12-31-2023
UNRAVELING THE EFFECTS OF TRANSFER PRICING UNRAVELING THE EFFECTS OF TRANSFER PRICING DOCUMENTATION REGULATION: INDONESIA’ EVIDENCE DOCUMENTATION REGULATION: INDONESIA’ EVIDENCE
Anggari Dwi Saputra
Directorate General of Tax, Indonesia, [email protected]
Follow this and additional works at: https://scholarhub.ui.ac.id/jaki
Part of the Accounting Commons, Econometrics Commons, and the Taxation Commons Recommended Citation
Recommended Citation
Dwi Saputra, Anggari (2023) "UNRAVELING THE EFFECTS OF TRANSFER PRICING DOCUMENTATION REGULATION: INDONESIA’ EVIDENCE," Jurnal Akuntansi dan Keuangan Indonesia: Vol. 20: Iss. 2, Article 4.
DOI: 10.21002/jaki.2023.10
Available at: https://scholarhub.ui.ac.id/jaki/vol20/iss2/4
This Article is brought to you for free and open access by the Faculty of Economics & Business at UI Scholars Hub.
It has been accepted for inclusion in Jurnal Akuntansi dan Keuangan Indonesia by an authorized editor of UI Scholars Hub.
Jurnal Akuntansi dan Keuangan Indonesia Volume 20 Issue 2 December 2023
UNRAVELING THE EFFECTS OF TRANSFER PRICING DOCUMENTATION REGULATION: INDONESIA’ EVIDENCE
1Anggari Dwi Saputra
Directorate General of Tax, Indonesia [email protected]
Received: 19 August 2023; Revised: 30 October 2023, 15 December 2023; Accepted: 19 December 2023
Abstract
To counter tax avoidance using transfer mispricing practices, Indonesia introduced a transfer pricing documentation policy. This policy requires taxpayers to be transparent with their transfer pricing decisions. Treating the implementation of this policy as a shock to the taxpayers, this paper examines how the transfer pricing documentation policy affects a firm's tax avoidance behaviour by employing regression discontinuity design and difference-in- difference. Immediately after introducing the policy, a regression discontinuity analysis results indicate a 0.9 percentage point increase in tax/sales among taxpayers obligated to prepare transfer pricing documentation. A 0.3 to 0.7 percentage point increase in the tax/sales of the treatment group is observed when difference-in-difference is established.
These findings show that such policy implementation can discourage taxpayers' tax avoidance behaviour. In light of these results, the Indonesian tax authority may consider taking several actions to improve the implementation of TP docs, such as amending summary of TP docs so that it contains more valuable information regarding taxpayer’s arm’s length principle application, requiring simple TP docs for taxpayers below the threshold, providing continuously providing assistance and capacity building to the taxpayers regarding appropriate TP docs preparation and arm’s length principle application.
Keywords: transfer pricing, transfer pricing documentation, tax avoidance, regression discontinuity, difference-in-difference
Abstrak
Dalam rangka pencegahan penghindaran pajak menggunakan praktik penyalahgunaan harga transfer, Indonesia mengadopsi kebijakan dokumen harga transfer. Pengaturan ini menwajibkan Wajib Pajak untuk transparan terhadap penetapan harga transfernya. Penelitian ini menggunakan kebijakan dokumen penetapan harga transfer sebagai shock untuk meneliti dampak implementasi dokumen penetapan harga transfer terhadap perilaku penghindaran pajak wajib pajak. Hasil analisis regression discontinuity design menunjukan bahwa satu tahun setelah kebijakan dokumen penetapan harga transfer diberlakukan terdapat kenaikan, secara rata-rata, 0.9 poin persentase pajak/penjualan pada wajib pajak yang wajib menyelenggarakan dokumen penetapan harga transfer. Hasil analasis difference-in- difference menunjukkan magnitudo dampak yang lebih kecil yakni sekitar 0.3 sampai 0.7 poin persentase. Hasil analisis menunjukkan bahwa implementasi kebijakan dokumen penetapan harga transfer dapat mendorong wajib pajak untuk mengurangi praktik penghindaran pajak melalui transfer pricing. Berdasarkan hasil tersebut, penelitian ini
1 An online appendix to this paper can be downloaded at https://1drv.ms/b/s!AvvQW9W- M8rVuh03m2ipvsnmJuzE?e=BohnyS.
mengusulkan otoritas pajak Indonesia untuk dapat mengambil Langkah untuk meningkatkan penerapan dokumentasi harga transfer seperti mengubah ikhtisar dokumen harga transfer agar memuat informasi yang lebih bermakna seperti ringkasan penerapan prinsip kewajaran dan kelaziman usaha wajib pajak, mensyaratkan dokumen harga transfer yang sederhana bagi wajib pajak yang saat ini dikecualikan, menyediakan bantuan dan pengembangan kapasitas secara terus menerus bagi wajib pajak terkait penyelengaaran dokumen harga transfer dan penerapan prinsip kewajaran dan kelaziman usaha.
Kata kunci: harga transfer, dokumen penetapan harga transfer, penghindaran pajak, regression discontinuity, difference-in-difference
INTRODUCTION
Tax avoidance by exploiting transfer pricing2 schemes has become a perennial problem for Indonesia. The OECD (2021) found an ample presence of profit shifting tax-motivated behaviour of Multinational Enterprises (MNEs).
Evidence shows that MNEs report their profit in locations that differ from their economic activities (OECD 2021). In countries where 0% or low tax rates3,
"MNEs report a relatively high share of profits (26%) compared to their share of employees (3%) and tangible assets (14%)"
(OECD 2021).
As preached by neoclassical economic theory, profit maximization drives the behavior of the enterprises to maximize its profit through economic efficiency. Minimizing cost, inter alia cost of tax using tax avoidance, could be one instrument to reach such economic efficiency goal. There are multiple common ways used by enterprises to avoid tax, such as transfer pricing, treaty shopping, controlled foreign companies, thin capitalization, excessive cost of debt, arrangement through special purpose company, dan hybrid mismatch arrangement, and etc.
