JRSSEM 2021, Vol. 01, No. 3, 279 – 294
E-ISSN: 2807 - 6311, P-ISSN: 2807 - 6494
DOI : 10.36418/jrssem.v1i3.23 https://jrssem.publikasiindonesia.id/index.php/jrssem/inde
THE EFFECT OF TAXES, EXCHANGE RATES, LEVERAGE,
AND BONUS MECHANISMS ON TRANSFER PRICING IN
MANUFACTURING COMPANIES LISTED ON THE IDX
Wenny Anggeresia Ginting
1
Bee Arlita Ade Putri Br.Sitorus
2
Cindy Lorenza
3*
Sania Surga Mas
4
1,2,3,4
Prima Indonesia University, Medan, Indonesia
e-mail: [email protected]
1
, [email protected]
2
,
[email protected]
3
, [email protected]
4
*Correspondence:[email protected]
Submitted: 08 October 2021, Revised: 22 October2021, Accepted: 27 October 2021
Abstract. This research examines the impact of taxes, exchange rates, leverage, and bonus
mechanism on transfer pricing. Tax is cal cu la ted by di vi di ng d ef er re d tax exp en se s ta xa ble by
profits. The exchange rate is calculated by dividing foreign exchange profit and loss by profit and
loss before tax. Leverage is calculated by dividing total debt by total assets. Bonus Mechanism is
calculated by multiplying net profit year t by net profit year t-1 by 100%. The population in this
research included 54 manufacturing firms listed on the Indonesia Stock Exchange in 2017-2019,
with 29 samples examined across three years. This study is quantitative since the data is numerical,
and the data analysis technique is multiple linear regression. The exchange rate has a substantial
impact on transfer pricing, according to the findings of this research. Based on the study, the
Adjusted R Square value is 0.104, which indicates 10.4% of the independent factors, namely tax,
exchange rate, leverage, and bonus mechanism, impact the dependent variable, transfer pricing.
The remaining 89.6% is affected by another variable.
Keywords: taxes; exchange rate; leverage; bonus mechanisms; transfer pricing
Wenny Anggeresia Ginting
1
, Bee Arlita Ade Putri Br.Sitorus
2
, Cindy Lorenza
3*
, Sania Surga
Mas
4
| 280
DOI : 10.36418/jrssem.v1i3.23 https://jrssem.publikasiindonesia.id/index.php/jrssem/inde
INTRODUCTION
The development of the business
world at this time is increasing. This causes
economic competition to grow so that
many countries are trying to be more
advanced and developing to prosper their
people. The more developed the business
world, the tighter the competition that
occurs between one company with
another. One example of a company
experiencing close economic competition
at this time is a manufacturing company.
Manufacturing companies use specific
machines, equipment, and labor to process
raw materials into finished goods that have
selling value and can be used by consumers
directly (Yadav et al., 2020). There are three
manufacturing sectors on the IDX: various
industries, consumer goods industry, and
elemental and chemical industry (Al-Abass,
2018). In this study, the sector used by the
researcher is the consumer goods industry
sector.
The consumer goods industry sector is
the leading supporter and has a vital role in
economic growth in Indonesia. Along with
the increase in population, the basic needs
needed by the community will increase.
Increasing market demand will result in
more production processes carried out by
manufacturing companies (Nagy et al.,
2018).
Some national companies that only
operate in one country become worldwide
multinational corporations. Changes may
stress a business because they will find it
difficult to determine the selling price and
production costs incurred. It will be
challenging to determine the price that
must be transferred or what is called
transfer pricing.
According to Gunadi (Suandy, 2011),
transfer pricing is the price agreed upon by
both parties to a transaction. For a long
time, most companies utilized transfer
pricing to assess all members, employees,
or divisions' performance. Tax management
often uses transfer pricing to minimize tax
due, according to (Azizah & Poren, 2014)
Viewed from the business side, the
company's corporate income tax is often
minimized to minimize existing costs (cost
efficiency). According to (Azizah & Poren,
2014), one of the effective methods for
multinational companies to win the
competition for limited resources is transfer
pricing. If the tax rate in a country is higher,
the possibility for companies to carry out
transfer pricing will also be more
significant.
