THE EFFECT
OF INCOME ON CAPITAL EXPENDITURE WITH BUDGET SURPLUS AS A MODERATING VARIABLE
Andi Sucito1,
Syukriy Abdullah2, Darwanis3 ��
Fakultas Ekonomi dan Bisnis, Universitas Syiah Kuala, Banda Aceh, Indonesia
[email protected]1, [email protected]2, [email protected]3
ABSTRACT
The realization of capital expenditure of regencies/cities in North
Sumatra Province during the 2019-2020 period decreased by more than 25%.
Similarly, the realization of local indigenous income (PAD) in the province
decreased in 2019-2020 by 4.75%. This decrease is thought to be caused by poor
budget planning at the beginning of the budgeting year. This study aims to
determine the effect of local income and general allocation funds on capital
expenditure moderated by budget surplus in districts/cities in north Sumatra
province in 2016-2020. This study uses descriptive quantitative method. The
population of this study is all regencies/cities in North Sumatra Province
which amounts to 33 regencies/cities. This study used multiple linear
regression techniques to determine the influence between research variables.
The results showed that local original income had a positive effect on capital
expenditure, the general allocation fund had a positive effect on capital
expenditure, the budget surplus moderated the effect of local original income
on capital expenditure, and the surplus budget moderated the effect of the
general allocation fund on district/city capital expenditure in North Sumatra
Province 2016-2020. The increase in PAD and DAU will have a positive impact on
Capital Expenditure of Regencies/Cities in North Sumatra Province. The increase
in PAD and DAU will provide sufficient budget for local governments to finance
the necessary development projects. This can have a positive impact, including
the availability of sufficient budgets, improving community welfare, increasing
economic growth, and increasing regional competitiveness.�
Keywords: a
surplus of budget financing, capital expenditure, general allocation fund,
own-source revenue.
Corresponding Author: Andi
Sucito
E-mail: [email protected]
INTRODUCTION
Regional expenditure is divided into two:
Operational Expenditure and Capital Expenditure. Operational expenditure is an
expense to finance non-investment activities that have a usefulness of less
than one year. In contrast, Capital Expenditures are investment expenditures in
the form of costs so that they are recognized on the balance sheet. Regional
expenditure management must be the focus of local governments so that regional
financial management can be optimised (Defitri, 2018).
Capital expenditure is government spending aimed at procuring tangible fixed
assets that have a useful life of more than one year that can be used to
support government operations for better public services (Pinem et al., 2020).
Adding assets will result in additional routine, operational, and maintenance
costs. The utilization of fixed assets can directly intersect with public
services or be used by the community, and some are utilized by local
governments (Suparta, 2021).
Based
on the Central Bureau of Statistics (BPS) data, the average capital expenditure
allocation for Sumatra Utara Province and regencies/municipalities in Sumatra
Utara Province during 2018-2019 was still below 30%, around 18.81% and 20.12% (Daulay, 2020).
The
realization of regencies/municipalities' capital spending in Sumatra Utara
Province based on regencies/municipalities' Budget Realization Reports (LRA)
during the 2019-2020 period has decreased by more than 25%. The realization of
local own-source revenue (PAD) based on the 2019 and 2020 LRA in Sumatra Utara
Province decreased in 2019-2020, amounting to IDR 128,136,593,961.00 or 4.75%.
The decline and realization that we still have not reached the target are
allegedly due to poor budget planning at the beginning of the budget
preparation year. The realization of regencies/municipalities' capital spending
in Sumatra Utara Province based on regencies/municipalities' Budget Realization
Reports (LRA) during the 2019-2020 period has decreased by more than 25% in
several regencies/municipalities, with details in the following table.