Tax avoidance through transfer pricing, however, has been concluded by several studies as the fairly effective way to
2 Transfer pricing is the price which is set in the transaction
between associated enterprises that are bound to each other, typically due to ownership. It is a legal practice in business; however, it is oftentimes used to manipulate profits. (OECD 2017)
avoid tax (Dyreng and Lindsey 2009;
Slemrod 2001; Taylor and Richardson 2012; Rego 2003). Taylor and Richardson (2012) which set the scene based on publicly listed Australian firms found that firms’ primary tools to perform international tax avoidance were thin capitalization and transfer pricing. Prior to that evidence, Slemrod (2001) has modeled MNEs’ response to the taxation, and has concluded that MNEs utilize intra group set of transactions based on group tax planning to minimize cost of tax. MNEs perform cross border transactions to shift their profit by exploiting the difference in tax rates in favor of minimizing their cost of tax (Rego 2003).
Indonesia which has attractive market size and massive and considerable low-cost labor supply has been one of main destinations for foreign direct investment by the MNEs. Even though Indonesia is gifted with such advantage, Indonesia is, without exception also facing the tax avoidance issue through transfer pricing undertaken by MNEs. By the presence of the MNE a possibility of economic loss due to tax avoidance through transfer pricing is essential to be addressed. Various policies have been constructed to limit transfer pricing issues; one is Transfer Pricing Documentation (TP docs). Indonesia has implemented the TP docs policy on December 30th, 2016, under Minister of
3 These countries are considered as investment hubs by World Bank Classification, such as the Bahamas, Bermuda, and British Virgin Island.
Finance Regulation No.213/PMK.03/2016 (MoFR-213/2016). The TP docs are intended to provide transparency from taxpayers who perform related party transactions in determining their transfer price and eventually furnish tax administration with information to deal with taxpayers' potential tax avoidance behaviour (OECD 2015).
The TP docs policy is designed to ensure that taxpayers have applied appropriate ways to determine price within related party transactions so that the shifting behaviour is restricted (OECD 2015). By mandating taxpayers to disclose how they apply the arm's length principle, taxpayers are expected to stop their tax avoidance behaviour using transfer pricing as an instrument. Even though the TP docs are not considered public disclosure, in which taxpayers will have no concern over the public's view, TP docs policy is believed to create a culture of compliance and integrity for taxpayers.
Implementing TP docs policy may be a panacea to overcome transfer mispricing issue. On the other hand, the drawback of implementing TP docs policy is that it may burden firms with administrative matters and incur extra costs, discouraging firms from engaging in business. Therefore, the policymakers should be cautious and ensure that such policy bears greater benefit than its cost.
However, the effect of TP docs policy on tax avoidance -especially in Indonesia- has not been observed so far. To what extent does the implementation of TP docs policy limit Indonesia MNEs' tax avoidance behaviour? The aim of this paper is to answer that question. This paper investigates how taxpayers will behave following the introduction of the TP docs policy. For that purpose, this paper examines the issue by observing taxpayers' tax avoidance behaviour in Indonesia that are obligated to prepare the TP docs.
4 Expectation of the observed and unobserved factor are different in the treatment and control group, so that the
The empirical strategies utilized in this paper to answer the matter in question are to employ regression discontinuity (RD) design and Difference-in-Difference (DID) using taxpayer tax return data.
Methodologically, this paper uses a similar design to de Simone and Olbert (2019), Joshi (2020), and Kurniawan and Saputra (2020). All papers also exploit policy thresholds for disclosure to explore the impact of Country-by-Country Report (CbCR) on firms’ tax avoidance using RD and DID design. Joshi (2020) used 750 million-euro thresholds for disclosure to observe the effect of CbCR policy.
Replicating Joshi's (2020) method, Kurniawan and Saputra (2020) investigated the effect of Indonesia's CbCR regulation.
The empirical strategies employed require the setting to have a treatment group and control group. The treatment group consists of taxpayers with an annual gross turnover of more than IDR 50 billion in the previous tax year, and the control group is otherwise. At a glimpse, as treatment group is bigger in terms of its size, the descriptive statistics show that the treatment group has mean of tax/sales which is 0.5 point percentage higher than control group. The higher average tax/sales in the treatment group is also followed by other firm’s specific characteristics such as average sales, average cost of goods sold (cogs) mean, average operating expense, and average operating income. Therefore, simple differences in the tax/sales between treatment and control group may be biased in drawing a conclusion since the number is not as good as randomized4.
As simple difference between treatment and control group is not sufficiently enough to draw conclusion about the causal effect, RD design is employed. RD design observes the taxpayers' tax avoidance behaviour immediately one year after implementation of the policy. By exploiting the IDR 50 million thresholds -the cutoff- for
difference in the outcome variable does not measure the causal effect.
disclosure, RD design can observe whether, at the cutoff, there is a difference in taxpayers' tax avoidance behaviour or not.
This design can address the endogeneity issue of the variable of interest under a relatively weaker assumption. In addition to estimation of the main experiment, a falsification test is established to ensure that the results hold by observing taxpayers' tax avoidance behaviour one year before the introduction of the policy.
The main RD design’ empirical results are that affected taxpayers have higher tax/sales on average by 0.9 percentage points, measured in 2017. The average increase in tax/sales lies between 0.005% to 1.85% points in a 95%
confidence level. As a comparison to see whether the increase is large or not in the real world, the mean5 of tax/sales for comparison taxpayers -those that are not obligated to prepare the TP docs is 1.4%, measured in 2017. It implies that the increase in tax/sales due to the introduction of this policy is 60% of the controls' tax/sales mean, which is quite substantial.
These results suggest that the implementation of TP docs policy negatively affected tax avoidance. This change of behavior may be explained that due to the implementation of TP docs policy, taxpayers are required to be transparent with their transfer pricing decision. They have to document and show that their pricing behavior complies with the arm’s length principle. This somehow limits their tax avoidance behavior. On the other hand, the falsification test found no evidence that there is a difference in tax/sales between the treatment and control groups before the implementation of the policy. The magnitude of the difference is - 0.1% point which concludes that there is no difference in tax avoidance behaviour of treatment and control groups.
5 The mean is used as comparison whether the increase is large or not in the real world since mean is the only statistic measure which may represent the expected valued of the random variable over many occurrences. As law of large numbers states, the sample averages (Y̅) will be close to
The causal effect of the TP docs policy is observed immediately around the cutoff -taxpayers around IDR 50 billion lag sales- using RD design. The effect is local to the cutoff. To observe the effect which is not only local to the cutoff, the second strategy DID is employed. The main result of DID design is that the introduction of TP docs policy negatively affects taxpayers' tax avoidance behaviour. There is an increase in tax/sales in the treatment group by around 0.6% to 0.7% points. The falsification test using all unaffected taxpayers is also employed, which shows no evidence of a difference in tax/sales in both groups after the implementation of the TP docs policy.