In addition to tax reasons, differences
in exchange rates can also affect transfer
pricing. In multinational companies, cash
flows can be categorized into several
currencies where the value of each coin is
not absolutely against the dollar value. Still,
the value can change at any time. The
different exchange rates influence the
practice of transfer pricing by multinational
companies (Mathewson, 2019). Companies
will be more interested in transferring their
profits to countries with more strong
currency values through transfer pricing
(Akhadya & Arieftiara, 2018).
Specifically, leverage can refer to the
amount of debt a company uses to finance
assets (Sutama & Lisa, 2018). Measurement
of the indebtedness to Total Asset Ratio
(DAR) gauges a company's ability to pay
back its debts. If the source of funds
through loans used to finance assets is
281 | The Effect of Taxes, Exchange Rates, Leverage, and Bonus Mechanisms on Transfer Pricing
in Manufacturing Companies Listed on the IDX
more significant, then the value of DAR will
also be higher (Salim, 2015). Due to the
increased risk of default, high DAR loans
are challenging to get (Kasmir, 2014).
The method may also incentivize
companies to adopt transfer pricing.
According to research (Saraswati & Sujana,
2017), the bonus mechanism provides
compensation other than salary based on
the results and work performance of the
directors or managers concerned. Many
companies offer profit-based incentives so
that directors and managers may affect the
company's net earnings to maximize bonus
payments. Directors or managers may use
transfer pricing to increase net profits and,
therefore, their pay.
As stated before, taxes, exchange rates,
leverage, and bonus mechanism all affect
the value of transfer pricing. Therefore,
researchers are interested in researching
with the title "The Effect of Taxes, Exchange
Rates, Leverage, and Bonus Mechanisms on
Transfer Pricing in Manufacturing
Companies Listed on the Indonesia Stock
Exchange in 2017-2019". (Indonesia Stock
Exchange, 2019)
Research Phenomenon
The phenomenon that occurs in the
company PT. Indofood CBP Sukses Makmur
Tbk, the tax value was Rp.
1,663,388,000,000 in 2017 and in 2018 it
was Rp. 1.788.004.000.000 seen an increase
of Rp. 124.616 million or 7.49% while the
value transfer pricing in 2017 was Rp.
4,126,439,000,000, in 2018 it was Rp.
4,271,356,000,000 also experienced an
increase of Rp. 144,917,000,000 or 3.51%.
At the company PT. Gudang Garam
Tbk, the exchange rate in 2017 was Rp.
10,436,512,000,000 and in 2018 Rp.
10,479,242,000,000 seen an increase of Rp.
42,730,000,000 or 0.40%, while the value of
transfer pricing in 2017 was Rp.
3,043,784,000,000 and in 2018 it was Rp.
1,725,933,000,000 seen a decrease of Rp.
1,317,851,000,000 or 43.29%.
At the company PT. Ultra Jaya Milk
Industry Tbk, the value leverage in 2018
was Rp. 5,555,871,000,000 and in 2019 it
was Rp. 6,608,422,000,000 seen an increase
of Rp. 1,052,551,000,000 or 18.94%. The
value of the bonus mechanism in 2018 is
Rp. 701,607,000,000 and in 2019 Rp.
1,035,865,000,000 seen an increase of Rp
334,258,000,000 or 47.64%. Meanwhile,
transfer pricing in 2018 was Rp. 560.619
million and in 2019 Rp.
652,067,000,000also increased by Rp.
91,448,000,000 or 16.31%.
METHODS
This study utilizes causal associative
research to evaluate the effect of tax,
exchange rate, leverage, and bonus
mechanisms on transfer pricing and
stresses the quantitative method—
numerical data (numbers). The type of data
used is secondary data obtained from the
Indonesia Stock Exchange or accessed
through www.IDX.co.id(Indonesia Stock
Exchange, 2019).
Population and Sample
The Population
The population utilized for this
research was from Indonesian
manufacturing firms listed in 2017-2019. In
Wenny Anggeresia Ginting , Bee Arlita Ade Putri Br. Sitorus , Cindy Lorenza, | 282
Sania Surga Mas
this research, we used purposive sampling,
which is based on specific criteria.