Table 1. Decrease in the Realization of Capital Expenditure in
Regencies/Municipalities in Sumatra Utara Province in 2020
Local
Government Name |
Realization
in 2019 (Rp) |
Realization
in 2020 (Rp) |
Decrease
Percentage |
Asahan
Regency |
304,478,575,304.52 |
146,983,023,065.25 |
51.73 |
Labuhan
Batu Selatan Regency |
220,503,868,788.16 |
136,042,412,265.68 |
38.30 |
Labuhan
Batu Regency |
238,729,009,917.30 |
136,621,343,879.00 |
42.77 |
Labuhan
Batu Utara Regency |
258,116,878,081.37 |
103,416,243,036.59 |
59.93 |
Padang
Lawas Regency |
241,420,449,752.03 |
143,366,541,808.00 |
40.62 |
Padang
Lawas Utara Regency |
247,484,629,027.00 |
152,155,180,883.00 |
38.52 |
Pak-Pak
Barat Regency |
145,937,021,774.00 |
63,702,287,295.00 |
56.35 |
Simalungun
Regency |
381,344,591,277.00 |
107,214,562,374.00 |
71.89 |
Toba
Regency |
135,339,350,834.00 |
66,583,199,217.00 |
50.80 |
Tanjung
Balai Municipality |
96,299,502,045.52 |
53,907,690,820.07 |
44.02 |
Medan
Municipality |
992,661,245,694.74 |
308,278,278,057.33 |
68.94 |
Padang
Sidempuan Municipality |
137,812,393,423.59 |
66,379,049,476.14 |
51.83 |
Source: LRA LKPD TA 2019 and 2020�
(Statistik, 2023)
The decrease in capital spending in 2020 can
also be caused by the Covid-19 pandemic, which requires the Regional Government
to refocus the budget on implementing Covid-19 disaster management. The budget
refocusing is regulated in Government Regulation instead of Law (Perpu) Number
1 of 2020 concerning State Financial Policies and Financial System Stability
for Handling the 2019 Corona Virus Disease (Covid-19) Pandemic and/or in the
Context of Facing Threats that Endanger the National Economy and/or Financial
System Stability (Juliani, 2020).
Based on the Government Regulation instead of Law, Regional Governments are
given prioritize the use of budget allocations for certain activities
(refocusing), change allocations, and use the Regional Revenue and Expenditure
Budget (APBD). With this budget refocusing, most local governments make budget
changes by reducing the allocation of capital expenditures.
Following Government
Regulation (PP) Number 12 of 2019, Capital Expenditure is a regional
expenditure component funded by regional income; The size of regional income
influences the size of the allocation for Capital Expenditure (Waskito et
al., 2019). Based on Law Number 12 of 2008, local governments
have local revenue sources in the form of Local Own-Source Revenue (PAD) (Nasir, 2019). In addition, the central government will
also transfer balance funds consisting of the local government's General
Allocation Fund (DAU). The contribution of PAD in budget allocation is quite
large, as is the Balance Fund, which consists of DAU and Special Allocation
Funds, which are transfer funds from the central government and the Budget
Surplus (SiLPA) (Mentayani,
2013).
Several previous studies have examined the
factors that influence Capital Expenditures, such as (Muttaqin et al., 2021), (Amran & Abdullah, 2015), (Mentayani, 2013), (Junaedy, 2015)) (Lourine Talluta et al., 2018), (Kasdy et al., 2018), (Asari & Suardana, 2018).
This study stated that the factors influencing Capital Expenditures include
PAD, DAU, DBH (Revenue Sharing Fund), fiscal balance transfers, and budget
financing surpluses. However, there is a difference between this study and previous
research. This study uses the DAU variable as an independent variable moderated
by SiLPA, which previous researchers have never studied.
Based on the background that has been
presented, it is necessary to formulate a problem that will be resolved in this
study: Whether PAD affects capital expenditure, whether DAU affects capital
expenditure, whether SiLPA affects capital expenditure, whether SiLPA moderates
the effect of PAD on capital expenditure, and whether SiLPA moderates the
effect of DAU on capital spending.
Based
on the formulation of the problem above, the purpose of this study is to
determine: the effect of PAD on capital expenditure, the effect of DAU on
capital expenditure, the effect of SiLPA on capital expenditure, the effect of
SiLPA moderation on the relationship between PAD and capital expenditure, and
the moderating effect of SiLPA on the relationship between DAU and capital
expenditure.
