Supervisory Function And Earnings Quality: Gender Analysis
Deden Tarmidi1*, Nurlis2, Feber Sormin3, Hendi Prihanto4, and Zinka Saputri5
1,2,3

Department of Accounting, Faculty of Economic and Business, Universitas Mercu Buana,
Jakarta, Indonesia
4,5
Department of Accounting, Faculty of Economic and Business, Universitas Prof. Dr. Moestopo
(Beragama), Jakarta, Indonesia
Email Address:
deden.tarmidi@mercubuana.ac.id*, nurlis@mercubuana.ac.id, feber.sormin@mercubuana.ac.id,
hendi@moestopo.ac.id, zinka.saputri@moestopo.ac.id
*
Corresponding author
Submitted 10-06-2023

Reviewed 14-07-2023

Revised 14-07-2023

Accepted 14-07-2023

Published 13-05-2024

Abstract: Gender analysis of independent commissioners and audit committees in carrying out supervisory
functions and their impact on the entity’s earnings quality is the purpose of this study. With the unit of
analysis of manufacturing companies listed on the Indonesia Stock Exchange from 2015 to 2021, using
multiple linear regression analysis methods with STATA software in analysing 745-panel data, this study
found a positive effect of multi-gender independent commissioners on earnings quality but has a negative
impact on mono-gender where female independent commissioners are more significant than male. While
gender diversity in the audit committee does not affect earnings quality, even so, the supervisory function
carried out by the male audit committee is more significantly positive than that of the female. Based on these
results, owners can appoint multi-gender independent commissioners and mono-gender audit committees for
proper supervisory functions, especially in preparing financial statements to improve earnings quality.
Keywords: Gender; Independent Commissioners; Audit Committee; Earnings Quality.
Abstrak: Analisis gender pada komisaris independen dan komite audit dalam melaksanakan fungsi
pengawasan dan dampaknya terhadap kualitas laba entitas merupakan tujuan penelitian ini. Dengan unit
analisis perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia dari tahun 2015 sampai dengan 2021,
menggunakan metode analisis regresi linier berganda dengan software STATA dalam menganalisis 745
panel data, penelitian ini menemukan adanya pengaruh positif komisaris independen multi gender terhadap
kualitas laba namun berpengaruh negatif pada mono gender dimana komisaris independen wanita lebih
signifikan dibandingkan pria. Sedangkan diversitas gender dalam komite audit tidak berpengaruh terhadap
kualitas laba, meskipun demikian fungsi pengawasan yang dilakukan oleh komite audit laki-laki lebih
signifikan positif dibandingkan perempuan. Berdasarkan hasil tersebut, pemilik dapat mengangkat komisaris
independen multi gender dan komite audit mono gender untuk mendapatkan fungsi pengawasan yang tepat
terutama dalam proses penyusunan laporan keuangan agar dapat meningkatkan kualitas laba.
Kata Kunci: Gender; Komisaris Independen; Komite Audit; Kualitas Laba.

INTRODUCTION
Companies that conduct IPOs on the stock exchange certainly have goals for the
sustainability of their business, so every policy taken becomes a public concern, especially
for investors in making investment policies. The issuer's annual report, including the
financial statements, is one of the pieces of information investors use to assess the issuer's
performance to indicate the company's management skills. Information about earnings is
still used by investors technically in analysing the issuer's performance (Tarmidi et al.,
2020), although sometimes the earnings information does not help investors in return

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prediction and can even be misleading (Sari & Febriyanto, 2019), so the quality of earnings
is very necessary for the financial statements published by issuers (Shahzad et al., 2019).
Quality financial statements help investors predict returns, which cannot be found in
financial statements with a high level of earnings management. Management generally
carries out earnings management so that financial performance looks good in the eyes of
investors. Several cases related to weak financial information domestically and abroad,
namely Enron, KAI, KAEF, GIIA, Jiwasraya, INAF, and MYRX (Sandria, 2021).
Management generally adopts a policy for organisational purposes, although it is not
uncommon for hidden personal management goals to exist. Every company policy
certainly impacts internal parties, such as management or members of management, and
external parties, such as the Government, banks, and the general public, including
investors. Independent commissioners and a team of audit committees are elected to carry
out the company's supervisory function while representing shareholders' interests.
The literature explains the influence of independent commissioners and audit
committees as a firm's supervisory function on earnings quality. As agency theory
describes, information asymmetry can occur between the principal and agent, and
independent commissioners and audit committees have a supervisory function to suppress
these asymmetries. As an independent external party, independent commissioners have the
function of overseeing company management in implementing good corporate governance
(Amin et al., 2017; Marlinah et al., 2022), including the quality of earnings that inventors
in investment policy can use (Handriani, 2020; Nuroniyah and Basuki, 2020; F. A.
Setiawan et al., 2020). However, the results of other studies did not find the same thing,
where the supervisory function performed by independent commissioners had no
discernible impact on earnings quality. (Arisanti, 2019; Kristian and Siswanto, 2022;
Permata Sari and Setiyawati, 2021; Rucita and Sanjaya, 2021), This is usually due to the
need for more supervisory functions carried out by independent commissioners.
Like independent commissioners, the audit committee also has a supervising
function to management. It implements good corporate governance in its policies and
minimises agency costs and information asymmetry with investors. As an internal party to
the company, an audit committee that has superior competence and carries out an excellent
supervisory function in the company can improve earnings quality and minimise
information asymmetry that usually exists so that investors as outside parties can use the
financial information needed (Ghafran et al., 2022; Hamdan, 2020; Mappadang, 2021;
Marlinah et al., 2022; F. A. Setiawan et al., 2020; Siagian and Siregar, 2018). However,
these results are not in line with other studies that did not find the effect of the audit
committee on earnings quality; this result is generally thought to be due to the lack of audit
committee supervision as well as the lack of power the audit committee has in overseeing
management so that it cannot carry out its functions optimally (Dewi and Mita, 2019;
Halim, 2022; Kawedar et al., 2021; Nelwan and Tansuria, 2019; Savka, 2019).
The importance of financial information in the quality of earnings for investors and
the many cases of information asymmetry from management to the emergence of financial
statements cases in Indonesia such as Garuda, Kimia Farma, Indofarma and others
(Sandria, cnbcindonesia.com, 2021) is a motivation for researchers to carry out research
in analysing the supervisory function of independent commissioners and audit committees
on firm earnings quality.
As individuals, independent commissioners and audit committees also have their
personalities, especially the personalities inherent in the male and female genders. The