The Sample
The study's sample was chosen based
on the following criteria:
a. companies Consumer Goods Industry
listed on the IDX from the 2017-2019
period. (Indonesia Stock Exchange, 2019)
b. companies Consumer Goods Industry
that does not publish financial reports
during the 2017-2019 period.
c. companies Consumer Goods Industry
that suffered losses during the 2017-
2019 period.
Table 1. Sample Selection Process
No.
Sampling Criteria
Number
of
1
Companies Consumer
Goods Industry listed on
the IDX from the 2017-2019
period
54
2
companies Consumer
Goods Industry that did not
issue financial reports
during the 2017-2019
period
(12)
3
companies Consumer
Goods Industry that
suffered losses during the
2017-2019 period
(13)
The number of samples
used
29
The number of observation
samples (29 x 3)
87
Source: www.IDX.co.id(Indonesia Stock Exchange, 2019)
Data Collection Techniques
In this study, the researcher used the
documentation method to obtain the data
needed in this study. (Sugiyono,
2016)states that the documentation
technique is utilized to collect data in
papers or financial reports to assist the
analysis.
Types and Sources of Data
This study utilizes secondary data
kinds, which are acquired indirectly from
the research object. The data came from
the 2017-2019 IDX annual financial reports
of manufacturing firms. In addition,
researchers utilized data from
www.IDX.co.id, the Indonesia Stock
Exchange's official website. (Indonesia Stock
Exchange, 2019)
Operational Definition of Variable
283 | The Effect of Taxes, Exchange Rates, Leverage, and Bonus Mechanisms on Transfer Pricing
in Manufacturing Companies Listed on the IDX
DOI : 10.36418/jrssem.v1i3.23 https://jrssem.publikasiindonesia.id/index.php/jrssem/inde
Table 2. Operational Definition of Variable
Variable
Definition of
Indicator
Tax
(X
1
)
Tax is a ma nd ato ry
contribution that the
people must pay to the
State, which is coercive
and does not get direct
reciprocity and is used
for state purposes.
(Prof. Dr. Rochmat
Soemitro, SH, 2013:1)
In (Eka Natalia, 2020).
ETR
= "
𝐷𝑒𝑓𝑒𝑟𝑟𝑒𝑑"𝑇𝑎𝑥"𝐸𝑥𝑝𝑒𝑛𝑠𝑒𝑠"𝑇𝑎𝑥𝑎𝑏𝑙𝑒
𝑃𝑟𝑜𝑓𝑖𝑡𝑠
Exchange
Rate
(X
2
)
The Exchange Rate
is
the price of a country's
currency value carried
out for exchange
transactions between
two countries.
(Dharmawan, 2021)
Exchange Rate
= "
𝑝𝑟𝑜𝑓𝑖𝑡"𝑎𝑛𝑑"𝑙𝑜𝑠𝑠"𝑜𝑛"𝑓𝑜𝑟𝑒𝑖𝑔𝑛"𝑒𝑥𝑐ℎ𝑎𝑛𝑔𝑒
"𝑝𝑟𝑜𝑓𝑖𝑡"𝑎𝑛𝑑"𝑙𝑜𝑠𝑠"𝑏𝑒𝑓𝑜𝑟𝑒"𝑡𝑎𝑥
Leverage
(X
3
)
Leverage is the ratio
used to measure the
amount of debt used
by the company to
finance assets. (Kasmir,
2014).