The antecedent studies exploring the effects of TP docs policy are still limited, notably, those observing regulations in Indonesia. Most of the studies observe the effects of transfer pricing regulation aggregately, i.e. observed together aggregately with the other regulations (Marques and Pinho 2016;
Lohse and Riedel 2013; Rathke et al. 2020;
Sari et al. 2020; Yoo 2020). Despite all those studies, this research is the first that observes the specific effect of TP docs regulation from all other transfer pricing regulations at the firm level using tax return data. Most of the studies above have been limited to observing the effect of transfer pricing regulations aggregately and at the country level, which the observations are actually affected or not by the regulation is puzzling. The specific effect of the TP docs policy remains unclear. Therefore, this study explores these issues by observing the impact of TP docs regulation separately based on firm-level analysis.
This study contributes to the literature by providing empirical evidence about the impact of TP docs regulation on taxpayers' transfer pricing avoidance in
the common mean (𝜇𝑌) with very high probability as number of sample (n) increases, or when n is large. The mean is generated from over 15.000 observations.
Indonesia. Finding how Indonesia MNE’s will behave following the introduction TP docs policy is expected to unravel the puzzle which remains unclear in the field of TP docs literature. In addition to that, as policymakers should be concerned about the benefit and cost of a policy, the results of this study are essential to delivering enlightenment and policy evaluation to the Directorate General of Taxes (DGT) Indonesia on whether the implementation of TP docs is effective or not.
The paper continues with a review of the literature on transfer pricing policies in Indonesia dan current studies in transfer pricing field. Next, the author will describe the methodology dan data employed to answer the question investigated. Next section will present the empirical findings and the discussion. Eventually, the conclusion and policy implications are incorporated to wrap up the paper.
LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT Transfer Pricing Policy in Indonesia
The DGT of Indonesia enacted the first6 detailed policy to taxpayers on how to set transfer price within affiliated transactions in 2010 through DGT Regulation No. PER43/PJ/20107. Taxpayers are required to apply arm’s length principle within affiliated transaction to show that such prices reflect the prices that would have been had by the independent enterprises engaging in a comparable transaction. However, the regulation may not discourage taxpayers' tax avoidance behaviour due to a lack of supervision mechanism on the taxpayer's compliance toward the regulation.
6 Although DGT’ right to adjust transfer pricing transactions was given in 1983, the regulation concerning transfer pricing was very limited. There were no regulations until 2010 on how taxpayers should treat their transfer pricing transactions in detail.
7 This regulation was later amended through DGT Regulation No. PER-32/PJ/2011 and the arm’s length
Taxpayers are not obliged to document each step taken to determine transfer prices.
There is no detailed evidence of whether taxpayers actually implement that arm’s length principle since taxpayers have no obligation to document, to be transparent and to prove to the tax authority that they have not manipulated their transfer price to avoid paying taxes.
It was only in 2016 that the DGT of Indonesia implemented the TP docs policy through MoFR-213/2016 to bridge the issue of transfer price determination transparency. Through the TP docs policy, taxpayers8 are expected to prepare two documents: the master and the local files.
The master file presents a big picture of taxpayers' global business operation, while the local file documents information regarding related party transactions, amounts of those transactions, and arm's length analysis9 of taxpayers' transfer pricing determination. In addition to that, they must submit the summary of those documents to the tax authority as an attachment when the tax return is submitted.
In those two documents, taxpayers must provide information regarding all transfer pricing transactions performed by taxpayers and how they calculate and assess their transfer price determination according to the arm’s length principle rules.
The implementation of the TP docs policy may incur extra costs for taxpayers.
They bear additional costs to pay employees or to have a contract with a tax advisor not only to prepare the TP docs but also to advise taxpayer’ pricing decision which comply with the arm’s length principle provision. In the case of tax advisors carrying out taxpayer rights and obligations, taxpayers often offer facts and circumstances to the tax adviser, and the tax
principle was also regulated through Ministry Finance of Regulation No.22/PMK.03/2020.
8 Taxpayers in this section are taxpayers who are obligated to prepare TP docs according to MoFR-213/2016.
9 Analysis to demonstrate that the price set in the related party transactions has reflected the price if the same transactions are carried out by an independent party (OECD 2017).
advisor then plays a significant role in advising the taxpayers so that their pricing decisions conform with the arm's length principle. Those significant responsibilities encompass comprehending the operations of taxpayers, conducting industry analysis, identifying economically significant attributes or comparability factors, conducting comparability analysis (which includes, among other things, providing a set of comparable data to substantiate that their pricing decisions reflect the prices independent businesses would have obtained by conducting comparable transactions), and ascertaining the arm's length price. In addition to that, each step taken in the arm’s length principle must be documented by tax advisor within TP docs.
Considering all above complex processes, it is no wonder that providing TP docs for taxpayers is quite burdensome since tax advisor must be remunerated properly.
Therefore, to prevent this policy from burdening small taxpayers that may carry a small risk of tax avoidance, not all taxpayers are obligated to prepare the TP docs. Taxpayers with annual gross turnover less than or equal to IDR 50 billion in the previous tax year are exempted from preparing TP docs. Even though exempted taxpayers are not required to prepare the TP docs, they still have to set their transfer price according to the transfer pricing rules, but again, since exempted taxpayers are not obliged to prepare the TP docs, DGT of Indonesia cannot ensure whether taxpayers actually implement arm’s length principle.
Treating the implementation of TP docs as a shock among required taxpayers, it is expected that there will be a change in taxpayers’ tax avoidance behaviour.
Affected taxpayers are supposed to have lower tax avoidance following the implementation of the TP docs policy. In the period when the policy has not been put into practice, all taxpayers have the same leeway of no transparency in the calculation of transfer price and are assumed to have similar mispricing behaviour.
Transfer Pricing and Firms' Behaviour Under no TP regulation, firms have opportunity to minimize their tax payment by shifting their profit from higher tax jurisdictions to lower tax jurisdictions (Choi et al. 2020). Let us consider two countries, country 1 with a higher tax rate, 𝑡1, and country 2 with lower tax rate, 𝑡2. Firms will choose the transfer price, 𝑦, and output 𝑞 such that firms maximize their group profit as follows.
