The effect of management characteristics on audit report readability

Salehi, Mahdi; Zimon, Grzegorz; Seifzadeh, Maryam

Article

The effect of management characteristics on audit

report readability

Economies

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Suggested Citation: Salehi, Mahdi; Zimon, Grzegorz; Seifzadeh, Maryam (2022) : The effect of

management characteristics on audit report readability, Economies, ISSN 2227-7099, MDPI, Basel,

Vol. 10, Iss. 1, pp. 1-23,

https://doi.org/10.3390/economies10010012

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Citation: Salehi, Mahdi, Grzegorz

Zimon, and Maryam Seifzadeh. 2022.

The Effect of Management

Characteristics on Audit Report

Readability. Economies 10: 12.

https://doi.org/10.3390/

economies10010012

Academic Editor: Angela Roman

Received: 22 October 2021

Accepted: 20 December 2021

Published: 1 January 2022

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economies

Article

The Effect of Management Characteristics on Audit

Report Readability

Mahdi Salehi

* , Grzegorz Zimon

* and Maryam Seifzadeh

Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran

Department of Finance, Banking, and Accountancy, The Faculty of Management, Rzeszow

University of Technology, 35-959 Rzeszow, Poland

Economics and Administrative Sciences, Qeshm Branch, Islamic Azad University, Qeshm 7953163135, Iran;

[email protected]

* Correspondence: [email protected] (M.S.); [email protected] (G.Z.)

Abstract:

The present study investigates the relationship between management characteristics (man-

agerial entrenchment, CEO narcissism, overconﬁdence, board effort, real and accrual-based earnings

management) and the audit report readability of listed ﬁrms. In other words, this paper seeks to

answer the question of “whether management characteristics can have a favourable effect on the

audit report readability or not.” The multivariate regression model is used for this study. Research

hypotheses were also examined using a sample of 1004 observations on the Tehran Stock Exchange

during 2012–2018 and by employing multiple regression patterns based on a panel data technique

and ﬁxed effects model. The results show a negative and signiﬁcant relationship between managerial

entrenchment and real and accrual-based earnings management and the audit report readability,

based on the FOG index, and a positive and signiﬁcant relationship between management narcissism,

CEO overconﬁdence, and board effort and the audit report readability, based on the FOG index.

Moreover, a negative and signiﬁcant relationship exists between management entrenchment, CEO

overconﬁdence, real and accrual-based earnings management, and audit report readability based

on text length and Flesch indices. A positive and signiﬁcant relationship was evident between CEO

narcissism and board effort and audit report readability based on the same indices. Besides, research

models were also examined for more conﬁdence using other additional methods, including FE, T + 1,

ABB, and GMM, which conﬁrm the study’s preliminary results. Since the present study is the ﬁrst

paper to investigate such a topic in the emergent markets, it provides valuable information about

intrinsic and acquisitive characteristics of management for users, analysts, and legal institutions that

contribute signiﬁcantly to ﬁnancial statement readability.

Keywords:

managerial entrenchment; CEO overconﬁdence; real and accrual-based earnings manage-

ment; audit report readability; board effort

1. Introduction

Audit report communications’ effectiveness is partly a function of ease of readability

and understanding of audit reports. Hence, the audit report is the main factor between

auditors and ﬁnancial statement users. Therefore, for such a relationship to be effective,

the auditor’s presented report should be easily understandable for the users and their

references to make sound decisions. In other words, ﬁnancial statement users should be

able to read the audit report easily and understand it. To some extent, comprehending

a written text is under the inﬂuence of the existing degree of difﬁculty in that text. The

previous studies, including Still (1972); Regazzi (1974); and Soper and Dolphin (1964), show

that readability contributes to the effectiveness of the relationship between the auditor and

ﬁnancial statement users.

Therefore, the audit report source of the business annual ﬁnancial reports is essential,

since ﬁnancial statements are provided based on such annual reports. The audit report

Economies 2022, 10, 12. https://doi.org/10.3390/economies10010012 https://www.mdpi.com/journal/economies

Economies 2022, 10, 12 2 of 23

is an inseparable part of the relationship between ﬁnancial statement users and business

economic information. Readability is a criterion for measuring the existing complication

within a text. Within a standard report for business, text narration indicates information

disclosure from the managers’ side. The US Securities and Exchange Commission (SEC)

acted clearly for the audit ﬁrms’ extremely complicated reports. As suggested by the

head of the Commission, some direct and transparent measures should be adopted for

combating complicated reports. According to SEC, the main reason for presenting and

disclosing information from the business ﬁrms’ side is to inform the investors and other

ﬁnancial statement users. Therefore, the presented reports should be understandable for

the public users, such that, by referring to them, the ﬁnancial statement users can easily

make decisions about their economic plans (SEC 2007). Li (2008) declares that the annual

report’s readability has enhanced the performance of business ﬁrms. Readability improves

auditing; some argue that the type of audit opinion affects investment analysts’ investment

decisions (Duréndez Gómez-Guillamón 2003; Zimon and Chlodnicka 2019), loan lending

(Duréndez Gómez-Guillamón 2003; Goicoechea et al. 2021) and investors’ decisions (Chen

et al. 2020; Kausar and Lennox 2017; Köhler et al. 2020; Ianniello and Galloppo 2015). The

audit report readability is important because audit reports are essential to analysts as a

signal of ﬁnancial statements’ reliability (Coram et al. 2011).

Burgstahler and Dichev (1997) state that managers conceal their earnings management

and managerial misbehavior, and complicate the ﬁnancial statements. Although businesses

deliver good news about reaching the objectives, they also have some derivers for conceal-

ing the tools used to fulﬁl the objectives. When the reported performance is different from

basic principles, the managers are expected to make the annual reports lengthier and use

circumlocution to hide their earnings management actions and misbehaviors.

Given the abovesaid facts, the present study assesses the relationship between man-

agement characteristics and audit report readability. In addition, this paper investigates

whether management entrenchment, CEO narcissism and overconﬁdence, board effort,

and real/accrual-based earnings management can enhance or debilitate the readability and

understanding of audit reports. Since no study has been carried out so far on such a topic

by considering the economic and political conditions of the emergent countries, including

Iran, the obtained results from this paper can provide the scholars and experts with helpful

information. Moreover, this paper’s results help develop science and knowledge in this

ﬁeld and ﬁll the existing literature gap to show the relationship between management

characteristics on auditors’ report readability. In the following, we discuss the theoretical

principles and conducted studies in this ﬁeld, methodology, data analysis, discussion,

and conclusion.

2. Theoretical Issues and Hypothesis Development

The audit report generally has a standard framework, and auditors are obliged to

be aligned with that for expressing their opinions. In a paragraph peculiar to opinion

principles, the auditor expresses a set of results that contain distortion, limitation, and

ambiguity. In this paragraph, the auditor is not limited to a particular framework and

voices his opinions relative to his experience and knowledge. Such a paragraph should

be understandable for all users, because a good relationship with the audit report users

will be established when the report is understandable for the readers. Today, auditing is

a well-established career, and all users are fully aware of the effect of decision-making

(Endaya and Hanefah 2013; Arena and Azzone 2009). However, it is noteworthy that

some factors will lower such effectiveness (Mihret and Yismaw 2007). Auditors should

identify such factors and neutralize their inﬂuences in their reporting, because users of audit

reports have relied on them for any kind of decision. In case of mistakes or dissatisfaction,

their professional credentials will be subject to question, and they will lose their position.

One factor affecting users’ inappropriate decisions, and even misleading them, is the audit

report’s unreadability. Writing audit reports will perplex the reader, for which specialization

and knowledge are required, and public users will not beneﬁt from the audit report.

Economies 2022, 10, 12 3 of 23

According to Standard 200, auditors’ primary duty is to assess the accuracy of annual

reports and give credit to ﬁnancial statements by voicing their opinions. Hence, the less the

ﬁnancial statement disorders, the higher the quality is expected to be from the audit report.