DAR
= "
𝑇𝑜𝑡𝑎𝑙"𝐷𝑒𝑏𝑡
𝑇𝑜𝑡𝑎𝑙"𝐴𝑠𝑠𝑒𝑡
bonus
mechanism
(X
4
)
The Bonus Mechanism
provides
compensation other
than salary based on
the results and work
performance of the
directors or managers
concerned. (Irpan,
2011) in (Saraswati &
Sujana, 2017)
ITRENDLB
= "
𝑁𝑒𝑡"𝑃𝑟𝑜𝑓𝑖𝑡"𝑌𝑒𝑎𝑟"𝑡"
𝑁𝑒𝑡"𝑃𝑟𝑜𝑓𝑖𝑡"𝑌𝑒𝑎𝑟"𝑡 − 1
"𝑋"100%
Wenny Anggeresia Ginting , Bee Arlita Ade Putri Br. Sitorus , Cindy Lorenza, | 284
Sania Surga Mas
Transfer
Pricing
(Y)
Transfer Pricing is
defined as the amount
price that has been
agreed by both parties
who have a special
relationship for the
transaction goods or
services, either in
financial business
transactions or other
transactions. (Gunadi
in (Suandy, 2011)
Transfer Pricing
= "
𝑅𝑒𝑐𝑒𝑖𝑣𝑎𝑏𝑙𝑒𝑠"𝑓𝑟𝑜𝑚"𝑟𝑒𝑙𝑎𝑡𝑒𝑑"𝑝𝑎𝑟𝑡𝑦"𝑡𝑟𝑎𝑛𝑠𝑎𝑐𝑡𝑖𝑜𝑛𝑠"
𝑇𝑜𝑡𝑎𝑙"𝑅𝑒𝑐𝑒𝑖𝑣𝑎𝑏𝑙𝑒𝑠
"𝑋"100%
Classical Assumption
Test Normality test is used to test
whether the independent, dependent, or
both variables have a normal distribution or
are even close to normal (Situmorang,
2020). The normality test is usually used in
two ways: a statistical analysis using the
Kolmogorov-Smirnov Test and graph
analysis using histograms and normal P-
Plots. If the significance value reaches >
0.05, then a residual is called customarily
distributed, but if the significance value
goes < 0.05, then a residual is called
abnormally distributed.
Multicollinearity test is used to test
whether a regression model can find a
correlation or not between independent
variables (Daoud, 2017). If the VIF value is ≥
10 or Tolerance ≤ 0.01, then the data can
be concluded that multicollinearity
symptoms occur, while if the VIF value is ≤
10 or Tolerance ≥ 0.01, then the data can
be concluded free from multicollinearity
symptoms.
The heteroscedasticity test is used to
determine if a regression model can occur
variance inequality from one observation
residual to another (Safrita et al., 2021).
Heteroscedasticity test using plot
graph test in the predictive value of the
dependent variable by using ZPRED and
the residual value using SRESID. In a
regression model, heteroscedasticity will
not occur if the pattern is unclear and some
points spread above and below the number
0 on the Y-axis(Sartika et al., 2021).
Autocorrelation test, used for
consecutive observations at any time and
stated to have a relationship with each
other (Ahmarian et al., 2019). Symptoms of
autocorrelation can be seen from the
residual observations that are not
independent of other words (Byannur &
Nursiam, 2021). In each study using the
Durbin-Watson (test DW). Autocorrelation
can be checked from the test Durbin-
Watson. If dU < DW < 4-dU, it can be
concluded that there is no autocorrelation
symptom.
Research Data Analysis Methods
We performed multiple linear
285 | The Effect of Taxes, Exchange Rates, Leverage, and Bonus Mechanisms on Transfer Pricing
in Manufacturing Companies Listed on the IDX
regression analyses to evaluate the
independent variable's impact on the
dependent variable in this research.
Multiple linear regression contains one
dependent variable and two or more
independent variables (Sugiyono, 2016).
Description:
Y = Transfer Pricing, a = Constant, b =
Regression Coefficient, X1 = Tax, X2 =
Exchange Rate, X3 = Leverage, X4 = Bonus
Mechanism, e = Term of Error
Coefficient of Determination
According to Sanusi (2011:141) in
(Alamsyah et al., 2018), the coefficient of
determination measures the model's
capacity to explain the independent
variables. The coefficient of determination
ranges from 0 to 1, describing the
independent variable's appropriateness to
the dependent variable. The dependent
variable's variation explained by the
independent variable increases as the
coefficient of determination increases.
Conversely, a decreasing coefficient of
determination indicates a decreasing
variance of the dependent variable defined
by the independent variable.
Partial Test (T-Test)
Used to compare two intervals or ratios
with confidence. If t-count > t-table or t-
test significance < 0.05, the independent
variable has a substantial impact on the
dependent variable.