METHOD
Based on the
relationships between variables that have been described in the framework, the
hypotheses in this study are:
H1������ PAD affects Capital Expenditures.
H2������ DAU affects Capital Expenditures.
H3������ SiLPA affects Capital Expenditures.
H4������ SiLPA moderates the effect of PAD on
Capital Expenditures
H5������ SiLPA moderates the effect of DAU on
Capital Expenditures.
����������� This
descriptive quantitative research analysed PAD and DAU on Capital Expenditures
with SiLPA as a Moderating Variable in regencies/municipalities in Sumatra
Utara Province in 2016-2020. The unit of analysis in this study is the Budget
Realization Report on the regencies/municipalities in the Government Financial
Reports of Sumatra Utara Province, totalling regencies/municipalities in
2016-2020. Variable data are collected at two or more time limits to answer the
research problem. A population can also be defined as a collection of data that
a researcher may observe or record. This research was conducted using a census
technique in which the entire population was used as the research unit.
This study uses a multiple
linear regression model with two tests, first without moderation and second
with moderation. The equation used can be written as follows:
Unmoderated equation:
BM = α+β1PADit +β2DAUit + β3SiLPAit + eit
BM = α + β1PADit + β2DAUit + β3SiLPAit + β4PADit*SiLPAit + β5DAUit*SiLPAit + eit
BM = β0+β1PAD+β2 DAU+β3 DO+β4 SiLPA+β5 PAD.SiLPA+β6 DAU.SiLPA+β7 DO.SiLPA+ε
where α is a constant, β1-5 is the regression coefficient, and e is the
error term.
RESULTS AND DISCUSSION
Research Results
The number of observations analyzed was 165, namely 33
local governments with five years of data (2016-2020). The data were processed
using SPSS 25 and presented in Table 2 (descriptive statistics) below.
Table 2. Descriptive
Statistics on Budget Realization Data (N=165)
Minimum |
Maximum |
Average |
Standard Deviation |
|
BM |
53907690820 |
997475991902 |
243445273352.77 |
158863394718.56 |
PAD |
15616742531 |
1829665882248 |
157483911181.67 |
296479349778.75 |
DAU |
10511999710 |
494507818421 |
56562737394.72 |
73089432216.93 |
SiLPA |
7007999807 |
329671878947 |
37708491596.46 |
48726288144.60 |
Classic Assumption Test
The classic assumption tests used in this study were the Normality Test,
Multicollinearity Test, and Heteroscedasticity Test. The classical assumption
test was analyzed using the SPSS program. The results of the classical
assumption test using SPSS 25 are presented in Table 3 below.
Table 3 results from Classic Assumption Test
Instrument |
Test Results |
Conclusions |
|
Normality
Test |
Kolmogorov-Smirnov
test |
Asymp.
Sig. (2-tailed) of 0.200 |
The sig value at 0.200 > 0.05 means these
variables have a normal distribution. |
Multicollinearity
Test |
Variance
Inflation Factor |
Tolerance
Value: PAD = 0.793; DAU = 0.439; SiLPA = 0.380 VIF
Value; PAD
= 1.261; DAU = 2.280; SiLPA = 2.632 |
Tolerance
values > 0.10 and VIF < 10, so the multicollinearity of each variable
is not found. |
Heteroscedasticity
Test |
SPSS
Scatterplot Graph |
The
dots denoting the variables' components spread randomly on the scatter plot. |
The
data is spread randomly, so it can be ascertained that there is no
heteroscedasticity problem. |
Regression Analysis Results
Regression
analysis was used to determine whether there is an influence between the independent
variables on the dependent variable. Multiple linear analysis was used to
obtain a regression coefficient to determine whether the hypothesis would be
accepted or rejected. The results of the regression analysis of budget
realization data in Sumatra Utara Province can be seen in table 4 below.