It is worth mentioning that the simpler the language of such reports, the better the users

can beneﬁt from them, since several ﬁnancial statement users may not have the required

specialization in this ﬁeld. Therefore, the report should be readable and straightforward to

understand by the users and applicable for their decisions. In this regard, Li (2008) posits

that investors less attract ﬁrms with less readable annual reports. Tan et al. (2015) show

that better readability of ﬁnancial statements will improve future decisions and investors

and users of ﬁnancial statements. Sultan (2016) studied the relationship between annual

reports’ readability and the auditing role. He found that less readable ﬁnancial statements

increase audit costs.

On the other hand, Lo et al. (2017) indicate that those business ﬁrms that embark

on either real or accrual-based earnings management have had highly complicated and

lengthy annual reports in that year. Ajina et al. (2016) also obtained similar ﬁndings to Lo

et al. (2017). Earnings management is a method that is increasingly used for manipulating

ﬁnancial results. However, a few studies have assessed the effect of that on the readability

of the independent auditor’s report. Pentland (1993); Carrington and Catasús (2007) show

that earnings management has a negative effect on the working volume of auditors and

ease of the auditing process (e.g., risk of non-discovery due to nonrealization of errors and

mistakes). According to the conducted studies, including Guénin-Paracini et al. (2014),

earnings management, especially real earnings management, causes auditors’ workload.

Lobo and Zhou (2001) express that, in ﬁrms with readable information, since their disclosure

policy and the amount of disclosure are easily tractable by the shareholders, managers are

less willing to manipulate the earnings. Ajina et al. (2016) show that earnings management

would decline ﬁnancial statement readability. Cheng et al. (2018) show a positive and

signiﬁcant relationship between real and accrual-based earnings management and ﬁnancial

statement readability. Salehi et al. (2020a) observe a negative and signiﬁcant relationship

between accrual-based earnings management and family and nonfamily ﬁrms’ reputation.

Seifzadeh et al. (2021) declare a signiﬁcant relationship between real and accrual-based

earnings management and ﬁnancial statement comparability. Moardi et al. (2019) perceive

that opportunistic earnings management is negatively and signiﬁcantly associated with

future cash ﬂows and shows no signiﬁcant relationship between accrual-based earnings

management and future cash ﬂows in the pharmaceutical industry. Such a relationship is

negative and inﬂuential in the car industry. So, the ﬁrst and second hypotheses of the study

are as follows:

Hypothesis 1 (H1).

There is a signiﬁcant relationship between real earnings management and

audit report readability.

Hypothesis 2 (H2).

There is a signiﬁcant relationship between accrual-based earnings management

and audit report readability.

The relationship between management entrenchment and board effort and audit

reports’ readability’.

In recent years, the amount of research carried out was mostly about the readability of

ﬁnancial statements and less attention to audit reports’ readability. In this study, we seek

the readability of auditors’ reports and their relationship with management characteristics.

On the other hand, according to corporate governance mechanisms, the CEO has always

been the ﬁrst executive power in organizations, and this factor arms him with a consider-

able inﬂuence on the board of directors. Thus, a conﬂict of interests between managers

and shareholders, given managers’ executive power, raises some organizations’ problems.

Moreover, the CEO’s dual role causes the managers to dominate the board of directors

to the extent possible and control the board’s receivable information. Broadly, compared

Economies 2022, 10, 12 4 of 23

with their peers, dual managers are more willing to better show the performance of the

business ﬁrm (Davidson et al. 2005). One of the motivational factors for manipulating

accounting earnings to show the performance of an organization better by managers is

CEO compensation, because one of the appropriate criteria for allocating the compensation

of managers is measuring their performance; furthermore, CEO compensation is positively

associated with the size and ﬁrm performance, and so CEO duality moderates the positive

association between CEO compensation and ﬁrm performance. Since there are no good

criteria for allocating rewards to managers, managers’ performance evaluation has always

been a metric for granting rewards. Hence, accounting ﬁgures and information are a

kind of available criterion for measuring managers’ rewards, among which accruals are

one of the major contributing factors for managers when signing contracts

(Kazan 2016).

Accruals’ presence provides the opportunity for managers to employ accounting policies

to manage the accruals and manipulate the ﬁrm’s real ﬁnancial events to preserve their

beneﬁts (Bianchi and Chen 2015). Li and Kuo (2017) show a positive relationship between

CEO compensation and earnings management. Besides, managers with ﬁnancial special-

ization will carry out better earnings management due to more familiarity with accounting

techniques and accounting policies.

Further, Krishnan et al. (2009) posit that managers with ﬁnancial knowledge are more

competent than others in earnings management through accruals and carry out some real

activities, including excessive production and the decline of optional costs. In other words,

managers with ﬁnancial experience guide the analysts more frequently, and the earnings

management less so. They have a more in-depth understanding of ﬁnancial information

disclosure’s advantages concerning the increased ﬁrm value and decreased information

asymmetry (Matsunaga and Yeung 2008; You and Zhang 2009).

Managerial entrenchment is a phenomenon that can be either useful or detrimental

to the business ﬁrm. Such a phenomenon occurs when the manager has a dual role (CEO

duality means the manager is both the head or vice president of the board and the CEO of

the ﬁrm at the same time (Salehi et al. 2018)). The presence of entrenched managers can

have favorable inﬂuences on the ﬁrm in the long run, but such a phenomenon can hurt

the Stock Exchange. For example, lowering the dividend can cause the nonsatisfaction

of short-term investors, reluctance of such investors, and withdrawal of capital from the

Stock Exchange (Salehi et al. 2018; Frankel and Kelly 2019; Wong et al. 2011). Moreover,

Zhou (2017) indicates that older managers present more readable reports than newer

ones. The tenure of managers is one of the salient features used to calculate managerial

entrenchment in this paper. In addition, there is a determining role in the quality of

papered ﬁnancial statements and management characteristics that affect the readability

of ﬁnancial statements (Seifzadeh et al. 2020). Smulders (1973) declares a signiﬁcantly

negative relationship between management entrenchment and the ﬁrm’s ﬁnancial leverage.

Levy and Szafarz (2016) show that parallel ownership when new shares are waiting

and should be granted to the management is a vital tool for the management entrenchment.

Salehi et al. (2018) found a signiﬁcant relationship between management entrenchment,

innovation, and ﬁrm reputation. Martins (2019) states a negative and signiﬁcant rela-

tionship between management entrenchment and cash holding. Akbari et al. (2018)

perceive a signiﬁcant relationship between managerial characteristics and tax avoidance.

Meo et al. (2017)

show that management entrenchment can have some advantages for the

business ﬁrms and their owners. When there are some motivations for increasing the

ﬁrm performance, the entrenched managers are less willing to be involved in earnings

management activities that endanger shareholders’ interests. Salehi et al. (2020b) indicate

no signiﬁcant relationship between management ability and competition in the product

market, which means management ability has no impact on competition in the product

market. Salehi and Moghadam (2019) reveal a positive and signiﬁcant relationship between

managerial characteristics, namely management ability, and CEO conﬁdence and ﬁrm

performance. These two managerial features enhance the performance level of business

ﬁrms.

Surroca et al. (2020)

indicate that management entrenchment is not always unwel-

Economies 2022, 10, 12 5 of 23

come, and social responsibility is not always beneﬁcial. That management entrenchment is

entangled with social responsibility, and each of them can, in some speciﬁc ways, increase

the interests of shareholders and the value of business ﬁrms. Lari Dashtbayaz et al. (2020)

show that board independence, ﬁnancial expertise, and audit committee are associated

negatively and signiﬁcantly with relational capital. The relationship between audit commit-

tee independence and relational capital is positive and signiﬁcant. Moreover, their study

results show that there is also a positive relationship between board independence and

human capital, and the relationship between audit committee size and human capital is

signiﬁcant and negative. Seifzadeh et al. (2021) posit that managerial entrenchment is

negatively associated and signiﬁcantly with ﬁnancial statement comparability.

Further, the board effort and ﬁnancial statement comparability are associated positively

and signiﬁcantly. Salehi et al. (2020a) observe that ﬁrms’ management entrenchment and

ﬁnancial performance, based on the indices of return on assets and Tobin’s Q, have a

positive and signiﬁcant relationship. Moreover, their results show that there is a positive

and signiﬁcant relationship between management entrenchment and social responsibility,

so the third and fourth hypotheses are as follows:

Hypothesis 3 (H3).

There is a significant relationship between board effort and audit report readability.

Hypothesis 4 (H4).

