Does Transfer Pricing, Sales Growth, Foreign Ownership, Asset Intensity Affect Tax Avoidance in Energy Companies in Indonesia?

Rio Dhani Laksana¹*, Intan Shaferi², İlkay Aydoğmuş³

^1,2 Departement of Management, Jenderal Soedirman University, Indonesia,

³ Department of Economics, Istanbul Medeniyet University, Turkey

Email: [email protected]

Keywords:

ABSTRACT

Transfer Pricing, Sales Growth, Asset Intensity, Foreign Ownership

Tax avoidance measures are carried out because of different interests on the part of the government and the companies, where the government needs to increase state revenues through large tax revenues while the companies want taxes to be as minimal as possible because taxes are a burden that reduces profits. The research aims to examine transfer pricing, sales growth, asset intensity and Foreign Ownership affected on tax avoidance in energy companies in Indonesia. A sample of companies in the energy sector that were listed on the Indonesia Stock Exchange (IDX) between 2020 and 2022 was selected. Descriptive statistical tests, conventional assumptions, multiple regression analysis, and hypothesis testing. According to the test, the findings of this study show that transfer pricing and asset intensity has positive impacts impacts tax avoidance.� Sales Growth and Foreign ownership, have a negative impact on tax avoidance.

INTRODUCTION

The tax sector is a crucial component of the Indonesian economy (Pattiasina et al., 2019). Taxes make up a sizable component of the revenue segment of the State Revenue and Expenditure Budget (APBN) compared to other sectors. The objective for tax revenue is Rp. 1,444.5 trillion in 2021, which is reflected in the overall state income of Rp. 1,743.6 trillion (Ministry of Finance of the Republic of Indonesia, 2022). In accordance with the philosophy of the tax law, it is not only an obligation for citizens to pay taxes, but also a citizen's right to participate in national development. To realize development independently can be done by optimizing tax revenues. Tax revenues must be increased optimally so that they can contribute to the country's economy which can be utilized for the growth and implementation of the country's development (Andrejovsk� & Pulikov�, 2018). In Indonesia, the Covid-19 epidemic has had a significant influence on several areas, including the economy. An economic crisis brought on by the Covid-19 outbreak resulted in a recession.

The policy issued by the government to deal with the Covid-19 pandemic was one of the aspects that caused tax revenue to contract by 19.7% from the previous year. The condition of tax revenue which is experiencing a decline will affect the tax ratio. in 2019 it was 9.77%, a decrease of 0.47% from the previous year. In 2020 Indonesia's tax ratio decreased drastically to 8.33% due to the Covid-19 pandemic which hampered economic activity so that among Asian and Pacific countries, Indonesia's tax ratio was only higher than Bhutan and Laos (OECD, 2022). Indonesia's tax ratio then increases in 2021 in line with the economic recovery of 9.11%.

Tax avoidance measures are carried out because of different interests on the part of the government and the companies, where the government needs to increase state revenues through large tax revenues while the companies want taxes to be as minimal as possible because taxes are a burden that reduces profits (Wang et al., 2020). In contrast to tax evasion which is an illegal act, tax avoidance is carried out by exploiting loopholes in tax regulations. Tax Avoidance encompasses behaviors that may be harmful to the state even when it is lawful and does not break the law.

One of the Tax Avoidance cases in the energy sector is the PT Adaro Energy Tbk case. According to the Taxing Times for Adaro report by Global Witness, Adaro Energy has avoided or reduced the tax payments it should have by transferring its profits to a network of overseas companies that are tax havens. In this way, it is possible for Adaro Energy to reduce the amount of tax by US$125 million between 2009 and 2017. In this case, Adaro practiced Tax Avoidance by utilizing transfer pricing (Global Witness, 2019).

Transfer pricing is typically used by businesses to decrease their tax liability in tax evasion strategies (Niskanen,J.2021). Multinational companies are starting to take advantage of transfer pricing practices in line with the development of the international economy (Sebele-Mpofu et al., 2021). Companies will be able to transfer their earnings to connected corporations in tax havens thanks to transfer pricing.

Sales have a strategic influence on the company since they must be supported by assets or, if sales are boosted, other assets must be added (Mahfudz et al., 2021). Looking at sales from the prior year might help businesses appropriately maximize their current resources. Sales growth is crucial to the management of work assets. As sales increase and earnings rise, businesses will often adopt more sustainable business practices Tax Evasion.

