Reimbursement Costs of Auditing Financial Assets Measured by Fair Value Model in Jordanian Financial Firms’ Annual Reports

Abstract

This paper investigates the impact of financial assets measured by the fair value (F.V.) model, proxied by held-for-trading (H.F.T.), available-for-sale (A.F.S.), and the fair value option (F.V.O.), on reimbursement costs charged by external auditors in the context of the Jordanian finance industry. The study applied fixed-effects regression with a sample of 2408 firm-year observations of Jordanian firms from 2005 to 2018. The regression results confirmed that higher H.F.T. and A.F.S. of fair-valued assets were the primary cause of high audit fees; however, the F.V.O. had no significant impact. The impact of the F.V. model on audit reimbursement expenses has received little scholarly attention even in developing countries. The current study introduces an updated audit-fee model and new empirical evidence to provide more insights into this relationship and bridge a gap in the auditing literature. As a result, it investigates the impact of each fair-valued financial asset category on audit pricing for the first time. This research is unique in that it uses the F.V. model to investigate the association between each item of fair-valued financial assets and audit fees. The findings of this research provide current empirical information on the implication of the F.V. model in Jordan. The results contribute by guiding audit fee determinants in the context of Jordan, where there is no specific limit for audit fees determined by the government. The outcomes guide regulatory authorities in monitoring and regulating the audit profession and regulating the audit of F.V. model practices.

1. Introduction

Following the publication of the “International Financial Reporting Standards (I.F.R.S.s),” the “International Accounting Standards Board (I.A.S.B)” emphasised the need to use the fair value (F.V.) model [1]. The I.F.R.S.s’ primary objective was to ensure the application of F.V. [2]. The first implementation of the (F.V.) model occurred with the publication of the “I.A.S.39: Financial Instruments: Recognition and Measurement” in 2005, and had a significant impact on the global banking sector [3]. According to the I.A.S. 39, F.V. for financial assets is classified into three categories: “held-for-trading (H.F.T.), available-for-sale (A.F.S.), and the fair value option (F.V.O.)”. Numerous international accounting standards, including the I.A.S. 39, the I.F.R.S. 7, the I.F.R.S. 13, and the I.F.R.S. 9, have been released and mandate recording some assets at F.V. in the balance sheet, income statement, and stockholders’ equity [4,5,6,7,8]. This is consistent with several cooperative efforts initiated by the “International Accounting Standards Board (I.A.S.B.)” and the “Financial Accounting Standards Board (F.A.S.B.)” to increase the usage of the F.V. model.

The use of F.V. can help businesses obtain more up-to-date financial information on how they are doing and make financial reporting more transparent than traditional accounting methods [9,10,11]. It also poses many problems for auditors because they have to make detailed estimates and adjustments when they look at the assets and liabilities of a company [12,13]. Because “Fair Value Measurements (F.V.M.s)” are based on the current prices, certain assets and liabilities were not evaluable because there were not enough efficient markets for them. There is an “agency problem” between managers and owners, which means more incentives for managers to manipulate and misrepresent financial information.

Previous research on monitoring costs of post-F.V. model implementation and its influences on the auditing profession is limited and inconclusive. Furthermore, it is mainly from more significant and established economies, such as the United States (U.S.) and countries in the European Union (E.U.), where the auditing sector is more apparent, as opposed to tiny, developing countries such as Jordan [14]. At the same time, the authors are not aware of any other research emphasising the impact of each type of fair-valued asset that significantly influences audit prices in both developed and developing nations. Different findings have been reached on the degree to which audit data support F.V. verifications due to institutional affiliations and variances in core features [15]. Therefore, this study aims to bridge this gap in auditing F.V. models by exploring the nature of the relationship between the F.V. model and audit fees, focusing on a principles-based framework (i.e., the I.F.R.S.s) instead of a rules-based framework (i.e., U.S. G.A.A.P.). Second, for the first time, it aims to test how each type of fair-valued asset is measured by the F.V. model as requested by the I.F.R.S.s and the I.S.A. on external auditor reimbursements in Jordan.

Moreover, the present research also illustrates the nature of Jordanian capital markets and the issues that arose after the initial implementation of the F.V. model in 2005. Many studies have been undertaken to present the recent empirical evidence dealing with the economic consequences of the I.F.R.S.s implementation and the incentives behind the adoption decision. However, no attempt has been made yet to summarise the significant impact of topics related to the actual implications of the application of the F.V. model and its noticeable effects on the auditing profession and, in particular, audit fees. The researchers are not aware of any effort in the M.E. that considers factual information about the actual application of the F.V. model and the real implications on audit prices.

The current paper extends the work of previous studies [3,16], emphasising the significant role of the F.V. model on financial disclosure. Their research results confirmed the increased revelations on items of F.V. figures in firms’ published annual reports, such as “held-for-trading (H.F.T.), available-for-sale (A.F.S.), and the fair value option (F.V.O.)” as mentioned by [3], especially in Jordan as discussed by [16] who found a significant improvement in Jordanian firms annual reports regarding F.V. disclosures as required by the I.F.R.S.7. Therefore, this study utilises the F.V. proxies required by the I.F.R.S.s to test the implementation of these strict measures in the Jordanian audit industry using audit fees which is one of the proxies of audit industry quality. It further examines the implications on the auditing profession by providing more insight into selecting and using the F.V. model as a modern measurement basis and the significant impacts on auditing practices using a sample of 105 Jordanian financial institutions operating on A.S.E. during the period (2005–2018).

The fixed effects model was used to evaluate the hypotheses made using data from 105 Jordanian financial listed enterprises from 2005 to 2018 (1470 firm-year observations). This study first examines and validates the many connections between the share of fair-valued assets and audit fees. Second, in terms of fair-valued financial assets, the regression findings revealed that higher levels of H.F.T. and A.F.S. of fair-valued assets were the primary drivers of high reimbursement costs; however, no significant influence was seen for the F.V.O. The overall findings have relevance for policymakers and standard setters since they give up-to-date empirical data on the use of the F.V. model. The results presented here pique the attention of both auditors and clients by updating existing audit price models that may be used to calculate auditing expenses. This report aids Jordan’s government in developing more detailed rules and regulations to simplify and ensure the best practices of the F.V. model.

The current study is valuable to researchers and academics. A review of prior research in this field may aid future researchers in offering further evidence on an under-researched area of accounting knowledge. According to the current report, F.V. and the repercussions for the auditing environment provide an ideal opportunity for additional investigation. In recent analyses of the area [2,17,18,19,20], numerous scholars have suggested that future academics should focus their attention on this under-researched area at a national or international level to educate regulators and standard-setters about the true impact of the F.V. model on the audit profession. This study may aid accounting organisations in countries that have not yet adopted F.V., such as those in the Middle East (M.E.), in underlining the observable implications for the auditing business of this adoption. Knowledge about how F.V. impacts auditing techniques and the fundamental difficulties confronting preparers and auditors, may be gained from the experiences of different nations. This article outlines the steps that local audit companies must take to ensure they receive the appropriate training and education after the introduction of the I.F.R.S.s and F.V., as specified by the “International Federation of Accountants (I.F.A.C.)” guidelines and the “International Standards on Auditing (I.S.A.)”. Consequently, auditors must be aware of the fraud and manipulation of financial data created in compliance with F.V. standards. This study lays the groundwork for future accounting research on F.V. occurrences and their consequences.

The remainder of this paper is structured as follows. Section 2 presents a historical overview of the development of F.V.A. Section 3 outlines the literature review and related discussion. Section 4 presents the research design. Section 5 outlines the related results and discussion. Section 6 provides the result of the robustness tests. Lastly, Section 7 concludes the paper.

2. Historical Development of the Fair Value Model

2.1. Fair Value Development Overview

The F.A.S.B. is not the only organisation responsible for developing standards for insurance accounting and financial instruments (F.I.)—the “International Accounting Standards Committee (I.A.S.C.),” which was renamed the I.A.S.B. in 1999, is another organisation that has been working hard to reach a level of homogeneity in the accounting principles used by other organisations and industrial entities operating on a global scale for high-level financial reporting. The work toward F.I. resulted in the publication of the I.A.S. 39 in 1998, and several revisions to the I.A.S. 39 have been made since then. For the most part, the I.A.S.C.’s activities have been aligned with the F.A.S.B., and both have F.I. as their focal point. However, the committee proposed two more initiatives: the I.A.S. 41 Agriculture (2000), which requires the F.V. model to be used by all individuals who engage in agricultural operations, and the I.A.S. 40 Investment Property (2000), which integrates the F.V. model into nonfinancial assets [21].