There is a signiﬁcant relationship between management entrenchment and

audit report readability.

The relationship between CEO narcissism and audit report readability.

Today, the management of business ﬁrms has a determining role in increasing efﬁ-

ciency and output. The increasing complication of societies has caused efﬁcient managers

to be recruited for managing business ﬁrms. Most scholars believe that decision-making

is among the most critical management cores that inﬂuences a ﬁrm’s failure or success

(Daft 1989). On the other hand, according to psychology, making an appropriate decision

from the managers’ side is also inﬂuenced by personal characteristics (narcissism and

overconﬁdence) and behaviors. Narcissism and overconﬁdence are a type of psychological

disorder, showing itself with some signs, including self-superiority, ignoring others, exces-

sive reward-seeking, and being at the center of attention (Tamborski et al. 2012). Hence,

such people in business ﬁrms, in terms of dominating others, annoying people, and making

decisions in such units, are based on agitation. So, such ﬁrms’ operations and performance

face serious interventions, because the managers have the intransitive power to affect

the unit’s strategies and general structure. The ﬁrm’s performance will be afﬂicted. The

conducted studies (e.g., Conger 2002; Chatterjee and Hambrick 2007; Olsen et al. 2014;

Olsen and Stekelberg 2016) show that narcissistic managers utilize the business as a tool

for increasing their beneﬁts, so such ﬁrms suffer from a weak organization. Hence, some

factors, such as risky operations, fraud, earnings management, and rules and regulations

infringement, are rampant (Johnson et al. 2013; Amernic and Craig 2010). Since the respon-

sibility for providing ﬁnancial reports is up to the board and business management is one

factor to be considered, in this paper, the effect of narcissistic and overconﬁdent managers,

managerial entrenchment, and board efforts on audit report readability is explored, because

such managers have personality characteristics, such as selﬁshness, exploiting others, and

seeking dominance (Campbell et al. 2011). Self-superiority is more likely than others to

present fraudulent and complicated ﬁnancial reports. This occurs because such managers

gain personal beneﬁts, satisfy the sense of superiority and arrogance, do not mind the

presented rules and regulations, manipulate ﬁnancial reports, make them complicated,

and conceal their misbehavior actions to draw the admiration and attention of others

(Capalbo et al. 2018). This will decline ﬁnancial statements’ readability and follow the

independent auditor’s report (Bloomﬁeld 2008). Therefore, we can claim that narcissism

can contribute to the managers’ judgment about the chance of their success. Extremely

narcissistic managers may consider those actions deemed impossible publicly, or with little

Economies 2022, 10, 12 6 of 23

chance of success, as optimistic and perform such bold efforts to attract others’ attention

(Wallace and Baumeister 2002). According to Nietzsche, narcissistic managers are “superior

men.” The regular rules cannot be applied. Such a belief can increase the chance of immoral

actions, such as earnings management, and justifying them. Zhang and Wiersema (2009),

Hasan (2017) show that competent managers publish more readable ﬁnancial reports.

Ajina et al. (2016); Bonsall and Miller (2017); Ertugrul et al. (2017) also note that ﬁnancial

statement readability leads to the decline in debt costs. Ham et al. (2017) also declare

that narcissistic managers often have the decision-making process under their dominance

and are unwilling to consult with others. Hence, the chance of earnings management is

higher in business with narcissistic managers. Ham et al. (2018) show a negative and

signiﬁcant relationship between narcissistic managers and performance in business ﬁrms.

Church et al. (2019)

identify a meaningful relationship between auditors’ narcissism and

aggressive reporting. Salehi et al. (2020c) indicate a negative and signiﬁcant relationship

between managers’ overconﬁdence and conservatism. They conclude that a negative and

signiﬁcant association exists between CEO overconﬁdence and real earnings management.

When overconﬁdent Iranian managers have ﬁnancial problems, they are not involved in

real earnings management. This does not increase the ﬁrm value in the long run, but hurts

the business units. Seifzadeh et al. (2020) show a positive and signiﬁcant relationship

between managers’ narcissism, overconﬁdence, and ﬁnancial statement readability. So, the

ﬁfth and sixth hypotheses of the study are as follows:

Hypothesis 5 (H5).

There is a signiﬁcant relationship between CEO narcissism and audit report

readability.

Hypothesis 6 (H6).

There is a signiﬁcant relationship between managers’ overconﬁdence and audit

report readability.

3. Research Methodology

The statistical population of this paper includes all listed ﬁrms on the Tehran Stock

Exchange. The systematic elimination method is used for samplings and, after imposing the

following conditions, the statistical sample of the study will be selected with the following

conditions:

Firms should be enlisted on the Tehran Stock Exchange until the end of 2011;

The required ﬁnancial information should be presented completely during the period

of the study;

Firms should not be afﬁliated with investment ﬁrms, banks, insurance, and ﬁnancial

intermediaries.

Concerning these limitations at the end of 2018, the ﬁnal sample was obtained accord-

ing to Table 1.

Table 1. The number of ﬁrms in the statistical population.

Description

Eliminated Firms in

Total Periods

Total No. of

Firms

Total listed ﬁrms on the Tehran Stock Exchange 395

Eliminating ﬁnancial intermediaries, ﬁnancial

supply, insurance, and investment ﬁrms

Eliminating ﬁrms entered the Stock Exchange

during the study period

Eliminating due to lack of access to information 133

Statistical population 150

3.1. Data Collection and Method

The primary and raw information and data for hypothesis testing were collected using

the Tehran Stock Exchange information bank, including Tadbir Pardaz and Rah Avard-e

Economies 2022, 10, 12 7 of 23

Novin. The published reports of the Tehran Stock Exchange were obtained via direct access

(by analyzing the released reports in the Codal Website and manually collected data) to

CDs and by referring to rdis.ir website and other necessary resources.

3.1.1. Data Analysis Method

The data analysis method is cross-sectional and year-by-year (panel data). This paper

uses the multivariate linear regression model for hypothesis testing. Descriptive and infer-

ential statistical methods are used for analyzing the obtained data. Hence, the frequency

distribution table is used for describing data. At the inferential level, the F-Limer, Hausman

test, normality test, and multivariate linear regression model are used for hypothesis testing.

3.1.2. Research Model

The following models are used to examine the hypotheses of the study:

Model (1)

FOGit = a0 + a1MEit + a2Over.Conit + a3CEO_NARit + a4REMit + a5AEMit + a6BEFit + a7ageit + a8roait +

a9levit + a10GRWit + a11sizeit + a12IINVit + a13Intangit + a14OWNit + a15segit + a16busyit + a17currentit

+ a18restit + a19lossit + a20mtbit + a21Yearit + a22Industryit + εit

Model (2)

textindexit = a0 + a1MEit + a2Over.Conit + a3CEO_NARit + a4REMit + a5AEMit + a6BEFit + a7ageit +

a8roait + a9levit + a10GRWit + a11sizeit + a12IINVit + a13Intangit + a14OWNit + a15segit + a16busyit +

a17currentit + a18restit + a19lossit + a20mtbit + a21Yearit + a22Industryit + εit

Model (3)

ﬂashindexit = a0 + a1MEit + a2Over.Conit + a3CEO_NARit + a4REMit + a5AEMit + a6BEFit + a7ageit +

a8roait + a9levit + a10GRWit + a11sizeit + a12IINVit + a13Intangit + a14OWNit + a15segit + a16busyit +

a17currentit + a18restit + a19lossit + a20mtbit + a21Yearit + a22Industryit + εit

where:

Dependent variables

Auditor’s report readability is computed using the following three indices:

FOG Index:

FOG: Audit report readability. To calculate the audit report readability, according to

the study of (Lawrence 2013) Zhang, You, Lawrence, and Ajina et al., the following index

is used, the reliability and validity of which for examining Persian text readability are

conﬁrmed by some local scholars. The audit report readability index is FOG (FOGIND),

which is a function of two variables of sentence length (based on words) and complicated

words (deﬁned in the form of the number of three or multi-syllable words), and is calculated

as follows:

FOG index = (average no. of words in each sentence + percentage of complicated words) × 0.4

The process and manner of determination of audit report level of readability in the

above index are as follows:

Selecting a 100-word sample from the beginning, a 100-word sample from the middle,

and a 100-word sample from the end of the report, randomly;

Counting the number of sentences of each sample;

Determining average sentence length by dividing the number of words into the

number of complete sentences of each sample of 100 words;

Counting the number of existing three-syllable and more than three-syllable words

(complicated words) in each 100-word text;

Economies 2022, 10, 12 8 of 23

Adding the number of complicated words with the average number of words in

sentences;

Multiplying the number of complicated words and average words in sentences by the

ﬁxed ﬁgure of 0.4;

Calculating no. 4, 5, and 6 for two other 100-word samples;

Calculating the average results of all three samples by adding and dividing by number.