The percentage of fixed assets that contain posts for businesses to add expenses, specifically the depreciation expense incurred by fixed assets as a deduction from income, is known as fixed asset intensity (Owusu, et.al. 2022). If the fixed assets are greater, the profit generated will be smaller because the depreciation expense contained in fixed assets can lower profit. Fixed asset intensity, according to (Owusu, et.al. 2022). is the proportion of fixed assets that have opportunities for enterprises to contribute expenditures, notably the depreciation expense experienced by fixed assets as a deduction from income (cox, 2006). Greater fixed assets will result in fewer profits since the depreciation expenditure incurred by fixed assets might reduce profits.

Foreign ownership is one of the reasons companies decide to practice Tax Avoidance (Wang, 2020) in selecting companies for investment, investors have considered which companies have the possibility of a high rate of return. To obtain a high rate of return, foreign ownership can contribute to determining company policies that lead to minimizing the tax burden (Pascan, I. & Turcas, M. (2012). Based on this background, it follows that many businesses, particularly the energy corporations being investigated, continue to attempt to adopt tax evasion.

LITERATURE REVIEW

Agency Theory

Agency theory will be utilized in this study to describe the connection that develops when there is a work contract between the principle, who acts as the authorizer, and the agent, who acts as the management of the business (Saw, K. & Sawyer, A. (2010).). In practice, this will lead to differences in interests between principals and agents (Mahfudz 2021). Conflicts of interest in the field of taxation can occur between the government and companies (Mahfudz 2021). Tax authorities representing the government acting as principals want greater corporate taxes in order to increase tax revenues while corporate taxpayers representing companies acting as agents want significant profits with a minimum tax burden.

Development of the Hypothesis

Transfer Pricing's Impact on Tax Avoidance

Based on agency theory, agents who have personal interests will seek the maximum profit (Zalata , 2017) In manipulating transfer pricing, companies (agents) have different interests from the government (principal) which seeks to maximize state revenue from the taxation sector Companies can manipulate transfer pricing by increasing the purchase price and reducing the selling price, then the company can transfer profits to the companies in tax havens (tax havens) corporations now have more chances to take advantage of transfer pricing with the goal of reducing their tax liability thanks to the position of corporations that are allowed to adopt a concept when determining transfer prices. According to the given description, the theory put forward:

H1: Transfer pricing has a Positive Effect on Tax Avoidance

Sales Growth's Impact on Tax Avoidance

Looking at sales from the prior year might help businesses appropriately maximize their current resources. Sales growth is crucial to the management of work assets. Since sales growth measurement may indicate if a company's sales growth rate is excellent or poor, it is used in this study. Businesses may forecast how much profit will be made based on the rate of sales growth. The agency theory, which analyzes the issues between principals and agents that lead to disagreements over the profits earned by the firm, is related to the theory used to explain sales growth. One of the variables that might affect tax evasion practices is sales growth. This is supported by research by Laksana (2021), which demonstrates how sales growth has a big impact on CETR, a measure of tax evasion activities. According to the given description, the theory put forward is as follows:

H2: Sales Growth has a positive effect on Tax Avoidance

Asset Intensity's Effect on Tax Avoidance

One of a company's features that might affect tax evasion is asset intensity. The intensity of a company's corporate assets might reveal how much it spends in fixed assets. Utilizing the study findings that asset intensity has a favorable influence on tax avoidance, the ratio of a company's asset intensity will illustrate how effective it is in producing sales, namely the study of Salihu et al. (2015). According to agency theory, managers who desire pay would boost business performance by investing company funds in fixed assets and taking advantage of depreciation expenses to reduce the tax burden on the company. The performance of the business will rise as a result of the tax burden reduction, enabling the manager's targeted pay to be realized. According to the given description, the theory put forward is as follows:

H3: Asset intensity has a positive effect on Tax Avoidance

Effect of Foreign Ownership on Tax Avoidance

Foreign ownership will often have positive effects, one of which is increased tax income, but foreign ownership can also affect how business policies are decided, which could result in tax evasion. The right of foreign investors to engage in management and enjoy profit sharing increases with the percentage of foreign investor ownership, meaning that they have a stronger influence when deciding on corporate policies, especially those that promote tax avoidance. In this case, an agency problem arises where investors the foreigner (principal) is able to make the manager (agent) do what he wants so that the personal interests he wants can be achieved According to the given description, the theory put forward:

H4: Foreign ownership has a positive effect on Tax Avoidance

METHOD

This study is a specific type of quantitative study that makes use of secondary research information from an annual report. A sample of companies in the energy sector that were listed on the Indonesia Stock Exchange (IDX) between 2020 and 2022 was selected using purposeful sampling. Descriptive statistical tests, conventional assumptions, multiple regression analysis, and hypothesis testing were the data analysis approaches employed.

Table 1

Research Sample

Criteria	Year			Amount
	2020	2021	2022
energy sector company listed on the IDX	76	76	76	228
Energy sector companies that do not publish an annual report	(15)	(10)	(8)	33
Energy sector companies that suffered losses	(22)	(17)	(16)	55
Energy sector companies that do not contain the data needed in the research	(20)	(21)	(20)	61
Total Sample	19	28	32	79

Source: idx.com, 2023

Operational Definition and Variable Measurement

Tax Avoidance

Tax avoidance is carried out so that profits are not reduced due to the tax burden (Wang et al., 2020). The Effective Tax Rate (ETR) is the substitute (January & Suardikha, 2019).

Transfer Pricing

The price for transactions involving parties having a particular relationship is known as transfer pricing. The proxies utilized are as follows (Roslita, 2020):

Sales Growth

Sales growth, which depicts the evolution of sales volumes from year to year, is the primary metric used to assess the company's growth. As a result, these developments may accelerate or slow down. Net sales for the current year period are divided by net sales for the prior year, minus one, to calculate sales growth (Dyreng et al, 2010).

Intensity of Asset

Asset intensity reflects how much money the company spent on fixed assets (Dharma & Noviari, 2017). The proxy used to calculate asset intensity is as follows (Indradi, 2018):

Foreign Ownership

The definition of investing in foreign assets is the activity of planting assets carried out by citizens, business entities and foreign governments in the territory of the Republic of Indonesia. The formula for calculating the foreign ownership ratio (Salihu et al., 2015) is as follows:

RESULTS

Statistical Analysis Descriptive

Table 2

Statistical Test Descriptive

	Y	X1	X2	X3
Means	0.237245	0.157502	0.088840	0.473800
Median	0.249800	0.050600	0.072900	0.464100
Maximum	0.745400	0.925500	0.949900	0.882200
Minimum	0.000200	0.000700	0.46500	0.132500
Std. Dev	0.122946	0.229067	0.203540	0.171122
Skewness	0.832764	1.91724	1.480321	0.159958
Kurtosis	8.328498	6.229992	9.957977	3.537495
Jarque-Bera	61.03512	49.23637	111.9752	0.766190
Probability	0.0000	0.0000	0.0000	0.68748
Sum	11.15050	7.402600	4.175500	22.26860
Sum Sq Dev.	0.6953255	2.413702	1.905709	1.347000
Observations	79	79	79	79

Source: secondary data processed through eviews

The number of N, or the total quantity of data examined, is 79 samples, as shown in the table of descriptive statistical test results. The investigation into the tax evasion variable revealed the following results: The tax avoidance variable has the following values: 0.000200 for the lowest value, 0.237245 for the highest value, and 0.122946 for the standard deviation (SD). The results of the study on the transfer pricing variable have an average (mean) value of 0.157502, a maximum (maximum) value of 0.925500, a lowest (minimum) value of 0.000700, and a standard deviation (SD) of 0.229067. The results of the study on the sales growth variable include an average (mean) value of 0.0888840, a maximum (maximum) value of 0.949900, a minimum (minimum), and a standard deviation of 0.203540.

