auditors analyze replies and give recommendations, notably on financial statements and related financial information (Westfall and Omer 2018; Moustafa Abdallah et al. 2024). The corporation subsequently submits a formal reply and updated IPO prospectus to the SEC (Li and Liu 2017). After the prospectus is approved, the firm may list its shares.
Since SEC remarks are a diversion from running the business and the material in the IPO prospectus might necessitate the insertion of further quarterly or yearly financial statements in the prospectus, firms have an incentive to keep them to a minimum (Cunningham and Leidner 2022). Corporations that obtain more SEC review letters between the time they file their first prospectus and the time their IPO is issued (the filling period) tend to have their IPO price reduced (Li and Liu 2017). According to research by Lowry et al. (2020), a larger drop in the number of shareholdings the firm plans to release during the filling period is linked to a higher number of SEC comment letters, and comments concerning revenue recognition in the first SEC comment letter are linked to a higher adverse price adjustments. Firms may benefit from improved quality IPO audit services by reducing the severity of the SEC’s first remarks and the likelihood of those issues resurfacing in the form of accounting comments (Westfall and Omer 2018).

2.3. Literature Review on Big 4 Audit Firm Quality

The literature commonly links superior accounting disclosure quality with the presence of Big 4 auditors. This literature suggests that the inclusion of a Big 4 auditor is associated with increased audit quality (Becker et al. 1998; Blackwell et al. 1998; Khurana and Raman 2004; Francis and Wang 2008; Law 2008; Francis and Yu 2009; Rusmin 2010; Khlif and Samaha 2016; Meckfessel and Sellers 2017; Zorio-Grima and Carmona 2019; Lento and Yeung 2021; Gong et al. 2022; Kang et al. 2023), and firms tend to prefer hiring Big 4 auditors due to their outstanding reputation, which is believed to result in higher quality audits and improved accuracy of accounting information in financial reports. According to Humayun Kabir et al. (2011), Big 4 affiliate audit firms are associated with high-quality audits, resulting in discernible variations in accrual quality when compared to non-Big 4 or local audit firms. The literature indicates that independent auditors, particularly Big 4 audit firms, play a crucial role in monitoring and scrutinizing the financial accounting and reporting practices of companies (Law 2008; Meckfessel and Sellers 2017; Zorio-Grima and Carmona 2019). This oversight assists in minimizing inaccuracies in reported accounting figures and enhances the quality of accounting disclosures (Feng et al. 2019; Ozili 2022). DeBoskey and Jiang (2012) find that the use of Big 4 audit firms by US banks is associated with a decrease in income smoothing. Alzoubi (2016) found that firms employing a Big 4 audit firm exhibit lower levels of earnings management compared to firms utilizing the services of a non-Big 4 audit firm.
Rusmin (2010) investigates the relationship between earnings management and auditor quality in Singaporean firms. The study reveals a negative correlation between auditor quality and the extent of earnings management. This implies that firms that engage a Big 4 specialist audit firm tend to have lower levels of earnings management compared to firms that use the services of a non-Big 4 audit firm. Persakis and Iatridis (2016) examine the combined impact of audit quality and investor protection on earnings quality in a cross-country sample from the 2008 financial crisis. The study reveals a positive relationship between audit quality and earnings quality in countries with robust investor protection. Rusmin et al. (2014) examine the impact of audit quality on the practice of income-increasing earnings management. The univariate analysis indicates that discretionary accruals in enterprises reviewed by Big 4 auditors are substantially lower than those in businesses reviewed by non-Big 4 auditors. Mokoaleli-Mokoteli and Iatridis (2017) examine the association between Big 4 audit firms, earnings management, and earnings conservatism in the context of South African publicly traded firms. The study reveals that companies audited by one of the Big 4 auditors exhibit reduced instances of earnings manipulation and increased levels of conditional conservatism. Alzoubi (2016) investigates the relationship between audit quality and earnings management in Jordanian listed companies during the period from 2007 to 2010. The results indicate a negative correlation between the quality of audits and the practice of earnings management. Companies that engage the services of a Big 4 audit firm exhibit lower levels of earnings management in comparison to firms that hire a non-Big 4 audit firm. In their study, Orazalin and Akhmetzhanov (2019) examine the impact of audit quality on earnings management and explore how the association between earnings management and the cost of debt is influenced by audit quality. The study demonstrates that a higher level of audit quality, specifically having a Big 4 auditor, is associated with a decrease in the cost of debt.

3. Theory and Hypothesis Development

3.1. Theory

This study utilizes signaling theory to discuss the anticipated relationship between the engagement of Big 4 audit firms and the occurrence of IPO failure. Within the context of IPOs, the selection of a Big 4 audit firm can be perceived as a strategic signal by which companies communicate pertinent details regarding their caliber and trustworthiness to prospective investors (Albring et al. 2007; De Franco et al. 2011; Defond et al. 2018; Jamaani and Alidarous 2022). In accordance with the tenets of signaling theory, IPO firms encounter a state of informational asymmetry as they endeavor to secure external capital (Jamaani and Alidarous 2019). Investors commonly possess a lesser degree of information pertaining to the genuine value and future prospects of a company in comparison to the individuals within the company who possess insider information (Jamaani et al. 2022). The presence of information asymmetry can give rise to the phenomenon of adverse selection, wherein investors exhibit hesitancy toward investing in IPOs owing to their apprehension regarding the potential risks associated with investing in firms of inferior quality (Jamaani and Ahmed 2021). By engaging the services of a prominent audit firm from the Big 4, a company effectively communicates to the market its unwavering dedication to fostering transparency and upholding the utmost standards in financial reporting (Francis and Wang 2008). The esteemed standing and trustworthiness of the Big 4 accounting firms, renowned for their specialized knowledge and stringent auditing protocols, can serve as an indicator of a company’s financial reporting soundness, internal governance mechanisms, and overall accounting excellence (Lee and Lee 2013).
IPO research has demonstrated a correlation between the engagement of Big 4 audit firms by IPO firms and a reduction in IPO underpricing (Albring et al. 2007; Chang et al. 2008; Jamaani and Alidarous 2022). The concept of IPO underpricing pertains to the remaining money that is handed over by IPO issuers to IPO investors and that results from the difference between the low offer price accepted by issuers and the first closing price of the IPO share in the first trading date (Jamaani and Ahmed 2022). This transfer of wealth is deemed as legitimate compensation for the inherent information asymmetry that prevails between the issuers and investors involved in the IPO process (Habib and Ljungqvist 2001). However, the ramifications of an IPO withdrawal on a company’s ability to endure are more significant than those resulting from IPO underpricing (Helbing 2019). The concept of IPO withdrawal risk pertains to the likelihood of an IPO being terminated or retracted prior to its full execution (Qing 2011). The level of risk is subject to a multitude of factors, encompassing market dynamics, idiosyncratic attributes of the company, and the overarching caliber and trustworthiness of the issuing entity (Lin et al. 2010). The phenomenon of IPO underpricing involves a temporary redistribution of wealth from IPO issuers to IPO investors (Habib and Ljungqvist 2001). However, recent research by Mumtaz and Yoshino (2021) demonstrates that numerous IPOs that are underpriced during their initial offering reveal exceptional long-term performance. As a result, this phenomenon has the potential to offset the temporary reduction in wealth experienced by IPO issuers as a consequence of IPO underpricing. Conversely, the decision to pursue withdrawal carries substantial implications for stakeholders, as it necessitates expenditures related to accounting, underwriting, and legal matters, and is infrequently susceptible to reversal (Reiff and Tykvová 2021). The repercussions of withdrawing an IPO can have significant implications for a company’s financial liquidity, potential avenues for funding, market worth, and vulnerability to insolvency (Busaba et al. 2001). These consequences primarily arise from the erosion of the company’s corporate reputation or credibility (Qing 2011).
Companies that enlist the services of a Big 4 audit firm experience a comprehensive and impartial audit procedure, thereby enhancing the reliability and quality of their financial information (Gao et al. 2011; Meckfessel and Sellers 2017). Consequently, the hiring of the Big 4 auditing firms serves to diminish the perceived level of risk linked to the investment in the IPO, thereby improving investor assurance (De Franco et al. 2011; Feng et al. 2019). The inclusion of a reputable auditor can furnish potential investors with a sense of confidence regarding the accuracy and integrity of a company’s financial statements, ensuring their freedom from significant errors or misrepresentations (Jamaani and Alidarous 2022). Furthermore, the engagement of a prominent audit firm from the Big 4 can additionally function as a means of certification (Downar et al. 2021). Through establishing a professional affiliation with a distinguished auditor, the IPO firm effectively capitalizes on the auditor’s esteemed standing and conveys its dedication to adhering to rigorous auditing and reporting protocols (Elemes and Chen 2022). This strategy can effectively address the issue of adverse selection by establishing a distinct identity for the company in comparison to its competitors, thereby appealing to a broader range of prospective investors (Lee and Lee 2013).
In basic terms, the theory of signaling posits that the engagement of a Big 4 audit firm in the context of an IPO can effectively mitigate the risk of withdrawal by conveying the company’s superior quality, credibility, and unwavering dedication to transparency. The reputable standing and specialized knowledge possessed by the Big 4 accounting firms serve as reliable indicators for prospective investors, bolstering their trust in the accuracy and reliability of the financial information provided by IPO firms.