The relationship between the FOG index and readability level is as follows: FOG >

18 means the text is not readable and more complicated; 14–18 (hard text), 12–14 (average

text), 10–12 (acceptable text), 8–10 (easy text).

Text length index (INDEX):

The second index for ﬁnancial reporting readability is text length (index), which is

calculated as follows:

Text length index = Ln number of text words.

Since higher values of the above indices indicate lower audit report readability, each

calculated index is multiplied by

−

1 to obtain a direct criterion from the audit report

readability index.

Flesch Index: The Flesch index determines the degree of difﬁculty or simplicity of the

text based on two linguistic factors of average sentence length and the number of syllables

of each sample.

Flesch readability index = average number of words × − 1.015 (average words length × 262.835 − 84.6)

The process and manner of placement of ﬁnancial reporting readability in the above

index are as follows:

Calculating average word length: syllables are counted in the text and divided into

total numbers of the text;

Word length is multiplied by 84.6;

The obtained ﬁgure from the previous step is subtracted from 206.835;

Calculating the number of average words: the number of words of the text is divided

into the number of complete sentences;

The average number of words is multiplied by 1.015;

The obtained ﬁgure from the previous step is subtracted from the one calculated in

the third step to determine the degree of text simplicity.

The relationship between the Flesch index and readability level is as follows: 71 or

higher (extremely simple), between 60 and 70 (normal readability), lower than 60 (hard

and unreadable).

Independent variables

ME: managerial entrenchment, for the evaluation of which, according to the study of

Salehi et al. (2020a), the following six indices will be used:

Managerial ownership: the number of stocks available to the CEO divided by total

published stocks of the ﬁrm;

CEO tenure: the duration the CEO has been in position consistently until the year

under study;

CEO duality: if the CEO is the head or vice president of the board, 1; otherwise, 0;

Board compensation: the amount of compensation assigned to the approved board of

Annual Ordinary General Assembly in the year under study;

CEO change: if the CEO has changed during the year, 1; otherwise, 0;

Board independence: unbounded members to total board members.

This paper uses the exploratory factor analysis to calculate the management entrench-

ment variable. Factor analysis is a multivariate statistical method for classifying and

realizing the available structures among research data. This statistical method is usu-

ally used for two purposes: ﬁrst, the exploratory factor analysis enables us to combine

a broad spectrum of corporate governance variables to create managerial entrenchment

proxy, while, in the previous studies, either a limited set of corporate governance factors

were considered as managerial entrenchment or the problem of multilinearity is taken for

Economies 2022, 10, 12 9 of 23

granted, which can be due to the presence of control and independent corporate governance

variables in empirical methods, and, on the other hand, controlling the potential mutual

relationship between variables is a signiﬁcant and hard task. Second, one of the exploratory

factor analysis characteristics assigns a weight to each involved variable in managerial

entrenchment based on the correlation coefﬁcient matrix’s output. This method contrasts

with the previous studies that assume each corporate governance factor’s effect is equal.

As for the calculation of the variable of managerial entrenchment, initially, the informa-

tion related to six corporate governance factors that affect the motivation and management

competency is collected for each year–company. The linear correlation coefﬁcient matrix of

the above six variables is extracted, divided by year, and, ﬁnally, exploratory factor analysis

is carried out. The weight of each sixfold variable is obtained. The factor’s total weight

coefﬁcient achieves the variable of managerial entrenchment by a numerical value of the

related factor.

Over.CON: managers’ overconﬁdence. In this paper, the index of surplus investment

in properties is used to measure managers’ overconﬁdence as follows:

Following Schrand and Zechman (2012) study, this index indicates the amount of

surplus investment in properties achieved from the residual of total asset growth regression

in sales growth, estimated separately for each industry year. If the regression residual is

larger than 0, this index equals 1; otherwise, 0 will be assigned. This index’s basis is that

managers invest more inﬁrm than their peers in ﬁrms whose assets go up at a higher rate

than sales.

Assets.Grit = a0 + a1sales.Grit + εit

CEO-NAR: CEO narcissism

There are three criteria for measuring managerial narcissism:

Cash compensation index: narcissistic executive managers usually ask for higher cash

compensations and stabilize their organizations. The cash compensation index of managers

is achieved by dividing the approved cash compensation in the general assembly session

into the ﬁrm’s total payroll for the ﬁscal year.

CEO signature: it seems that those ﬁrms managed by CEOs with big signatures (a psy-

chological index for narcissism) are less efﬁcient than CEOs with small signatures. Recently,

a research program focusing on leaders’ signature size effort to judge a narcissistic leader’s

impacts on his organization (Campbell et al. 2011) measured 605 CEOs’ signatures with

10 years of working experience from 400 ﬁrms (afﬁliated with 500 premium stocks in the

New York market). All signatures were placed at the bottom of the annual ﬁnancial reports.

It is speciﬁed that bigger signatures, which indicate narcissistic personal characteristics,

dominance on others, and self-conﬁdence, are associated positively with the managers’

mis-spend and lower return of the property. Compared with other active members in that

industry, such managers are contradictorily more inclined to pay an increase.

It is worth mentioning that two cash compensation and signature criteria are used in

this paper to measure narcissism, since the ﬁrst index is not available due to the nondisclo-

sure of managers’ pictures by ﬁrms.

REM: real earnings management. Abnormal cash ﬂow (EM_CFO), abnormal cost

(EM_PROD), and abnormal discretionary costs (EM_DISX) are used for measuring ﬁrm

sales control, production control, and discretionary cost control. Formula (2) is used for

estimating abnormal cash ﬂow of the ﬁrm (EM_CFO), Formula (3) for estimating abnormal

production cost of the ﬁrm (EM_PROD), and Formula (4) for estimating the abnormal

discretionary cost of the ﬁrm (EM_DISX). In this paper, Formula (4) is employed for

estimating real earnings management.

CFOi,t Ai,t-1 = β11 Ai,t-1 + β2si,t Ai,t-1 + β3∆si,t Ai,t-1 + δi,t (1)

PRODi,t Ai,t-1 = β11 Ai,t-1 + β2si,t Ai,t-1 + β3∆si,t Ai,t-1 + β4∆si,t-1 Ai,t-1 + δi,t (2)

DISXi,t Ai,t-1 = β11 Ai,t-1 + β2si,t-1 Ai,t-1 + δi,t (3)

Economies 2022, 10, 12 10 of 23

Si,t in Formula (2) is the sales income of the ﬁrm i in the year t. Prodi,t in Formula (3)

is the total cost of the ﬁrm i of product in the year t, which equals the total product cost and

inventory change.

DISX,t in Formula (4) is the total ofﬁce costs and sales costs of the ﬁrm i in the year t.

For a similar industry and year, given the Formulas (2)–(4), EM_COF (abnormal cash ﬂow

of the ﬁrm), EM_PROD (abnormal production cost), and EM_DISX (abnormal discretionary

costs) are assigned to the regression residuals. Since the ﬁrm may select a combination of

these three methods, we used Cohen and Zarowin (2010) and Zang (2012) to create a total

index of real earnings management:

EM PROXY = EM PROD − EM CFO − EM DISX

AEM: accrual-based earnings management, the calculation of which uses the adjusted

Jone’s model. The coefﬁcients are estimated through Equation (2):

TAi,t Assetsi,t-1 = α11 Assetsi,t-1 + α2∆Salesi,t Assetsi,t-1 + α3PPEi,t Assetsi,t-1 + εi,t (4)

After estimating the coefﬁcients, nondiscretionary accruals are calculated after coefﬁ-

cient estimation:

NDAi,t Assetsi,t-1 = α11 Assetsi,t-1 + α2∆Salesi,t-∆ARi,t Assetsi,t-1 + α3PPEi,t Assetsi,t-1 (5)

Finally, for the calculation of the discretionary accruals, we have:

DAi,t Assets,t-1 = Tai,t Assets,t-1 − NDAi,t Assets,t-1 (6)

In the above equation, TA is accruals, Assets is total assets, Sales is income, AR is

accounts receivable, PPE is gross properties, machinery, and instrument, and NDA is

nondiscretionary accruals.