Panel Data Regression Model

Common Effect Model Testing

Table 3

Common Effect Model (CEM)

Variables	Coefficient	Std. Error	t- Statistics	Prob.
C	0.177864	0.050186	3.544055	0.0010
X1	0.254251	0.071296	3.566633	0.0009
X2	0.087041	0.080312	1.083787	0.2875
X3	0.024490	0.095850	0.255499	0.7996
X4	0.0145868	0.069986	0.785635	0.3238
R-Squared	0.250660	Mean dependent var		0.237245
Adjusted R-Squared	0.198381	SD dependent var		0.122946
SE of regression	0.110078	Akaikecriterion info		-1.493996
Sum squaredresid	0.521035	Schwarzcriteria		-1.336537
Likelihood logs	39.10892	Hannan-Quinncriter		-1.493996
F-statistics	4.794621	Durbin-Watson stat		1.553246
Prob (F-statistic)	0.115724

Source: secondary data processed through eviews

Fixed Effect Model Testing

Table 4

Fixed Effects Model (FEM)

Variables	Coefficient	Std. Error	t- Statistics	Prob.
C	0.206518	0.110867	1.86274	0.0712
X1	0.217353	0.083039	2.617475	0.0131
X2	0.109013	0.084114	1.296014	0.2037
X3	-0.027842	0.231018	-0.120519	0.9048
X4	0.181345	0.074624	1.213732	0.0137
Effects Specification Cross-section fixed (dummy variables)
R-Squared	0.51335	Mean dependent var		0.23325
Adjusted R-Squared	0.341687	SD dependent var		0.12869
SE of regression	0.099753	Akaikecriterion info		-1.52842
Sum squaredresid	0.338320	Schwarzcriteria		-1.031099
Likelihood logs	49.25678	Hannan-Quinncriter		-1.350270
F-statistics	2.98997	Durbin-Watson stat		2.36214
Prob (F-statistic)	0.005973

Source: Secondary data processed through eviews.

Testing the Random Effect Model

Table 5

Random Effects Model (BRAKE)

Variables	Coefficient	Std. Error	t- Statistics	Prob.
C	-0.1866782	0.070254	2.656893	0.0121
X1	-0.2331	0.07539	3.10011	0.00
X2	-0.0974	0.07881	1.23595	0.224
X3	-0.2272	0.063502	3.24414	0.00
X4	-0.3531	0.07248	1.54729	0.21
Effects Specification			SD	Rho
Random cross-sections			0.065591	0.3013
Idiosyncratic random			0.099751	0.6946
Weighted Statistics
R-Squared	0.235	Mean dependent var		0.137837
Adjusted R-Squared	0.182535	SD dependent var		0.104572
SE of regression	0.096116	Sum squared residue		0.397242
F-statistics	4.416663	Durbin-Watson stat		2.029672
Prob (F-statistic)	0.008357
Unweighted Statistics
R-squared	0.248827	Mean dependent var		0.237245
Sum squared residue	0.522310	Durbin-Watson stat		1.54366

Source: secondary data processed through eviews

Panel Data Regression Model Selection

Chow test

Table 6

Chow Test Table

Effect Test	Statistics	Df	Prob.
Cross-section F	2.040243	(9,34)	0.0644
Chi-square cross-sections	20.295732	9	0.0164

Source: Secondary data processed through eviews.

Based on the Chi Square (0.0162) > (0.05) probability cross-section value, the value of the Chi Square Cross-section Probability is 0.0162, in accordance with the aforementioned facts. Given that H0 is disregarded and H1 is permitted, it can be claimed that the Fixed Effect Model (FEM) is the most appropriate model to use when estimating panel data.

Hausman test

Table 7

Hausman Test Results

Test Summary	Chi-Sq. Statistics	Chi-Sq. df	Prob.
Random cross-sections	0.258509	3	0.9676

Source: Secondary data processed through eviews.

According to the table above, the probability cross-section random value is 0.0001. Based on the likelihood that the cross-section random is (0.9676) > (0.05). Given that H0 is rejected and H1 is accepted, it may be claimed that the Random Effect Model (REM) is the best model to use when estimating panel data. As a result, it can be concluded from the results of the model selection that the Random method is the most appropriate model to use in this inquiry. Models of Effect (REM).

Lagrange multiplier test (LM test)

Table 8

LM Test Results

Test Hypothesis
	Cross-section	time	Both
Breusch- Pagan	3.160064	1.411910	4.571974
	(0.0755)	(0.2347)	(0.0325)

Source: Secondary data processed through eviews.

Since the cross-sectional value of Breusch-Pagan is less than 0.05 and is shown as 0.0325 in Table 4.6, it can be seen that H0 is rejected and H1 is authorized. This indicates that the results support the Random Effect Model (REM).