𝜋 = (1 − 𝑡1) [𝑃(𝑞) − 𝑦]𝑞 + (1 − 𝑡2)(𝑦 − 𝑐)𝑞 ………. (1) Let us denote demand function as 𝑞 = 𝐷(𝑝) and 𝑃(𝑞) is the inverse of the demand function. Firms will choose the optimal transfer price 𝑦 so that the profit is shifted to jurisdiction 2, which has a lower tax rate.
In most transfer pricing cases, the determination of transfer price is centralized within the group. Subsidiaries usually do not have power to determine their prices. Therefore, we can write the above equation into one firm's profit function as follows.
𝜋 = (1 − 𝑡1) [𝑃(𝑞) − 𝜀]𝑞 𝑤ℎ𝑒𝑟𝑒 𝜀 =
(1−𝑡2)𝑐−(𝑡1 −𝑡2)𝑦
1−𝑡1 ……… (2)
As 𝜀 increases, the global tax profit decreases. Therefore, MNE can minimize 𝜀 in choosing 𝑦. Let us denote 𝑞𝑚(𝜀(𝑦)) as output when firms choose 𝜀. By solving first-order conditions, there is 𝑃(𝑞𝑚(𝜀(𝑦))) = 𝑦∗ where profits are shifted to country 2 at the maximal 𝑦, and there is a probability that all profits are shifted to country 2, while leaving 0 profit for firms in country 1.
In the event that there is transfer pricing regulation, taxpayers are required to set their prices at some value cap, denoted by 𝑦, MNE will choose 𝑦 = 𝑦 , if 𝑦 <
𝑃(𝑞𝑚(𝜀(𝑦∗))). Firms cannot choose their maximum 𝑦, given the 𝑦 is smaller. Firms should adjust their transfer prices, increasing profit in country 1, reducing profit in country 2, and leading to higher tax payments in country 1. Firms 1 may choose not to set their transfer price at 𝑦. However,
this will raise suspicion from tax authorities, which can lead to firms 1 being audited, and tax authorities will adjust the transfer price at 𝑦.
As believed from above notion, the absence of TP policy, either policy which regulates arm’s length principle in determining transfer prices or policy which requires TP doc to supervise the implementation of arm’s length principle, will enhance taxpayer’ incentive to avoid tax. Taxpayers openly shifts their profit to minimize cost of tax and there are no supervision and no fines that could be imposed by tax authorities. The view corresponds to the well-known slippery slope framework designed by Kirchler et al.
(2008). Enforced tax compliance to the arm’s length principle is likely to be large when tax authority has the power to raise audit and detection probabilities and to inflict severe fines. TP docs policy carries rights and obligations, including the authority to conduct audits and impose penalty when the obligations are not respected, thus taxpayers have less and less incentives to avoid to tax (Kirchler et al.
2008). Furthermore, the TP docs policy, which may be considered tax disclosure, may reduce tax evasion by requiring taxpayers to declare their arm's length principle implementation, and the likelihood of audit is raised when the responsibility is breached (Allingham and Sandmo 1972; Joshi 2020).
Effect of Transfer Pricing Policy on Tax Avoidance
Even though the literature concerning transfer pricing is quite extensive, the studies focusing on to what extent transfer pricing legislations affect taxpayers' behavior are primarily scarce.
Several categories of studies explore the effect of the transfer pricing regulation.
First are studies that examine the effect of CbCR regulations. The CbCR regulation
10 Master file, local file, and CbCR are three-tiered documents concerning transfer pricing.
has a similar intention to the TP docs regulation10, i.e., to provide MNEs worldwide businesses tax transparency. The CbCR document provides some types of MNE information to the tax administrations, such as global allocation of MNEs’ income, taxes paid, and indicators of MNEs’ economic activity (OECD 2015).
The appropriate use of that document is for assessing high-level transfer pricing risk and should not be misused to make a price adjustment to the transfer pricing transactions. Only the global ultimate owner (GUO) of the MNEs is obliged to provide the CbCR documents.
A number of studies found that CbCR can deter firms’ tax avoidance through profit shifting (Hugger 2019; Joshi 2020; Kurniawan and Saputra 2020). CbCR provides new tax-related information to the tax authority and such information will be used as transfer pricing risk assessment. If the tax authorities receiving CbCR information find that the risk of the firms shifting their profit is high, those firms will be audited. Firms that do not want to take the risk of being audited, because it is time- consuming and they are likely to be penalized, will alter their behaviour by reducing profit shifting. Through this channel, (i.e., detection risk) the introduction of CbCR changes firms’ tax behaviour (Joshi 2020; Kurniawan and Saputra 2020). It is also parallel with was declared by Allingham and Sandmo (1972) where decline in the tax avoidance would be observed as the detection risk increases and tax disclosure to the tax authority may lead to an increase in the probability of detection. In addition to that, Joshi (2020) also mentioned that tax disclosure may bring transparency to the tax authority.
Through transparency to tax authority, taxpayers could not conceal their tax avoidance activities. Transparency provides the ability for tax authority to supervise taxpayers’ tax avoidance activities.
Taxpayers would also believe that their tax
avoidance activities are monitored and they may reduce their tax avoidance activities to lower the probability of audit and sanctions imposition. Another channel of how CbCR changes firms’ tax avoidance behaviour is through public exposure risk (Eberhartinger et al. 2020; Joshi 2020; Kurniawan and Saputra 2020). Public scrutinization of inappropriate tax behaviour can lead to negative market response and cost firms’
reputations (Eberhartinger et al. 2020; Joshi 2020; Kurniawan and Saputra 2020).
The second group of the related studies are the studies which empirically investigate the effect of multiple transfer pricing regulations in one package (Lohse and Riedel 2013; Marques and Pinho 2016;
Rathke et al. 2020; Sari et al. 2020; Yoo 2020). They create an index based on country specific transfer pricing strictness.
The tightening of transfer pricing regulations can curb the profit shifting behaviour (Lohse and Riedel 2013;
Marques and Pinho 2016; Rathke et al.
2020; Sari et al. 2020; Yoo 2020). The effect is stronger when the tax rate differential between two countries is larger.