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literature states that males are courageous in taking action for personal goals (Friscilla &
Nugroho, 2020). Thus overriding ethics compared to females. Other studies have found
that female audit committees cause more errors and are less accurate in earnings
forecasting (Ammer & Ahmad-Zaluki, 2017). However, many other studies have found a
positive influence of female directors on the readability of financial information (E-vahdati
et al., 2022) by suppressing the level of earnings management (Damak, 2018; Mnif &
Cherif, 2021) so that earnings quality is high (García-Sánchez et al., 2017; Tee &
Kasipillai, 2022; Yousuf & Aldamen, 2021).
Based on this, gender differences in independent commissioners or audit committees
can lead to different analysis results on the supervisory function carried out on earnings
quality. This study develops previous research which found that female independent
commissioners can reduce earnings quality, but female audit committees improve earnings
quality (Setiawan et al., 2020). This study will also analyse the gender of males who have
functioned as independent commissioners and audit committees. Meanwhile, other studies
found that female independent commissioners have a weak relationship with earnings
quality (Orazalin, 2020), otherwise the female audit committee increases the quality of
financial information and suppresses the level of earnings management (Al-absy et al.,
2019; Khlif & Achek, 2017; Oradi, 2020).
Gender analysis of the supervisory function carried out by independent
commissioners and audit committees on a firm’s earnings quality is a novelty of this study
that has never been analysed in previous studies. Generally, previous studies have analysed
the performance of only female directors (Syamsudin et al., 2017) on earnings quality or
financial performance while male performance is not, even though the differences in male
and female characters are unique to analysed each (Darma & Astuti, 2021), especially in
the practice of supervisory functions carried out as independent commissioners and audit
committees on the process of preparing financial statements.

THEORETICAL REVIEW
Agency Theory. According to agency theory, there is a contract between the owner
and management, where the owner has specific objectives in providing capital to
management in the form of profit. In contrast, the agent has particular objectives in
managing the capital provided through benefits that can be used personally and the
organisation’s sustainability. With this contract, the owner of the capital authorizes the
agent to manage the capital employed in the company's operational activities. With this
authority, management has the right to take an excellent policy, e.g. tax policies, so that
the company's profit desired by the principal is achieved while the principal is not directly
involved in operational activities; in the end, management as an internal party who knows
directly the internal state of the company can use this information in making policies that
may not always be good for capital owners. This causes information asymmetry between
management and capital owners, so the quality of information published by management,
especially earnings information, has a vital role in the delegation of authority process.
Good earnings quality helps capital owners analyze management's performance and the
prospects for future profits. As an internal party, management has factual information about
what is happening in the company, so the policies or practices may have a personal agenda.
On the other hand, as owners of capital, principals need financial information to
assess the company's and management's past performance and predict how profitability