The Financial Accounting Standards Board (F.A.S.B.) created the Statement of Financial Accounting Standards (F.A.S.) 115 in 1994, categorising financial assets as “held-to-maturity, held-for-sale or held-for-trading.” This statement applies to all enterprises operating in the financial sector. F.A.S. 115 permitted enterprises to utilise discounted cash flow as the primary criteria for “held-to-maturity” assets and mandated that firms use F.V. when valuing assets falling into the other two categories. In 1998, a new and better statement—F.A.S. 133—was produced based on F.A.S. 115. According to F.A.S. 133, derivatives must be held on the balance sheet at fair value. Any changes in their F.V., other than those resulting from particular hedging operations, must be reported in the income statement. While it is true that F.V. principles have been reinstated, this has made their implementation in practice more intimidating and contentious than ever. To decrease complexity and controversy, a new standard, F.A.S. 157, was issued by the F.A.S.B. The Standard was called “Fair Value Measurements”, and it gave a basic, noncontroversial definition for F.V. It provided a general framework to develop “fair value estimates (F.V.E.)” and required those estimates to be disclosed. In other words, the primary function of F.A.S. 157 is to specify how F.V. must be determined in the cases where the F.V. is requested by a different standard—prescribing specific accounting treatments or imposing requirements for F.V. are not within the scope of the functions of F.A.S. 157.

Following the release of the I.A.S. 39 “Financial Instruments: Recognition and Measurement,” the F.V. model was used for the first time. This had a significant impact on the international finance industry [3]. When the I.A.S. 39 came out in 2004, it explained how to recognise and measure financial assets and liabilities and certain agreements to purchase or sell nonmonetary things such as automobiles [5]. It was then changed to the “I.A.S. 39 for the fair value option” on 15 June 2005 and began on 1 January 2006. The I.A.S. 39 states that businesses must follow a three-level hierarchy when using the F.V. model to figure out the F.V. for F.I. Additionally, the I.A.S. 39 advises businesses to include most of their financial assets and liabilities on the balance sheet at F.V. or “financial value” [4]. Financial assets must be classified in one of the following ways under the I.A.S. 39: [4].

“Financial assets at fair value through profit or loss, Available-for-sale financial assets, Loans and receivables and Held-to-maturity investments”.

These sections must be utilised to identify how a particular financial asset is realised and measured in the financial statements. Variation can occur in the implementation criteria and how unrealised F.V. profits or losses were recognised according to the classification used [5]. Financial assets analysed at F.V. via gains or losses are classified into two parts: designated and held-for-trade. Designated refers to any financial asset initially recognised as being measured at F.V., including changes in profit or loss at F.V. and held-for-trading refers to financial assets acquired to quickly sell to retain shorter-term profits, such as all derivatives except hedging instruments. Second, available-for-sale financial assets (A.F.S.) are nonderivative financial assets first identified as such.

Furthermore, those assets include instruments that are not loans and receivables, held-to-maturity investments, or financial assets valued at F.V. via gains or losses. A.F.S. assets are valued at F.V. and reported on the balance sheet in line with the I.A.S. 39, with changes in F.V. recognised in the equity statement as soon as they occur. Third, nonderivative financial assets with no predetermined payments and seldom traded are valued at their amortised cost. Finally, held-to-maturity investments (H.T.M.) or fair value options (F.V.O.s) are a type of financial asset that denotes specific payable treasury bonds that entities intend to hold until maturity, other than loans and receivables, and are not designated as assets at F.V. through profit or loss or as readily available for sale at the time of initial recognition. The amortised cost method is used to determine the worth of H.T.M. investments. On 12 November 2009, the “I.F.R.S. 9: Financial Instruments” became effective, replacing the I.A.S. 39, which previously classified and measured financial assets [5]. The release of the I.F.R.S. 9, which is part of the I.A.S. 39 replacement effort, represents a significant step forward in this sector. The published version mainly replaces the I.A.S. 39, with new rules on impairment or hedging still under consideration. The primary goal of the I.F.R.S. 9 is to simplify the I.A.S. Plus 2019f (financial statement standard).

In 2003, the I.A.S. 32: Financial Instruments: Presentation was renamed “Financial Instruments: Disclosure and Presentation” to reflect the relocation of all required disclosures for financial instruments to the “I.A.S. 32: Financial Instruments: Presentation.” The I.A.S.B. issued the “I.F.R.S. 7: Financial Instruments: Disclosures” on 1 January 2007, to replace the I.A.S. 32′s disclosure regulations. Additionally, the I.F.R.S. 7 has replaced the “I.A.S. 30: Disclosures in Bank and Similar Financial Institutions’ Financial Statements.” In 2005, the International Accounting Standards Board (I.A.S.B.) issued the I.F.R.S. 7. [4]. According to the I.F.R.S. 7, entities must declare certain information on their financial statements. Regardless of their sector, all publicly listed firms must apply the I.F.R.S. 7 to all financial and nonfinancial operations [6]. Level 1 represents quoted prices for identical assets or liabilities in active markets that are unadjusted, level 2 represents quoted prices for assets or liabilities that are observable directly or indirectly, and level 3 is based on estimated unobservable inputs to determine asset and liability prices using a variety of valuation techniques [4]. Financial assets were scheduled to be reclassified on 13 October 2008, due to changes to the I.A.S. 39 and the International Financial Reporting Standards (I.F.R.S.s) 7. As a result, corporations are required to disclose information about the significance of Financial Instruments under the I.F.R.S. 7. (F.I.). Assets held to maturity, such as investments, loans, and receivables, are included in this statement. Financial obligations are assessed at F.V. via profit and loss, separating trade from designated.

The International Accounting Standards Board (I.A.S.B.) and the Financial Accounting Standards Board (F.A.S.B.) worked on the “I.F.R.S. 13: fair value measurement,” which was released in May 2011 and became effective on 1 January 2013. Companies are obliged to report more information on the F.V. hierarchy under the I.F.R.S. 13. The hierarchy of the F.V. and the definitions for each level are identical to prior standards. The F.V. is defined in the I.F.R.S. 13 as “the price that would be received for selling an asset or paid for transferring a liability in an orderly transaction between market participants at the measurement date” [7]. For instance, the I.F.R.S. 13 broadens the scope of F.V.M.s to include nonfinancial assets and liabilities, thereby making it a more comprehensive application of I.F.R.S. 7. The International Accounting Standards Board (I.A.S.B.) released the new Standard in response to the 2008 financial crisis. The principles-based I.F.R.S. 13 F.V.M.s standard offers advice to businesses on assessing and disclosing the F.V. of their assets, liabilities, and equity instruments.

2.2. Jordan Profile

Jordan is an Arab country with strong social and international relationships. Cultural and political factors have led to several improvements in its corporations and how they conduct business, especially their preparation of accounting information [6,7]. Significant improvements in accounting regulations began in early 1988 when Jordan became a member of the International Accounting Standards Committee (I.A.S.C.). This was followed by the establishment of the Jordanian Association of Certified Public Accountants (J.A.C.P.A.) as a local accounting body in 1989. The I.A.S.C. then advised the J.A.C.P.A. to adopt the I.A.S.s for all Jordanian firms in 1990. In 1997, the “Companies Law” introduced government policy framework in Jordan and the “Companies Law No. 22” was issued which required all Jordanian companies regulated by the Companies Law to prepare accounting records and present audited financial information based on “internationally recognised accounting and auditing principles” [5]. Shortly after, in 1998, the “Securities Act No. 23” was issued and the Jordan Securities Commission (J.S.C.) declared that all listed companies were required to follow the financial reporting rules of the I.F.R.S.s, and auditing had to be completed under the guidelines of the International Standard on Auditing (I.S.A.) [4].