Moreover, Yoo (2020) stated that the effect of multiple transfer pricing regulations must not be observed from the point of view of one country. He found that the firms would reduce the motivation to shift profit if the country strengthens its domestic transfer pricing regulations while if the foreign country strengthens its transfer pricing regulations, it will reduce the incentive of foreign firms to shift income into the domestic country. Contrary to those findings, Sari et al. (2020) only found that the transfer pricing rules are only effective in preventing transfer mispricing behavior in the sales transactions.
Taking into account the above notion and previous studies, this paper therefore hypothesizes that:
H1: Taxpayers who are obligated to prepare Transfer Pricing
11 Sometimes the firm's data contain the consolidated data of the group, not standalone financial performance of the firms.
Documentation have lesser tax avoidance than those who are not.
RESEARCH METHOD Data
My analysis draws the data from tax return data of Indonesia taxpayers administered by DGT. Taxpayers included in the analysis belong to taxpayers who perform transfer pricing transactions from 2013 to 2018. The data used is to ensure that the setting can sufficiently observe not only one-year effect of TP docs policy, but whether the impact also remains in the following year. The observation only incorporates taxpayers who carry out transfer pricing because they are the subject of the policy. Moreover, this can ensure that the observations only include taxpayers with tax avoidance behavior through transfer pricing. Only few empirical studies in the transfer pricing literature used the primary data obtained directly from the taxpayers. Most of the existing transfer pricing literature (Buettner et al. 2017; de Mooij and Liu 2020, 2021; de Simone and Olbert 2019; Eberhartinger et al. 2020;
Hugger 2019; Joshi 2020; Kurniawan and Saputra 2020; Lohse and Riedel 2013;
Marques and Pinho 2016; Merlo et al. 2019;
Rathke et al. 2020; Sari et al. 2020; Yoo 2020) used the secondary data drawn from the external database, such as Bureau van Dijk’s, whose data reliability cannot be ascertained11.
Table 1 compares the restricted and unrestricted data used. The unbalanced panel data consist of 3,619 taxpayers with 19,463 observations data from 2013 to 2018. The RD approach will estimate equation (3) using the unrestricted 2017, 2016, and 2013 to 2016 (pooled years) tax data, while the DID approach will use the 2014 to 2018 data as explained in the
Table 1
Restricted and Unrestricted data used
Unbalanced Data Panel Balanced Data Panel Control
Groups
Treatment
Groups Total Control Groups
Treatment
Groups Total
2014 1,448 1,581 3,029 1,266 1,533 2,799
2015 1,657 1,661 3,318 1,266 1,533 2,799
2016 1,699 1,684 3,383 1,266 1,533 2,799
2017 1,813 1,675 3,488 1,266 1,533 2,799
2018 1,806 1,644 3,450 1,266 1,533 2,799
Note. The calculation of 2013 year data is omitted from this table. The determination of control and treatment groups are based on the 2016 sales year data.
methodology section to estimate the equation (4). DID uses longer time periods as DID design is also used to identify the two-year effect of the policy. To implement DID approach, not only is the unbalanced panel data established, but this paper will also restrict the firms to be the same across periods.
Methodology
The empirical strategy employed to estimate the effect of the TP docs policy was regression discontinuity (RD) design and difference-in-difference (DID). The details of each statistical analysis is discussed below.
Regression Discontinuity Design
The RD design was established to identify the identify the causal effect of TP docs on taxpayer’s tax avoidance. The design identifies the impact of the TP docs policy by comparing taxpayers’ tax/sales above and below the threshold for disclosure in the period one year after the implementation of the policy. Tax/sales is used as a proxy for tax avoidance. A higher amount of tax/sales implies a lower tax avoidance, and a lower amount of tax/sales suggests a higher tax avoidance. The amount of tax/sales is uncommonly used in the literature, but it gives more neutrality in estimating tax avoidance. Effective tax rate (ETR), which has been commonly used in work on tax avoidance, may lead to
12 It is impracticable to interpret the negative ETR, it does not match with the implication that lower ETR has higher tax avoidance.
misinterpretation and misestimation due to the inclusion of negative ETR12 if used.
Joshi (2020) and Kurniawan and Saputra (2020) reset ETR at 0 and 1 to deal with negative and huge ETR issues. That approach will only create a new problem of misinterpretation and misestimation since the data is not based on the actual data.
Nevertheless, complementary to tax/sales, this paper furthermore, in the Online Appendix B and Online Appendix D, presents the proxy used by Joshi (2020) and Kurniawan and Saputra (2020), ETR and the proxy used by Lohse and Riedel (2013), and the log of profit before tax (PBT)13.
RD design was performed since the setting is benefitted from having cutoff. The cutoff used was the threshold for disclosure, (i.e., IDR 50 billion). This design observed the causal effect immediately around the cutoff and can address the endogeneity issue of the variable of interest under a relatively weaker assumption which led to an estimate that identified the causal impact. In addition to that, the estimate of the policy immediately around the cutoff ensured the internal validity.
To get estimation of TP docs policy effect, this paper utilized sharp RD.
Taxpayers are supposed to have perfect compliance by the design of the policy. The TP docs summary is submitted as an attachment to the tax return. If taxpayers submit tax returns not along with the TP docs summary, tax return will be in the
13 ETR is also reseted at 0 and 1 as suggested by Joshi
(2020), and following Lohse and Reidel (2013), this paper limits the sample for firms with positive log PBT when log PBT is used.
status of not complete and tax authority will notify the taxpayers to complete and submit it. In the event taxpayers do not submit tax returns, the tax authority will notify the taxpayers to submit it along with the summary of TP docs. Therefore, it is quite difficult to think that there is non- compliance due to cross-overs or no-shows in this setting. Moreover, the current studies also used sharp RD when estimating impact of the CbCR regulation, which has similar features to the TP docs regulation (Joshi 2020; Kurniawan and Saputra 2020).
Sharp RD results identify the average causal effect of the policy under some key identifying assumptions. The fundamental identifying assumption to estimate the causal impact of TP docs policy using this design is that the unobservable varies smoothly as a function of lagged sales (running variable), or specifically, no discontinuity at the cutoff.
As displayed in Lee (2008) and Lee and Lemieux (2010), the continuity of unobservable to be sufficient is that the densities of the treatment-determining variable are continuous. In other words, the taxpayers cannot precisely manipulate their lagged sales to be on either side of the cutoff. It is plausible to think taxpayers easily control their lagged sales in this setting. However, for the taxpayers to be able to locate precisely on which side, they must be aware of the existence of the cutoff.