Panel Data Regression Analysis

Table 9

Panel Data Regression Analysis Results

Variables	Coefficient	Std. Error	t- Statistics	Prob.
C	0.0186663	0.070256	2.65987	0.0110
X1	0.233743	0.075398	3.100113	0.0034
X2	0.097415	0.078818	1.235952	0.2232
X3	0.12367	0.135025	0.091598	0.0063
X4	0.212542	0.072432	2.754313	0.01237

Source: Secondary data processed through eviews.

The regression model equation between the independent variables (Tax Avoidance) and the dependent variable (Tax Avoidance) is derived as shown in the table above:

Y = α + β1X1 + β2X2 + β3X3+ β4X4 + e

Y = 0.186663 + 0.233743 + 0.097415 + 0.012367+0.212542 + e

Hypothesis Testing

Coefficient of Determination (Adjusted R2)

Table 10

Adjusted R2 Test Results

R-squared	0.235555	Mean dependent var	0.135139
adjustedR-squared	0.182222	SD dependent var	0.106609
SE of regression	0.096116	Sum squared residue	0.397242
F-statistics	4.416663	Durbin-Watson stat	2.029672
Prob (F-statistic	0.008563

Source: Secondary data processed through eviews.

The corrected R-squared value is 0.182222, as seen in the table above. This shows that the variable tax avoidance may be explained by the independent variables of transfer pricing, sales growth, and sales growth of 18.2%. While other variables not considered in the study's regression model are responsible for 81.8% of the variation.

Simultaneous Test (Test F)

Table 11

F Test Results

R-squared	0.235555	Mean dependent var	0.135139
Adjusted R squared	0.182222	SD dependent var	0.106609
SE of regression	0.096116	Sum squared residue	0.397242
F-statistics	4.416663	Durbin-Watson stat	2.029672
Prob (F-statistic)	0.008563

Souce: secondary data processed through eviews

According to the table above, the probability value is 0.008563, and the F-statistic is 4.416663. Given that the probability value is substantially lower (0.008563 0.05) than the value, H0 is rejected and H1 is approved. Therefore, it may be said that the independent factors might influence the dependent variable concurrently (together).

Partial Test (T Test)

Table 12

Partial Test Results

Variables	coefficient	std. Error	t-Statistics	Prob.
C	0.01742	0.0702	2.6785	0.0110
X1	0.23374	0.0753	3.1041	0.0034
X2	0.09741	0.0786	1.2395	0.2232
X3	0.21415	0.0623	2.8653	0.00635
X4	0.07674	0.0646	1.4130	0.23853

Source: Secondary data processed through eviews.

Effect of Transfer Pricing on Tax Avoidance

The first hypothesis (H1) is accepted since the findings of this study's testing for it indicated a significance value of 0.0034, which is less than the 5% or 0.05 significance level. This indicates that transfer pricing significantly affects tax evasion.

Sales Growth's Impact on Tax Avoidance

The second hypothesis (H2) was tested in this study, and the results indicated a significance value of 0.2232 larger than the 5% or 0.05 significance threshold, which suggests that H2 is rejected since sales growth has no discernible impact on tax evasion.

Asset Intensity's Impact on Tax Avoidance

The second hypothesis (H3) is supported based on the study's test results, which reveal a significance value of 0.00635 that is less than the threshold of 5% or 0.05, indicating that there is no significant relationship between capital intensity and tax evasion.

Foreign ownership's impact on tax evasion

Sales growth has no discernible impact on tax evasion, according to the test findings for the second hypothesis (H2) in this study, which reveal a significance value of 0.012367, which is less than the 5% or 0.05 significance threshold. Accordingly, H4 is rejected.

DISCUSSION

Transfer Pricing's Impact on Tax Avoidance

According to the results of this study's testing of the first hypothesis (H1), transfer pricing has a considerable impact on tax evasion. H1 is allowed since the significant value of 0.0034 is less than the 5% or 0.05 significance level. The findings of this study are validated by Wahyudi,et.al (2019) , who reached the same conclusion as this study that transfer pricing has a beneficial effect on tax evasion.