Given the scarce natural resources in Jordan, the government has tried to enhance governance and disclosure frameworks during the last few decades to improve trust and confidence in the economy [4]. Therefore, the adoption of the I.A.S.s and I.F.R.S.s by developing market economies, such as Jordan, became critical to reaching a high level of transparency and comparability of financial information, which expanded the international trade between Arab countries at global levels [16,18]. The main objective of these requirements was to increase the number of disclosures in firms’ annual reports. Thus, improving the quality of firms’ financial reporting and assisting users in making decisions [18]. However, the transition to the I.F.R.S.s and I.A.S.s has remarkable implications for the accounting and auditing profession worldwide given that the situation is worsening in developing countries and Jordan, in particular [16].

By 2005, Jordanian finance businesses were required to use F.V.A. under the I.A.S. 39, and the common assets measured based on F.V.A. were held-for-trading and held-for-sale. The adoption of F.V.A. in Jordan was the major issue that brought severe problems to the country’s economy. The recognition of unrealised gains and losses of the fair-valued assets in Jordan raised share prices to their highest levels during the economic downturn. The volatility in share prices caused poor investment decisions due to the lack of marketplace efficiency. The growing reliance of Jordan’s economy on external exports caused the increased usage of financial assets in Jordanian companies which eventually led to damaging publicity about financial instruments’ losses in the press [20]. The problem of implementing F.V.A. was escalated by the growing need for disclosures regarding the fair value of financial assets. Such events forced the government to take steps through the J.S.C. to overcome the problems caused by fair-value adoption on Jordan’s stock market. The “New Fair Value” regulations were released in February 2008 through the J.S.C. and later revised in 2011 to overcome volatility in the market. Recently, in 2014 during the years of boom before the recession, the J.S.C.’s new regulations emphasised supervising external auditors’ roles in improving the quality of disclosed fair-valued information by Jordanian firms. In 2015, the government promulgated the “Jordan 2025” plan, which focused on an export-oriented economic strategy through boosting trade with other countries in the region and especially the Gulf Cooperation Council (G.C.C.) states. The plan aims to make Jordan a gateway to regional markets and take advantage of free trade agreements [20]. Such regulations could meet the Jordanian’s government objectives: to attract foreign investors by sending positive signals about the country’s firms’ financial stability; and to publish high-quality financial information.

The Middle East (M.E.) region is economically diverse, with significant discrepancies in natural resources between countries. These countries are most likely to rely on foreign investments and international funds, connecting to the global environment, which becomes paramount to sustaining their economic cooperation and political integration [16]. Clarity and transparency of accounting practices become extremely important in connecting to investors, trading partners, and foreign buyers. Considered an attractive setting, Middle Eastern nations operate under a unique political, cultural, legal, and economic environment [14]. The growing interest in accounting research on Middle Eastern countries is boosted by common heritage, language, religion, beliefs, traditions, and geography that reinforce their cultural, social, and economic lives [12]. A combination of political, financial, and technological improvements channel critical changes in accounting, such as the adoption of the I.F.R.S.s, which have a common effect across all areas of life [15]. Jordan enjoys political stability in a very turbulent region. Difficult political and economic conditions have seriously affected Jordan’s economy [20]. Despite the increased involvement of the state in these political conditions in neighbouring economies, the basics of the economy were already built [18]. These cultural and political factors have led to several improvements in the behaviour of Jordanian corporations and how they communicate their financial information [16]. With limited information about the Middle Eastern accounting environment and Jordan in particular, this study reflects an increasing interest in the area as a channel for foreign investments [16,17,18]. With dramatic changes happening in the Middle Eastern business environment [16], there is further motivation to contribute to government authorities’ current and future policy developments to create favourable financial reporting conditions. This can be achieved by integrating and promoting the Middle East and Jordan in the international business environment.

Therefore, Jordan as a case scenario for this examination is selected for many reasons: firstly, results obtained from this examination can be generalised to the broader M.E. The growing interest in accounting research on Middle Eastern nations is boosted by their similar heritage, political system, language, religion, beliefs, traditions, culture, etc. [16]. Secondly, the increasing use of financial instruments by Jordanian companies and the public around financial instrument losses reported in the media further encourages this examination to concentrate on F.V.A. of financial assets in Jordan [16]. Thirdly, Jordan is the only Arab country which requires listed firms to disclose the audit fees paid in their annual reports as a legal requirement and has required this since 2001. Finally, the implementation of the I.A.S.s and I.F.R.S.s for almost 30 years in Jordan provides insightful evaluations on how F.V.M.s are prepared and audited under different circumstances [16].

3. Theoretical Perspective, Fair Value Implementation Background, and Hypotheses Development

3.1. Theoretical Perspective

The F.V. model is used in this study to combine agency, stakeholder, and signalling theories (see [22,23,24,25,26]). The F.V. model is a popular paradigm in today’s organisations and is closely related to the signalling and stakeholder theories. This is due to the use of intricate and inaccurate calculations and the likelihood of management abuse—agency theory. Stakeholder theory allows examination of the F.V. model’s applicability in a wider social fabric where managers are responsible for many stakeholders [27].

3.2. Fair Value Implementation Background and Hypotheses Development

In response to the 2008 credit crunches, the E.U. asked the “International Auditing and Assurance Rules Board (I.A.A.S.B.)” to alter its financial reporting rules to use historical host (H.C.) accounting instead of the F.V. model. As a result, banks may now categorise assets kept for trade [28]. It was amended on 13 October 2008, titled “Amendment to I.A.S. 39 for financial asset reclassifications” [4]. Securities are classified, continuing to follow the I.A.S. 39: expected-to-hold financial assets must be reported at F.V. with unrealised gains and losses included in the income statement. A.F.S. financial assets should be noted at F.V. as unrealised gains exempted from the financial statements but included in changes in equity, and held-to-maturity securities must be reported at market price (amortised cost) [4]. There were interesting ramifications of these financial reporting adjustments, for example, in 2008, the I.A.S.B. revisions allowed European banks to enhance earnings by 29 billion (US dollars) [28]. Additionally, bank executives and boards revealed that they employ H.C. accounting instead of F.V. when dealing with assets in low-liquidity markets. Thus, financial statements are generated and audited in line with modern financial reporting standards, and they fairly depict the stated corporate entity’s financial situation.

In Ref. [3], the authors categorised the nations studied on the value significance of F.V. in the banking sector into market-based and bank-based. A robust information environment, high stock market development, and high disclosure norms are all indicators of a prosperous market-based economy. Furthermore, investors correctly valued F.V.s in these economies [29,30,31]. On the other hand, banks tend to be located in areas with less established stock markets, weaker information infrastructure, and no formal enforcement procedures. These economies experience difficulty acquiring the information they need for fair valuation, which means that measurement mistakes and biases are more prevalent, which negatively impacts the value relevance of F.V. [3].

In Ref. [3], the authors examined how F.V. of F.I. was implemented in 907 banks located in 46 countries: Australia, Austria, Bahrain, Belgium, Botswana, Bulgaria, China, Croatia, Cyprus, Czech Republic, Denmark, Egypt, Finland, France, Germany, Greece, Hong Kong, Hungary, Ireland, Israel, Italy, Kazakhstan, Kenya, Kuwait, Latvia, Lithuania, Macedonia, Malaysia, Mauritius, Norway, Oman, Pakistan, Philippines, Poland, Portugal, Romania, Russia, Saudi Arabia, Slovakia, South Africa, Spain, Sweden, Switzerland, Turkey, and the United Kingdom. According to [3]’s descriptive analysis of the application of F.V. to F.I. in several countries, the average proportion of F.I. measured under F.V. is 23%, which includes an average of 17.1 per cent of fair-valued financial assets and 5.9 per cent fair-valued financial liabilities.

The most widespread use of fair-valued assets is found on average in Belgium and France, where it may reach up to 40%. Fair-valued financial assets offered for sale are mostly utilised in Belgium, whereas those kept for trade are mostly used in France. France and Sweden have the greatest shares of fair-valued liabilities utilised, accounting for 27 per cent of total liabilities. The average percentage of F.I. assessed under F.V. is quite low, according to [3]. Still, it varies greatly among nations, as follows: the biggest proportion of fair-valued financial assets is found in Belgium, France, and Sweden, which has reached up to 40%; and the lowest percentage is found in Macedonia, Oman, and Romania, which has not reached more than 3%. To underline further, F.V.O. implementation varies greatly among countries. According to [3], 12 countries (26.1% of the whole sample) do not use F.V.O., while 19 countries (41.3% of the sample) do not employ F.V. for financial commitments. Overall, it is obvious that the F.V. measurement feature was less critical than other measurement alternatives, such as amortised cost.