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and performance will be in the future, so the company’s information is essential to have
high quality. The role of an independent commissioner and an audit committee in carrying
out their functions in overseeing management in the policies taken and practices carried
out is needed so that the company is in good governance and can grow and be sustainable.
This study analyses gender in independent commissioners and audit committees and their
effect on the quality of corporate earnings.
Gender Theory. Gender is an intrinsic feature of males and females formed by
social and cultural circumstances, resulting in various assumptions about male and female
social and cultural roles (Handayani & Sugiarti, 2017). The social mould of males and
females includes males being perceived as strong, rational, virile and powerful, while
females are perceived as meek, beautiful, emotional and motherly. However, these traits
can change over time. Therefore, it can be said that gender is defined as a social concept
that distinguishes functions and roles between males and females. These differences are
not only determined by biological or natural differences. However, they can also be
distinguished according to their respective positions, functions, and roles in various fields
of life, including the carrying out supervisory functions in the entity.
In line with the concept of gender above, gender is the difference between males and
females when viewed from the values and behaviours of males and females (Darma &
Astuti, 2021). Gender is a term usually used to describe the differences between males and
females in various ways. Gender is a set of cultural characteristics and behaviours in men
and women. Thus, gender is the outcome of human intellect, constructed by society in such
a way that it is dynamic and can alter owing to variances in customs, culture, religion,
value systems, and ethnic groupings. Furthermore, gender can alter due to historical events,
political, social, economic, and cultural changes, or development advances. Only in some
situations does gender apply, not universally and generally.
The literature explains that there are two approaches used to determine gender
perceptions of ethical and unethical behaviour; these approaches are the structural
approach and the socialisation approach. The structural approach describes how male and
female perspectives differ due to early socialisation to the job and the needs of other roles.
The rewards and incentives provided to individuals in a career impact this first
indoctrination. Because the nature of the work and the task accomplished can mould
behaviour through the reward and incentive system, male and female employees will
perform similarly and develop ethical and moral beliefs in the same workplace. In other
words, the structural approach predicts that both male and female professionals will behave
ethically the same way.
The second technique is the gender socialisation approach, in which males and
females bring different values and qualities to the workplace and the classroom. These
gender variations in values and traits will influence male and female decision-making and
behaviour. Males compete for success and are more prone to disobey the rules because
they see success as a competition. Females are more concerned about their performance.
Females will place greater importance on task performance and pleasant working
relationships. Therefore, they will be more compliant with existing regulations and more
critical of those violating them.
The Effect of Independent Commissioners on Earnings Quality. Independent
commissioners are external parties that oversee management in making policies and
implementing business activities. Like the external board of commissioners, independent
commissioners have a supervisory function so that management follows audit findings and

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recommendations from the risk management function, compliance and internal audit
functions, the results of the supervision of the board of commissioners, and the results of
the supervision of the Financial Services Authority (POJK 55/2017). As an external and
independent party, if independent commissioners carry out their supervisory functions,
management is wiser in policy making and implementation, including producing quality
financial information to benefit the public and investors in making investment policies.
Independent commissioners' supervision position can limit opportunistic managers and
motivate managers to select appropriate accounting policies. Then, the policies taken by
management have the potential to output quality financial information (Handriani, 2020)
and produce earnings quality that can help the public and investors in making investment
policies that ultimately return the impact on the company (Nuroniyah & Basuki, 2020;
Siagian & Siregar, 2018). The first hypothesis tested, as shown in Figure 1, is as follows:
H1: Independent commissioners affect earnings quality.
The Effect of Audit Committee on Earnings Quality. The audit committee is an
internal party formed by the board of commissioners and chaired by the commissioner.
The audit committee performs the same job as the commissioners, overseeing policy
formulation and implementation management to ensure it conforms with the company's
internal and external direction and objectives. With this supervisory function, the more
parties who oversee the company make management think of many considerations in every
policy-making and implementation of business activities so that they are by external and
internal regulations, as well as principle objectives. The more the number of audit
committees that carry out their supervisory functions, the higher the earnings quality
because it is the output of the policies taken by management and their implementation
(Ghafran et al., 2022; Hamdan, 2020; Mappadang, 2021; Marlinah et al., 2022; Setiawan
et al., 2020), then the second hypothesis as shown at Figure 1 is as follows:
H2: The Audit Committee affects earnings quality.

Male
Female

Independent
Commissioners

Earnings
Quality

Male
Female

Audit
Committee
Figure 1. Research Model

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METHODS
This causality study analyses the influence of independent commissioners and audit
committees that carry out supervisory functions and their impact on earnings quality. This
research also uses a quantitative and qualitative mix method, from regression analysis to
gender analysis of independent commissioners and teams of audit committees.
Manufacturing companies on the Indonesia Stock Exchange from 2015 to 2021 are
the population of this study. The manufacturing sector is a critical factor in Asia,
necessitating proper inputs and outputs from other sectors. In the Indonesian setting, the
government fosters the development of this business as the Asian Economic Community
expands, where the manufacturing industry has made a consistent contribution to GDP
(GDP) in recent years compared to other sectors. This is an excellent time to investigate
the role of company financial information, particularly earnings quality.
Purposive sampling was used to choose samples based on specified criteria: (1) Have
complete published financial reports for seven years (2015 to 2021, including t-1, namely
2014 to calculate earnings quality), (2) These criteria eliminate companies that have just
IPO / listing on the IDX in 2015 to 2021 and companies that are delisted from the IDX in
2015 to 2021 because they do not have complete published financial reports. In addition,
this criterion also eliminates companies that are still listed on the IDX from 2015 to 2021.
Still, there are financial reports that need to be published or published but cannot be read,
such as publication files in a small size, making it difficult to read the contents. (3) Have
complete analysis data on published reports; this criterion requires that in the published
financial statements, there is information used in measuring research variables both in
measuring earnings quality, independent commissioners, audit committees to age and
company size, including male or female gender in the gender analysis test. Table 1 shows
the sample selection:
Table 1. Sampling Criteria

1.

2.