Sales Growth's Impact on Tax Avoidance

The findings of this study's second hypothesis (H2) test showed a significance value of 0.9274 that was higher than the 5% or 0.05 significance level, which suggests that H2 is rejected since capital intensity does not significantly affect tax evasion. This study's findings are in line with those of Smith, D. & Richardson, G. (1999), and they demonstrate that having a large proportion of fixed assets would not reduce the amount of tax evasion by enterprises.

Sales growth has a significant influence on tax avoidance, according to a research by Wang, 2020, which implies that the more profit a company earns, and the less probable it is to have a tax evasion policy since it can afford to pay taxes as a legal obligation.

Asset Intensity's Impact on Tax Avoidance

Transfer pricing, sales growth, and capital intensity all affect tax evasion simultaneously, according to the findings of this study's simultaneous hypothesis testing. The results, specifically the Prob F-statistic value of 0.008563, which shows that the outcome is less significant than the threshold of 0.05, make this clear. Therefore, it can be inferred that whether examined concurrently or simultaneously, the independent variables consisting of transfer pricing, sales growth, and capital intensity have an impact on tax evasion. To put it another way, the fourth hypothesis is true.

According to research by Viryatama (2020), asset intensity significantly affects tax avoidance. Asset intensity has to do with how much money the business spends on fixed assets. The cost of depreciating fixed assets will rise as a company's capital intensity rises. As a result, the company's earnings will drop, which will result in a drop in the amount of taxes due. If a company's earnings declines, it will have a low CETR, which means there will be more tax evasion taking place.

Oktaviana, Sunarta, and Fadillah's (2019) finding that transfer prices have a large beneficial impact on tax evasion supports the findings of this study, leading to the conclusion that corporations collaborate in tax evasion. This suggests that the Company takes use of tax evasion strategies by capitalizing on flaws in tax laws.

Foreign ownership's impact on tax evasion

Tax avoidance is negatively impacted by foreign ownership. Alkurdi & Mardini's (2020) study, which demonstrates that foreign ownership has a favorable impact on tax evasion, contradicts the conclusions of this study, which were based on testing. Companies with a foreign ownership structure will maintain a good image of the company by not doing tax evasion and providing benefits to society through appropriate tax payments by observing and complying with applicable regulations. This is in accordance with the legitimacy theory that the company's awareness that its survival depends on the community and the surrounding environment, will make the company not cross the boundaries and norms of society that apply. It can be concluded that high foreign ownership of companies will reduce tax evasion. The study's results support those of Uyar, A., (2022) who discovered that foreign ownership negatively impacted tax evasion.

CONCLUSION

This study investigates how asset intensity, foreign ownership, and transfer pricing affect tax evasion. According to the test, the findings of this study show that transfer pricing and asset intensity has positive impacts impacts tax avoidance.� Sales Growth and Foreign ownership, have a negative impact on tax avoidance. The limitation of this research is that it only examines the effect of transfer pricing, foreign ownership and asset intensity with research samples used by energy sector companies.

In order to more easily identify the transfer pricing phenomena that businesses exploit to evade taxes, future study might concentrate on enterprises that are linked with or have particular links with businesses in tax havens. Growth in sales does not significantly affect tax evasion. Tax evasion is significantly impacted by asset intensity.

In light of the limitations and deficiencies identified in this study, the authors propose the following recommendations. Firstly, future research endeavors should address these constraints by broadening the sample size to include companies listed on the Indonesia Stock Exchange (IDX) and extending the study period. Additionally, researchers are encouraged to incorporate additional variables, such as firm size, to comprehensively analyze the factors influencing tax evasion. Secondly, companies contemplating going public are advised to exercise greater caution in evaluating their use of tax management and associated risks, aiming to avoid tax administration penalties, including potential criminal consequences. It is crucial for companies to fulfill their tax obligations responsibly and refrain from engaging in tax avoidance practices. The cointegration equation (long-term) estimation results underscore that changes in oil prices and the natural logarithm of relative money supply from the previous one-quarter period do not impact the exchange rate. Conversely, variations in foreign exchange reserves, the natural logarithm of comparable gross domestic product, and relative interest rates from the previous one-quarter period exhibit a negative influence on the exchange rate.

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Copyright holder:

Rio Dhani Laksana, Intan Shaferi, İlkay Aydoğmuş (2023)

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Journal of Social Science

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