In Ref. [32], the authors show that 1280 publicly traded financial firms in 42 countries worldwide use the F.V. model. These 42 countries are Australia, Austria, Bahrain, Belgium, Brazil, Canada, Chile, Denmark, Finland, France, Germany, Ghana, Hungary, Ireland, Italy, Jordan, Kenya, Kuwait, Morocco, Netherlands, Norway, Poland, Portugal, Russia, Slovakia, South Africa, South Korea, Spain, Sweden, Switzerland, Turkey, U.A.E., and the U.K. Additionally, this study from [32] demonstrated that the average F.V. of Bahrain was 23.1% (99.8%), Egypt 8.6 per cent (99.8%), Jordan 13.8 per cent (0%), Kuwait 6.1 per cent (0.1%), Oman 2.6 per cent (0.5%) as well as other countries in the Arab M.E. (0.8%). According to this research, Bahrain, Jordan, and Oman are the countries with the most extensive and lowest use of fair-valued assets. Bahrain and Egypt have the most significant percentage of fair-valued financial obligations, whereas Jordan does not.

It is clear from the analysis in [3] that the proportion of fair-valued assets and liabilities in these countries vary across countries. Assets, not liabilities, are where most F.V.s are used.

Since Jordan’s natural resources are scarce, the government has worked for decades to build governance and transparency frameworks to enhance public trust and confidence in the economy. Developing market economies, such as Jordan, must adopt the I.A.S.s and I.F.R.S.s to achieve a high level of financial information transparency and comparability, which will promote global trade among Arab countries and globally [33,34,35,36]. As a result of these new regulations, annual reports produced by firms are expected to become more detailed. Improving the quality of financial reporting allows end-users of businesses to make better-informed choices [18]. Given Jordan’s deteriorating financial status, the I.F.S.R. and I.A.S.s changeover has significant global consequences for the accounting and auditing professions [37,38].

Jordanian financial institutions were required to use the F.V. model in compliance with the I.A.S. 39 by 2005. The most often measured assets utilising the F.V. model are H.F.S., and H.F.T. Jordan’s adoption of the F.V. model has been a significant subject of disagreement in the country’s economy. During the economic slump in Jordan, the realisation of unrealised gains and losses on fair-valued assets drove share prices to all-time highs. Share price volatility led to poor investment decisions due to a lack of market efficiency. Jordan’s increasing dependence on foreign exports demanded a greater reliance on financial assets by Jordanian enterprises, leading to negative news coverage of F.I. losses [16,39]. The growing need for financial asset F.V. disclosures exacerbated the complexity of implementing the F.V. model. These incidents compelled the government to act via the J.S.C. to address the issues highlighted by the introduction of F.V. on the Jordanian stock exchange. To alleviate market volatility, the J.S.C. issued the “New Fair Value” rules in February 2008 which were revised in 2011. Before the recession, the J.S.C.’s new rules in 2014 emphasised the need for external auditor oversight in improving the quality of Jordanian firms’ reported fair-valued information. In 2015, the government released the “Jordan 2025” plan, stressing an export-oriented economic strategy focused on increased commerce with neighbouring nations, particularly the Gulf Cooperation Council (G.C.C.) members. Jordan’s objective is to become a regional market gateway and leverage free trade agreements [37]. Such limits might help Jordan’s government attract foreign investors by sending strong signals about the financial soundness of the country’s businesses and sharing high-quality financial data.

The Middle Eastern and North African (M.E.A.) economies are very diversified, with significant differences in natural resources. These nations are more likely to depend on foreign investments and international funding, which is essential to their economic cooperation and political integration in the global environment [40]. When dealing with overseas investors, trade partners, and purchasers, it is critical to have clear and transparent accounting processes. The Middle East’s political, cultural, legal, and economic conditions are considered desirable [41]. The rising interest in accounting research in Middle Eastern nations is bolstered by the countries’ shared cultural, linguistic, religious, philosophical, and historical heritages and geography [42]. Accounting reforms such as the adoption of International Financial Reporting Standards (I.F.R.S.s) are made possible by a trifecta of political, financial, and technology advancements [43,44]. In a region where political unrest is rampant, Jordan is a haven of peace. Jordan’s economy has suffered greatly due to the country’s complex political and economic circumstances [40]. As a result of these political circumstances, the foundations of an economy were already in place in neighbouring economies [45]. Due to these cultural and political reasons, Jordanian firms have made several changes in their business practices and in how they publish their financial information. The research demonstrates a rising interest in the Middle East and Jordan as a gateway for international investments because of the lack of knowledge regarding the region’s accounting environment [16,18,33]. There is an additional reason to contribute to government authorities’ present and future policy improvements to promote favourable financial reporting circumstances in the Middle Eastern corporate environment [37,46]. Integrating and promoting the Middle East and Jordan in the global commercial arena may help.

In Ref. [16], the authors examined the evolution of financial information disclosure in Jordan after implementing the I.F.R.S. 7 in 2007. The researchers compare the disclosure of financial information under the I.F.R.S. 7 to that under the I.A.S. 30 and I.A.S. 32. To accomplish the study objectives, the researchers created obstacles and difficulties associated with implementing F.V.s in Jordan, returning to the accounting repercussions of fair value, and consistent with the preceding disclosure index checklist. The study revealed that disclosure of financial information as evaluated by the F.V. model rose significantly when adopting the I.F.R.S. 7. Interestingly and consistent with the analysis in [3] the use of the F.V. model for F.I., including “fair value through profit or loss–held-for-trading; fair value through profit or loss–designated; held-to-maturity investments; available-for-sale financial assets; loans and receivables; and financial liabilities measured at amortised cost,” has increased significantly in the years since the adoption of the I.F.R.S. 7. This evidence of widespread use and expansion of disclosure of F.V.s emphasised the need to discuss the primary concerns of literature. It is clear that F.V. has ramifications for the accounting and auditing professions in particular, which is the primary focus of the present examination. Few attempts have been made to address concerns associated with using the F.V. model and its consequences for the auditing profession (i.e., audit fees, in this study), particularly in developing nations.

Increased disclosure requirements for F.V.s in Jordanian enterprises’ annual reports will increase external auditors’ workload since a significant number of complicated disclosures on F.V. numbers require more attention from auditors. As the primary monitoring tool used by shareholders to mitigate the information asymmetry issue, external auditors are expected to devote far more time and effort to the auditing process than conventional auditors do. To pay auditors for the time and effort used throughout the auditing process, auditors will likely pursue high reimbursement expenses. The following theories have been made in light of the theoretical evidence given previously:

Hypothesis 1 (H1).

There is a positive relationship between the proportion of fair-valued assets and audit fees among Jordanian financial listed firms.

Hypothesis 2 (H2).

There is a positive relationship between fair-valued assets for option and audit fees among Jordanian financial listed firms.

Hypothesis 3 (H3).

There is a positive relationship between held-for-trading and audit fees among Jordanian financial listed firms.

Hypothesis 4 (H4).

There is a positive relationship between held-for-sale and audit fees among Jordanian financial listed firms.

Jordan was chosen as the case scenario for this analysis for a variety of reasons, the most important of which is that the conclusions of this examination may be applied to the rest of the M.E. Due to their shared ancestry, political system, language, religion, beliefs, customs, and culture there is an increasing interest in accounting studies in Middle Eastern countries [37,47]. Second, the rising use of financial instruments (F.I.) by Jordanian firms and media coverage of F.I. losses in the nation compel this inquiry to concentrate on the valuation of financial assets in Jordan [16]. Third and lastly, Jordanian law has mandated the inclusion of information on yearly auditors’ fees since 2001, making it the first Arab country to mandate this. Interestingly, the I.A.S.s and I.F.R.S.s have been used in financial statement preparation and auditing in Jordan for over 30 years now (F.V.M.s) [33,48,49].