Purpose
Manufacture Companies listed at IDX FY 2015 to 2021
Year of Analysis
Amount of data panel (117 x 7)

All
114
7
798

Male
114
7
798

Female
114
7
798

Company with no complete data analysed
Data panel analysed

-53
745

-84
714

-730
68

There are three sorts of variables in this study, the most important of which is
earnings quality, the dependent variable, which is the value of earnings that is informed
close to the actual value and without manipulation so that investors can use the earnings
information in making investment policies. In this study, earnings quality is measured by
Performance-adjusted discretionary accruals, including Tax (PAiT) developed in previous
studies (Tarmidi et al., 2021) of the prior measurement, namely performance-adjusted
discretionary accruals (PAccr) (Yasser et al., 2016) with the following formula:
PAiT = α0 + α1(1/Assetsi. t − 1) + α2∆Rev i. t + α3PPE i. t + α4ROA i. t +
α5DIT i. t + εi. t …………………..………………........………................. (1)

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PAiT is Total Accruals, measured by reducing current assets without bank cash with
current debt without bank debt minus depreciation expense divided by total assets. Then,
the regression residuals are solved and multiplied by 1. ∆Rev is the increase in revenue
divided by total assets, PPE is Plant, Property, and Equipment, ROA is Profit after Tax
divided by total assets, and DIT is deferred tax expense divided by total assets.
Then there are two independent variables: first is independent commissioners, and
second is the audit committee. Independent commissioners are external parties appointed
to serve as part of the board of commissioners in a company. As the function of the board
of commissioners, the independent board of commissioners also has a supervisory function
for every management policy and implementation so that they are based on company goals,
do not conflict with the rules, and benefit investors as owners of capital. In this study,
independent commissioners were measured by measurements that had been used in several
previous studies (Kawedar et al., 2021; Marlinah et al., 2022; F. A. Setiawan et al., 2020) :
COMIN =

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐼𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝐶𝑜𝑚𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑒𝑟𝑠

………………..........…..…........... (2)

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐶𝑜𝑚𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑒𝑟𝑠

Then, the gender analysis test grouped the independent commissioner data as follows:
MCOMIN =

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑀𝑎𝑙𝑒 𝐼𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝐶𝑜𝑚𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑒𝑟𝑠

FCOMIN =

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐹𝑒𝑚𝑎𝑙𝑒 𝐼𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝐶𝑜𝑚𝑚𝑖𝑠𝑠𝑜𝑛𝑒𝑟𝑠

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐶𝑜𝑚𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑒𝑟𝑠

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐶𝑜𝑚𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑒𝑟𝑠

………..........……….......... (3)
……………...................... (4)

An audit committee is a person in charge constituted by the board of commissioners
and chaired by an independent commissioner whose purpose is to help the board in
supervision function within the firm in the hope of improving the company's performance
that management in making policies and implementing activities is by business objectives
and does not violate applicable regulations to improve performance and provide quality
information that investors can use. In this study, audit committees are measured by
calculating the number of entity audit committees, which indicators have been used by
several previous studies (Kawedar et al., 2021; Marlinah et al., 2022; Siagian & Siregar,
2018).
COMAU = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐴𝑢𝑑𝑖𝑡 𝐶𝑜𝑚𝑚𝑖𝑡𝑡𝑒𝑒 ………………….......………............ (5)
Then, the gender analysis test grouped the panel data based on the gender of the audit
committee as follows:
MCOMAU =

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑀𝑎𝑙𝑒 𝐴𝑢𝑑𝑖𝑡 𝐶𝑜𝑚𝑚𝑖𝑡𝑡𝑒𝑒

FCOMAU =

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐹𝑒𝑚𝑎𝑙𝑒 𝐴𝑢𝑑𝑖𝑡 𝐶𝑜𝑚𝑚𝑖𝑡𝑡𝑒𝑒

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐴𝑢𝑑𝑖𝑡 𝐶𝑜𝑚𝑚𝑖𝑡𝑡𝑒𝑒

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐴𝑢𝑑𝑖𝑡 𝐶𝑜𝑚𝑚𝑖𝑡𝑡𝑒𝑒

………..………................................. (6)
…….…………................................ (7)

In addition, firm size and firm age are control variables. Firm size is information on
how much the company has resources used in business activities. Assets are generally used
as an indicator of firm size; the more significant the firm size indicates the number of

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resources that support the company in business activities, and this size is one of the things
that management takes into account in making policies, one of which is earnings quality.
This study measures firm size by the log nature of firms' total assets (Yasser et al., 2016).
FSIZE = 𝐿𝑜𝑔 𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝐴𝑠𝑠𝑒𝑡 ……………………………..................................... (8)
The firm's age is how long it has been in operation. With long experience, it is
assumed that the company is more aware of the information published, especially financial
information, thus encouraging management to improve the quality of financial
information. Company age is measured by the company's years established (Yasser et al.,
2016).
FAGE = 𝐶𝑢𝑟𝑟𝑒𝑛𝑡 𝑌𝑒𝑎𝑟 − 𝐸𝑠𝑡𝑎𝑏𝑙𝑖𝑠ℎ𝑚𝑒𝑛𝑡 𝑌𝑒𝑎𝑟 …………….............................. (9)
Research Model. Based on the framework described, this study has three models.
Model 1: Model 1 examined the effect of multi-gender independent commissioners and
multi-gender audit committees on firm earnings quality. In contrast, Model 2 looked at the
impact of male independent commissioners and male audit committees on firm earnings
quality. Model 3: Model 3 looked at the effect of female independent commissioners and
female audit committees on firm earnings quality, as described in the equations of Model
1, Model 2, and Model 3.
Model 1,
PAiT = α + β1COMIN + β2COMAU + β3FSIZE + β4FAGE + ε..................... (10)
Model 2,
PAiT = α + β1MCOMIN + β2MCOMAU + β3FSIZE + β4FAGE + ε............... (11)
Model 3,
PAiT = α + β1FCOMIN + β2FCOMAU + β3FSIZE + β4FAGE + ε................. (12)
Where PAiT is earnings quality, COMIN is independent commissioners, COMAU
is audit committee, FSIZE is firm size, FAGE is firm age, MCOMIN and MCOMAU is
male independent commissioners and male audit committee, FCOMIN and FCOMAU is
female independent commissioners and female audit committee.
Panel data are used in this analysis because they have advantages over other data
types in that model selection can be adjusted to fit the already available data. This is so
because panel data combines cross-sectional and time series data. STATA is used in
numerous data analysis steps, including choosing the optimal model using the Chow, LM,
and Hausman tests. The top three models are selected using three tests: the Common
Effects Model, the Fixed Effects Model, and the Random Effects Model.
Ordinary least squares (OLS), a fundamental panel data regression model or
estimation technique, is still used in the Common Effect model. As a result, this technique
is also known as combined least squares. The OLS method estimates the panel data model
in the interaction model, which combines cross-sectional and time series data. Compared
to the other two types, this one is the most straightforward. Because this model has a fixed
intercept and does not fluctuate randomly, it cannot tell the difference between cross-