3.2. Hypothesis Development

According to the signaling theory, Big 4 auditing firms should possess superior audit quality since they are more concerned with reputation and possess greater independence than non-Big 4 auditors (DeAngelo 1981). Big 4 auditors are also increasingly concerned about lawsuits, having more to lose due to their vast coffers and the resources spent in creating their reputation (Palmrose 1988; Gao et al. 2011). Furthermore, Big 4 auditors are regarded as having greater efficiency because of their bigger size, which helps them to recruit and maintain higher-quality human resources (Simunic 1984; Zimmerman et al. 2021). Literature among publicly traded businesses indicates that Big 4 auditors deliver superior audit quality than non-Big 4 auditing firms (Becker et al. 1998; Lennox and Pittman 2011; Defond et al. 2018).
Given their extensive expertise in auditing, Big 4 auditors may be better at auditing IPOs. Big 4 auditors have substantial worldwide networks, advising practices, and numerous professional policy experts (Elemes and Chen 2022). This might help them discover audit modifications or foresee and react to SEC accounting comments. Big 4 auditing firms demand higher IPO audit fees than non-Big 4 auditors, allowing them to dedicate greater resources to IPO audits (Jacob et al. 2019). IPO lawsuit and reputational concerns also imply that Big 4 auditing firms are encouraged to deliver high-quality services (Lin et al. 2013). Since many nations have lawsuit risk acts, IPO auditors should have substantial litigation incentives. IPO audits provide large margins, the prospect of a long-term engagement with the IPO business, and accessibility to the IPO client, which might boost the auditor’s reputation (El-Rajabi and Gunasekaran 2006; Khlif and Samaha 2016; Harymawan 2020).
Research shows that Big 4 auditing firms charge more for IPOs (Beatty 1989; Jacob et al. 2019). Thus, auditing businesses’ reputations indicate quality, reducing asymmetric information among IPO company investors and owners (Sundarasen et al. 2018). Reliable audit organizations like the Big 4 reduce misunderstanding and ex ante ambiguity regarding the IPO’s prospectus’ accounting and financial details (Sundarasen et al. 2021). Investors see conservatively audited prospectuses as safer and seek less compensation for ex ante uncertainty risk (Simunic 1984; Gao et al. 2011; Meckfessel and Sellers 2017). This reduces the informational imbalance among IPO investors and founders (Wang and Song 2021). The market expects credible auditing companies to lower the likelihood of the prospectus being faked, reducing IPO failure risk (Beatty 1989).
IPO researchers back up empirical proof of a link between the signaling role of Big 4 auditing firms and IPO underpricing (Albring et al. 2007; Chang et al. 2008; Wang and Song 2021; Jamaani and Alidarous 2022). According to research, Big 4 auditors may provide several advantages to IPO businesses (Albring et al. 2007; De Franco et al. 2011; Wang and Song 2021). IPO firms with Big 4 auditors may offer higher-quality IPO audit services since they have a better grasp of a wider range of accounting issues because of their considerable experience auditing IPO companies (Jamaani and Alidarous 2022). The Big 4 auditors have vast global contacts, extensive advisory activities, and many past policy specialists (Elemes and Chen 2022). This knowledge may help them to detect audit revisions and foresee and respond to SEC accounting comments more correctly (Li and Liu 2017; Defond et al. 2018). Big 4 auditors also charge significant IPO audit fee premiums, which allows them to dedicate more resources to IPO audits than non-Big 4 auditors (Beatty 1989; Jacob et al. 2019). Furthermore, because of their considerable financial resources and substantial effort in developing their image, the Big 4 auditing companies have more to lose in a lawsuit (Khurana and Raman 2004; Law 2008; Habib et al. 2014). As a result, this study hypothesizes that Big 4 auditing firms may function as a quality signal of IPO quality, reducing IPO failure.
H1: 
IPOs audited by the Big 4 auditors have a decreased likelihood of failure.

4. Data and Methodology

The paper analyzes 33,500 failed and successful IPOs from January 1995 to December 2019 in 22 countries with different socioeconomic, regulatory, and cultural environments. The dataset comprises countries from the largest 20 economies, often referred to as the G20. The countries included in this study include Australia, Saudi Arabia, Turkey, Germany, China, France, Japan, Brazil, India, Canada, Italy, Mexico, Indonesia, Russia, the United Kingdom, South Africa, South Korea, and the United States. These countries were selected based on the availability of data. The selection of G20 economies is based on their provision of a substantial and varied dataset, which facilitates a thorough and complete analysis (Jamaani and Ahmed 2020; Jamaani and Alidarous 2022). Moreover, the conclusions drawn from these findings possess a higher degree of generalizability owing to the substantial number of IPOs listed within the G20 nations, which together account for nearly 81% of the worldwide IPO market (Jamaani and Ahmed 2022).
The data related to IPO prospectuses are secondary data obtained primarily from Bloomberg and Thomson Reuters databases. Real estate investment trusts, American depositary receipts, closed-end or mutual funds, special purpose businesses, and rights issues are excluded from our analysis, in line with previous studies on IPOs (Helbing et al. 2019; Jamaani and Ahmed 2021; Jamaani and Alidarous 2022). A cross-sectional probit regression model is utilized to investigate the influence of hiring the Big 4 auditing firms on IPO failure, building upon prior studies on IPO failure (Busaba et al. 2001; Dunbar and Foerster 2008; Qing 2011; Reiff and Tykvová 2021). Cross-sectional regression estimation is commonly used to analyze IPO failure or listing events for IPO firms. These events are typically unique and occur only once across countries, representing a one-time occurrence in a broader context.
A probit model is employed in this study due to the nature of the outcome variable. The dependent variable represents a categorical variable, where a value of 1 indicates failure of the IPO firm and a value of 0 indicates successful listing. Therefore, the use of probit regression, as suggested by Cappellari and Jenkins (2003), is more suitable for this analysis. Our study is primarily focused on a qualitative outcome. To conduct our analysis, we incorporate a dummy variable into our econometric model. This enables us to estimate the likelihood of the outcome (Y = 1) occurring. The probit function’s conditional probabilities display a nonlinear association with the independent variables (Horowitz and Savin 2001). Additionally, it is important to mention that a probit function demonstrates asymptotic behavior, gradually approaching 0 and 1 (Aldrich and Nelson 1984). Consequently, the predicted probabilities obtained from our probit function remain consistently appropriate. The main independent variable, the Big 4, is a categorical variable that indicates a value of 1 when the IPO firm at the time of offering hires one of the Big 4 and a value of 0 otherwise. Our basic model is presented in Equation (1):
P = Pr (yj = 1 xj) = x′β
F(x′β) equals x′β for the independent variables presented in Table 1. The cumulative distribution function for the standard normal distribution is F(x′β), as shown in Equation (2):
F x β = Φ x β = x β Φ Z d z
To determine the controlling variables for our study, we conducted a thorough literature review on IPO failure, as shown in Table 1. The table displays the range of IPO research findings, which aids in determining the optimal number of significant controlling variables to incorporate into our analysis. Given the limited data availability, especially in developing countries within the sample we used, our research has been executed on an international basis from 1995 to 2019. We have included firm accounting ratios, firm level-corporate governance, IPO firm-specific, IPO market-specific, and macroeconomic characteristics (Busaba et al. 2001; Dunbar and Foerster 2008; Qing 2011; Helbing 2019; Helbing et al. 2019; Reiff and Tykvová 2021). Table 1 provides explanations and reference measures for each parameter.