4. Research Data and Methodology

4.1. Sample Selection

The research data were hand-collected from Jordanian listed firms’ annual reports disclosed on the Amman Stock Exchange (A.S.E.) website from 2005 to 2018. This study commences in the year 2005 mainly because in 2005 the fair value for financial assets in Jordan became law as required by I.S.A. 39, followed by the amendment of the I.F.R.S. 7 in 2009. Therefore, the chosen study period aligns with the first and more recent F.V.D. requirements as requested by various I.A.S.s and I.F.R.S.s, such as the I.A.S. 39 in 2005, the I.F.R.S. 7 in 2009, and the I.F.R.S. 13 in 2013. The data relating to the years from 2019 onwards are either not available or disrupted because of COVID-19.

As presented in

Table 1. Sample selection procedure.

	Total Firms	Pooled
Initial sample	235	3290
(-) Firms with missing data	(13)	(182)
(-) Firms belonging to the nonfinance industry	(24)	(336)
(-) Firms belonging to industries with less than ten firms	(72)	(1008)
(-) Firms using other accounting methods (firms with non-VFD)	(21)	(294)
Final sample	105	1470

, the total sample comprised 235 firms, excluding: first, 13 firms with missing financial ratio data; second, 24 firms belonging to nonfinance industries (nonfinancial institutions are removed from the sample because their financial structure is diverse); third, 72 firms operating in industries with less than ten businesses; and fourth, 21 firms using other accounting methods (i.e., historical cost accounting) or firms with missing F.V.D.s for financial assets. Consequently, the overall sample consisted of 105 firms.

Table 2. Final distribution of the sample by industry.

	Total Accepted Firms	Percentage
Financial Industry Sample
Real estate	28	27
Diversified Financial Services	38	36
Banks	16	15
Insurance	23	22
Total sample from the financial industry	105	100

categorises the final accepted firms into their primary or sub- industries.

4.2. Research Design

This analysis employs a quantitative methodology and extends the previous F.V.A.-based auditing models devised by [14,50,51]. Used here for the first time are new F.V.A. proxies (FV_Option, FV_AFT, FV_AFS) as suggested by [3] as part of audit pricing models with a reference under the I.F.R.S.s, as a proxy of client complexity and risk. This analysis extends previous auditing and F.V.A. models to the following equations to test the developed hypotheses:

LnAFEES_it= δ0_it + δ1FV_TA_it + δ2SIZE_it + δ3SUBS_it + δ4ROI_it + δ5LEV_it + δ6GROWTH_it + δ7BLOCK_OWN_it + δ8FOR_OWN_it + δ9INST_OWN_it +δ10RECINV _it +δ11BIG4_it + δ12TENURE_it + δ13OPINION_it + IndFE _it + YearFE_it + ɛ_it.

(1)

LnAFEES_it= δ0_it + δ1FV_Option_it + δ2SIZE_it + δ3SUBS_it + δ4ROI_it + δ5LEV_it + δ6GROWTH_it + δ7BLOCK_OWN_it + δ8FOR_OWN_it + δ9INST_OWN_it +δ10RECINV _it +δ11BIG4_it + δ12TENURE_it + δ13OPINION_it + IndFE _it + YearFE_it + ɛ_it.

(2)

LnAFEES_it= δ0_it + δ1FV_AFT_it + δ2SIZE_it + δ3SUBS_it + δ4ROI_it + δ5LEV_it + δ6GROWTH_it + δ7BLOCK_OWN_it + δ8FOR_OWN_it + δ9INST_OWN_it +δ10RECINV _it +δ11BIG4_it + δ12TENURE_it + δ13OPINION_it + IndFE_it + YearFE_it + ɛ_it.

(3)

LnAFEESit= δ0it + δ1FV_AFSit + δ2SIZEit + δ3SUBSit + δ4ROIit + δ5LEVit + δ6GROWTHit + δ7BLOCK_OWNit + δ8FOR_OWNit + δ9INST_OWNit +δ10RECINVit +δ11BIG4it + δ12TENUREit + δ13OPINIONit + IndFE it + YearFEit + ɛit.

(4)

Certain control variables are incorporated into the current study, including the ones that have been utilised in prior auditing models, including [51,52,53], i.e., SIZE, SUBS, R.O.I., LEV, GROWTH, BLOCK_OWN, FOR_OWN, INST_OWN, RECINV, BIG4, TENURE and OPINION. All variables are defined in

Table 3. Variables measurements.

Variable	Label	Measurement
Audit fees	LnAFEES	The natural Log of total audit fees.
The proportion of fair-valued assets	FV_TA	Total assets deflate a firm’s total fair-valued assets.
Fair value for Option	FV_Option	Firm’s total fair-valued financial assets for Option.
Fair-valued financial assets available for trading	FV_AFT	The firm’s total fair-valued financial assets are available for trading.
Fair-valued financial assets available for sale	FV_AFS	The firm’s total fair-valued financial assets are available for sale.
Client size	SIZE	The natural Log of a firm’s total assets.
Number of subsidiaries	SUBS	The number of firm’s subsidiaries or branches.
Return on investment	ROI	The net income by total assets.
Growth ratio	GROWTH	The current year’s revenues compared to last year’s revenues.
Receivable and inventory ratio	RECINV	The sum of total receivables and inventory divided by total assets.
Block-holder ownership percentage	BLOCK_OWN	The percentage of the total shares held by the block-holder investors of the total number of a firm’s shares.
Foreign ownership percentage	FOR_OWN	The proportion of total shares owned by foreign investors to the total number of shares in a company.
Institutional ownership percentage	INST_OWN	The proportion of institutional investors’ overall holdings to the total number of shares in a company.
Big four audit firms	BIG4	The dummy variable is coded as 1 if the audit firm is one of the big four (PwC, KPMG, Deloitte, or E&Y), and 0 otherwise.
Auditor tenure	TENURE	Three-year tenure for auditors, coded 1 if the audit firm did not change, 0 if it did.
Unqualified opinion	OPINION	Dummy variable with a value of 1 if the company obtains an unqualified opinion and 0 if it does not.
Subsidiaries	SUBS	SUBS is the number of the firm’s subsidiaries.

.

To confirm the best estimator of the current study, the models were tested using panel data first through Stata software. Hausman’s test chooses between fixed and random effects. The analysis accepts the null hypothesis and confirms that the fixed effects model is more appropriate than random effects. The p-value of each model is highly significant and lower than 5% (untabulated Hausman prob > chi2 ranged from 0.01 to 0.05). Therefore, it is evident that the fixed effects model is better for the multivariate analysis of the present study.

Moreover, following preliminary analyses [52,54,55,56], the current study uses the fixed effects regression technique. The research data must meet four fundamental assumptions that must be true for the regression analysis to be accurate to conduct the analysis. Regression assumptions are tested (including: first, normality, linearity, homoscedasticity and multicollinearity) and confirmed that the current data satisfy these assumptions (see Figure A1 and Figure A2 in Appendix A).

5. Results and Discussion

5.1. Descriptive and Correlation Statistics

As indicated in

Table 4. Descriptive Statistics.

Variable	Mean	Std. Dev.	Min	Max
LnAFEES	9.397833	1.085241	6.907755	12.41187
FV_TA	0.1487079	0.1825532	0.0000284	0.9939833
FV_Option	5,216,992	7.83 × 107	0	2.04 × 109
FV_AFT	5,105,472	3.26 × 107	0	7.16 × 108
FV_AFS	2.38 × 107	1.67 × 108	0	3.48 × 109
SIZE	17.32962	1.972169	13.1846	22.07602
SUBS	2.254422	3.458285	0	17
ROI	1268.633	762.5071	29	2590
LEV	1500.548	850.372	32	2763
GROWTH	1.635998	3.356879	−2.864738	22.52969
RECINV	0.262524	1.02215	0	37.63185
BLOCK_OWN	0.5608269	0.2379901	0.0493206	0.964
FOR_OWN	0.1296985	0.2306555	0	0.910538
INST_OWN	0.3357593	0.2766584	0	0.9793341
BIG4	0.4047619	0.4910129	0	1
TENURE	0.5326531	0.4991024	0	1
OPINION	0.8768707	0.3286973	0	1
N	1470

, this table summarises the descriptive statistics utilised in the empirical study from 2005 to 2018. Audit fees are a determining variable that must be considered (LnAFEES). The mean value of LnAFEES is 9.397, with a standard deviation of 1.085, indicating that audit fees vary little among Jordanian-listed firms. Based on the independent experimental variables “Fair value option, Fair-valued financial assets accessible for trading, and Fair-valued financial assets available for sale,” the percentage of total fair-valued assets (FV_TA) has a mean value of 0.148 a low standard deviation of 0.182. F.V.O., fair-valued financial assets for trading, and selling assets had mean values of 5,216,992, 5,105,472, and 2.38 × 10⁷, respectively, with low standard deviation values. According to this survey, Jordanian enterprises’ fair-valued assets account for around 15% of total assets. While [14] found 0.17 in the U.S. and [50] reported 0.31 in the E.U., where the capital market is notably different from that of small and developing nations such as Jordan, the size of fair-valued assets in Jordan is smaller. According to these data, the most prevalent categories of fair-valued assets owned by Jordanian enterprises are fair value option (F.V.O.), fair-valued financial assets accessible for trade, and selling assets. The F.V.O. is the second most prevalent form of fair-priced assets owned by Jordanian businesses, behind only the fair-valued financial asset.