Simultaneous Test (F Test)
Examines the simultaneous effects of
the independent factors on the dependent
variable. If F-count > F Table or probability
< 0.05, then the independent variable is
influencing the dependent variable.
RESULTS AND DISCUSSION
RESULTS
Classical Assumption
Test Normality Test
Table 3. One-Sample Kolmogorov-
Smirnov Test
One-Sample Kolmogorov-Smirnov
Test
Unstandardized
Residual
N
87
Normal
Parameters
a,b
Mean
0E-7
Std.
Deviatio
n
.29424123
Most
Extreme
Differences
Absolute
.280
Positive
.280
Negative
-.204
Kolmogorov-Smirnov Z
2.611
Asymp. Sig. (2-tailed)
.000
a. Test distribution is Normal.
b. Calculated from data.
Source: SPSS Statistics 20
Table 3 shows that the data is not
normally distributed because of the value
Asymp. Sig. (2-tailed) above is 0.000, which
is less than 0.05.
Good data must meet the
requirements of the normality assumption
or must be normally distributed, which is
the value Asymp. Sig. (2-tailed) must be
Y = a + b
1
X
1
+ b
2
X
2
+ b
3
X
3
+ b
4
X
4
+ e
Wenny Anggeresia Ginting , Bee Arlita Ade Putri Br. Sitorus , Cindy Lorenza, | 286
Sania Surga Mas
greater than 0.05.
Figure 1. Normality Test Histogram Graph
Therefore, it is necessary to transform
the data. The technique used to change the
data is Square Root (SQRT). The normality
test results that have been converted are:
Figure 2. Normality Test Plot Graph
Based on the display output in Figure1,
it can see that the histogram graph is
shaped like a bell. While the display output
in Figure 2 shows a graph plot following the
points of the diagonal line so that it can
state that the data meets the requirements
of the normality assumption and is usually
distributed.
Table 4. Normality Test After Data
Transformation
One-Sample Kolmogorov-Smirnov
Test
Unstandar
dized
Residual
N
52
Standard
Parameters
A, B
Mean
0e-7
Std.
Deviation
.29316725
Most Extreme
Differences
Absolute
.121
Positive
.121
Negative
-.083
Kolmogorov-Smirnov Z
.874
Asymp. Sig. (2-Tail ed)
.430
A. Test Distribution Is Normal.
B. Calculated From Data.
Source: SPSS Statistics 20
Table 4 shows that the number of N
decreases from 87 to 52 because there is
data with a minus value, so that it is wasted
during data transformation. It is also shown
that the information is generally distributed
because of the importance of Asymp. Sig.
(2-tailed) above is 0.430, which is greater
than 0.05
287 | The Effect of Taxes, Exchange Rates, Leverage, and Bonus Mechanisms on Transfer Pricing
in Manufacturing Companies Listed on the IDX
Multicollinearity Test
Tabel 5. Multicollinearity Test
Source: SPSS Statistics 20
Based on the data results above, the
value Tolerance for all variables is greater
than or equal to 0.01, and the Variance
Inflation Factor (VIF) is less than or equal to
10. So it can conclude that the data is free
from multicollinearity symptoms.
Heteroscedasticity Test
Figure 3. Scatterplot Heteroscedasticity
Test
Based on the graph scatterplot above,
it can see that the dots spread randomly.
Therefore, it can conclude that the data is
free from heteroscedasticity symptoms.
Coefficients
Model
Unstandardized
Coefficients
Standardize
d
Coefficients
Sig.