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sectional and time-point variation. The most-easy method is the joint effect method, which
combines cross-temporal data with time series data independent of time and individual
size. The common effects model's panel data regression coefficient includes (Ghozali &
Ratmono, 2017), (1) Coefficient: The panel data regression's beta coefficient versus the
variables listed in the variables column. This coefficient value is used in the panel data
regression equation, and this coward error is the coefficient value's standard deviation in
the coefficient column. (2) In a panel data regression, the partial t-value for each variable
in the variable column is the t-statistic. In a panel data regression model, this t-value
denotes the predictor variable's partial impact on the response variable (3) The partial tvalue or significance level is indicated by the word "prob" in the t-statistics column. The
partial t's level of significance in addressing the partial test's hypothesis is indicated by the
p-value. If the p-value is less than the critical limit, accepting H1 indicates that the
predictor variable has a statistically significant impact on the responder variable, often set
at 0.050.
According to the fixed effect method, an object's constant has a significant value
over a long period. The magnitude is occasionally constant (time-invariant), much like the
regression coefficient. A fixed effects model is one in which the slope does not change
over time for each subject, but each subject has a different intercept (cross-section).
According to this concept, the slope is constant across all items, whereas the intercept
varies. Sample variables are used to differentiate between subjects. Cross-sectional fixed
effects presuppose that intercept disparities between individuals may be corrected.
The dummy variable approach estimates the Fixed Effects Model with various
individual intercepts. The Least Squares Dummy Variable technique, sometimes LSDV,
is a frequent name for this estimate strategy. To avoid the dummy variable trap, which
occurs when perfect collinearity occurs, a study with ten cross-sections should only utilise
nine dummy variables. Although the fixed effect model differs from the general effect
model, it uses the ordinary least squares approach. Because the modelling assumption of a
constant cross-section for each cross-section and time is deemed unfeasible, a model that
can more appropriately describe the difference is necessary.
An error component model, sometimes called a random effects model, can be used
to overcome panel data models that feature time-varying correlation of error terms caused
by various observations. Both distinct errors and groups of mistakes are thought to be
unrelated. Using the random effects model instead of the fixed effects model, which
reduces the sum, can save degrees of freedom. This indicates that the outcomes of
parameter estimation are more effective.
After choosing the best model, classical assumption tests like multicollinearity,
autocorrelation, and heteroskedasticity are carried out. This multicollinearity test is
designed to detect whether the independent variables in a regression model have a high or
perfect correlation. The difference is required because the modelling assumption of a
constant cross-section for each cross-section and time is deemed impracticable. The
variance inflation factor (VIF) is one tool that may be used to identify significant
correlations between independent variables. The fluctuation in chosen independent
variables that other independent variables cannot be accounted for is known as tolerance
(Ghozali & Ratmono, 2017). In the multicollinearity test, if the VIF is less than ten and the
tolerance value is more than 0.100, describe data as no multicollinearity. The
autocorrelation test is used in the linear regression model to determine whether residual or
mixed errors from t-period and the mistakes from period t-1 are correlated (Ghozali &