5. Empirical Findings

5.1. Statistical Outputs

Table 2 shows dataset descriptive statistics and correlation assessment. The first column of Table 2 also offers a descriptive analysis of the dataset analyzed. For example, the statistics show that the average IPO rate of failure for the sample is 15%, while the average proportion of Big 4 auditing firms recruited as companies prepare to go public is 19.10%. Furthermore, 3.50% and 22.70% of IPO founders sell their shares as secondary and primary shares, respectively. Almost 11% of IPOs are classed as technology businesses, while 16.50% are launched during stock market downturns. Moreover, the average listing duration time for our IPOs has been about 101 days, with underwriting costs averaging 23.80% of IPO proceeds. The table indicates that, on average, there have been 51 IPOs listed every year. Furthermore, it reveals that 39% of all IPOs have been issued during times characterized by severe market volatility. The also shows that the average number of independent directors in our sample is eight, with CEO duality occurring in just 5.30% of IPOs. At the time of listing, our dataset shows that the average interest rate is 10.30%, while the inflation rate is 2.60%. The average IPO proceeds are USD 108 million, with retail investors accounting for 94% of all IPOs. The presence of multicollinearity in the regressors is tested to be absent according to the variance inflation factor (VIF)2 test. Table 2 also displays the results of the Pearson correlation matrix, which captures the linear relationship between variables along with their corresponding significance levels. The table also shows that IPO failure risk decreases with Big 4 auditors, technology business type, IPO volume, hot markets, retail subscription, independent directors, IPO proceeds, interest rate, GDP growth, and CEO duality. IPO failure risk is positively correlated with primary and secondary share sales, integer offer price, IPO duration, stock market collapse, underwriting fees, inflation rate, FDI outflow, and return on common equity.
In Figure 1, Figure 2 and Figure 3, the percentage of Big 4 auditors and the number of failed IPOs are shown according to industry, year, and country. When it comes to IPOs, the consumer technology sector has the largest (smallest) percentage of failure, which is 28.90% (12.50%). On the other hand, the financial materials industry has the highest (lowest) share of Big 4 auditors, which is 29% (12.70%). The highest (lowest) reported presence of Big 4 auditors in 2019 (1996) was 32.50% (2.0%), whereas the greatest (lowest) failure rate for IPOs was 39.10% (1.1%) in 2014 (1995). South Korea (Poland) has the greatest (smallest) reported presence of Big 4 auditing firms at 43% (1.70%), while Russia (Japan) has the highest (smallest) IPO failure rate at 43% (2.11%).

5.2. Regression Results

Table 3 displays the results obtained by applying two different models, with Model 1 including just the variable that was investigated (Big 4 auditors). Model 2 gradually introduced more controlling variables to control for differences in industry, year, and country effects, in addition to company-, market-, accounting ratio-, macroeconomic-, and corporate governance-specific variables. This was completed in accordance with the IPO literature (Busaba et al. 2001; Jamaani and Alidarous 2022). The findings for the Big 4 variable, which investigates how the presence of Big 4 auditors influences the probability of IPO failure risk, are similar across all the models. The coefficient is statistically relevant when the significance threshold is set at 1%. (−0.40). This clearly shows that the presence of the Big 4 auditing firms lowers the risk of failure for IPOs by up to 40% throughout the entire IPO market. This supports the validity of our hypothesis.

5.3. Discussion

Our findings are consistent with prior research on the effect of Big 4, which found that the reputations of the Big 4 auditing businesses signal quality, hence lowering information asymmetries among IPO firm investors and owners (Lee and Lee 2013; Meckfessel and Sellers 2017; Sundarasen et al. 2018; Asthana et al. 2019; Lento and Yeung 2021; Sundarasen et al. 2021; Chen et al. 2022). Trustworthy audit organizations such as the Big 4 assist in eliminating confusion and ex ante uncertainty over the financial and accounting elements of an IPO’s prospectus (Beatty 1989; Sundarasen et al. 2018). Our findings support the signaling theory, which proposes that hiring a Big 4 audit firm in the context of an IPO may successfully reduce the risk of failure by communicating the business’s superior quality, trustworthiness, and unwavering commitment to transparency. Prospective investors’ confidence in the reliability and validity of the financial information offered by IPO companies is bolstered by the prestigious reputation and specialized expertise of the Big 4 accounting firms (Chen et al. 2005; Albring et al. 2007; Lee and Lee 2013; Alhadab and Clacher 2018; Westfall and Omer 2018). Based on the results of our research, it is evident that IPO investors perceive audited prospectuses prepared by the Big 4 firms as a safer option, despite occasional instances of fraud scandals. Consequently, these investors require less compensation for the inherent ex ante uncertainty associated with the IPO process (Jamaani and Alidarous 2022). This results in a reduction in the informational gap that exists between IPO investors and founders (Wang and Song 2021). Accordingly, one conclusion that may be drawn from our findings is that the IPO market expects reputable auditing businesses to reduce the possibility of the prospectus being falsified, thereby lowering the danger of an IPO failing. Big 4 auditors are superior in auditing IPOs due to the breadth and depth of their experience in auditing (Chen et al. 2022). The Big 4 auditing firms each have extensive global networks, consulting operations, and a large number of professional policy specialists (Elemes and Chen 2022). This in fact enables them to identify audit revisions or anticipate and respond to concerns made by the SEC about financial reporting (Defond et al. 2018; Cunningham and Leidner 2022). Research has confirmed that the Big 4 auditing firms charge more fees for IPO audits than auditors who are not part of the Big 4, which enables them to devote more resources to IPO audits (Beatty 1989; Jacob et al. 2019). The other explanation for the observed presence of the Big 4 auditors in the IPO market comes from IPO lawsuits and worries over reputation, which suggest that Big 4 auditing firms are driven to supply services of high quality (Palmrose 1988; Gao et al. 2011; Lin et al. 2013). Considering that many countries have laws protecting citizens from the threat of legal action, IPO auditors need to have considerable incentives to avoid litigation (Khlif and Samaha 2016). Large profit margins, the possibility of a long-term engagement with the IPO company, and accessibility to the IPO client are all benefits that come with conducting audits of IPOs, which may also help an auditor’s reputation (Beatty 1989; Jacob et al. 2019). As a consequence of this, the Big 4 firms do in fact serve as a quality signaling indicator of IPO quality, which helps to reduce the number of failed IPOs.

6. Sensitivity Checks

6.1. The Difference in Market Maturity, Accounting Profession, Business Ethics, Legal System, and Cultural Environments

Research contends that the institutional environment of a nation might influence the function of intermediaries in stock markets (Aggarwal and Goodell 2009; Jamaani and Ahmed 2021; Jamaani and Alidarous 2021; Jamaani and Ahmed 2022; Jamaani et al. 2022). Scholars claim that the projected impact of prominent intermediaries, such as the Big 4 auditing firms, on the price and survivability of IPOs may vary depending on market maturity, accounting profession, legal system, and cultural setting (Choi et al. 2008; Mokoaleli-Mokoteli and Iatridis 2017; Jamaani and Alidarous 2022). For instance, Hopp and Dreher (2013), Jamaani and Ahmed (2021), Jamaani and Alidarous (2022), and Sundarasen et al. (2021) assert that nations with feeble (robust) market maturity, accounting profession, business ethics, legal system, and cultural environments have less (more) mature investors and equity markets, lower (greater) firm rules and adherence, poorer (harsher) investor protection and legal frameworks, and further (fewer) state interventions. Consequently, prominent intermediaries such as the Big 4 may benefit at the cost of their IPO owners by taking advantage of the low degree of market maturity, accounting profession, legal system, and cultural milieu in such nations. The level of market maturity is captured using three proxies including spilling the data across developed and developing equity markets, across large and small financing through local equity markets, and strong and weak enforcement of security market regulations (Jamaani and Ahmed 2020). The level of the accounting profession (business ethics) is also captured by spilling our dataset across countries with strong and weak strength of auditing and reporting standards (ethical behavior of firms) (Jamaani and Alidarous 2021; Jamaani et al. 2022). Differences in legal systems are captured by splitting our population between countries with weak and strong rules of law and countries with and with low country-level transparency (Jamaani and Ahmed 2021). Finally, the difference in cultural environments is captured using the financial secrecy index developed by Gray in 1988 (Jamaani 2021; Jamaani et al. 2021). Models 3–18 in Table 4 report consistent results confirming the positive signaling role of the presence of the Big 4 auditors in providing comforting signals to the IPO market, resulting in lowering the problem of information asymmetry between participants in IPOs and, in turn, lowering the probability of IPO failure risk by up to 42%. We find consistency across our results, showing that Big 4 auditors indeed provide a stronger economic impact on the success of IPO firms in countries with better market maturity, accounting profession, business ethics, and legal systems. For example, Big 4 auditors managed to reduce the possibility of IPO failure by 38% (30%) in developed (developing) market economies, by 42% (30%) in countries where financing through local equity markets is strong (weak), by 40% (29%) in countries with strong (weak) auditing and reporting standards, by 36% (32%) in countries with strong (weak) ethical behaviors of firms, and by 38% (32%) in countries with strong (weak) rules of law.
These findings are also in agreement with prior research indicating that in nations with strong market maturity, the accounting profession, corporate ethics, and rule of law, the lawsuit risk associated with fraudulent intermediary operations is substantial (Hughes and Thakor 1992; Lowry and Shu 2002; Liao et al. 2014). Hope (2003) and Fan and Wong (2005), for instance, provide evidence corroborating the relationship between asymmetric information issues, inadequate disclosure standards, and lower audit quality in nations with a high lawsuit risk. Lawrence et al. (2011) and Cheong and Zurbruegg (2016) discover evidence that the Big 4’s auditing quality can thrive better in nations with strong auditing and reporting standards and robust legal frameworks. The cultural proxy, financial secrecy, is significant in strong and low cultural secrecy countries, yet its impact of the presence of Big 4 on the failure risk of IPO firms is slightly stronger (40%) in high financial secrecy countries than in low (37%) financial secrecy nations. This slight difference may be attributable to the tolerance of IPO participants for unequal knowledge and power (Jamaani and Ahmed 2022) as well as the significant signaling function of the Big 4 auditing companies in countries where cultural secrecy is the default. IPO participants in such societies are likely to be aware that IPOs audited by the Big 4 companies are more transparent and that the Big 4 abstain from making absurd opinion remarks about the quality of IPO prospectuses that might undermine their market reputation and investor wealth.