Collinearity
Statistics
Std. Error
Beta
Tolerance
VIF
1
(Constant)
.260
.132
SQRT_X1
.187
-.079
.607
.759
1.318
SQRT_X2
.570
.452
.004
.812
1.231
SQRT_X3
.307
-.133
.344
.908
1.101
SQRT_X4
.154
-.008
.956
.843
1.187
a. Dependent Variable: SQRT_Y
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Table 6. Test Park
Coefficients
a
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
Collinearity
Statistics
B
Beta
Tolerance
VIF
1
(Const
ant)
-3.531
-3.418
.002
LN_X1
-.433
-.263
-1.174
.250
.644
1.552
LN_X2
.010
.011
.057
.955
.922
1.084
LN_X3
.034
.012
.067
.947
.939
1.065
LN_X4
-1.008
-.279
-1.241
.225
.639
1.565
a. Dependent Variable: LNU2i
Source: SPSS Statistics 20
the table above is the result of the
heteroscedasticity test using test park. The
heteroscedasticity test is considered free
from heteroscedasticity symptoms if the
value of Sig. on the variable X is greater
than or equal to 0.05. Based on the data
above, it can be seen that the entire value
of Sig. is above 0.05, so it can state that the
data is free from heteroscedasticity
symptoms.
Autocorrelation Test
Table 7. Autocorrelation Test
Model Summary
b
Model
R Square
Adjusted R
Square
Std. The error
of the Estimate
Durbin-
Watson
1
.174
.104
.30539
1.855
a. Predictors: (Constant), SQRT_X4, SQRT_X2, SQRT_X3, SQRT_X1
b. Dependent Variable: SQRT_Y
Source: SPSS Statistics 20
Based on the results output above, the
conclusion of the new test for the sample
(n) is 52, the independent variable (k) is four
variables, and the value Durbin-Watson
with α= 5% obtained dU of 1.7223. Then dU
< DW < 4-dU (1.7223 < 1.855 < 2.2777)
which means that it can be concluded that
the data is free from autocorrelation
symptoms.
289 | The Effect of Taxes, Exchange Rates, Leverage, and Bonus Mechanisms on Transfer Pricing
in Manufacturing Companies Listed on the IDX
Hypothesis Testing
Multiple Linear Regression Analysis
Table 8. Multiple Linear Regression Analysis Equation
Coefficients
a
Model
Unstandardized
Coefficients
Standardize
d
Coefficients
t
Sig.
Collinearity
Statistics
B
Std.
Error
Beta
Tolerance
VIF
1
(Constan
t)
.398
.260
1.533
.132
SQRT_X1
-.097
.187
-.079
-.519
.607
.759
1.318
SQRT_X2
1.750
.570
.452
3.069
.004
.812
1.231
SQRT_X3
-.293
.307
-.133
-.956
.344
.908
1.101
SQRT_X4
-.009
.154
-.008
-.056
.956
.843
1.187
a. Dependent Variable: SQRT_Y
Source: SPSS Statistics 20
Based on the table above, it can be
seen that multiple linear regression analysis
equations is as follows:
Transfer Pricing (Y) = 0.398 (a) – 0.097
TAX(b1) + 1.750 EXCHANGE RATE(b2) –
0,293 LEVERAGE(b3) – 0,009 BONUS
MECHANISM(b4) + e
From the multiple linear regression
equation above, it can be explained that
the constant (a) of 0.398 means that Tax
(b1), Exchange Rate (b2), Leverage (b3), and
the Bonus Mechanism (b4) is constant or
zero, then Transfer Pricing (Y) is positive or
will increase by 0.398. The Tax regression
coefficient (b1) is -0.097, meaning that for
every change in one unit of the financial tax
ratio (b1), the Transfer Pricing (Y) is
negative or will decrease by -0.097. The
Exchange Rate regression coefficient (b2) is
1.750, meaning that for every change in
one unit of the financial ratio Exchange
Rate (b2), the Transfer Pricing (Y) is
favorable or will increase by 1.750. The
Leverage regression coefficient (b3) is -
0.293, which means that for every change
in one unit of financial ratio leverage (b3),
then Transfer Pricing (Y) is negative or will
decrease by -0.293. The Bonus Mechanism
regression coefficient(b4) is -0.009,
meaning that for every one unit change in
the Bonus Mechanism's financial ratio (b4),
the Transfer Pricing (Y) is negative or will
decrease by -0.009.
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Coefficient of Determination
Table 9. Coefficient of Determination Test
Source: SPSS Statistics 20
Based on the data results above, it can
seem that the value is Adjusted R Square
0.104 or 10.4%. So it can conclude that the
independent variable affects the
dependent variable by 10.4%, and the rest
comes from other variables outside the
model.