The threshold for disclosure was unknown to taxpayers until 2017, since the regulation was first introduced at the end of 2016. The main experiment of RD analysis is the 2017 tax year, in which the firm’s sales for the year 2016 (running variable) were reported when the cutoff was introduced. For the falsification test, the 2016 tax year data are used, in which the cutoff is not yet known by taxpayers. Therefore, it is hard to think that taxpayers can have precise control over which side they want to be on14.
14 Internal validity check on the RD design is presented in the Online Appendix A by performing McCrary density test (McCrary 2008).
This paper's primary estimation approach used local linear regression in the samples around the cutoff following Hahn et al. (2001). Furthermore, this paper added nonlinear specifications in the Online Appendix C to complement the main results. The specification used distant neighbourhoods within ± IDR 50 billion from the thresholds (bandwidth (ℎ) ± 50).
The maximum ℎ that minimizes the absolute mean squared error (AMSE) is also employed following Calonico et al.
(2014). The bias-corrected and robust standard error estimates were also reported.
The local linear specification for observations within distance ℎ of the cutoff is:
𝑌𝑖 = 𝜏𝐼[𝑋𝑖 > 50] + 𝛽0+ 𝛽1(𝑋𝑖 − 50) + 𝛽2(𝑋𝑖− 50)𝑥 𝐼[𝑋𝑖 > 50] + 𝜃𝑊𝑖 + 𝑎𝑖 +
𝑈𝑖 ……….. (3)
𝑌𝑖 is a representation of the outcome variable, i.e., tax avoidance, which is proxied15 by tax/sales for each observation 𝑋𝑖 is the lagged sales, and (𝑋𝑖− 50) is the normalized lagged sales with respect to the cutoff. The cutoff is the threshold for the TP docs disclosure, which is IDR 50 billion of previous annual sales. 𝐼[𝑋𝑖 > 50] is an indicator for a lagged sales above the cutoff, and 𝜏 is the effect of crossing the cutoff on the outcome 𝑌𝑖. 𝑊𝑖 is a set of pretreatment covariates; 𝑎𝑖 is the industry fixed effect;
and 𝑈𝑖 is the error terms. As a main experiment, this paper estimates the equation (3) without pretreatment covariates and the industry fixed effect.
Then I include the pretreatment covariate ratio cost of goods sold (cogs) per sales, ratio operating expense (opex) per sales, and the industry fixed effect.
Data from one year after implementation was employed to observe the effect of policy on tax avoidance. This paper employed the data one year before the implementation and pooled year of three years before the policy implementation as a falsification test.
15 This paper also presents ETR and log of PBT as a proxy for tax avoidance in the Online Appendix B and Online Appendix D.
Difference-in-Difference
DID design was employed as supplementary to the RD design. DID design is used to answer the question of whether the effect is not only local to the cutoff as estimated by RD design. In addition to that, DID design also estimated the effect in the year two TP docs policy was introduced. DID design was established using this following equation.
Yit = α + β1 TPDi + β2 POSTt + β3 POST x TPDit + εit ……… (4)16 The strategy was to divide the treatment group as taxpayers that fall into requirement of the TP docs regulation and the control group as taxpayers that were exempted from preparing the TP docs. Yit is the outcome variable, (i.e., tax avoidance for observation 𝑖 at time 𝑡), which is proxied by tax/sales. Tax/sales was calculated as tax paid divided by sales. As mentioned in the regression discontinuity design section, the use of tax/sales was not common but it delivered a neutrality in estimating tax avoidance through transfer pricing. Low tax/sales may indicate that taxpayers shift their profit elsewhere since lower tax was derived from lower taxable profit. OECD (2017) was also employed certain ratio using sales as denominator to justify whether the intra group pricing transaction is already at arm's length or not. In addition to that, the use of effective tax rate somehow could not indicate the profit shifting behavior since the corporate tax rate is the same for the most taxpayers and the ETR tends to be the same as corporate tax rate in Indonesia. TPDi is a dummy variable that takes a value of 1 if taxpayers are obliged to prepare the TP docs and 0 otherwise. To implement DID design, this paper used the 2016 sales (2017 lagsales) as a basis to determine treatment and control
group, denoting 0 for taxpayers whose annual gross turnover less than or equal to IDR 50 billion in the tax year 2016, and 1 otherwise. POSTt is an indicator variable equal to 1 for all years where the TP docs regulation is in place and 0 otherwise. The main variable of interest is the interaction of TPD and POST variables, which indicate the difference-in-difference estimator.
Two equations based on the equation (2) were employed to identify the one-year and two-year effects. The first is the equation which employed the 2017 data as the post-implementation period and 2016 data as the pre-implementation period. For the second equation, the 2018-year data were used as the post-implementation period, while 2016 data were still used as the pre-implementation period. The robustness check was also conducted.
Those steps in the main experiment were repeated but the 2015 sales data was used as a base to determine the treatment and control group, then the difference in the tax/sales between pre-implementation period (2015) and post-implementation period (2017 and 2018 respectively) was observed.
To estimate the policy effect properly, the key identification assumption is common trends. This assumption requires that the changes in tax/sales for the treatment and control taxpayers would follow the same trend in the absence of TP docs policy. One can never test this fundamental identification assumption of the same trend in the absence of treatment.
However, if there are more than two periods, one can test whether the assumption of a common trend in the pre- implementation periods seems to be satisfied. To test the common trends17 in the
16 The author also includes additional covariate in the Online Appendix I which are ratio cost of goods sold (cogs) per sales, ratio operating expense (opex) per sales, and the industry fixed effect, apart from the main experiment model.
17 The detail of DID estimates of common trends assumption can be seen in Online Appendix E. The estimates of DID for the common trends test with additional covariates can also be seen in the Online Appendix I.