6.2. Additional Robustness Tests

Additional tests are undertaken by dividing the data into subsets such as high- and low-volatility market periods, IPOs supported by venture capital versus those without, prestigious versus non-prestigious underwriters, IFRS adopters versus those who have not adopted IFRS, and technology versus non-technology companies following prior IPO research (Jamaani and Ahmed 2021; Jamaani and Alidarous 2022; Jamaani et al. 2022). We also consider the issue of clustering of standard errors across years, sectors, and nations, all of which are known to impact empirical findings, following Jamaani and Ahmed (2020). In line with IPO studies, we use the 2SLS estimate to control for any endogeneity in the relationship between secondary share sales and the employment of the Big 4 accounting firms (Boulton et al. 2010; Humayun Kabir et al. 2011). Research on IPOs has shown that the more secondary shares the IPO owners anticipate selling at the time of the offering, the more concerned they become about the IPO listing being successful, and the more they seek to employ prestigious intermediaries like the Big 4 to guarantee the IPO’s listing (Habib and Ljungqvist 2001; Jamaani and Ahmed 2020). Models 19–32 in Table 5 all agree that IPO investors interpret the presence of the Big 4 auditors in IPO prospectuses as a quality signal, which decreases information asymmetry in the IPO market and, in turn, lowers the likelihood of the IPO failing by up to 67%.

7. Conclusions

The auditing and finance literature does not provide a complete explanation for why businesses are unable to obtain public funding and instead decide to cancel their first public offerings. Underwriting, auditing, and legal costs are high, and once an IPO founder takes this decision, there is typically no turning back. IPO issuers have a critical duty to discover methods to reduce IPO failure risk because of the significant impact an IPO failure has on the growth prospects and survival of IPO enterprises. Credible signals, such as the involvement of the Big 4 auditing firms, are hypothesized to expose underappreciated issuer qualities, hence lowering the information asymmetry and the associated IPO failure risk, according to the signaling theory. Big 4 auditors are better at auditing IPOs owing to their extensive expertise. The Big 4 auditing companies have worldwide networks, consultancy activities, and many policy professionals. This helps them spot audit modifications and predict local SEC financial reporting difficulties. The Big 4 auditing firms may dedicate more resources to IPO audits because they demand more fees than other auditors. IPO litigation and reputation concerns suggest that Big 4 auditors are pushed to provide high-quality services, which might explain their participation in the IPO market.
We analyzed a huge dataset of failed and successful IPOs from January 1995 to December 2019 to investigate the impact of Big 4 auditors on IPO failure probability. This study is built on the outstanding work of Firth and Liau-Tan (1998), Busaba et al. (2001), Chang et al. (2008), De Franco et al. (2011), Defond et al. (2018), and Reiff and Tykvová (2021) in exploring the link between the function of Big 4 auditors in the IPO market. They all ignored the probable link between the signaling role of the Big 4 auditors and the risk of IPO failure. Furthermore, we collect substantial evidence demonstrating that the involvement of the Big 4 auditors in IPO prospectuses as a quality signal reduces information asymmetry in the IPO market, lowering the risk of the IPO failing in the worldwide IPO market.
The findings of our study indicate that IPO investors tend to see audited prospectuses generated by the Big 4 corporations as a more secure choice, notwithstanding infrequent occurrences of fraud incidents. We discover that the Big 4 auditors are successful in delivering reassuring signals to the IPO market, minimizing the issue of information asymmetry between IPO participants, which reduces the likelihood of IPO failure by up to 67%, despite the frequent occurrences of audit fraud scandals. Big 4 auditors audit IPOs better owing to their extensive auditing expertise. This helps them spot audit amendments and respond effectively to stock market regulators’ comments on financial reporting difficulties. The Big 4 auditing firms can dedicate more attention to IPO audits because they demand higher rates than other auditors. IPO litigation and reputation considerations show that Big 4 auditors are pushed to provide high-quality services, which might explain their participation in the IPO market. IPO auditors have strong incentives to avoid lawsuits since many nations have laws shielding people from legal action. Auditing IPOs may boost an auditor’s reputation due to high profit margins, the likelihood of a long-term relationship with the IPO business, and client accessibility. The Big 4 auditing firms serve as reliable indicators of quality for IPO firms, thereby mitigating the occurrence of IPO failures.
The study’s results, which suggest that using Big 4 audit firms decreases the likelihood of IPO failure, provide a substantial contribution to research on signaling theory in several aspects. The paper offers concrete evidence that supports the signaling theory in the context of IPOs. The research confirms the notion that businesses use signals to communicate information about their quality and prospects to prospective investors by establishing a connection between selecting a Big 4 auditor and a decreased likelihood of IPO failure. Furthermore, the research emphasizes the efficacy of the signal sent via the engagement of a Big 4 audit firm. Investors interpret the selection of a recognized auditor as an indication of the company’s high quality, transparency, and dedication to solid financial processes. This research enhances our comprehension of how signals impact investor perceptions and behavior inside the IPO market. Furthermore, the research elucidates the influence of signals on risk perception specifically within the setting of IPOs. The research establishes that using a Big 4 auditor lowers the likelihood of IPO failure, consequently indicating that signals may aid in alleviating perceived risks linked to investing in recently listed firms. This observation may provide valuable guidance for future studies on the impact of various signals on risk perceptions in financial markets. Furthermore, this research enhances our comprehension of the market dynamics that revolve around IPOs. This paper illustrates how signals, such as the selection of an auditor, may impact investor confidence, and market perception, and eventually decide the outcome of an IPO. Having this comprehension is essential for firms, investors, regulators, and academics who want to navigate and comprehend the intricacies of the IPO market. This study’s conclusions may have significant ramifications for legislative choices concerning auditing standards, disclosure requirements, and investor protection in the context of IPOs. Analyzing the influence of indicators such as the selection of an auditor may assist policymakers in formulating policies that enhance openness, market effectiveness, and investor trust in the IPO process.
This study is limited to examining the effect of employing the Big 4 audit firms on IPO failure. However, in the field of IPO studies, the effect of employing a Big 4 audit firm on the duration of an IPO listing could be a fruitful area for future research. The period from the date of an IPO to the date of its listing is commonly known as the “IPO waiting period,” according to IPO research (Brooks et al. 2009). When the IPO prospectus is filed, information about the company’s financial strategy, products, and services becomes widely known (Colaco et al. 2018). As a result, a brief IPO waiting period is crucial for a new company. Extended delays in an organization’s IPO may heighten the risk that its competitors will siphon off the capital that the IPO was intended to secure, potentially increasing the probability of IPO withdrawal. Thus, future research could compare the listing durations of firms that retained the Big 4 audit firms to those that did not. This may serve as a further development of the noteworthy research conducted by Guo and Brooks (2009), Colaco et al. (2018), and Mumtaz and Smith (2021). An analysis of the impact that the selection of an auditor has on this time period may yield valuable insights regarding the effectiveness of the IPO procedure, the reception of the company in the market, and its performance after the IPO (Hogan 1997; Albring et al. 2007; De Franco et al. 2011; Alhadab and Clacher 2018). Further research is warranted to determine how the auditor’s selection of a company influences investors’ perceptions of the firm and how this perception affects the listing period. Organizations that retain the services of a Big 4 audit firm might receive a more positive reception from investors, resulting in expedited market integration and reduced listing periods (Alhadab and Clacher 2018; Colaco et al. 2018). Gaining insight into investor behavior regarding audit firm selections can be highly beneficial for companies strategizing to initiate the public offering process. Organizations that maintain shortened listing durations may potentially benefit from more seamless transitions, more favorable market reception, and enhanced long-term performance. This aspect holds significant importance for policymakers, investors, and analysts who are keen on observing the results of IPOs. The potential consequences of further investigation regarding the influence of auditor selection on the length of time an IPO remains on the market may be of interest to regulatory agencies that supervise the IPO procedure. A comprehension of the impact that audit firm selection has on the duration of an IPO’s listing can provide valuable insights for deliberations surrounding audit quality, disclosure obligations, and investor protection strategies.

Funding

This research was funded by Taif university, Saudi Arabia. The author extends her appreciation to Taif University, Saudi Arabia, for supporting this research.

Data Availability Statement

Data is available upon request from the corresponding author.

Conflicts of Interest

The author reports no potential conflicts of interest.