Table 5. Correlation analysis.

	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16
1. LnAFEES	1.000
2. FV_Option	0.137 ***	1.000
3. FV_AFT	0.291 ***	−0.003	1.000
4. FV_AFS	0.312 ***	0.0640 *	0.514 ***	1.000
5. SIZE	0.830 ***	0.144 ***	0.271 ***	0.288 ***	1.000
6. SUBS	0.229 ***	0.022	0.216 ***	0.201 ***	0.250 ***	1.000
7. ROI	0.330 ***	0.028	0.122 ***	0.121 ***	0.357 ***	−0.161 ***	1.000
8. LEV	0.538 ***	0.0796 **	0.135 ***	0.156 ***	0.523 ***	−0.0829 **	0.268 ***	1.000
9. GROWTH	−0.0752 **	−0.011	0.0782 **	0.024	−0.0558 *	−0.006	0.0536 *	−0.022	1.000
10. RECINV	0.0589 *	0.006	0.036	0.006	0.041	−0.0588 *	0.0766 **	0.0553 *	−0.015	1.000
11. BLOCK_OWN	0.128 ***	−0.003	−0.006	−0.011	0.100 ***	−0.0968 ***	0.123 ***	0.161 ***	0.0542 *	0.041	1.000
12. FOR_OWN	0.433 ***	0.047	0.030	0.0612 *	0.361 ***	−0.035	0.185 ***	0.317 ***	−0.036	0.012	0.287 ***	1.000
13. INST_OWN	0.232 ***	0.036	0.025	0.035	0.173 ***	−0.013	0.115 ***	0.149 ***	0.0607 *	0.002	0.538 ***	0.421 ***	1.000
14. BIG4	0.575 ***	0.0784 **	0.135 ***	0.154 ***	0.514 ***	0.0628 *	0.223 ***	0.256 ***	−0.0614 *	0.0652 *	0.249 ***	0.278 ***	0.295 ***	1.000
15. TENURE	0.167 ***	−0.012	0.009	0.027	0.131 ***	0.0879 ***	0.013	0.111 ***	−0.035	0.020	0.107 ***	0.0569 *	0.0861 ***	−0.028	1.000
16. OPINION	0.0531 *	0.025	0.043	0.047	0.044	−0.147 ***	0.235 ***	0.015	0.006	0.029	0.137 ***	0.113 ***	0.126 ***	0.0897 ***	−0.015

Notes: This table presents the Spearman correlation matrix results between the dependent and independent variables. Each year, all continuous variables are winterised at the 1 and 99 levels to minimise the impact of probable outliers. ***, **, and * Correlation is statistically significant at the 0.01, 0.05 and 0.10 (2-tailed) levels, respectively.

and

Table 6. Correlation analysis.

	1	2	3	4	5	6	7	8	9	10	11	12	13	14
1. LnAFEES	1.000
2. FV_TA	−0.181 ***	1.000
3. SIZE	0.830 ***	−0.269 ***	1.000
4. SUBS	0.229 ***	−0.0787 **	0.250 ***	1.000
5. ROI	0.330 ***	−0.005	0.357 ***	−0.161 ***	1.000
6. LEV	0.538 ***	−0.182 ***	0.523 ***	−0.0829 **	0.268 ***	1.000
7. GROWTH	−0.0752 **	0.0515 *	−0.0558 *	−0.006	0.0536 *	−0.022	1.000
8. RECINV	0.0589 *	0.035	0.041	−0.0588 *	0.0766 **	0.0553 *	−0.015	1.000
9. BLOCK_OWN	0.128 ***	−0.017	0.100 ***	−0.0968 ***	0.123 ***	0.161 ***	0.0542 *	0.041	1.000
10. FOR_OWN	0.433 ***	−0.0684 **	0.361 ***	−0.035	0.185 ***	0.317 ***	−0.036	0.012	0.287 ***	1.000
11. INST_OWN	0.232 ***	0.012	0.173 ***	−0.013	0.115 ***	0.149 ***	0.0607 *	0.002	0.538 ***	0.421 ***	1.000
12. BIG4	0.575 ***	−0.159 ***	0.514 ***	0.0628 *	0.223 ***	0.256 ***	−0.0614 *	0.0652 *	0.249 ***	0.278 ***	0.295 ***	1.000
13. TENURE	0.167 ***	0.021	0.131 ***	0.0879 ***	0.013	0.111 ***	−0.035	0.020	0.107 ***	0.0569 *	0.0861 ***	−0.028	1.000
14. OPINION	0.0531 *	0.138 ***	0.044	−0.147 ***	0.235 ***	0.015	0.006	0.029	0.137 ***	0.113 ***	0.126 ***	0.0897 ***	−0.015	1.000

Notes: This table presents the Spearman correlation matrix results between the dependent and independent variables. All continuous variables are winsorised at the 1 and 99 levels each year to reduce the influence of potential outliers. ***, **, and * Correlation is statistically significant at the 0.01, 0.05 and 0.10 levels (2-tailed), respectively.

summarise the findings of the Spearman correlation matrix for the dependent and independent variables and the degree to which they are related. The multicollinearity test verifies that no connection exists between the independent variables utilised in the same regression model. When the mean of the V.I.F. test is less than 2, there is no concern with multicollinearity.

5.2. Univariate Analysis

Table 7. Univariate analysis.

Variable	Mean		t-Value (sig)
Panel A: Firms with F.V.O. vs. Firms with Non-F.V.O. Disclosures
	(F.V.O. = 1) N = 67 firm-year observation	(F.V.O. = 0) N = 1403 firm-year observation
LnAFEES	10.986	9.3219	−12.9414 ***
Panel B: Firms with AFT vs. firms with non-AFT disclosures
	(AFT =1) N = 953 firm-year observation	(AFT =0) N = 517 firm-year observation
LnAFEES	9.3978	9.0911	−8.1560 ***
Panel C: Firms with A.F.S. vs. firms with non-AFS disclosures
	(AFS = 1) N = 1273 firm-year observation	(AFS =0) N = 197 firm-year observation
LnAFEES	9.4533	9.0392	−5.0249 ***

*** denote significance at the 0.10, 0.05, and 0.01 levels, respectively. Notes: ISP1: dummy variable with a value of 1 if the auditor market share exceeds ten, and 0 otherwise. PS DUMMY: dummy variable with a value of 1 if the auditor portfolio shares are superior to the industry-year cut-off and a value of 0 otherwise.

shows the results of the univariate analysis using Welch’s approximation of the parametric test of the independent t-test. It shows the significant difference (p-value) between the natural Log of audit fees (LnAFEES), the dependent variable, and the audit client’s financial assets measured using the F.V. model (F.V.O.), the F.V. of financial assets available for trading (FV_AFT), and the sale (FV_AFS) at the 0.01 level (t-value = −12.9414), the Log of audit fees (LnAFEES) at the 0.01 level. A longer, more complicated, and more dangerous auditing procedure may be expected if the F.V. model is used as the foundation for assessment. This finding validates that following the use of the F.V. model, inherent uncertainties increased due to managerial bias. To compensate for this increased complexity and risk in assessing fair values, auditors seek higher audit fees by putting in more effort [3,50,53].

5.3. Regression Analysis

Table 8. Fixed effects regression results.