In this paper, the following formula is used for calculating accruals, which is referred

to as proﬁt and loss:

Accruals = Operational cash ﬂow − proﬁt before unpredicted items

Most previous studies have used discretionary accruals (DA) to measure earnings and

audit quality. This paper uses DA as a proxy for audit quality because it presents a degree

of negotiations related to audit setting decisions. Abnormal accruals of performance setting

estimate the size of DA.

BEF: board effort equal to the number of sessions held by the board during the year.

Control variables

LEV: ﬁnancial leverage, which is equal to total debts divided by total assets;

Age: ﬁrm age, which is equal to the time interval between ﬁrm establishment date

until the year under study;

Size: ﬁrm size, the natural logarithm of ﬁrm assets;

ROA: return on assets, which is equal to net proﬁt divided by total assets;

GRW: sales growth that is equal to the sales of this year minus that of the previous

year divided by sales of the previous year;

OWN: major shareholder, a shareholder with more than 5% ownership, 1; otherwise, 0;

linve: institutional shareholder, the number of stocks available to investors, public

institutions, banks, insurance, and state-owned institutions;

Intang: intangible assets to total assets of the ﬁrm;

Seg: the number of commercial sections of the ﬁrm in the year under study;

Current: a current ratio that is equal to total current assets divided by current debts;

Economies 2022, 10, 12 11 of 23

Rest: ﬁnancial restatement, if the ﬁrm has restated the ﬁnancial statements of the

current year, 1; otherwise, 0;

Loss: ﬁrm loss, should the ﬁrm be losing in the year under study, 1; otherwise, 0;

Busy: if the end of the fiscal year is set on January 20, one will be assigned; otherwise, 0;

Mtb: market value to book value of equity;

Year: dummy variable for the year.

Industry: dummy variable for industry.

4. Results

This paper uses three models to assess the relationship between management charac-

teristics (real/accrual-based earnings management, management entrenchment, managers’

overconﬁdence, managers’ narcissism, and board effort) and the audit report readability.

The present study (Table 2) has inserted the panel data method in its database, including

150 Iranian ﬁrms from 2012 to 2018. The variables of real/accrual-based earnings man-

agement, management entrenchment, managers’ overconﬁdence, managers’ narcissism,

board effort, auditor’s readability report, and a series of control variables have been used

for estimating the models.

Table 2. Descriptive statistics.

Variable OBS Mean Std.dev Min Max

Fog 1004 21.748 0.234 20.196 23.801

Textindex 1004 7.155 0.304 6.421 8.268

Flashindex 1004 99.816 18.432 54.921 177.105

Me 1004 17.016 6.449 0.111 28.229

Over con 1004 0.5 0.5 0 1

Ceonar 1004 0.011 0.022 0 0.364

Rem 1004 −2.54 0.178 −0.837 0.691

Aem 1004 0.066 0.055 0 0.378

Bef 1004 14.743 5.592 1 60

Age 1004 38.896 13.123 10 67

Roa 1004 0.104 0.161 −0.789 0.9

Lev 1004 0.623 0.259 0.105 2.626

Grw 1004 0.231 0.45 −0.739 3.579

Size 1004 14.235 1.447 10.532 19.773

Own 1004 0.51 0.209 0.021 0.994

Iinv 1004 0.594 0.323 0 0.994

Intang 1004 0.005 0.007 0 0.057

Seg 1004 14.235 3.414 7 32

Busy 1004 0.726 0.445 0 1

Current 1004 1.399 0.726 0.164 7.405

Rest 1004 0.73 0.443 0 1

Loss 1004 0.139 0.346 0 1

mtb 1004 4.405 7.514 −59.594 53.464

4.1. Linearity Test

According to Tables 3 and 4, by analyzing the linearity of variables, no linearity is

evident among variables, and they are independent of each other.

Economies 2022, 10, 12 12 of 23

Table 3. The collinearity model.

Model (1)

Variable VIF 1/VIF

Roa 2.25 0.445

Lev 2.23 0.447

Current 1.81 0.551

Loss 1.63 0.615

Iinv 1.59 0.629

Own 1.38 0.723

Size 1.38 0.725

Seg 1.33 0.751

Bef 1.22 0.820

Age 1.12 0.896

Busy 1.11 0.901

Aem 1.09 0.918

Intang 1.07 0.930

Rest 1.07 0.931

Grw 1.07 0.935

Ceonar 1.06 0.940

Overcon 1.06 0.946

Mtb 1.05 0.950

Me 1.05 0.951

rem 1.03 0.974

Mean VIF 1.33

As shown in the table, since the obtained VIF statistic for all variables is less than 10,

there is no linearity among model variables.

4.2. Sensitivity Analysis

Table 4 shows the results of sensitivity analysis model.

We should ﬁrst analyze whether the data are pooled or panel, using the F test to esti-

mate the model. This test’s null hypothesis expresses that data are pooled, and hypothesis

1 declares that data are panel. After performing the F test, H0 is rejected. The question

is based on which models of ﬁxed effects or random effects that the model is analyzable,

which is determined by the Hausman test. Regarding the pooled test results reported in

Table 6, the null hypothesis concerning the pooled data is rejected for the ﬁrst models at

99%. Hence, a model with panel data should be used to estimate the model’s coefﬁcients.

Moreover, according to Table 6, the Hausman test statistic based on the ﬁrst model’s

estimation equals 33.54. The probability level of 0.0294 is smaller than the table, so the

null hypothesis is rejected. Hence, a model with a ﬁxed effect is more appropriate for the

research model.

Table 6 shows a negative and signiﬁcant relationship between managerial entrench-

ment and real/accrual-based earnings management and auditor’s report readability based

on the FOG index. Their p-values are 0.000, 0.000, and 0.048 lower than the 0.05 signiﬁcance

level. Their coefﬁcients are 0.016, 0.096, and 0.217, showing a negative relationship between

these variables and the auditor’s report readability. Moreover, according to the hypotheses’

results, there is a positive and signiﬁcant relationship between managers’ overconﬁdence,

managers’ narcissism, and board effort and auditor’s report readability based on the FOG

index. Because their p-values are 0.042, 0.000, and 0.043 lower than the 0.05 signiﬁcance

level, their coefﬁcients are 0.114, 0.042, and 0.003, there is a positive and signiﬁcant relation-

ship between these variables and audit report readability based on the FOG index. Since

the p-value of the model is 0.0082, the model enjoys sufﬁcient signiﬁcance.

Economies 2022, 10, 12 13 of 23

Table 4. Sensitivity analysis model.