T-test
Table 10. T-test
Source: SPSS Statistics 20
Based on the results output above, it
can see that the t-table is 2.01174. The
following is the explanation:
Tax (X1) at t-count is -0.519 where t-
count < t-table is 0.519 < 2.01174 and sig
value > 0.05 which means partially Tax (X1)
has no significant effect on Transfer Pricing
( Y), then the statement1 rejected.
Exchange Rate (X2) at t-count is 3.069
where t-count > t-table is 3.069 > 2.01174
and sig value < 0.05, which means partial
Exchange Rate (X2) has a significant
positive effect on Transfer Pricing (Y), then
the statement2 is received.
Leverage (X3) at t-count is -0.956
where t-count < t-table is 0.956 < 2.01174
and sig value > 0.05 which means partially
Model Summary
Model
R
R Square
Adjusted R
Square
Std. The error of the
Estimate
Durbin-
Watson
1
.417
a
.174
.104
.30539
1.855
a. Predictors: (Constant), SQRT_X4, SQRT_X2, SQRT_X3, SQRT_X1
b. Dependent Variable: SQRT_Y
Coefficients
Model
Unstandardized
Coefficients
Standardize
d
Coefficients
t
Sig.
Collinearity
Statistics
B
Std. Error
Beta
Tolerance
VIF
1
(Constant)
.398
.260
1.533
.132
SQRT_X1
-.097
.187
-.079
-.519
.607
.759
1.318
SQRT_X2
1.750
.570
.452
3.069
.004
.812
1.231
SQRT_X3
-.293
.307
-.133
-.956
.344
.908
1.101
SQRT_X4
-.009
.154
-.008
-.056
.956
.843
1.187
a. Dependent Variable: SQRT_Y
291 | The Effect of Taxes, Exchange Rates, Leverage, and Bonus Mechanisms on Transfer Pricing
in Manufacturing Companies Listed on the IDX
Leverage (X3) has no significant effect on
Transfer Pricing (Y), then statement3
rejected.
Bonus Mechanism (X4) at t-count is -
0.056 where t-count < t-table is 0.056
<2.01174 and sig value > 0.05, which
means partial Bonus Mechanism (X4) has
no significant effect on Transfer Pricing (Y),
then the statement 4 rejected.
F-Test
Table 11. F Test
ANOVA
a
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
.922
4
.231
2.472
.057
b
Residual
4.383
47
.093
Total
5.306
51
a. Dependent Variable: SQRT_Y
b. Predictors: (Constant), SQRT_X4, SQRT_X2, SQRT_X3, SQRT_X1
Source: SPSS Statistics 20
Based on the table above, it can see
that the F is calculated at 2.472 while the F-
table is 2.57. Thus, F-count (2.472) < F-table
(2.57), which means that Tax(X1), Exchange
Rate (X2), Leverage (X3), and Bonus
Mechanism (X4) have no simultaneous
effect on transfers pricing (Y) in 2017-2019.
Discussion
Effect of Tax on Transfer Pricing
The discovered coefficient of -0.519 in
the research indicates that the Tax variable
has no significant impact on Transfer
Pricing in manufacturing firms listed on the
IDX in 2017-2019. Thus, the original
hypothesis (Refgia et al., 2017)that taxes
have a beneficial impact on Transfer Pricing
is rejected.
According to (Azizah & Poren, 2014)
and (Agustina, 2020), taxes have no
substantial impact on Transfer Pricing. The
assertion that a company's objective is to
reduce taxes is inaccurate since the findings
of this research indicate that businesses
that minimize taxes do not necessarily seek
to conduct transfer pricing. Apart from this,
the Income Tax Law regulates specific
connections to avoid tax evasion (Setiawan
& Sulistyono, 2017).
Effect of Exchange Rate on Transfer
Pricing
The study results found that the
variable Exchange Rate has a coefficient of
3.069 with a significance value of 0.004,
which means that the Exchange Rate
variable has a significant effect on Transfer
Pricing in manufacturing companies listed
on the IDX in 2017-2019(Indonesia Stock
Exchange, 2019). So the initial hypothesis
quoted from research conducted by
(Pratiwi, 2018), which states that the
Exchange Rate has a positive effect on
Transfer Pricing, is accepted.