Table 4 Test Results of
Multiple Linear Regression Analysis on Budget Realization Data
Variable |
Coefficient Value |
t-Value |
Sig.Value |
F/Sig.Value |
R/R2/Adj.R2 |
PAD |
0.041 |
2.635 |
0.020 |
789.220/0.000 |
0.968/ 0.936/ 0.935 |
DAU |
0.121 |
2.528 |
0.009 |
||
SiLPA |
0.641 |
12.214 |
0.012 |
||
Constant |
6.739 |
16.314 |
0.000 |
Based on the results of data processing using
the SPSS program, as shown in table 4, the multiple linear regression equation
is obtained as follows:
BM=
6,739+ 0,041PAD + 0,121DAU + 0,641SiLPA + e
The
results of hypothesis testing can be explained as follows:
The regression coefficient of the PAD
variable is 0.041, which means that a change in the PAD variable by one unit
will cause a change in the BM variable by 0.041 units. This effect is
significant or cannot be ignored at the 5% (α) significance level. This
means that statistically, PAD has a significant impact on Capital Expenditures.
The test results show that the regression coefficient value of the PAD variable
(X1) is β1 = 0.041 with a significance of 0.020. Hypothesis testing shows
that if sig <0.05, Ha is accepted, meaning PAD affects Capital Expenditures.
This study's results align with the research (Nainggolan & Hantono, 2018),
proving that PAD affects Capital Expenditures. These results indicate that the
higher the PAD, the higher the Capital Expenditure. This research aligns with (Lourine Talluta et al., 2018),
which state that the PAD variable affects capital expenditures. Research on the
effect of PAD on Capital Expenditures has been conducted (Daulay, 2020),
where the results prove that there is an influence of PAD on Capital
Expenditures with the explanation that the higher the PAD, the higher the
Capital Expenditures that the local government can allocate. Increased PAD will
provide benefits to increase the provision of public facilities through the
development of facilities and infrastructure, especially infrastructure
development. Another study was conducted by (Abba et al., 2015) on
local government in the State of Adamawa, Nigeria, from 2003-2012, where PAD
affects Capital Expenditures.
The results of regression testing for the
second hypothesis in this study were conducted to determine whether DAU affects
Capital Expenditures. The test results show that the regression coefficient
value of the DAU variable is β2 = 0.121 with a significance of 0.009.
Hypothesis testing shows that if sig <0.05, Ha is accepted, meaning that DAU
affects Capital Expenditures. This research aligns with (Mentayani, 2013),
who states that DAU affects Capital Expenditures. This research was conducted
in 46 regencies/municipalities in the provinces on the island of Borneo from
2010-2012. In addition, a study (Nainggolan & Hantono, 2018)
states that DAU affects Capital Expenditures.
However, some studies do not align with the
current study's results. Research (Sholikhah & Wahyudin, 2014) states
that DAU does not affect Capital Expenditures. This difference may be due to
the difference in the number of samples used in this study, namely 93
regencies/municipalities with a span of one year, namely in 2010.
The results of regression testing for the
third hypothesis in this study were conducted to determine whether SiLPA
affects Capital Expenditures. The test results show that the regression
coefficient value of the SiLPA variable is β3 = 0.641 with a significance
of 0.012. Hypothesis testing shows that if sig <0.05, then Ha is accepted,
meaning that SiLPA affects Capital Expenditure. This study's results align with
research by (Angelina et al., 2020) with
a sample of 33 regencies/municipalities in Sumatra Utara Province, showing that
SiLPA significantly affects capital expenditure (Kasdy et al., 2018) also
found that SiLPA affects capital expenditure. The research was conducted with a
broader sample, namely in 311 regencies/municipalities in Indonesia during
2013-2015.
Results of Linear Regression
Analysis with Moderation
The results of data processing using
multiple linear regression models with moderation can be seen in Table 5.
