Agency Problem: The Role of Governance as a Mitigant in two Tier Governance System in Indonesia

Nico ALEXANDER

doi:10.2478/fman-2025-0002

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Agency Problem: The Role of Governance as a Mitigant in two Tier Governance System in Indonesia

Foundations of Management

Volume 17 (2025): Issue 1 (January 2025)

By: Nico ALEXANDER

Open Access

|Mar 2025

Figures & Tables

Type of Agency Problem
(*Source:* Flayyih and Khiari, 2023, p.201)

Research Framework
(*Source:* Author’s own research)

Table 1.

Sample Selection Procedure (Source Author’s own research)

No	Description	Total
1.	During the research period, companies in the consumer cyclical and consumer non-cyclical sectors that were listed on the Indonesia Stock Exchange were examined.	191
2.	Companies that do not present financial reports as of December 31	(16)
3.	Companies that do not to use the Rupiah currency	(13)
4.	Companies that experience losses	(96)
Total number of companies		66
Research period		3 years
Total number of samples		198

Table 2.

Variable Measurement (Source: Author’s own research)

Variable	Definition	Measurement
Agency problem (AP)	Agency conflicts stem from misaligned incentives between the principal and the agent. In this study, agency conflicts are assessed through the lens of earnings management as proposed by Dechow in 1995. The evaluation of agency conflicts can be conducted by examining earnings management. Thus, this study aims to utilize framework for measuring earnings management. (Dechow, et al., 1995)	$\begin{matrix} TACt = NIt - CFOt \\ \frac{TACt}{At - 1} = α 1 (\frac{1}{At - 1}) + α 2 (\frac{Δ REVt - Δ RECt}{At - 1}) + α 3 (\frac{PPEt}{At - 1}) + e \\ NDAt = α 1 (\frac{1}{At - 1}) + α 2 (Δ REVt - \frac{Δ RECt}{At - 1}) + α 3 (\frac{PPEt}{At - 1}) \\ DACt = (\frac{TACt}{At - 1}) - NDAt \end{matrix}$
Board of commissioners (BOC)	The board of commissioners serves as the overseeing body within a company that operates under a two-tier system. Its primary role is to supervise and offer guidance to the board of directors.	∑ Number of commissioners
Independent commissioners (IND)	Independent commissioners are individuals serving on the board of commissioners without any ties to the company.	$\frac{Number of independent commissioners}{\sum Number of commissioners}$
Audit committee (AC)	The audit committee functions as an additional supervisory entity selected by the board of commissioners.	∑ Number of audit committees
Audit committee expertise (EXP)	Audit committee members are chosen based on a specific criterion, which is possessing proficiency and practical knowledge in finance.	$\frac{Members with financial background}{\sum Number of audit committees}$
Audit quality (AQ)	External auditors are individuals who are not affiliated with the company and are designated to ensure the reliability and accuracy of the financial statements.	Audit quality can be assessed by utilizing a binary variable, assigned a value of 1 when the external auditor of the company is affiliated with one of the Big 4 firms, and 0 otherwise.
Profitability (PROF)	The profitability of a company demonstrates its capacity to generate a net income	$\frac{Net income}{Total assets}$
Leverage (LEV)	Leverage refers to the assessment of the proportion of debt to equity within a company.	$\frac{Debt}{Equity}$
Firm size (SIZE)	The size of a company is determined by the quantity of assets it possesses. As the number of assets owned increases, so does the magnitude of the company.	Natural logarithm (Total assets)

Table 3.

Descriptive Statistics (Source: Author’s own research)

	Maximum	Minimum	Mean	Std. deviation
AP	0.8393	- 0.2282	0.0045	0.1075
BOC	10	2	4.1818	1.6912
IND	0.8333	0.3333	0.4389	0.1141
AC	3	3	3.0151	0.1224
EXP	1	0	0.5795	0.2503
AQ	1	0	0.4595	0.4996
PROF	0.4930	0.0002	0.0799	0.0705
LEV	7.5853	0.0004	0.9304	0.9918
SIZE	259,692,979,111	180,433,300,000,000	14,557,693,746,764	27,683,481,766,119

1 AP = Agency Problem, BOC = Board of Commissioners, IND = Independent Board of Commissioners, AC = Audit Committee, EXP = Audit Committee Expertise, AQ = Audit Quality, PROF = Profitability, LEV = Leverage, SIZE = Firm Size (in IDR)

Table 4.

Correlation Results (Source: Author’s own research)

	EM	BOC	IND	AC	EXP	AQ	PROF	LEV	SIZE
AP	1	-	-	-	-	-	-	-	-
BOC	- 0.078	1	-	-	-	-	-	-	-
IND	- 0.030	- 0.130	1		-	-	-	-	-
AC	- 0.016	0.060	0.393	1	-	-	-	-	-
EXP	- 0.186	0.202	- 0.150	- 0.163	1	-	-	-	-
AQ	- 0.159	0.441	- 0.022	- 0.114	0.321	1	-	-	-
PROF	0.331	0.003	0.209	- 0.124	0.215	0.146	1	-	-
LEV	- 0.137	0.214	0.315	0.409	0.007	0.118	- 0.134	1	-
SIZE	0.046	0.506	0.072	- 0.111	0.176	0.470	0.058	0.157	1

Table 5.

Multicollinearity Results (Source: Author’s own research)

Variable	VIF
BOC	1.646
IND	1.522
AC	1.492
EXP	1.164
AQ	1.531
PROF	1.167
LEV	1.412
SIZE	1.620

Table 6.

Autocorrelation Results (Source: Author’s own research)

Durbin – Watson

1.883

Table 7.

Heteroskedasticity Results (Source: Author’s own research)

F-statistic	11.9135	Prob. F	0.0000
Obs*R²	66.3754	Prob. chi-square	0.0000

Table 8.

Hypothesis Results (Huber-White) (Source: Author’s own research)

Variable	Predicted Sign	Coefficient	t-Statistic	Prob.
Constanta	-	- 0.567556	- 2.684904	-
BOC	-	- 0.003839	- 0.994104	0.3214
IND	-	- 0.129492	- 1.790326	0.0750*
AC	-	0.072867	1.437175	0.1523
EXP	-	- 0.105775	- 3.045734	0.0027*
AQ	-	- 0.044776	- 2.688230	0.0078*
PROF	-/+	0.660226	2.272222	0.0242*
LEV	-/+	- 0.007082	- 0.761935	0.4470
SIZE	-/+	0.015775	3.365222	0.0009*