Fog Textindex Flashindex Me Overcon Ceonar Rem Aem Bef Age Roa Lev Grw Size Own Iinv Intang Seg Busy Current Rest Loss Mtb

Fog 1.000

Textindex 0.022 1.000

Flashindex −0.051 0.067 1.000

me −0.032 0.060 0.049 1.000

Overcon 0.036 −0.054 −0.083 −0.009 1.000

Ceonar −0.003 0.017 0.017 −0.065 0.086 1.000

Rem 0.026 0.003 −0.004 −0.038 − 0.070 −0.054 1.000

Aem 0.068 0.001 0.012 0.051 −0.054 −0.009 −0.006 1.000

Bef −0.005 0.090 −0.014 0.099 −0.011 −0.032 −0.013 −0.026 1.000

Age −0.060 0.004 −0.027 −0.074 0.034 −0.090 0.007 0.056 −0.013 1.000

Roa −0.010 −0.073 −0.032 0.050 0.003 0.089 −0.023 0.054 0.049 −0.103 1.000

Lev 0.065 0.085 −0.070 −0.020 0.065 −0.056 0.062 −0.031 −0.046 0.048 −0.620 1.000

Grw 0.021 0.017 0.038 −0.045 −0.024 0.003 0.000 0.019 0.019 0.011 0.208 −0.092 1.000

Size −0.007 0.189 −0.013 0.026 −0.079 0.065 0.014 −0.089 0.371 0.035 0.038 0.071 0.003 1.000

Own 0.089 −0.087 −0.004 −0.041 0.084 0.030 −0.006 −0.068 −0.107 −0.138 0.016 0.089 −0.034 −0.080 1.000

Iinv −0.007 −0.015 −0.048 0.051 0.025 0.122 −0.024 −0.105 0.077 −0.195 0.037 0.148 −0.011 0.189 0.455 1.000

Intang −0.000 0.005 −0.049 0.004 −0.064 −0.018 −0.022 − 0.097 −0.054 −0.126 0.000 −0.029 −0.007 −0.056 0.124 0.116 1.000

Seg −0.005 0.282 0.006 0.055 −0.032 −0.041 0.013 0.082 0.149 0.068 −0.266 0.246 −0.073 0.247 −0.190 −0.076 −0.127 1.000

Busy −0.120 0.016 0.090 0.009 −0.053 −0.017 −0.015 0.075 −0.065 0.035 −0.000 −0.029 0.020 −0.035 0.142 0.233 0.031 −0.067 1.000

Current −0.069 −0.042 0.102 0.051 −0.044 0.009 −0.009 0.158 −0.032 0.084 0.492 −0.594 0.104 −0.132 −0.121 −0.215 −0.051 − 0.128 0.016 1.000

Rest 0.007 0.035 0.044 0.036 −0.044 0.046 −0.002 0.043 0.065 0.036 −0.090 0.058 −0.043 0.001 −0.086 0.025 −0.063 0.178 0.013 −0.055 1.000

Loss 0.021 0.056 0.012 −0.061 0.010 −0.042 −0.051 0.051 0.022 0.078 −0.559 0.463 −0.146 0.001 −0.033 0.017 0.009 0.309 −0.023 −0.262 0.087 1000

Mtb 0.043 0.001 −0.037 0.007 0.013 −0.035 −0.008 0.024 −0.032 0.021 0.068 −0.067 0.101 0.097- 0.015 −0.020 0.068 0.004 0.037 0.019 −0.107 −0.055 1.000

Economies 2022, 10, 12 14 of 23

4.3. Research Models Estimation

Based on the FOG index (Table 5).

Table 5. FOG model estimation.

Variable

(FOG)

coef Std. Err. z Prob.

ME −0.016 0.004 −4.18 0.000

Overcon 0.114 0.056 2.04 0.042

Ceo_nar 0.042 0.009 4.38 0.000

REM −0.096 0.148 −3.72 0.000

AEM −0.217 0.109 −1.98 0.048

BEF 0.003 0.002 2.02 0.043

Age 0.038 0.017 2.18 0.029

ROA 0.093 0.029 3.20 0.002

LEV −0.008 0.004 −1.77 0.076

GRW 0.073 0.044 1.66 0.098

Size 0.005 0.008 0.71 0.481

OWN −0.014 0.005 −2.80 0.005

IINVE −0.049 0.021 −2.35 0.019

Intange 0.095 0.049 1.92 0.056

SEG −0.003 0.003 −1.00 0.316

Busy −0.070 0.026 −2.64 0.008

current −0.038 0.019 −1.90 0.0057

REST 0.144 0.055 2.61 0.010

Loss 0.098 0.032 3.06 0.002

MTB 0.001 0.001 1.65 0.099

_Con 21.819 0.119 182.07 0.000

R-SQ 0.8568

R-SQ

0.3107

F-Limer

F(149,834) = 2.81

Prob. > F = 0.000

Hausman

Chi2(20) = 33.54

Prob. > chi2 = 0.0294

Prob. Model

Wald chi2(20) = 38.28

Prob. > chi2 = 0.0082

Based on a text index.

We should ﬁrst analyze whether the data are pooled or panel using the F test to estimate

the model. This test’s null hypothesis expresses that data are pooled, and hypothesis

1 declares that data are panel. After performing the F test, H0 is rejected. The question is

based on which models of ﬁxed effects or random effects that the model is analyzable, which

is determined by the Hausman test. Regarding the pooled test results reported in Table 6,

the null hypothesis concerning the pooled data is ejected for the ﬁrst models at 99%. Hence,

a model with panel data should be used to estimate the model’s coefﬁcients. Moreover,

according to Table 6, the Hausman test statistic based on the ﬁrst model’s estimation equals

21.76, larger than in the table, so the null hypothesis is not rejected. Hence, a model with a

random effect is more appropriate for the research model.

Table 6 shows a negative and signiﬁcant relationship between managerial entrench-

ment, managers’ overconﬁdence, real/accrual-based earnings management, and auditor’s

report readability based on the text length index, because their p-values are 0.007, 0.024,

0.049, and 0.001 lower than the 0.05 signiﬁcance level. Their coefﬁcients are 0.019, 0.046,

0.086, and 0.042, showing a negative relationship between these variables and the auditor’s

report readability. Moreover, according to the hypotheses’ results, there is a positive and

signiﬁcant relationship between managers’ overconﬁdence, board effort, and auditor’s

report readability based on the text length index. Their p-values are 0.000 and 0.006 lower

than the 0.05 signiﬁcance level. Their coefﬁcients are 0.106 and 0.023, showing a positive

and signiﬁcant relationship between these variables and audit report readability based on

Economies 2022, 10, 12 15 of 23

the text length index. Since the p-value of the model is 0.0014, the model enjoys sufﬁcient

signiﬁcance based on the Flesch index

We should ﬁrst analyze whether the data are pooled or panel using the F test to estimate

the model. This test’s null hypothesis expresses that data are pooled, and hypothesis 1

declares that data are panel. After performing the F test, H0 is rejected. The question is

based on which models of ﬁxed effects or random effects that the model is analyzable,

which is determined by the Hausman test. Regarding the pooled test results reported in

Table 7, the null hypothesis concerning the pooled data is rejected for the ﬁrst models at

99%. Hence, a model with panel data should be used to estimate the model’s coefﬁcients.

Moreover, the Hausman test statistic based on the ﬁrst model’s estimation equals 21.76,

which is larger than the table, so the null hypothesis is not rejected. Hence, a model with a

random effect is more appropriate for the research model.

Table 6. Indext model estimation.

Variable

(Indext)

coef Std. Err. z Prob.

ME −0.019 0.007 −2.70 0.007

Overcon −0.046 0.021 −2.25 0.024

Ceo_nar 0.106 0.028 3.76 0.000

REM −0.086 0.044 −1.97 0.049

AEM −0.042 0.012 −3.36 0.001

BEF 0.023 0.008 2.74 0.006

Age 0.058 0.023 2.49 0.013

ROA −0.003 0.013 −1.92 0.054

LEV 0.042 0.009 4.38 0.000

GRW 0.059 0.033 1.75 0.080

Size 0.031 0.013 2.36 0.018

OWN −0.092 0.069 −1.35 0.178

IINVE 0.093 0.029 3.20 0.002

Intange −0.035 0.015 −2.31 0.021

SEG 0.018 0.004 4.20 0.000

Busy 0.034 0.034 0.99 0.321

Current −0.001 0.001 −1.79 0.074

REST −0.024 0.019 −1.20 0.230

Loss −0.013 0.008 −1.65 0.098

MTB −0.014 0.005 −2.81 0.005

_Con 6.452 0.230 28.04 0.000

R-SQ 0.8105

R-SQ

0.3359

F-Limer

F(149,834) = 5.66

Prob. > F = 0.000

Hausman

Chi2(20) = 21.76

Prob. > chi2 = 0.35.37

Prob. Model

Wald chi2(20) = 44.32

Prob. > chi2 = 0.0014

Table 7 shows a negative and signiﬁcant relationship between managerial entrench-

ment, managers’ overconﬁdence, real/accrual-based earnings management, and auditor’s

report readability based on the Flesch index p-values, which are 0.000, 0.016, 0.030, and

0.000 lower than the 0.05 signiﬁcance level. Their coefﬁcients are 0.028, 0.019, 0.074, and

0.028, showing a negative relationship between these variables and the auditor’s report

readability. Moreover, according to the hypotheses’ results, there is a positive and signiﬁ-

cant relationship between board efforts and auditor’s report readability based on the Flesch

index, because its p-value is 0.004 lower than the 0.05 signiﬁcance level. Its coefﬁcient is

0.024, showing a positive and signiﬁcant relationship between these variables and audit

report readability based on the Flesch index. Since the p-value of the relationship between

managers’ narcissism and auditor’s report readability, based on the Flesch index, is 0.051,

Economies 2022, 10, 12 16 of 23

there is no signiﬁcant relationship between these two variables at a 95% conﬁdence level.