Table 2
Comparison of Mean of All Observations
Unbalanced Data Panel Balanced Data Panel Control Groups Treatment Groups Control Groups Treatment Groups
Sales 219.81 3,159.21 188.83 3,288.02
Cost of Goods Sold 106.58 2,240.89 80.15 2,324.01
Operating Expense 92.83 603.42 95.57 632.33
Operating Income 20.63 316.93 13.28 333.77
Tax/Sales (%) 1.59 2.05 1.59 2.07
Tax/Operating Income (%) 9.06 15.73 8.84 15.94
Log of PBT 21.74 24.48 21.71 24.51
Note. This table reports descriptive statistics in the data. The data are in IDR billion unless otherwise stated. The determination of control and treatment groups is based on the 2016 sales year data.
period where the regulation policy has not been in effect, the 2014 sales data was used to determine which group the observations belonged to. Then, the estimate in the equation (4) was obtained using the 2015 and 2016 data as the post-implementation period and 2014 data as the pre- implementation period, the difference in the tax/sales between pre and post implementation year was observed respectively. However, no one knows what the common trends assumption was during the time when the TP rule was implemented since we would need to know what would have happened if the TP regulation had not been implemented.
RESULTSANDDISCUSSION Descriptive Analysis
Table 2 reports a comparison of the mean of the variables used between treatment and control groups. On average, the treatment group was more profitable and had higher tax/sales than the control groups. Table 2 shows that specific firm characteristics, (e.g., sales, cogs, and opex), were significantly different in both groups.
The treatment group had a relatively more considerable amount of those characteristics than the control groups.
Therefore, the higher tax/sales of the treatment group cannot be interpreted due to the observations belonging to the group that was affected by the TP docs policy since the simple difference in the tax
avoidance’ behaviour between the two groups may be driven by the firm's specific characteristics rather than being driven by the policy.
The average tax/sales in Table 2 is translated into average tax/sales per year (2014 to 2018) and is depicted in Figure 1.
Corresponding to Table 2, the average tax/sales of the treatment group was higher than the control groups in each year. Both groups followed the same trends until the year before the TP docs policy was in effect and then start to deviate, particularly one year after the implementation of the TP docs policy.
Regression Discontinuity Design
The results are presented in the following subsections. The subsections present the graphical presentation and the estimates from RD design.
Graphical Presentation
Figure 2 presents the graphical evidence of the impact of the TP docs policy on tax avoidance. The x-axis represents the annual sales in the previous year. The y-axis shows the tax avoidance proxied by tax/sales in the percentage. Linear fitted lines were included to estimate the discontinuity at the cutoff. The figure involves taxpayers within ± IDR 50 billion.
In the post-implementation period (Panel A), taxpayers just to the right of the cutoff had a higher tax/sales (%). Panel B, the pre- implementation period, showed no
Figure 1
Average Tax/Sales Trend by Groups
Note: This table reports average tax/sales trends between treatment and control groups over 2014 to 2018. The determination of control and treatment groups are based on the 2016 sales year data.
Figure 2
Regression Discontinuity Plot of IDR 100 billion Bandwidth
Note. Each dot represents the sample average of the tax/sales (%) in a given bin. The bin width is in every IDR 5 billion of the lagged sales.
difference in tax/sales immediately at the cutoff.
Panel A, the post-implementation period, showed clear evidence of discontinuity in tax/sales at the cutoff. At the same time, Panel B, the pre- implementation period, showed no discontinuity in tax/sales. The results depicted in the Figure 2 were also robust when different tax avoidance measures were employed as shown in the Online Appendix D. The discontinuity demonstrated in the post-implementation period suggested that taxpayers began to dampen their tax avoidance behavior when the TP docs policy was introduced.
Taxpayers had lesser incentive to avoid tax
since they had to comply with arm’s length principle which must be declared in the TP docs. The violation of such obligation would only lead to higher probability of audits and penalty imposed.
Because the average tax/sales of the observation just to the right of the cutoff changed insignificantly from 2016 to 2017, one may argue that perhaps something happened to the observations below the cutoff in the year 2017 that was not caused by the introduction of TP docs policy.
Therefore, this research offers Figure 3 to refute such an argument and show that taxpayers immediately to the right and left
Figure 3
Regression Discontinuity Plot of 100 IDR billion Bandwidth-Pooled Years Pre Implementation18
Note. The pooled specification includes the year 2013 to 2016. Each dot represents the sample average of the tax/sales (%) in a given bin. The bin width is in every IDR 5 billion of the lagged sales.
Table 3
RDD Estimates of the Effect of Transfer Pricing Documentation on Tax Avoidance
Variable Post-Implementation (2017) Pre-Implementation (2016) Pooled Years Pre-Implementation (2013-2016)
Tax/Sales (%) 0.979* 0.927*** -0.123 -0.137 -0.081 -0.153
(0.544) (0.348) (0.589) (0.436) (0.320) (0.259)
[0.07] [0.01] [0.83] [0.75] [0.80] [0.42]
N 569 1,990 661 2,015 2,621 7,547
Spline Linear Linear Linear Linear Linear Linear
Bandwidth 0 to 100 0 to 28578.139 0 to 100 0 to 33855.382 0 to 100 0 to 60505.582
Control Mean 1.35919 1.35919 1.521885 1.521885 1.452057 1.452057
Note. Local linear regression estimations. Standard errors in parentheses. P-values in brackets. *Significant at the 10 percent level. ** Significant at the 5 percent level. *** Significant at the 1 percent level.
of the cutoff behave the same way when it comes to tax avoidance.
Figure 3 graphically represents the results of no discontinuity in the pooled years of the pre-implementation period.
This suggests that not only immediately one year before the implementation of the TP docs policy but also for other years before the introduction of the policy, taxpayers just to the right and the left of the cutoff had similar tax avoidance behaviour. With this in mind, in this setting, it should prove that in the absence of the treatment, taxpayers who are obligated to prepare the TP docs and those who are not will behave similarly19. Therefore, in the case of Figure 2 Panel A, in the absence of the implementation of the TP docs policy, taxpayers above the cutoff will have a
18 The test of continuity assumption of this experiment can be found in the Online Appendix A.
19 Unfortunately, the estimation of pooled years of the post-implementation period is unable to be analyzed due to the violation of the continuity assumption.
similar level of tax/sales (tax avoidance) to the taxpayers below the cutoff.
Estimate of discontinuity
Table 3 shows RDD estimates that correspond to Figure 1 and Figure 2. The estimates also included the maximum bandwidth that minimized AMSE, as Calonico et al. (2014) suggested. The discontinuity estimated in the post- implementation period range from 0.927 to 0.979 percentage points. On the contrary, in the pre-implementation period, consistent with the graphical evidence, this paper found no statistical evidence of discontinuity at the cutoff.