Notes

1
Existing literature suggests that managers of IPOs tend to exaggerate pre-IPO profits in order to maximize the value of the IPO (Teoh et al. 1998). However, Ball and Shivakumar (2008) find that the ability of top management in IPO firms to manipulate earnings during the pre-IPO period is limited due to the significant legal risks associated with artificially inflating earnings and the heightened scrutiny from various market monitoring entities such as auditors, boards, underwriting banks, the press, analysts, and other parties involved in the deal.
2
In addition, we use the VIF test to verify the absence of multicollinearity in our utilized models. Cazavan-Jeny and Jeanjean (2007) and Premti and Smith (2020) demonstrate that a mean VIF value below 5 for a regression model indicates the absence of multicollinearity among independent variables. The mean VIF test for each model is presented in the last step of empirical testing. Each of these models has a mean VIF value that is below the threshold of 5, suggesting the lack of multicollinearity issues in our models.
3
According to Morgan Stanley Capital International (2020), capital markets are categorized into two classifications: developing and developed. The latter exhibits more developed capital markets. According to scholarly investigations, it has been found that developing equity markets exhibit inefficient market allocation of resources, less robust regulations, significant volatility, limited diversity in financial markets, and significant disparities in information (Jamaani and Alidarous 2022). Developed economies consist of a range of countries, such as the United States, Australia, Canada, Denmark, France, Germany, Japan, Greece, the United Kingdom, South Africa, Italy, and Sweden. The group of developing nations includes Saudi Arabia, South Korea, Brazil, China, India, Indonesia, Mexico Poland, Turkey, and Russia.
4
We use a 1995–2019 time series index to evaluate securities law enforcement (Global Competitiveness Report 2019). The index examines yearly developments in securities exchange regulation worldwide. The grade goes from 0 to 7 for securities regulation enforcement (Global Competitiveness Report 2019). Population-wide securities regulatory enforcement averages 4.95. High (low) enforcement is when a nation’s enforcement rating is over 4.95. The US, Germany, Canada, Japan, France, South Africa, the UK, Australia, and Sweden have high enforcement regulations. Italy, Greece, Brazil, South Korea, India, China, Brazil, Poland, Mexico, Russia, Turkey, Indonesia, and Saudi Arabia have law enforcement.
5
It is a series of data points that spans the years 1995–2019 and is based on the weighted average of poll results relevant to the question presented to accountants. How stringent are your country’s financial auditing and reporting standards? [1 represents severe inferiority; 7 represents great strength] (Global Competitiveness Report 2019). A high (low) Auditing Reporting score is one that is higher (lower) than the sample mean.
6
It shows the market’s financial capability and measures listed businesses’ local equity availability annually (Global Competitiveness Report 2019). It assesses organizations’ capacity to raise cash by selling stock and bonds from 1995 to 2019. Scores above (below) the population’s mean indicate large (small) finance markets.
7
The ethical behavior of businesses is a 1995–2019 series composed of the weighted average of opinion surveys answering the following question: How would you assess an organization’s corporate ethics in your country (ethical relationships with government officials, political leaders, and other businesses)? [1 = extremely poor—among the world’s lowest; 7 = excellent—among the best] (Global Competitiveness Report 2019). A value that is above (below) the population’s mean indicates strong (poor) ethical behavior.
8
The average of the weighted scoring outcomes of a survey was used to calculate the transparency of government policymaking from 1995 to 2019. How easy is it for corporations in your country to acquire information about modifications to laws that affect them? 1 = very difficult; 7 = very easy (Global Competitiveness Report 2019). Transparency of government policymaking is strong (weak) when values are above (below) the population mean.
9
This time series index, which covers the years 1995 through 2019, gauges how much individuals believe and follow social rules that protect property rights, enforce contracts, and prevent crime and violence (Jamaani and Alidarous 2022). A rule of law that is higher (weak) than the sample mean.
10
A method developed by Gray and Vint (1995) determines our financial secrecy grade. The calculation for financial secrecy is uncertainty avoidance + power distance − individuality. When a nation’s cultural secrecy value is high, it is thought that its financial secrecy is high, and the reverse is true. The dataset’s cultural secrecy average is 44. Financial secrecy is high (low) if a nation’s score is over (below) 44. The United States of America, Germany, Sweden, South Africa, the UK, Canada, and Australia have minimal financial secrecy. Financially secretive countries include Brazil, Japan, South Korea, France, Italy, Poland, Mexico, Indonesia, Greece, Turkey, China, Saudi Arabia, and Russia. Hofstede (2001) defines an oligarchy as a nation with a major power gap dominated by a few. Hofstede (2001) defines a risk-averse nation as one that avoids uncertainty and risk. Hofstede (2001) characterizes strong individualism as a culture where individuals prioritize their freedom, overlook the common good, and respect family less.
11
The metric in question is the standard deviation of stock exchange returns calculated 15 days before the first trading day (Jamaani et al. 2022). High (low) volatility is denoted by a score that is greater than (less than) the sample mean.
12
Models 21 and 22 separate IPOs sponsored by prominent and non-prestigious underwriters. Employing a rating system developed by Carter and Manaster (1990), we reproduce the binary variable renowned underwriter from IPO literature. If an underwriter firm is one of the top 100 globally licensed underwriters by BD market share, it is one (Jamaani and Alidarous 2022). Otherwise, it is zero.
13
If the firm is classified as technological during the offering, the dummy variable is one. Otherwise, it is zero. We classify software and hardware, specialty chemical substances, complex electronics, healthcare devices, technologies for communication, medications, and biotechnology enterprises using (Jamaani and Alidarous 2022)’s method.
14
The dummy variable is equal to a value of one when the business adopts the use of International Financial Reporting Standards (IFRS) during the offering and zero otherwise.
15
The binary variable takes on a value of one if the company receives financial support from venture capital companies during the public offering and zero if it does not.