Still, there is a positive and signiﬁcant relationship at a 90% level, because the coefﬁcient

of that is 0.094, showing that, if managers’ narcissism goes up, the readability of the au-

dit report increases. Since the p-value of the model is 0.000, the model enjoys sufﬁcient

signiﬁcance.

Table 7. Flesch model estimation.

Variable

(Flesch)

coef Std. Err. z Prob.

ME −0.028 0.004 −6.97 0.000

Overcon −0.019 0.008 −2.43 0.016

Ceo_nar 0.094 0.048 1.95 0.051

REM −0.074 0.034 −2.18 0.030

AEM −0.028 0.004 −6.96 0.000

BEF 0.024 0.008 2.89 0.004

Age 0.026 0.009 2.88 0.004

ROA 1.560 0.909 1.72 0.086

LEV −0.099 0.036 −2.75 0.006

GRW −0.233 0.061 −3.82 0.000

Size 0.107 0.015 6.93 0.000

OWN 0.013 0.006 2.28 0.023

IINVE −2.634 1.923 −1.37 0.171

Intange 111.877 44.854 2.49 0.013

SEG 0.183 0.095 1.92 0.055

Busy 3.689 2.245 1.64 0.100

current −0.372 0.197 −1.89 0.059

REST 0.165 0.033 5.04 0.000

Loss 0.107 0.015 6.93 0.000

MTB 0.038 0.035 1.07 0.283

_Con 93.537 8.914 10.49 0.000

R-SQ 0.8543

R-SQ

0.3779

F-Limer

F(149,834) = 53.26

Prob. > F = 0.000

Hausman

Chi2(19) = 6.24

Prob. > chi2 = 0.9973

Prob. Model

Wald chi2(20) = 66.21

Prob. > chi2 = 0.0000

Robustness testing.

The FOG index.

In this paper, to obtain better results and conﬁrm them, research hypotheses were also

tested by using other additional methods, the results of which are as follows:

To conﬁrm model (1), the relationship between management characteristics and audi-

tor’s report readability is examined based on the FOG index using the FE, GMM, and t + 1

methods. According to the results in Table 8 and based on the FOG index, there is a negative

and signiﬁcant relationship between management entrenchment and real/accrual-based

earnings management and audit report readability, and the relationship between managers’

overconﬁdence, managers’ narcissism, and board effort and auditor’s report readability

is positive and signiﬁcant. The ﬁndings follow the results of the primary method and

conﬁrm that. Since the results of the additional methods are in total conformity with the

study’s main method, we can conﬁdently claim that a signiﬁcant relationship between

management characteristics and auditor’s report readability is examined based on the FOG

index. It is worth mentioning that the relationship between board effort and managers’

narcissism and auditor’s report readability based on the FOG index is conﬁrmed via ﬁxed

effects and t + 1 methods at a 90% level.

Economies 2022, 10, 12 17 of 23

Table 8. FOG model estimation.

Variable

FE GMM t + 1

coef Prob. coef Prob. coef Prob.

FOG - - −0.005 0.041 - -

ME −0.046 0.024 0.057 0.028 −0.034 0.001

Overcon 0.128 0.001 0.058 0.013 0.046 0.024

Ceo_nar 0.044 0.054 −0.042 0.001 0.037 0.052

REM −0.012 0.015 −0.086 0.049 −0.003 0.054

AEM −0.037 0.024 0.093 0.002 −0.214 0.036

BEF 0.110 0.002 0.004 0.000 0.037 0.088

Age 0.016 0.050 0.060 0.098 0.001 0.068

ROA 0.018 0.000 0.028 0.546 0.002 0.071

LEV −0.075 0.217 0.020 0.057 −0.046 0.386

GRW 0.069 0.008 0.069 0.008 0.013 0.057

Size 0.013 0.057 0.079 0.138 0.003 0.000

OWN −0.219 0.040 −0.073 0.018 −0.064 0.000

IINVE 0.078 0.357 0.148 0.022 −0.104 0.088

Intange 0.114 0.042 −0.067 0.027 1.068 0.374

SEG −0.005 0.090 −0.039 0.057 −0.012 0.000

Busy −0.021 0.029 −0.019 0.147 −0.033 0.000

current −0.061 0.002 0.163 0.003 −0.014 0.385

REST 0.004 0.069 −0.001 0.087 0.016 0.017

Loss 0.002 0.014 0.001 0.178 0.039 0.000

MTB 0.001 0.225 0.344 0.000 0.003 0.000

_CON 21.850 0.000 14.251 0.000 0.025 0.837

R-SQ 0.8325 0.7664

R-SQ

0.3572 0.7396

Prob.

Model

F(20,834) = 1.51 F(20,833) = 17.75

Prob. > F = 0.0704 Prob. > F = 0.0000

Based on a text index.

To conﬁrm model (2), the relationship between management characteristics and au-

ditor’s report readability is examined based on the text index using the ABB, FE, and

t + 1

methods. According to the results in Table 9 and based on the text index, there is

a negative and signiﬁcant relationship between management entrenchment, managers’

overconﬁdence, and real earnings management and auditor’s report readability, and the

relationship between managers’ narcissism and auditor’s report readability is positive and

signiﬁcant. The relationship between accrual-based earnings management and auditor’s

report readability was negative and signiﬁcant based on the same index. Simultaneously,

the board effort has a positive and signiﬁcant relationship with the so-called variable at a

90% level. All these relations were not evident at the 95% level. Since the random effects

method results conform with the study’s main method, we can conﬁdently claim that a

signiﬁcant relationship between management characteristics and independent auditor’s

report readability is examined based on the text index.

Based on the Flesch index.

To conﬁrm model (1), the relationship between management characteristics and audit

reports’ readability is examined using the t + 1 method. According to the results in Table 10

and based on the Flesch index, there is a negative and signiﬁcant relationship between

management entrenchment, managers’ overconﬁdence, and real/accrual-based earnings

management and auditor’s report readability, and the relationship between managers’

narcissism and board effort and auditor’s report readability is positive and signiﬁcant.

Since the results of the additional methods are in total conformity with the study’s main

method, we can conﬁdently claim that a signiﬁcant relationship between management

characteristics and auditor’s report readability is examined based on the Flesch index

(Table 11).

Economies 2022, 10, 12 18 of 23

Table 9. Indext model estimation.

Variable

t + 1 Fixed Affect Method ABB

coef Prob. coef Prob. coef Prob.

Indext - - - - 0.698 0.000

ME −0.003 0.001 −0.011 0.000 −0.016 0.000

Overcon −0.003 0.054 −0.003 0.000 −0.003 0.004

Ceo_nar 0.046 0.024 0.042 0.029 0.036 0.042

REM −0.007 0.004 −0.061 0.022 −0.097 0.043

AEM −0.787 0.067 −0.043 0.054 −0.019 0.000

BEF 0.044 0.054 0.057 0.028 0.069 0.008

Age 0.029 0.001 0.016 0.012 0.015 0.104

ROA −0.095 0.119 −0.034 0.001 −0.005 0.041

LEV 0.080 0.022 0.062 0.342 0.037 0.052

GRW 0.036 0.076 0.281 0.000 0.042 0.064

Size −0.006 0.198 0.297 0.000 0.041 0.006

OWN −0.029 0.360 −0.163 0.158 −0.202 0.134

IINVE 0.047 0.064 0.098 0.280 0.042 0.097

Intange −0.026 0.047 −0.014 0.007 −0.005 0.041

SEG 0.006 0.008 0.015 0.000 0.018 0.000

Busy −0.012 0.372 0.092 0.595 0.027 0.847

current −0.003 0.000 −0.036 0.089 −0.051 0.068

REST −0.001 0.084 −0.019 0.353 −0.002 0.941

Loss −0.036 0.188 −0.053 0.097 −0.068 0.061

MTB −0.001 0.044 −0.096 0.000 −0.033 0.002

_CON 0.191 0.012 6.189 0.000 1.759 0.050

R-SQ 0.8105 0.7943 -

R-SQ2 0.3359 0.2133 -

Prob. Model

Wald chi2(20) = 41.39 F(20,834) = 2.97 Wald chi2(21) = 141.62

Prob. > chi2 = 0.0033 Prob. > F = 0.0000 Prob. > chi2 = 0.0000

Table 10. Flesch model estimation.