The estimates in the post- implementation period suggested that taxpayers immediately above the cutoff had higher tax/sales by around 0.9 percentage
Table 4
RDD Estimates with the Additional Covariates of the Effect of Transfer Pricing Documentation on Tax Avoidance20
Post-Implementation Pre-Implementation
Bandwidth 0 to 100 0 to 100 0 to 100 0 to 100
Additional covariates No Yes No Yes
Industry fixed effect No Yes No Yes
Tax/Sales (%) 0.979* 1.161** -0.123 0.144
(0.544) (0.520) (0.589) (0.552)
Observations 569 569 661 661
r2 0.0150 0.129 0.0115 0.0994
Note. Local linear regression estimations. Standard errors in parentheses. *Significant at the 10 percent level. ** Significant at the 5 percent level. *** Significant at the 1 percent level.
points of tax/sales21. The average tax/sales for taxpayers below the cutoff, taxpayers with lagged sales of IDR 0 to 50 billion, was 1.4 percent, with a standard deviation of 3.1 percent. Therefore, the increase in tax/sales in taxpayers obligated to prepare the TP docs was about 70% of tax/sales control groups or 0.3 standard deviation.
It is also worth noting that the discontinuity in the post-implementation period was still displayed when other tax avoidance measures were used as shown in the Online Appendix B. The treatment group had a higher ETR (Log of PBT) by around 4 to 8 (1 to 1,5) percentage points (points) than the control group. Given that the average ETR (Log of PBT) of the control group was about 8 percent (22 points), with a standard deviation of 15 percent (1.4 points), the difference in ETR (Log Of PBT) amount to 50 to 100 (5 to 7) percent of ETR (Log of PBT) or 0.2 to 0.5 (0.7 to 1.07) standard deviation.
The result of discontinuity in the ETR corresponded with the result presented by Joshi (2020) and Kurniawan and Saputra (2020), who stated that in the post- implementation of the CbCR policy, they documented lower tax avoidance among affected firms. CbCR and TP docs policy had the same intention to provide transparency to tax authority which may prevent tax avoidance through transfer pricing transactions. Taxpayers which was
20 The estimates of RD with additional covariates for the maximum bandwidth can also be seen in the Online Appendix H.
21The larger magnitude is observed when the non-linear specification is used. Online Appendix C shows the estimate of different specifications.
obligated to disclose their intra group transactions through CbCR or TP docs did not have opportunity to hide their tax avoidance activities and they may lower their tax avoidance activities to prevent being audited and imposed penalty.
One may argue that the effect of TP docs policy in this setting may coincide with CbCR policy. It is important to note that, as mentioned before, CbCR policy does not affect the subsidiaries directly because CbCR is prepared by the parent entity. In addition to that, Joshi (2020) observed that the CbCR does not change firms’ tax avoidance behaviour at the subsidiary level. Moreover, most of the observations in this setting are not subject to the CbCR policy. Therefore, it is unplausible to think that the magnitude of discontinuity due to the TP docs policy in this setting is also influenced by CbCR policy.
Table 4 provides the estimates without and with inclusion of additional covariates: ratio opex per sales, ratio cogs per sales, and industry fixed effect. The covariates were significant predictors of tax/sales, and thus lowering the standard errors. The covariates also seemed to be weakly related to the treatment indicators since the changes in the point estimate was relatively minor. The point estimates, those that controlled for covariates were the most precisely estimated, because the covariates
Table 5
Difference-in-Difference Estimates of the Effect of Transfer Pricing Documentation on Tax Avoidance (Main Experiment)22
Unbalanced Data Panel Balanced Data Panel 2016 (pre)
2017 (post)
2016 (pre) 2018 (post)
2016 (pre) 2017 (post)
2016 (pre) 2018 (post)
DID 0.69** 0.59** 0.67* 0.59
se 0.28 0.30 0.34 0.37
r2 0.0082 0.0058 0.0064 0.0033
N 6,871 6,833 5598 5598
Note. This table reports the DID estimates in the main experiment. The determination of control and treatment groups are based on the 2016 sales year data. *Significant at the 10 percent level.** Significant at the 5 percent level. *** Significant at the 1 percent level.
Table 6
Difference-in-Difference Estimates of the Effect of Transfer Pricing Documentation on Tax Avoidance (Falsification Test)23
Unbalanced Data Panel Balanced Data Panel 2015 (pre)
2017 (post)
2015 (pre) 2018 (post)
2015 (pre) 2017 (post)
2015 (pre) 2018 (post)
DID 0.19 0.04 0.07 -0.41
se 0.23 0.26 0.26 0.48
r2 0.0077 0.0053 0.0069 0.0030
N 6,806 6,768 5598 5598
Note. This table reports the DID estimates in the falsification experiment. The determination of control and treatment groups are based on the 2015 sales year data. *Significant at the 10 percent level.** Significant at the 5 percent level. *** Significant at the 1 percent level.
absorbed some of the variation in the tax/sales.
Difference-in-Difference
The results are presented in the following subsections. Main experiment was employed to identify the causal effect of TP docs policy. The falsification experiment was then discussed as a robustness check.
Main experiment
Table 5 shows the DID estimates of the two-year effect of the TP docs policy. The results in the Table 5 suggest that, on average, following the implementation of the TP docs policy, the treatment group had higher tax/sales by 0.6 to 0.7 percentage points, thus lower tax avoidance.
Another point worth noting is that the DID estimates were more generalizable
22 The detail of DID estimates can be seen in Online Appendix F. The estimates of DID for the main experiment with additional covariates can also be seen in the Online Appendix I.
23 The detail of DID estimates (falsification experiment) can be seen in Online Appendix G. The estimates of DID for the falsification test with additional covariates can also be seen in the Online Appendix I.
since it did not only observe the difference around the cutoff. Therefore, it can be used to calculate the economic magnitude of TP docs policy. Using the average sales of the treatment group (IDR 3,159 billion), the estimates of DID translated into an increase in tax revenue of IDR 1895 to 2,211 billion for an average treatment taxpayer. Taking all results above together, the findings suggested that the introduction of the TP docs policy did change taxpayers’ tax avoidance behaviour.
Falsification Test
The results of the falsification test are presented in Table 6. Needless to say, the estimate of DID was lesser than in the main experiment. The estimates of DID was around -0.41 to 0.19 percentage point, which suggested no difference in the