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Figure 1. Distributions of average values by industry.
Figure 1. Distributions of average values by industry.
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Figure 2. Distributions of average values by years.
Figure 2. Distributions of average values by years.
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Figure 3. Distributions of average values by countries.
Figure 3. Distributions of average values by countries.
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Table 1. Definitions of variables.
Table 1. Definitions of variables.
VariablesDescriptionReference for Related LiteratureSource of Data
Dependent variable
FIPOThe outcome variable is the failed IPO (FIPO), which is one if the IPO company withdraws and zero if it lists. Bloomberg Database (BD)
Main variable
Big 4 The Big 4 firms are the key independent variable, which has a value of one if the IPO company hires one of the biggest and most prominent four auditing firms (Deloitte, PricewaterhouseCoopers, Ernst & Young, and KPMG) during the offering and zero otherwise. BD
Controlling variables
IPO firm accounting ratio variables
PROPRO is the total dividends given to shareholders divided by the net revenue ratio.Busaba et al. (2001)BD
LEVLEV is a firm’s equity-to-liabilities ratio.Busaba et al. (2001)BD
PERPER is a firm’s common equity return ratio. Busaba et al. (2001)BD
Corporate governance variables
CEOD CEOD represents COE duality and has a value of zero when the IPO firm’s Chef Operational Officer (CEO) is also the chairman at the time of offering and one otherwise.Boeh and Southam (2011), Helbing et al. (2019), and Reiff and Tykvová (2021)BD
IDID reflects the IPO firm’s number of independent directors at offering.Boeh and Southam (2011)BD
IPO firm-specific variables
TT is a categorical variable that is one if the IPO company is a technology firm and zero otherwise.Dunbar and Foerster (2008), Qing (2011), and Helbing et al. (2019)BD
SECSEC indicates the proportion of secondary shares IPO owners offered at offering.Qing (2011) and Helbing et al. (2019)BD
PRIPRI shows IPO owners’ primary shares offered at offering.Qing (2011) and Helbing et al. (2019)BD
INTG INTG is a binary variable that is one if the IPO firm’s offer price is an integer and zero otherwise.Jamaani and Alawadhi (2023)BD
DURDUR represents the time between the offering announcement and the IPO businesses’ withdrawal or listing.Jamaani and Alawadhi (2023)BD
SIZESIZE shows offering proceeds.Dunbar (1998) and Qing (2011)BD
FEES FEES is the underwriting fee percentage of proceeds.Jamaani and Alidarous (2024b)BD
RETAILRetail is the ratio of retail investments to overall IPO investments at offer time.Jamaani and Alidarous (2024a)BD
IPO market-specific variables
Hot Hot is 1 if an IPO launches in an above-average listing year and 0 otherwise.Qing (2011) and Boeh and Southam (2011)The World Bank (TWB)
VOLVol is the ratio of annual IPOs in each sample nation.Dunbar and Foerster (2008)TWB
VOLAVOLA measures pre-IPO stock market volatility by measuring each stock market’s standard deviation 15 days before the IPO.Qing (2011), Helbing et al. (2019), and Reiff and Tykvová (2021)Calculated using DataStream
Macroeconomic variables
INTINT is the average governmental rate of interest charged to local and international firms from 1995 to 2019. It includes securities, long-term mortgage loans, and other treasury instruments.Helbing et al. (2019) and Jamaani and Alidarous (2024a)TWB
GDPThe 1995–2019 Gross Domestic Product (GDP) time series index shows GDP per capita growth for each country in the group being studied.Jamaani and Alidarous (2024a)TWB
INFLINFL is the average annual inflation rate for each nation from 1995 through 2019.Helbing et al. (2019) and Jamaani and Alidarous (2024a)TWB
FDIThe 1995–2019 FDI time series index gauges net foreign investment inflows as a percentage of GDP.Helbing et al. (2019) and Jamaani and Alidarous (2024a)TWB
DummiesThis binary variable controls for year, country, and industry impacts.Jamaani and Alidarous (2024a)Self-constructed variable
Table 2. Descriptive statistics and Pearson correlation matrix.
Table 2. Descriptive statistics and Pearson correlation matrix.
ValuesAverage Statistical ValuesFIPOBig4PROLEVPERCEODIDTPRISECINTGDURSIZEFEESRETAILVOLHotVOLAINTGDPINFLFDI
FIPO0.151.00
Big40.19−0.02 ***1.00
PRO−0.01−0.02 ***0.01 *1.00
LEV0.040.010.010.011.00
PER−0.050.010.01 **0.010.011.00
CEOD 0.05−0.08 ***0.07 ***0.010.010.011.00
ID8.35−0.10 ***0.14 ***0.01 **0.010.010.36 ***1.00
T0.11−0.02 ***0.01−0.01−0.02 ***0.010.01−0.011.00
PRI0.230.06 ***0.07 ***−0.010.010.01 **0.02 ***0.05 ***0.03 ***1.00
SEC0.040.09 ***0.17 ***−0.010.010.000.05 ***0.09 ***0.08 ***0.39 ***1.00
INTG 0.690.21 ***0.08 ***0.01 *0.010.010.06 ***0.02 ***0.06 ***0.19 ***0.39 ***1.00
DUR101.410.24 ***0.04 ***0.010.010.01−0.03 ***−0.01 **−0.03 ***0.06 ***0.010.03 ***1.00
SIZE108.04−0.01 **0.12 ***0.010.010.01 *0.04 ***0.11 ***−0.04 ***0.03 ***0.03 ***0.08 ***0.39 ***1.00
FEES 0.240.09 ***0.13 ***0.010.010.01−0.010.09 ***−0.01 **−0.03 ***0.17 ***0.06 ***0.19 ***0.39 ***1.00
RETAIL0.94−0.06 ***−0.05 ***0.010.010.01−0.03 ***−0.05 ***−0.01 **−0.02 ***−0.11 ***−0.03 ***0.06 ***0.01−0.09 ***1.00
VOL50.95−0.14 ***−0.12 ***0.01−0.02 ***0.010.01−0.04 ***−0.03 ***−0.08 ***−0.26 ***−0.04 ***0.03 ***0.03 ***−0.19 ***0.011.00
Hot 0.39−0.08 ***0.010.010.01−0.010.03 ***0.04 ***−0.02 ***−0.03 ***0.06 ***−0.01 **−0.03 ***0.17 ***−0.03 ***−0.07 ***0.01 **1.00
VOLA0.170.08 ***0.05 ***0.010.010.010.04 ***0.010.04 ***0.04 ***0.06 ***0.01 **0.27 ***0.03 ***−0.18 ***0.09 ***0.20 ***−0.13 ***1.00
INT0.110.010.02 ***0.010.010.010.10 ***0.04 ***0.04 ***0.09 ***0.43 ***−0.01 **−0.02 ***−0.11 ***−0.02 ***0.18 ***−0.01−0.09 ***−0.04 ***1.00
GDP0.04−0.02 ***−0.10 ***0.01 **0.010.01−0.04 ***0.01 **−0.04 ***−0.08 ***−0.38 ***−0.03 ***−0.08 ***−0.26 ***−0.25 ***−0.04 ***−0.03 ***−0.19 ***0.17 ***0.06 ***1.00
INFL0.030.05 **−0.05 **0.010.010.01−0.09 ***0.01−0.03 ***−0.12 ***−0.08 ***−0.02 ***−0.03 ***0.06 ***−0.03 ***−0.18 ***0.01−0.03 ***0.06 ***−0.11 ***0.18 ***1.00
FDI0.020.02 ***−0.05 ***0.010.010.01−0.12 ***−0.01 **−0.04 ***−0.11 ***−0.23 ***0.04 ***0.09 ***0.40 ***0.03 ***−0.12 ***0.01−0.02 ***−0.03 ***−0.15 ***−0.12 ***0.06 ***1.00
Robust T-statistics results indicate that the p-values are *** p < 0.01, ** p < 0.05, and * p < 0.1.
Table 3. Main regression results.
Table 3. Main regression results.
VariablesModel 1Model 2
Main variable
Big4−0.310 ***−0.400 ***
[−12.9][−14.1]
IPO firm accounting ratio variables
PRO 0.010
[0.97]
LEV 0.001
[1.10]
PER −0.010
[−0.19]
Corporate Governance variables
CEOD −0.630 ***
[−8.37]
ID −0.010 ***
[−15.6]
IPO firm-specific variables
T −0.340 ***
[−9.26]
SEC 0.022 ***
[4.40]
PRI 0.021 ***
[9.78]
INTG 0.012 ***
[35.2]
DUR 0.003 ***
[12.6]
SIZE 0.010
[0.18]
FEES 0.011 ***
[15.4]
RETAIL −0.650 ***
[−2.68]
IPO market-specific variables
HOT 0.140 ***
[6.06]
VOL −0.001 ***
[−19.1]