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Ratmono, 2017). There is an autocorrelation issue if there is a correlation. If there is no
autocorrelation, a regression model is deemed successful. A heteroscedasticity test
indicates that the regression model contains variances that are not all the same. Contrarily,
homoskedasticity is the condition in which all of the variables in the regression model have
the same value (Ghozali & Ratmono, 2017).
A t-test, F-test, and coefficient of determination were used to demonstrate the
hypothesis. An F-test, a simultaneous test, a one-sample test, or an ANOVA test
determines the independent factors' combined impact on the dependent variable. Or to
determine whether our regression model is significant and fit or not significant and fit. The
regression model can only be used for prediction if it is substantial; otherwise, it is not
appropriate or significant and cannot be used for prediction. The model is considerable if
the significance column is less than Alpha (ten per cent, five per cent, or one per cent),
which can be determined by comparing the F-number to an F-table. However, the model
is insignificant if the F-number is less than that in the F table, as indicated by the value
(per cent) in the significance column being more than Alpha. The partial test, known as
the t-test, examines the individual effects of each independent variable on the dependent
variable.
This test can be carried out by examining the significance column for each t-statistic
or by comparing the t-statistic with the t-table. The coefficient of determination, or Rsquared, measures how well the independent data can explain the dependent data. Rsquared ranges from 0.000 to 1.000, with the caveat that a value nearer to 1 is preferable.
An R-squared of 0.600 indicates that the independent variable accounts for 60 per cent of
the dependent distribution. The remaining 40 per cent can either be explained by factors
other than the independent variable (error component) or cannot be explained by the
independent variable at all. The error component is significant if the r-squared value is
low. For instance, the corrected R-squared value in the study is 0.500. The model's
predictive potential can be increased by measuring the new independent variables' level of
confidence using the adjusted R-squared value, which helps to resolve one of the issues
with the R-squared value that is frequently encountered. Specifically, the model's constant
value rises as independent variables are included.

RESULTS
Manufacturing is the largest industry sector on the Indonesian stock exchange (IDX).
Thus, it makes sense to focus on that sector. STATA software determines the best model,
tests classical assumptions, and concludes with the coefficient of determination test, f-test,
and t-test. Seven hundred forty-five panel data from financial statements were analysed
using STATA software based on purposive sampling, as shown in Table 2.
Based on Table 2, it can be seen that on average, the value of PAiT or Performance
Accrual, including Tax as an indicator of earnings quality, is -3.266, which is quite close
to the highest value of earnings quality, namely -0.004, which explains that the earnings
quality of the analysis unit is relatively high on average, even so with a standard deviation
below the average value, it illustrates that little panel data deviates from the panel data as
a whole. The average value of the independent commissioner of the analysis unit is 0.392,
which indicates that, on average, 40 per cent of independent commissioners are in the
analysis unit of this study. However, it is quite high, and the number of internal

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commissioners is higher at 60 per cent, which may impact the supervisory function
performed by independent commissioners.
Table 2. Descriptive Statistics
Variable
PAiT
COMIN
COMAU
FSIZE
FAGE

Min
-8.985
0.166
1.000
0.011
25.000

Max
-0.004
0.800
5.000
6.116
35.000

Mean
-3.266
0.392
3.020
3.410
31.951

Std. Dev
2.390
0.099
0.329
0.735
2.023

Notes: PAiT = Earnings Quality, COMIN=Independent Commissioners, COMAU=Audit Committee,
FSIZE=Firm Size, FAGE=Firm Age

Table 2 shows also, the average value of the audit committee in the analysis unit is
three people, a minimum of 1, and a maximum of 5 in this study. The average natural log
value of assets owned by the analysis unit is 3.410, while 0.011 is minimum and 6.116 is
maximum; it reflects that, on average, the assets owned by the analysis unit are quite large
and are between the minimum value and the maximum value. The average age of the
companies analysed is 32 years, which is long enough for the business continuity of an
entity.
The best model selection analysis is then performed, as shown in Table 3, using the
Chow test to compare the Fixed Effect Model with the Common Effect Model, the LM
test to compare the Random Effect Model with the Common Effect Model, and the
Hausman test to compare the Fixed Effect Model and Random Effect Model. Based on
three model selection tests, the Chow test chose the Fixed Effect Model, the LM test chose
the Common Effect Model, and the Hausman test chose the Fixed Effect Model. Based on
these choices, it was determined that the Fixed Effect Model was the best in the data
analysed after the Chow, LM and Hausman tests were chosen.
Table 3. Selection of the Best Model
Test

Comparison

Criteria

Result

Selected

Chow

FEM Vs CEM

ProbF less than 0.050

Prob.F = 0.049

FEM

LM

REM Vs CEM

ProbChibar2 less than 0.050

Prob.Chibar2 = 0.071

CEM

Hausman

FEM Vs REM

ProbChi2 less than 0.050

Prob.Chi2 = 0.024

FEM

Notes: FEM=Fixed Effect Model, CEM=Common Effect Model, REM=Random Effect Model

When it is determined that the Fixed Effect Model is the optimal model, the classical
assumption test is performed, as indicated in Table 4. The traditional assumption tests
performed on the Fixed Effect Model include the multicollinearity and heteroscedasticity
tests. However, the normality and autocorrelation tests are not required for data using the
FEM model because it uses the original least square (OLS) technique.