Variable

t + 1 GMM FE

coef Prob. coef Prob. coef Prob.

Flesch - - −0.014 0.007 - -

ME −0.027 0.026 −0.028 0.000 −0.011 0.000

Overcon −0.006 0.000 0.161 0.000 −0.019 0.000

Ceo_nar 0.164 0.000 −0.015 0.027 0.106 0.000

REM −0.096 0.000 −0.002 0.004 −0.011 0.000

AEM -0.003 0.004 0.002 0.012 −0.003 0.000

BEF 0.002 0.014 0.022 0.026 0.023 0.006

Age 0.069 0.008 0.001 0.040 0.002 0.000

ROA −1.830 0.226 −1.735 0.225 0.009 0.000

LEV −0.001 0.027 −0.001 0.040 −0.124 0.000

GRW −0.001 0.000 0.013 0.001 −0.543 0.279

Size 0.078 0.021 1.387 0.365 0.712 0.091

OWN 1.031 0.224 −0.001 0.020 0.022 0.000

IINVE −0.058 0.005 0.120 0.010 −1.657 0.507

Intange 0.004 0.000 0.033 0.000 126.956 0.004

SEG 0.056 0.355 −0.390 0.528 0.190 0.041

Busy −0.701 0.025 −0.702 0.002 2.665 0.574

current −0.001 0.000 0.007 0.023 −0.887 0.121

REST 0.057 0.028 0.012 0.097 0.009 0.000

Loss 0.218 0.000 0.043 0.249 0.002 0.071

MTB 0.056 0.158 0.927 0.000 0.039 0.191

_CON −0.924 0.650 6.033 0.099 90.436 0.000

R-SQ 0.7727 0.7589

R-SQ2 0.3858 0.2355

Prob.

Model

Wald chi2(20) = 30.01 F(20,834) = 1.47

Prob. > chi2 = 0.0698 Prob. > F = 0.0823

Economies 2022, 10, 12 19 of 23

Table 11. Summary of the results.

Hypothesis Results Details

H1: There is a signiﬁcant relationship

between real earnings management

and audit report readability.

Conﬁrm

There is a negative and signiﬁcant

relationship between real earnings

management and audit report readability.

H2: There is a signiﬁcant relationship

between accrual-based earnings

management and audit report

readability.

Conﬁrm

There is a negative and signiﬁcant

relationship between accrual-based

earnings management and audit report

readability.

H3: There is a signiﬁcant relationship

between board effort and audit report

readability.

Conﬁrm

The relationship between board effort and

audit report readability is positive and

signiﬁcant.

H4: There is a signiﬁcant relationship

between management entrenchment

and audit report readability.

Conﬁrm

There is a negative and signiﬁcant

relationship between management

entrenchment and audit report readability.

H5: There is a signiﬁcant relationship

between CEO narcissism and audit

report readability.

Conﬁrm

The relationship between managers’

narcissism and audit report readability is

positive and signiﬁcant.

H6: There is a signiﬁcant relationship

between managers’ overconﬁdence

and audit report readability.

Conﬁrm

The FOG index shows a positive and

signiﬁcant relationship between managers’

overconﬁdence and audit report readability.

The Flesch index shows a negative and

signiﬁcant relationship between managers’

overconﬁdence and audit report

readability.

5. Conclusions

The study results show a negative and signiﬁcant relationship between management

entrenchment, real/accrual-based earnings management, and audit report readability based

on the FOG index. There is a positive and signiﬁcant relationship between management

narcissism, managers’ overconﬁdence, board effort, and audit report readability. More-

over, the Flesch index shows a negative and signiﬁcant relationship between management

entrenchment, managers’ overconﬁdence, real/accrual-based earnings management, and

audit report readability. Further, there is a positive and signiﬁcant relationship between

management narcissism, board effort, and audit report readability. However, various

studies conducted on the relationship between management characteristics and ﬁnancial

statement readability are used in this paper for comparison, because the audit report read-

ability is, to a great extent, associated with the readability of ﬁnancial statements. Hence,

should ﬁnancial statements enjoy good readability. The audit report will be more readable.

The primary ﬁndings demonstrate that entrenched managers are more likely to pro-

vide less readability of audit reports. Moreover, it can be reasoned that entrenched man-

agers may cover their opportunistic behavior, such as earning managers under the unclear

ﬁnancial notes; the negative and signiﬁcant relationship between real/accrual-based earn-

ings management and audit report readability leads to such a conclusion. In contrast, the

obtained results show a positive and signiﬁcant relationship between CEO narcissism and

board effort and overconﬁdence and audit report readability, which means that higher CEO

narcissism and overconﬁdence, and board effort, lead to higher audit report readability.

Thus, the present study results align with (Lo et al. 2017), Ajina et al. (2016), Bloomﬁeld

(2008). They declare that ﬁrms with accrual-based earnings management propose more

complicated and lengthier reports. The results also contrast with that of Cheng et al. (2018).

They posit that accrual-based earnings management is associated positively and signiﬁ-

cantly with ﬁnancial statement readability. Since these units make the annual report more

complicated and conceal their illegal actions, including earnings management and annual

reports, unreadability is the best method for fulﬁlling such purposes. The more unread-

able the ﬁnancial statements and the quality of ﬁnancial reporting, the more inﬂuence the

auditor presented. To increase their social position, auditors make an effort to present

Economies 2022, 10, 12 20 of 23

reports with an appropriate level of readability to enable the users to understand and better

decide on their economic affairs. So, we recommend future studies to assess the effect of

audit quality and its components, including ﬁnancial independence and auditor’s industry

specialization, on audit report readability. The present study’s ﬁndings show, ﬁrst, the

evidence relative to the advantages that audit report readability has for analysts, investors,

and creditors. Second, it shows how managers’ psychological features affect the audit

report readability. The ability to foresee the effect of such attributes on ﬁrm statements

is of great importance for audit report users who make their most important economic

decisions based on such comparisons. Then, these ﬁndings can lead to the development

of theoretical principles of the previous studies concerning audit reporting linguistics in

emerging markets in Iran and developing countries. Furthermore, results show to what

extent do the psychological features and to what extent does the management competency

in real and accrual-based earnings management contribute to audit report readability of

business ﬁrms, and this issue, as a scientiﬁc achievement, can provide useful information

for investors, capital market legislation, accounting standard compilers, and other users of

accounting information. Finally, the results of this study presented new ideas for conduct-

ing new studies in the ﬁeld of personal characteristics of managers and audit report styles

of business ﬁrms.

Author Contributions: Conceptualization, M.S. (Mahdi Salehi), G.Z. and M.S. (Maryam Seifzadeh);

methodology, M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh); software, M.S. (Mahdi Salehi) and

M.S. (Maryam Seifzadeh), and G.Z.; formal analysis M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh);

investigation, M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh); resources, M.S. (Mahdi Salehi) and

M.S. (Maryam Seifzadeh); data curation, M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh); writing—

original draft preparation, MahdiSalehi., G.Z. and M.S. (Maryam Seifzadeh); writing—review and

editing, MahdiSalehi., G.Z. and M.S. (Maryam Seifzadeh); visualization, MahdiSalehi., G.Z, and M.S.

(Maryam Seifzadeh); supervision, MahdiSalehi., G.Z. and M.S. (Maryam Seifzadeh) All authors have

read and agreed to the published version of the manuscript.

Funding: This research received no external funding.

Data Availability Statement:

This does not apply to this article. this is a survey. The results of the

surveys are presented in the article. Authors have the polls.

Conﬂicts of Interest: The authors declare no conﬂict of interest.

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