VOLA 0.440 ***
[15.3]
Macroeconomic variables
INT −0.012 ***
[−5.62]
GDP −0.012 **
[−2.28]
INFL 0.042 ***
[7.98]
FDI 0.050 ***
[7.59]
Industry dummy YESYES
Year dummyYESYES
Country dummyYESYES
Constant−2.13 ***−3.71 ***
[−70.7][−54.6]
Observations33,53633,535
R squared 0.200.0630.29
Mean VIF value for each model1.21.9
Robust Z-statistics were modified to account for heteroscedasticity, and the results indicate that the p-values are *** p < 0.01 and ** p < 0.05.
Table 4. Sensitivity tests.
Table 4. Sensitivity tests.
Variables Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9 Model 10 Model 11 Model 12 Model 13 Model 14 Model 15 Model 16 Model 17 Model 18
Developing Markets3 Developed Markets High Enforcement of Securities4 Low Enforcement of Securities High Auditing Reporting5 Low Auditing Reporting High Financing through Local Equity6 Low Financing through Local Equity High Ethical Behavior7 Low Ethical Behavior High Transparency of Policymaking8 Low Transparency of Policymaking High Rule of Law9 Low Rule of Law High Secrecy10 Low Secrecy
Main variable
Big4−0.300 ***−0.380 ***−0.420 ***−0.310 ***−0.400 ***−0.290 ***−0.420 ***−0.300 ***−0.360 ***−0.320 ***−0.390 ***−0.300 ***−0.380 ***−0.350 ***−0.400 ***−0.370 ***
[−4.44][−11.6][−12.0][−5.39][−12.3][−5.92][−11.9][−5.75][−9.91][−6.79][−11.8][−4.80][−11.7][−5.45][−6.93][−10.9]
IPO firm accounting ratio variables
PRO−0.0100.0100.0100.0100.0100.0100.0100.0100.0100.001 **0.0100.0100.0100.010 ***0.0100.010
[−0.49][0.99][0.79][0.76][1.05][0.90][0.78][0.75][0.59][2.41][1.10][1.15][1.06][3.83][1.93][1.07]
LEV−0.053 ***0.0010.001−0.035 ***0.001−0.041 ***0.001−0.030 ***0.001−0.032 ***0.001−0.041 ***0.001−0.053 ***0.0010.001 *
[−3.26][0.49][0.27][−3.13][0.44][−3.74][0.38][−2.62][0.40][−2.90][0.30][−3.17][0.24][−3.45][0.28][1.69]
PER0.004 ***−0.010−0.0100.004 ***−0.010−0.001 **−0.0100.004 ***0.001−0.001 **−0.0100.004 ***−0.0010.004 ***0.002 ***−0.001
[4.86][−0.32][−0.40][3.02][−0.25][−2.31][−0.54][3.91][1.31][−2.16][−0.34][4.64][−0.31][4.84][4.05][−0.34]
Corporate governance variables
CEOD−0.620 ***−0.600 ***−0.550 ***−0.790 ***−0.610 ***−0.790 ***−0.430 ***−0.770 ***−0.540 ***−0.620 ***−0.530 ***−0.760 ***−0.580 ***−0.610 ***−0.500 ***−0.710 ***
[−4.13][−6.79][−5.36][−6.83][−6.68][−7.06][−4.21][−6.82][−5.29][−4.78][−5.77][−5.38][−6.30][−3.97][−4.65][−6.48]
ID−0.011 ***−0.010 ***−0.011 ***−0.007 ***−0.009 ***−0.008 ***−0.013 ***−0.006 ***−0.009 ***−0.012 ***−0.010 ***−0.011 ***−0.010 ***−0.012 ***−0.012 ***−0.010 ***
[−6.29][−14.7][−14.2][−5.86][−14.1][−7.35][−14.9][−5.77][−12.2][−10.4][−14.4][−7.37][−14.5][−7.06][−7.29][−14.8]
IPO firm-specific variables
T−0.340 ***−0.330 ***−0.300 ***−0.380 ***−0.290 ***−0.380 ***−0.290 ***−0.390 ***−0.260 ***−0.380 ***−0.270 ***−0.400 ***−0.270 ***−0.400 ***−0.440 ***−0.240 ***
[−4.57][−7.51][−6.84][−5.37][−6.73][−5.87][−6.30][−5.94][−5.61][−5.97][−6.10][−5.74][−6.03][−5.70][−7.11][−5.16]
SEC0.4100.029 ***−0.5400.029 ***0.7500.040 ***0.015 **0.037 ***−0.7000.041 ***0.019 ***0.030 ***0.019 ***0.028 ***0.029 ***0.011 *
[0.29][5.41][−0.89][3.50][1.21][5.69][2.03][5.05][−0.95][5.94][2.86][3.81][3.04][3.77][3.85][1.65]
PRI0.023 **0.017 ***0.011 ***0.026 ***0.013 ***0.033 ***0.012 ***0.027 ***0.013 ***0.037 ***0.021 ***0.030 ***0.021 ***0.023 ***0.011 ***0.019 ***
[2.44][6.91][5.01][4.45][6.10][7.24][4.64][6.85][4.40][8.53][7.99][6.28][7.75][4.50][2.58][6.96]
INTG0.016 ***0.900 ***0.910 ***0.017 ***0.870 ***0.016 ***0.890 ***0.015 ***0.830 ***0.015 ***0.830 ***0.016 ***0.850 ***0.016 ***0.015 ***0.860 ***
[18.6][22.8][23.5][18.9][23.0][20.8][21.2][24.5][19.5][21.4][20.8][20.0][21.1][20.7][20.8][20.1]
DUR0.002 ***0.003 ***0.004 ***0.002 ***0.003 ***0.002 ***0.004 ***0.002 ***0.004 ***0.002 ***0.004 ***0.002 ***0.004 ***0.002 ***0.002 ***0.004 ***
[9.46][6.79][10.1][9.04][9.75][10.6][8.98][10.1][9.08][11.2][9.63][10.3][10.7][10.0][10.4][8.46]
SIZE−0.0010.0010.0100.0010.0010.001−0.0010.0010.0010.0010.001−0.0010.001−0.001−0.001 *0.001
[−1.12][0.58][0.096][1.20][0.44][0.84][−0.058][0.46][0.19][0.67][0.74][−0.85][0.46][−0.63][−1.66][1.01]
FEES0.860 ***0.990 ***0.013 ***0.850 ***0.011 ***0.950 ***0.013 ***0.011 ***0.710 ***0.990 ***0.012 ***0.810 ***0.011 ***0.710 ***0.1600.011 ***
[3.82][12.4][16.4][3.03][15.3][5.22][15.4][6.34][7.58][5.93][15.1][4.14][13.4][3.36][0.73][13.3]
RETAIL−0.650 ***−0.011 ***−0.480 **−0.032 ***−0.370 **−0.650 ***−0.012 ***−0.650 ***−0.010 **−0.670 ***−0.011 ***−0.650 ***−0.011 ***−0.650 ***−0.640 ***−0.012 ***
[−2.61][−3.25][−2.45][−2.96][−2.25][−2.62][−3.59][−2.61][−2.44][−2.66][−3.26][−2.62][−3.28][−2.62][−2.58][−3.13]
IPO market-specific variables
HOT−0.0660.210 ***0.190 ***0.0410.140 ***−0.0640.270 ***−0.078 *0.240 ***−0.0290.170 ***0.0470.180 ***0.0090.089 **0.120 ***
[−1.29][7.91][6.93][0.74][5.23][−1.45][9.44][−1.83][8.50][−0.61][6.30][0.95][6.44][0.19][2.20][4.06]
VOL−0.001 ***−0.000 ***−0.001 ***−0.003 ***−0.001 ***−0.001 ***−0.001 ***−0.001 ***−0.002 ***−0.001 ***−0.001 ***−0.002 ***−0.001 ***−0.001 ***−0.001 ***−0.001 ***
[−7.35][−13.3][−14.1][−8.62][−15.4][−7.85][−13.9][−8.50][−16.8][−7.34][−14.5][−8.43][−14.0][−7.69][−8.22][−13.7]
VOLA0.370 ***0.480 ***0.350 ***0.610 ***0.330 ***0.470 ***0.350 ***0.540 ***0.290 ***0.440 ***0.360 ***0.500 ***0.370 ***0.480 ***0.480 ***0.390 ***
[6.94][12.5][9.34][10.4][8.89][9.26][8.55][10.5][7.12][9.06][9.02][10.0][9.29][9.72][11.3][8.64]
Macroeconomic variables
INT−0.006 **−0.043 ***−0.006 *0.003−0.018 ***−0.003−0.017 ***−0.002−0.043 ***0.001−0.051 ***−0.004−0.056 ***−0.003−0.008 ***−0.052 ***
[−2.01][−8.70][−1.76][0.70][−5.19][−1.17][−4.06][−0.57][−8.61][0.30][−10.00][−1.50][−10.4][−1.00][−2.89][−8.37]
GDP−0.026 **−0.038 ***−0.077 ***0.001−0.070 ***−0.030 ***−0.053 ***−0.042 ***−0.062 ***−0.034 ***−0.061 ***−0.035 ***−0.053 ***−0.042 ***−0.012−0.055 ***
[−2.35][−3.19][−7.35][0.11][−7.35][−3.06][−4.14][−5.49][−5.22][−3.49][−5.26][−3.52][−4.37][−4.37][−1.45][−4.17]
INFL0.029 ***0.059 ***0.077 ***−0.038 ***0.110 ***0.015 **0.074 ***0.017 **0.086 ***0.0040.0190.019 ***0.035 **0.013 *0.050 ***0.026 *
[3.76][4.53][6.26][−3.29][10.9][2.11][6.96][2.20][5.24][0.53][1.58][2.63][2.47][1.75][6.84][1.70]
FDI0.061 ***0.0100.055 ***0.0300.039 ***0.037 **0.044 ***0.048 ***0.025 ***0.0180.030 ***0.031 *0.022 ***0.0180.081 ***0.013
[3.39][1.28][7.15][1.50][5.06][2.11][5.63][2.59][3.05][1.08][3.74][1.87][2.69][1.07][4.87][1.54]
Industry dummy YESYESYESYESYESYESYESYESYESYESYESYESYESYESYESYES
Year dummyYESYESYESYESYESYESYESYESYESYESYESYESYESYESYESYES
Country dummyYESYESYESYESYESYESYESYESYESYESYESYESYESYESYESYES
Constant−3.18 ***−3.28 ***−3.69 ***−3.19 ***−3.48 ***−3.31 ***−3.73 ***−3.11 ***−3.00 ***−3.22 ***−3.14 ***−3.22 ***−3.14 ***−2.90 ***−3.35 ***−3.11 ***
[−14.6][−36.0][−44.9][−20.4][−44.3][−23.2][−39.7][−26.1][−30.8][−22.7][−34.2][−20.7][−33.7][−19.0][−24.1][−30.6]
Observations11,43422,10122,30011,23522,84912,98720,66512,87019,96913,56621,39712,13821,46312,07215,72617,809
R squared 0.450.220.230.440.220.40.230.40.230.390.230.440.230.440.40.23