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Table 4. Classical Assumption Test
Test
Multicollinearity
Heteroscedasticity

Indicator
VIF less than 10
ProbChi2 more than 0.050

Result
Range 1.010 to 1.030
Prob.Chi2 is 0.807

Description
Ok
Ok

This classical assumption test starts with a multicollinearity test to see if there is a
high or perfect correlation between the independent variables in the regression model
(Ghozali & Ratmono, 2017). The data is declared to pass the multicollinearity test if the
Variance Inflation Factor or VIF value is less than 10. Based on Table 4, the VIF value
ranges from 1.010 to 1.030. Hence, the test is deemed to pass. The heteroscedasticity test
is then performed to assess the variance of variables in the regression model, which should
be different (Ghozali & Ratmono, 2017). If the ProbChi2 value exceeds 0.050, the data
passes the heteroscedasticity test, according to Table 4.
Table 5. Coefficient Determination
Information
Model 1
Model 2
Model 3
N
745
714
68
R-Square
0.110
0.023
0.121
Prob F
0.049**
0.001**
0.015**
* Significant 90 per cent, ** Significant 95 per cent, *** Significant 99 per cent

The t-test, F-test, and coefficient of determination are then used to prove the
hypothesis, and as a discussion of the key findings of this study, the fixed effect model
(FEM) is used as the model selection test. Table 5 shows that the first research model has
an R-square value of 0.110 for model 1, where independent commissioners and audit
committees explain earnings quality by 11.060 per cent. Meanwhile, model 2 has an rsquare value of 0.023, which means that male independent commissioners and audit
committees can explain earnings quality by 2.360 per cent. Model 3 has an r-square value
of 0.121, which means that female independent commissioners and audit committees can
explain earnings quality by 12.110 per cent. According to the F-test, the first model has a
significant value of 0.049, the second model has a substantial value of 0.001, and the third
model has a significant value of 0.015, indicating that these three research models are fit
and practicable.
Table 6. Main Hypothesis
PAiT = β₀ + β₁COMIN + β₂COMAU + β₃FSIZE + β₄FAGE + ε

Variable
Coefficient
Prob t-stat
COMIN -> PAiT
1.113
0.047**
COMAU -> PAiT
0.294
0.199
FSIZE -> PAiT
0.915
0.910
FAGE -> PAiT
-0.022
0.233
Notes: PAiT=Earnings Quality, COMIN=Independent Commissioners, COMAU=Audit
Committee, FSIZE=Firm Size, FAGE=Firm Age
* Significant 90 per cent, ** Significant 95 per cent, *** Significant 99 per cent

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Table 6 shows, the coefficient value of the effect of independent commissioners on
earnings quality is 1.113. With a significance value of 0.017, it explains that independent
commissioners positively affect earnings quality, indicating that hypothesis 1 is accepted.
Meanwhile, the coefficient value of 0.294 and significance value of 0.199 explains that the
audit committee does not affect earnings quality; hence, hypothesis 2 is rejected. In this
study, firm size and firm age do not significantly affect earnings quality.
Table 7. Gender Analysis
Variable

Male
Female
Coefficient
Prob t-stat
Coefficient
Prob t-stat
COMIN -> PAiT
-1.834
0.037**
-10.496 0.005***
COMAU -> PAiT
0.800
0.049**
1.801 0.080*
FSIZE -> PAiT
-0.405
0.001***
-0.626 0.052*
FAGE -> PAiT
0.000
0.999
-0.092 0.458
Notes: PAiT=Earnings Quality, COMIN=Independent Commissioners, COMAU=Audit
Committee, FSIZE=Firm Size, FAGE=Firm Age
* Significant 90 per cent, ** Significant 95 per cent, *** Significant 99 per cent

Gender analysis is carried out by dividing panel data based on the male and female
gender of independent commissioners and audit committees to analyse the role of gender
in the supervisory function carried out by independent commissioners and audit
committees on the quality of corporate earnings. After conducting a model selection test
on a sample of companies with male independent commissioners and male audit
committees, the Common Effect Model (CEM) was selected as the best model, as well as
on a sample of companies with female independent commissioners and female audit
committees, so that gender analysis in the regression model uses the Common Effect
Model (CEM).
Table 7 shows explains that male and female independent commissioners influence
management policies in preparing financial statements, but a negative influence on
earnings quality happens. Even so, when compared, the results can be explained that
female independent commissioners have more impact on low earnings quality than male
independent commissioners. Meanwhile, on the other hand, in the gender analysis, it was
also found that the role of male and female audit committees in supervising management
to improve earnings quality was quite effective. However, the level of influence was more
substantial for male audit committees than for female audit committees in carrying out
their supervisory role.
Although not hypothesised, the proof of gender diversity in the influence of
independent commissioners and audit committees in the context of the supervisory
function on earnings quality is proven to have different results for males and females.

DISCUSSION
The test results of hypothesis 1 found that independent commissioners positively
affect earnings quality. These results explain that independent commissioners of diverse
genders supervise management in preparing financial statements in the analysis unit. So,
the greater the number of independent commissioners with gender diversity in a company,