Table 5. Moderation Test
Results
Variable |
Coefficient |
t-Value |
Sig.Value |
F/Sig.Value |
R/R2/Adj.R2 |
PAD |
0.065 |
3.951 |
0.000 |
520.678/0.000 |
0.971/0.942/ 0.941 |
DAU |
0.136 |
2.951 |
0.004 |
||
SiLPA |
0.616 |
11.249 |
0.000 |
||
PAD*SiLPA |
0.043 |
3.393 |
0.001 |
||
DAU*SiLPA |
0.033 |
3.395 |
0.001 |
||
Constant |
6.904 |
17.319 |
0.000 |
Based on the results of statistical
calculations using the SPSS program, as shown in Table 5, the multiple linear
regression equation is obtained as follows:
BM =� 6,904 +
0,065PAD + 0,136DAU + 0,616SiLPA + 0,043PAD*SiLPA + 0,033DAU*SiLPA� + e
The
results of hypothesis testing can be explained as follows:
The results of regression
testing for the fourth hypothesis in this study were conducted to determine
whether SiLPA moderates the effect of PAD on Capital Expenditures. The
test results show that there is a quasi-moderator. The results of subsequent tests found that the regression
coefficient value was 0.043 if it is associated with the significance level of
β4, which is insignificant (0.001 <0.05). So, it can be interpreted
that SiLPA positively and significantly moderates PAD on Capital Expenditures.
Using SiLPA to finance
capital expenditure (Surya & Darwanis, 2015) shows that SiLPA can be a PAD substitute, especially at the
beginning of the relevant fiscal year. This is because, at the beginning of the
year, not all the funds sourced from this income had entered the regional
treasury, so it was handled first with SiLPA. This condition indicates that
SiLPA can affect the relationship between regional revenue sources from PAD and
capital expenditure. If SiLPA is large, then sources of funding such as PAD
which SiLPA for capital expenditure replaces, are also considerable. On the
other hand, if SiLPA is small, the funding sources to finance capital expenditures
will also be small.
The results of regression
testing for the fifth hypothesis in this study were conducted to determine
whether SiLPA moderates the influence of DAU on Capital Expenditures. The
test results show that there is a quasi-moderator. The results of subsequent tests found that the regression
coefficient was 0.033 if it is associated with a significance level of β5,
which is insignificant (0.001 <0.05). So, it can be interpreted that SiLPA
positively and significantly moderates DAU on Capital Expenditures.
The amount of SiLPA is thought to be
able to moderate the effect of DAU on capital expenditure. With increasing
SiLPA from an area, the PAD and capital expenditure will increase. An increase
in the capital investment (capital expenditure) of the Regional Government is
expected to be able to improve the quality of public services and, in turn, be
able to increase the level of public participation (contribution) to
development, which is reflected in an increase in PAD (Mardiasmo, 2009, p. 93).
When linked to the contingency theory, local governments must behave
differently to make PAD and SiLPA effective in forming high capital
expenditures.
CONCLUSION
PAD affects Capital Expenditures; The
higher the PAD, the higher the Capital Expenditures that the regional
government can allocate; Increased PAD will provide benefits to increase the
provision of public facilities through the development of facilities and
infrastructure, especially infrastructure development DAU affects Capital
Expenditures. This shows that the greater the DAU, the greater the Capital
Expenditures. DAU is one of the balance funds originating from the APBN, which
is allocated with the aim of inter-regional financial equity to finance
expenditure needs in the context of implementing decentralization. Thus, with
significant transfers from the central government to regional governments,
local governments can use these funds to carry out basic public service
functions. DAU is also a source of financing for Capital Expenditure to procure
facilities and infrastructure in the context of providing good public services.
Local governments can allocate DAU to finance Capital Expenditures. SiLPA
affects Capital Expenditures. SiLPA, based on applicable regulations, can fund
activities and obligations that have not been completed by the end of the year.
A high SiLPA at the end of the year can indicate high capital expenditure in
the following year.� SiLPA positively and
significantly moderates PAD on Capital Expenditures. If SiLPA is large, then sources
of funding such as PAD which SiLPA for capital expenditure replaces, are also
large. On the other hand, if SiLPA is small, the funding sources to finance
capital expenditures will also be small. SiLPA positively and significantly
moderates DAU on Capital Expenditures. The amount of SiLPA is thought to be
able to moderate the effect of DAU on capital expenditure. With the increasing
amount of SiLPA from an area, the PAD and capital expenditure will increase.
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