The results of this study are supported
Wenny Anggeresia Ginting , Bee Arlita Ade Putri Br. Sitorus , Cindy Lorenza, | 292
Sania Surga Mas
by research conducted by (Ayshinta et al.,
2019). Namely, the exchange rate has a
significant effect on transfer pricing.
Exchange Rate is the exchange rate of a
currency against current or future
payments. If the exchange rate fluctuates
continuously, it will affect the selling price
of the product or service to be traded
(Nagahisarchoghaei et al., 2018). Therefore,
management will choose to conduct
transfer pricing to ascertain the amount of
cash available for payment.
The exchange rate affects the
company's decision to transfer pricing. The
management will use currency exchange
rates to transfer profits to countries with a
more substantial currency value. In budget
planning, the yield on the foreign exchange
will increase every year (Pratiwi, 2018). This
is because they believe that the value of
foreign currencies will get more robust, and
the rupiah's deal will get weaker. The
stronger the foreign currency value, the
higher the foreign exchange profit earned
by the company. Then the company will
choose to sell products abroad through
transfer pricing so that the profits will be
even greater (Pratiwi, 2018).
Effect of Leverage on Transfer Pricing
The study results found that the
variable leverage has a coefficient of -0.956
with a significance value of 0.344, which
means that the variable influence has no
significant effect on Transfer Pricing in
manufacturing companies listed on the IDX
in 2017-2019(Indonesia Stock Exchange,
2019). So the initial hypothesis quoted from
research conducted by (Deanti, 2017),
which states that leverage has a positive
effect on Transfer Pricing, is rejected.
The results of this study are also
supported by research conducted by
(Pratiwi, 2018), namely, leverage has no
significant effect on Transfer Pricing.
Leverage can be used as a factor that
encourages transfer pricing to reduce the
company's tax burden. Companies with
high debt will focus on paying debts
because this will impact the company's
conducting transfer pricing (Deanti, 2017).
The potential for a company to carry out
transfer pricing will be higher if the level of
leverage companies are also higher
(Pratiwi, 2018).
Effect of Bonus Mechanism on Transfer
Pricing
A coefficient of -0.056 and a
significance value of 0.956 indicate that the
Bonus Mechanism variable does not affect
Transfer Pricing in manufacturing
companies listed on IDX in 2017-2019
(Indonesia Stock Exchange, 2019). This
disproves the initial premise (Refgia et al.,
2017) that the Bonus Mechanism helps
transfer pricing.
The Bonus Mechanism has no
significant effect on Transfer Pricing
(Rachmat, 2019). Bonuses are a method to
recognize a company's achievement.
According to research (Saraswati & Sujana,
2017), using transfer pricing to create fast
profits is highly unjust for the firm to
receive a bonus since numerous other
factors affect a company's destiny.
CONCLUSIONS
So this study will examine the effect of
taxes, exchange rates, leverage, and bonus
293 | The Effect of Taxes, Exchange Rates, Leverage, and Bonus Mechanisms on Transfer Pricing
in Manufacturing Companies Listed on the IDX
mechanism on transfer pricing. This
research utilized a manufacturing firm
listed on the Indonesian Stock Exchange in
2017-2019. Based on the study's results, we
may say: Tax impacts Transfer pricing with
a significance value of 0.607 > 0.05. The
tariff's magnitude has no bearing on the
company's decision. In terms of
importance, Exchange Rate impacts
Transfer Pricing with a significance value of
0.004 < 0.05. The increasing currency rate
will affect the company's decision to
transfer pricing. Leverage impacts Transfer
Pricing with a significance value of 0.344 >
0.05. The results of this research indicate
that leverage does not affect transfer
pricing. Bonus Mechanism impacts Transfer
pricing with a significance value of 0.956 >
0.05. The results of this research suggest
that the bonus mechanism does not affect
Transfer Pricing. The Adjusted R Square of
10.4% shows that the independent factors
only affect the dependent variable 10.4%,
while variables outside the model influence
the rest.
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