Mean VIF value for each model1.861.991.642.11.891.652.141.581.841.772.111.392.101.981.791.94
Robust Z-statistics were modified to account for heteroscedasticity, and the results indicate that the p-values are *** p < 0.01, ** p < 0.05, and * p < 0.1.
Table 5. Sensitivity tests.
Table 5. Sensitivity tests.
VariablesModel 19Model 20Model 21Model 22Model 23Model 24Model 25Model 26Model 27Model 28Model 29Model 30Model 31Model 32
High
Volatility11
Low
Volatility
Prestigious Underwriters12Non-Prestigious UnderwritersTechnology Firms13Non-Technology FirmsClustered TestIFRS Firms14Non-IFRS FirmsVC Backed15Non-VC BackedEndogeneity
by Industriesby Yearsby Country
Main variable
Big4−0.670 ***−0.230 ***−0.370 ***−0.470 ***−0.530 ***−0.390 ***−0.400 ***−0.400 ***−0.400 ***−0.290 ***−0.520 ***−0.500 ***−0.390 ***−0.670 ***
[−13.0][−6.62][−9.06][−9.51][−5.87][−13.1][−5.96][−3.77][−7.65][−3.97][−12.1][−4.47][−12.9][−29.6]
IPO firm accounting ratio variables
PRO0.010 ***0.010 ***0.010 ***0.0100.0100.0100.0100.0100.010 ***0.0010.0100.001 **0.0100.010
[7.66][2.75][3.09][1.37][0.67][1.23][1.09][0.91][3.00][0.37][0.99][2.39][1.03][0.99]
LEV0.001 *−0.0010.001 **−0.001−0.032 *0.0010.0010.0010.0010.0010.001−0.095 **0.0010.001
[1.66][−0.15][2.47][−0.28][−1.79][1.15][1.09][1.13][1.15][1.53][1.62][−2.50][1.20][1.12]
PER0.005 ***−0.010−0.001 **0.004 ***0.004 ***−0.010−0.010−0.001−0.0100.003 ***−0.0100.006 ***−0.010−0.010
[8.10][−1.10][−2.01][8.01][4.37][−0.39][−0.20][−0.19][−0.23][4.57][−1.45][3.46][−0.33][−0.16]
Corporate governance variables
CEOD−0.360 ***−0.850 ***−0.500 ***−0.820 ***−0.460 *−0.650 ***−0.630 ***−0.630 ***−0.630 ***−0.220−0.680 ***−0.010 ***−0.620 ***−0.610 ***
[−3.22][−7.54][−5.19][−6.22][−1.77][−8.19][−6.00][−5.71][−8.86][−0.96][−5.84][−3.89][−7.77][−7.37]
ID−0.012 ***−0.009 ***−0.012 ***−0.006 ***−0.012 ***−0.010 ***−0.010 ***−0.010 ***−0.010 ***−0.001−0.011 ***−0.008 ***−0.010 ***−0.011 ***
[−9.59][−12.4][−14.2][−6.90][−5.70][−14.7][−12.4][−4.71][−7.62][−0.38][−13.6][−4.15][−14.4][−11.6]
IPO firm-specific variables
T−0.370 ***−0.280 ***−0.190 ***−0.470 *** −0.340 **−0.340 ***−0.340 ***−0.220 *−0.150 **−0.100−0.350 ***−0.340 ***
[−6.30][−5.66][−3.53][−8.84] [−2.29][−6.35][−3.89][−1.80][−2.27][−0.71][−9.02][−8.26]
SEC−0.011 **0.017 ***0.050 ***0.6200.058 ***0.020 ***0.022 ***0.022 *0.022−0.016−0.8600.0190.022 ***0.021 ***
[−2.29][2.62][5.39][1.06][2.67][3.98][2.83][1.81][1.53][−1.45][−0.48][0.47][4.39][3.40]
PRI−0.011 ***0.032 ***0.029 ***0.016 ***0.024 ***0.020 ***0.021 ***0.021 ***0.021 ***−0.5800.051 ***0.050 ***0.018 ***0.022 ***
[−2.93][13.2][6.37][6.12][3.68][9.13][5.62][3.82][2.83][−1.27][5.46][3.82][8.38][7.78]
INTG0.016 ***0.930 ***0.015 ***0.980 ***0.012 ***0.012 ***0.012 ***0.012 ***0.012 ***0.740 ***0.013 ***0.022 ***0.011 ***0.013 ***
[24.8][23.7][20.6][25.3][8.67][33.9][17.2][11.6][5.03][10.1][11.0][8.33][33.0][32.2]
DUR0.004 ***0.010 ***0.003 ***0.003 ***0.005 ***0.003 ***0.003 ***0.003 ***0.003 ***0.008 ***0.0010.004 ***0.003 ***0.003 ***
[19.5][6.12][6.93][10.1][8.85][12.1][10.7][4.08][4.49][4.00][1.32][9.73][11.2][12.6]
SIZE0.001−0.001−0.0100.001 **0.0010.0100.0100.0100.0100.001−0.001 *−0.001 *0.0010.010
[0.59][−1.00][−0.14][2.05][0.84][0.14][0.19][0.16][0.14][1.61][−1.79][−1.65][0.58][0.19]
FEES0.016 ***0.830 ***0.700 ***0.012 ***0.012 ***0.011 ***0.011 ***0.011 ***0.011 ***0.1200.820 *0.022 ***0.011 ***0.011 ***
[8.02][10.4][4.70][14.3][4.53][14.8][15.0][5.36][4.31][0.68][1.96][2.96][15.6][11.4]
RETAIL−0.490 **−0.001 ***−0.031 ***−0.450 **−0.430 **−0.620 ***−0.650 ***−0.650 ***−0.650 **−0.870 *−0.016 ***−0.490 ***−0.590 ***−0.640 ***
[−2.26][−3.12][−3.28][−2.42][−2.32][−2.64][−2.98][−2.67][−2.49][−1.92][−3.17][−3.65][−2.65][−3.68]
IPO market-specific variables
HOT0.150 ***0.076 **0.0560.210 ***0.340 ***0.110 ***0.140 *0.1400.140 *0.0660.280 ***−0.500 ***0.160 ***0.141 ***
[3.80][2.53][1.62][6.62][4.70][4.79][1.88][1.00][1.65][1.02][4.15][−3.80][6.89][6.16]
VOL−0.003 ***−0.001 ***−0.001 ***−0.001 ***−0.002 ***−0.001 ***−0.001 ***−0.001 ***−0.001 ***−0.001 ***−0.002 ***−0.003 ***−0.001 ***−0.001 ***
[−16.2][−11.7][−14.5][−11.4][−8.05][−16.7][−5.30][−5.64][−4.03][−3.94][−11.6][−6.70][−17.0][−20.1]
VOLA0.290 ***0.920 ***0.440 ***0.460 ***0.290 ***0.450 ***0.440 ***0.440 ***0.440 ***0.200 **−0.320 ***0.0330.410 ***0.441 ***
[6.61][14.2][9.65][12.1][2.64][15.0][6.12][4.73][5.12][2.21][−3.54][0.19][14.1][12.3]
Macroeconomic variables
INT−0.026 ***0.004−0.012 ***−0.005 *−0.038 ***−0.011 ***−0.012 ***−0.012 *−0.012−0.002−0.340 ***−0.130 ***−0.007 ***−0.011 ***
[−7.49][1.20][−3.05][−1.72][−3.74][−4.77][−2.63][−1.80][−1.05][−0.36][−9.24][−5.12][−3.31][−5.66]
GDP−0.006−0.074 ***−0.007−0.019 ***−0.054 **−0.011 **−0.012 ***−0.012−0.0120.007−0.150 ***−0.062−0.015 ***−0.011 **
[−0.72][−9.42][−0.76][−2.79][−2.49][−2.00][−4.08][−0.92][−0.46][0.49][−5.34][−1.42][−2.74][−2.29]
INFL0.045 ***0.065 ***0.066 ***0.013 *0.140 ***0.036 ***0.042 ***0.042 ***0.042 *0.043 ***0.170 ***0.320 ***0.038 ***0.042 ***
[5.27][9.13][5.58][1.76][4.64][6.89][4.56][2.58][1.71][2.84][6.14][6.57][7.32][7.98]
FDI0.091 ***0.033 ***0.092 ***0.027 ***0.0420.049 ***0.050 ***0.050 **0.050 *−0.003−0.100 **−0.0720.050 ***0.051 ***
[7.10][3.61][7.98][3.37][1.60][7.24][2.99][2.24][1.84][−0.27][−2.16][−1.19][7.78][7.99]
Industry dummy YESYESYESYESYESYESYESYESYESYESYESYESYESYES
Year dummyYESYESYESYESYESYESYESYESYESYESYESYESYESYES
Country dummyYESYESYESYESYESYESYESYESYESYESYESYESYESYES
Constant−3.36 ***−3.66 ***−4.28 ***−3.42 ***−3.77 ***−3.67 ***−3.71 ***−3.71 ***−3.71 ***−3.08 ***−0.83−3.14 ***−3.70 ***−2.35 ***
[−25.6][−45.9][−32.5][−40.9][−14.7][−52.5][−28.4][−16.1][−13.5][−17.2][−1.49][−5.47][−53.5][−73.0]
Observations13,55219,98315,68217,853346529,92133,53533,53533,53593447898184631,16833,536
R squared 0.420.250.370.250.340.290.290.290.290.160.290.520.260.29
Number of Clusters 132522
Mean VIF value for each model1.901.841.882.101.941.951.991.991.991.881.891.781.79
Robust Z-statistics were modified to account for heteroscedasticity, and the results indicate that the p-values are *** p < 0.01, ** p < 0.05, and * p < 0.1.
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Alidarous, M. Can the Presence of Big 4 Auditors in IPO Prospectus Reduce Failure Risk? J. Risk Financial Manag. 2024, 17, 234. https://doi.org/10.3390/jrfm17060234

AMA Style

Alidarous M. Can the Presence of Big 4 Auditors in IPO Prospectus Reduce Failure Risk? Journal of Risk and Financial Management. 2024; 17(6):234. https://doi.org/10.3390/jrfm17060234

Chicago/Turabian Style

Alidarous, Manal. 2024. "Can the Presence of Big 4 Auditors in IPO Prospectus Reduce Failure Risk?" Journal of Risk and Financial Management 17, no. 6: 234. https://doi.org/10.3390/jrfm17060234

APA Style

Alidarous, M. (2024). Can the Presence of Big 4 Auditors in IPO Prospectus Reduce Failure Risk? Journal of Risk and Financial Management, 17(6), 234. https://doi.org/10.3390/jrfm17060234

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