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the more attention management will pay to improving earnings quality in the financial
statements it prepares.
As explained in POJK No. 57 / POJK.04 / 2017, one of the duties of independent
commissioners is to ensure the transparency and openness of the company's financial
statements. As an outsider to the company, independent commissioners have a duty or
supervisory function to management, one of which is the process of preparing financial
reports so that the resulting financial information is of quality so that it can be used by
outsiders, especially investors in their investment policies (Handriani, 2020; Nuroniyah
and Basuki, 2020; Setiawan et al., 2020). With a well-executed supervisory function by
independent commissioners, good corporate governance will be achieved, such as
transparency, accountability, and independence, which are contained in the quality of
earnings on the company's financial statements. The running of the supervisory function
by independent commissioners also minimises information asymmetry that usually arises
between management and investors, as in agency theory. Gender diversity among
independent commissioners has a beneficial impact on the level of information disclosure
(Aribi et al., 2018) and earnings quality (Yousuf & Aldamen, 2021) so that the level of
earnings management is reduced (Kapoor & Goel, 2019; Orazalin, 2020). Gender diversity
is an effective monitoring instrument, which reduces agency conflicts and thus improves
the quality of financial reporting (El-Dasty & Elamer, 2022)
Meanwhile, from the results of the gender analysis, it was found that the role of
independent commissioners with gender specifically, either male only or female only,
hurts earnings quality, and the supervisory role of female independent commissioners is
more vital than male independent commissioners which has an impact on low earnings
quality. These results indicate that in the absence of gender diversity in independent
commissioners, the supervisory function of independent commissioners does not run well
according to its function and encourages management to carry out earnings management
practices so that financial information looks beautiful even though it is far from the quality
of earnings expected by investors. The authority possessed by female independent
commissioners is related to the level of earnings management more strongly than that of
male independent commissioners (Al-absy et al., 2019; Kumar & Ravi, 2022). Female
directors generally consider more issues, not only economic but also social sustainability,
which in turn does not focus on the financial information investors need, which should be
reflected in the earnings quality (Kanadlı et al., 2022), thus getting an adverse reaction in
the stock market (Ghafoor et al., 2022). Meanwhile, male independent commissioners also
negatively impact the quality of corporate earnings, presumably related to the nature and
characteristics of men who tend to take action due to personal goals (Friscilla & Nugroho,
2020). However, the significance is less vital than that of female independent
commissioners.
The results of hypothesis testing did not find a significant effect of the audit
committee on earnings quality. These results explain that the supervisory function carried
out by the audit committee cannot encourage management to improve the quality of
earnings as an output of the process of preparing financial statements. In carrying out its
supervisory function and assisting independent commissioners, the audit committee in the
analysis unit and within the time of this study was found to be ineffective, which was
thought to be due to the limited number of audit committees owned in a company in
Indonesia. It is alleged that an audit committee in a public company is only required for
the company to be listed on the Indonesia Stock Exchange.

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The absence of a significant effect of the audit committee on earnings quality is
thought to be due to not only the lack of supervisory function carried out by the audit
committee but also the lack of power possessed by the audit committee in supervising
management so that its function does not run well (Dewi & Mita, 2019; Halim, 2022;
Kawedar et al., 2021; Nelwan & Tansuria, 2019; Savka, 2019).
Meanwhile, the gender analysis test on the audit committee found a positive effect
of male and female audit committees on earnings quality. However, when compared, it is
known that the impact of male audit committees is more significant than female audit
committees. This result is likely due to the courage males possess compared to the
prudence and ethical thinking of the female audit committee, so the male audit committee
is bolder in its supervisory function than the female audit committee (Rahma & Wahjudi,
2021). With too much caution in the supervisory function, female audit committees make
more mistakes and must be more accurate in estimating earnings (Ammer & AhmadZaluki, 2017).
The different results of the primary regression and gender analysis explain that in
the implementation of the audit committee's duties in supervising management, there
should be no gender diversity in the audit committee team so that it is in line with the
procedures for managing the preparation of financial statements by management and also
in providing opinions and input to independent commissioners. Both female and male audit
committee teams can still perform their supervisory functions well, even though males are
stronger in carrying out their functions. Even so, the imbalance of the unit of analysis is
also one of the reasons that causes different results between the units of study with male
and female audit committees. However, the fact is that in Indonesia, female audit
committees are still much lower than male audit committees. This can be a concern for all
parties, both regulators, organisations and academics, so that the number of female
practitioners with qualified audit skills can increase, and companies can use their role in
their supervisory function as an audit committee.

CONCLUSION
Using 745-panel data points from manufacturing businesses listed on the Indonesia
Stock Exchange from 2015 to 2021 as the unit of study, and the findings of hypothesis
testing, as well as gender analysis on 714 panel data with male independent commissioners
and male audit committees, and gender analysis on 68-panel data with female independent
commissioners and female audit committees, the following can be concluded: The
supervisory function carried out by gender-diverse independent commissioners has a
positive influence on the quality of corporate earnings, but a negative influence occurs
when the supervisory function is carried out by only female independent commissioners
or only male independent commissioners. The supervisory function carried out by the audit
committee does not have a significant effect on the company's earnings quality; even so,
the audit committee's supervisory function can be carried out optimally when the audit
committee team consists of the same gender, both men and women, where the influence
of the male audit committee has a more substantial effect on improving earnings quality
than when gender diversity occurs.
Suggestions. From the results of hypothesis testing and gender analysis in this study,
the following suggestions can be conveyed: This study found a positive effect of
independent commissioners with a variety of genders on earnings quality and vice versa.

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If only a specific gender, investors should consider a policy of determining independent
commissioners of various genders so that the supervisory function can run better. This
study found that male or female audit committees significantly increase earnings quality
compared to gender diversity in the audit committee team. These can be input by
independent commissioners in forming committee teams to help carry out the supervisory
function. The role of the female audit committee, although quite significant in improving
earnings quality, is more important for the male audit committee; this is thought to be due
to the number of female audit committees that are not as many as men, so the role of the
Government as a regulator, audit or accountant organisation to the role of company owners
in policies to increase the ability and opportunities for more women so that they can carry
out their functions as audit committees.

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