DV = LnAFEES Variables	Model 1 Coeff. (t)	Model 2 Coeff. (t)	Model 3 Coeff. (t)	Model 4 Coeff. (t)	Model 5 Coeff. (t)
Intercept	3.221	3.435	3.577	3.568	3.659
	(18.76) ***	(20.44) ***	(21.35) ***	(21.30) ***	(21.69) ***
FV_TA	0.360
	(4.34) ***
FV_Option		0.000			0.000
		(1.310)			(1.390)
FV_AFT			0.000		0.000
			(5.88) ***		(3.74) ***
FV_AFS				0.000	0.000
				(5.74) ***	(3.36) ***
SIZE	0.319	0.308	0.301	0.302	0.297
	(29.21) ***	(28.44) ***	(28.08) ***	(28.13) ***	(27.53) ***
SUBS	0.025	0.026	0.021	0.021	0.019
	(5.51) ***	(5.67) ***	(4.52) ***	(4.63) ***	(4.22) ***
ROI	0.000	0.000	0.000	0.000	0.000
	(2.83) ***	(3.11) ***	(2.83) ***	(2.84) ***	(2.78) ***
LEV	0.000	0.000	0.000	0.000	0.000
	(8.94) ***	(8.74) ***	(8.51) ***	(8.41) ***	(8.36) ***
GROWTH	−0.005	−0.005	−0.007	−0.006	−0.007
	(−1.240) *	(−1.190)	(−1.700) *	(−1.380)	(−1.690)
RECINV	0.015	0.018	0.015	0.018	0.016
	(1.120)	(1.290)	(1.130)	(1.310)	(1.170)
BLOCK_OWN	−0.274	−0.275	−0.275	−0.272	−0.268
	(−3.83) ***	(−3.83) ***	(−3.87) ***	(−3.83) ***	(−3.79) ***
FOR_OWN	0.566	0.575	0.596	0.585	0.598
	(7.95) ***	(8.03) ***	(8.40) ***	(8.26) ***	(8.47) ***
INST_OWN	0.092	0.100	0.105	0.104	0.102
	(1.440)	(1.560)	(1.650)	(1.630)	(1.610)
BIG4	0.446	0.443	0.438	0.437	0.436
	(12.72) ***	(12.57) ***	(12.57) ***	(12.53) ***	(12.55) ***
TENURE	0.098	0.115	0.116	0.112	0.116
	(3.13) ***	(3.68) ***	(3.74) ***	(3.63) ***	(3.76) ***
OPINION	0.011	0.030	0.019	0.023	0.015
	(0.240)	(0.670)	(0.440)	(0.520)	(0.350)
N	1470	1470	1470	1470	1470
Prob > F	(13) ***	(13) ***	(13) ***	(13) ***	(18) ***
Adj. R2	76.06%	75.96%	76.37%	76.36%	77%
Mean VIF	1.38	1.36	1.38	1.37	1.38

*** and * indicate statistical significance at the 0.01 and 0.10 levels, respectively, using a two-tailed test. Note: This table presents the results of the random effect regression of Log of audit fees (LnAFEES) on the F.I. factors with fixed effects for subindustries following Abernathy et al. (2019) [51]. All variables are defined in Table 3.

displays the outcomes of four fundamental models: The direct impact of FV_TA and audit fees may be seen in model 1. There are natural effects on audit fees in models 2–4; however, model 5 merged the components in one regression model to assess their combined influence on the dependent variable and confirm the single effect of each variable on audit fees. All five models have a p-value of more than 0.01 at the 0.01 level, with decent explanatory power between 76% and 77%. According to the current models, the R2 of audit fees in emerging countries is comparable to the R2 of prior studies [52].

The findings of model 1 regression, demonstrates a fairly strong correlation between the percentage of fair-valued assets and audit fees (Coeff. = 0.360, Robust t = 4.34). This conclusion is consistent with the results of the prior univariate study. Furthermore, the regression result is compatible with other research, such as [14,57]. As a result of the F.V.A.’s passage, auditors must expend more time and effort on analysing the underlying risks and complexity [58]. However, this discovery contradicts [50,53,59]. In Ref. [60], for example, the authors failed to find a significant link, although the authors in [53,59] did find one. The fundamental reason for the discrepancy is that previous assessments utilised assets with a different fair-value structure than those used in this analysis. As a result, hypothesis 1 is accepted.

Model 2 revealed no significant relationship between the fair value option (F.V.O.) and audit fees (coeff. = 0.000, robust t = −1.310). The result is in an agreement with [50]. This conclusion was influenced by the fact that, in response to the negative repercussions of the F.V. model’s implementation in Jordan, the government issued new F.V. laws before the end of 2007. J.S.C. approved the new F.V. rules—“Instructions on the Mandatory Policies and Standards for Re-Evaluation of Fair Value and Disposition of Re-Evaluation Surplus”—to combat market instability. These rules imposed the following requirements: First, profits resulting from the F.V.M.s of trading securities must be recorded in businesses’ retained earnings statements as unrealised gains. However, companies cannot pay unrealised earnings to shareholders as dividends. Second, H.C. should be utilised instead of applying the I.A.S. 40′s F.V. accounting to investment assets and stating their fair values in the notes to financial statements. Finally, H.C. for property, plant, and equipment will be utilised with the I.A.S. 16 standards. These instructions and restrictions are primarily intended to restrict the usage of optional F.V.M.s. This legislation prohibits the voluntary acknowledgement of appropriate value modifications in the financial statements’ body.

Consequently, such improvements are intended to reduce the volatility of publicly traded corporations’ reported earnings [18] due to the government’s constraints in using the fair value option. Therefore, auditing this account does not influence the audit fees imposed by external auditors in Jordan. As a result, Hypothesis 2 is rejected.

There is a statistically significant correlation between audit fees and fair-valued financial assets available for trading or sale (FV_AFT) and sale (FV_AFS) in models 3 and 4 (coeff. = 0.000, robust t = 5.78). According to these findings, auditors doing F.V.D. audits are most responsible for reducing the danger of exaggerated assets due to agency conflict [14,50,55]. This finding supports the agency theory. These results show that auditors in Jordan devote more time and effort to assessing fair-valued assets because of the complexity and hazards they confront. According to Abdullatif [18], Jordanian enterprises aggressively employ F.V. to suit the interests of managers because of the agency issue. Consequently, the Jordanian capital market was plagued by substantial matters due to this fraud, which exacerbated market instability. Due to a lack of active Jordanian markets, inadequate corporate governance systems, and a lack of norms for measuring and auditing fair value, fraud and abuse are prevalent [39].

As previously discussed, the lack of reliable F.V.M.s which prompted the government to establish specific regulations concerning F.V.A. may be the main reason for the significant positive findings on the effect of fair-valued financial assets available for trading and sale (FV_AFT and FV_AFS) on the audit fees. There has been a considerable rise in auditors’ effort and complexity when dealing with contentious F.V. issues after the publication of the “new fair value rules” at the end of 2007 and their subsequent 2011 amendments. Detecting management fraud and misstatements, thus, takes up more time for Jordanian auditors than it should. Increased financial reporting quality is regarded as a good signal that aids stakeholders in their decision-making process.

Furthermore, the Jordanian government’s growing focus on the quality of financial reports, notably for international investors and shareholders following the “Jordan 2025 plan,” has contributed to these achievements. The adoption of the I.F.R.S.s is a critical component of this strategy. Jordan’s legal system has transitioned toward a typical law structure, emphasising investor protection [45]. As a result, Jordan’s capital market has become an essential source of funding, and the quality of publicly available financial information has dramatically improved [60]. Consequently, external auditors demanded high audit fees to examine financial asset figures that must be evaluated according to the F.V. model by law, such as fair-valued financial assets accessible for trade and selling instead of the appropriate value choice. Hypotheses 3 and 4 are rejected as null. The study accepted the alternative hypothesis that fair-valued financial assets accessible for trade and sale have a considerable impact on the levied audit fees.

Additionally, model 5 findings corroborate the regression outcomes given in models 1–4. The results of the control variables utilised in this analysis are not significantly different from those reported by previous research.

6. Sensitivity Analysis

6.1. Excluding (Big Four Auditors)

In

Table 9. Fixed effects regression results.

DV = LnAFEES Variables	Model (1) Coeff. (t)	Model (2) Coeff. (t)	Model (3) Coeff. (t)	Model (4) Coeff. (t)	Model (5) Coeff. (t)
Intercept	2.314	2.535	2.697	2.689	2.783
	(14.02) ***	(15.83) ***	(16.81) ***	(16.76) ***	(17.17) ***
FV_TA	0.366
	(4.20) ***
FV_Option		0.000			0.000
		(1.120)			(1.200)
FV_AFT			0.000		0.000
			(5.77) ***		(3.67) ***
FV_AFS				0.000	0.000
				(5.63) ***	(3.31) ***
SIZE	0.375	0.364	0.356	0.356	0.351
	(35.92) ***	(35.32) ***	(34.82) ***	(34.86) ***	(34.12) ***
SUBS	0.025	0.025	0.020	0.020	0.019
	(5.14) ***	(5.24) ***	(4.11) ***	(4.21) ***	(3.79) ***
ROI	0.000	0.000	0.000	0.000	0.000
	(2.68) ***	(2.98) ***	(2.72) ***	(2.73) ***	(2.67) ***
LEV	0.000	0.000	0.000	0.000	0.000
	(7.84) ***	(7.66) ***	(7.43) ***	(7.33) ***	(7.27) ***
GROWTH	−0.007	−0.007	−0.009	−0.008	−0.009
	(−1.630)	(−1.590)	(−2.10) **	(−1.780) *	(−2.09) **
RECINV	0.284	0.265	0.250	0.248	0.241
	(4.14) ***	(3.85) ***	(3.66) ***	(3.64) ***	(3.54) ***
BLOCK_OWN	−0.162	−0.164	−0.164	−0.161	−0.158
	(−2.17) **	(−2.19) **	(−2.23) **	(−2.18) **	(−2.15) **
FOR_OWN	0.556	0.565	0.587	0.576	0.590
	(7.44) ***	(7.52) ***	(7.89) ***	(7.75) ***	(7.96) ***
INST_OWN	0.212	0.220	0.224	0.222	0.221
	(3.20) ***	(3.31) ***	(3.40) ***	(3.36) ***	(3.36) ***
TENURE	0.026	0.044	0.046	0.042	0.046
	(0.820)	(1.370)	(1.430)	(1.330)	(1.450)
OPINION	0.032	0.052	0.040	0.044	0.036
	(0.680)	(1.110)	(0.870)	(0.950)	(0.780)
N	1470	1470	1470	1470	1470
Prob > F	(12) ***	(12) ***	(13) ***	(12) ***	(14) ***
Adj. R2	73.69%	73.39%	76.37%	73.96%	74.19%
Mean VIF	1.34	1.32	1.38	1.33	1.35

***, **, and * indicate statistical significance at the 0.01, 0.05 and 0.10 levels, respectively, using a two-tailed test. Note: This table presents the results of the random effect regression of Log of audit fees (LnAFEES) on the F.I. factors excluding the big four variables with fixed effects for subindustry following Abernathy et al. (2019) [51]. All variables are defined in Table 3.

, models 1–5 were retested in light of previous research to confirm that the primary analysis findings were not influenced by an auditor component, big four [61,62]. The results are consistent with those reported in the initial analyses and remain unchanged.

6.2. Excluding the Year of the Crisis (2008)

We retested the proposed hypotheses excluding 2008 firm-year data from the whole sample, in

Table 10. Fixed effects regression results.

DV = LnAFEES Variables	Model 1 Coeff. (t)	Model 2 Coeff. (t)	Model 3 Coeff. (t)	Model 4 Coeff. (t)	Model 5 Coeff. (t)
Intercept	3.163	3.380	3.524	3.498	3.592
	(17.85) ***	(19.46) ***	(20.35) ***	(20.20) ***	(20.58) ***
FV_TA	0.370
	(4.30) ***
FV_Option		0.000			0.000
		(1.230)			(1.310)
FV_AFT			0.000		0.000
			(5.65) ***		(3.70) ***
FV_AFS				0.000	0.000
				(5.14) ***	(2.68) ***
SIZE	0.321	0.309	0.303	0.304	0.299
	(28.38) ***	(27.59) ***	(27.27) ***	(27.37) ***	(26.79) ***
SUBS	0.026	0.026	0.021	0.022	0.020
	(5.42) ***	(5.51) ***	(4.38) ***	(4.57) ***	(4.15) ***
ROI	0.000	0.000	0.000	0.000	0.000
	(2.56) **	(2.94) ***	(2.66) ***	(2.63) ***	(2.60) ***
LEV	0.000	0.000	0.000	0.000	0.000
	(8.39) ***	(8.17) ***	(7.92) ***	(7.89) ***	(7.81) ***
GROWTH	−0.004	−0.004	−0.006	−0.005	−0.006
	(−0.830)	(−0.790)	(−1.300)	(−0.990)	(−1.300)
RECINV	0.226	0.208	0.194	0.194	0.186
	(3.29) ***	(3.01) ***	(2.83) ***	(2.83) ***	(2.73) ***
BLOCK_OWN	−0.276	−0.277	−0.277	−0.276	−0.271
	(−3.71) ***	(−3.70) ***	(−3.74) ***	(−3.72) ***	(−3.67) ***
FOR_OWN	0.537	0.546	0.567	0.555	0.569
	(7.24) ***	(7.31) ***	(7.66) ***	(7.50) **	(7.71) ***
INST_OWN	0.096	0.108	0.113	0.111	0.110
	(1.440)	(1.600)	(1.700)	(1.670)	(1.650)
BIG4	0.443	0.438	0.433	0.434	0.432
	(12.12) ***	(11.91) ***	(11.89) ***	(11.91) ***	(11.91) ***
TENURE	0.093	0.110	0.110	0.110	0.113
	(2.86) ***	(3.41) ***	(3.44) ***	(3.44) ***	(3.52) ***
OPINION	0.005	0.027	0.016	0.021	0.000
	(0.110)	(0.580)	(0.350)	(0.450)	(1.310)
N	1470	1470	1470	1470	1470
Prob > F	(13) ***	(13) ***	(13) ***	(13) ***	(15) ***
Adj. R2	76.07%	75.77%	76.31%	76.21%	76.47%
Mean VIF	1.39	1.37	1.39	1.39	1.40

*** and ** indicate statistical significance at the 0.01, 0.05, and 0.10 levels, respectively, using a two-tailed test. Note: This table presents the results of the random effect regression of Log of audit fees (LnAFEES) on the F.I. factors excluding the crisis year of 2008 with fixed effects for subindustry following Abernathy et al. (2019) [51]. All variables are defined in Table 3.

. All results remain unchanged.

7. Conclusions

We report for the first time empirical results on the impact of the three main items of financial assets measured by the F.V. model on audit fees under the principle-based accounting standards for the F.V. model: the I.F.R.S.s, using data from 1470 firm-year observations from 105 Jordanian banks from 2005 to 2018. The study results include the theory of agency, signalling, and stakeholders. According to the regression study and in line with the literature, the proportion of fair-valued assets and audit fees have a high positive link [14,50,53,57,58,59,60]. The results are consistent with the agency, signalling, and stakeholder participation theories because the conflict between auditing increased business risk and measurement uncertainty, such as F.V.E.s. In this situation, auditors may aid stakeholders in requiring plain and trustworthy F.V. metrics, therefore mitigating the agency information asymmetry problems [41,53]. When examining the three categories of financial assets that the F.V. model assesses, namely the F.V.O., H.F.T., A.F.S., and audit fees, it becomes clear that there is no association between the F.V.O. and audit fees. According to the study’s findings, more involved and dangerous audits cost more money.

Academics, the audit profession, and government organisations in Jordan are anticipated to benefit from the results of this study. Jordan’s regulatory authorities will benefit from the study’s results in monitoring and regulating the external auditing profession. Additionally, the results might be utilised to calculate audit fees. Due to this expanded inclusion, a broader range of contexts, including Middle Eastern nations with comparable cultural and institutional characteristics and accounting and auditing standards, may now benefit from these results. This research may be relevant to more Middle Eastern countries and a more extended period to capture the effect of economic instability during the devastating COVID−19 outbreak. These and other factors contribute to a fuller picture of the long-term impacts of F.V.A. adoption.