Corresponding Author: Sri
Hartono
E-mail: [email protected]
INTRODUCTION
Infrastructure provision is one of the strategic
choices to accelerate Indonesia's economic growth and equity (Gunawan & Maryoni,
2017). The government needs to accelerate the program for
proportional distribution of development in all regions. Thus, the development
process that occurs is biased in already advanced areas and other areas
considered to be lagging (Sukwika, 2018).
Every infrastructure development expenditure is hoped
to support and facilitate economic activity. Previous research has shown that
the realization spending spent on public infrastructure development has a
positive role in social welfare and economic growth (Luter et al., 2019), (Ramadhan, 2019), (Ram�rez & Vargas,
2018).
The State Revenue and Expenditure Budget for 2020-2022
stipulates that infrastructure spending will receive an allocation of 22% of
the total APBN, one of which is aimed at supporting the national economic
recovery program through infrastructure development under the National Medium
Term Development Plan (RPJMN) 2020-2024. In the 2020-2024 RPJMN, the need for
infrastructure spending is estimated at IDR 6.445 trillion, while the APBN is
only 37% or IDR 2.385 trillion in financing infrastructure development.
The limited budget that is owned requires the
government to be more efficient in managing infrastructure development
spending. However, based on previous research, it is known that local
government spending in Indonesia in 2015 - 2018 has yet to reach a good level
of efficiency (Rambe, 2020). There are 20 provinces (58.8%) that are inefficient,
nine provinces (26.5%) are relatively efficient in certain years, and only five
provinces (14.7%) are always efficient. Nationally, the level of spending efficiency in
Indonesia's infrastructure sector has an average value of 61.9%. This
efficiency level is below Malaysia, with an average value of 73.6%, and
Singapore and Thailand, with an average of 100% (Merini,
2013). The Ministry of Finance,
through a study related to the efficiency of infrastructure spending at the
Ministry of Public Works and Public Housing, the Ministry of Transportation,
and the Ministry of Energy and Mineral Resources, stated that only two
provinces (West et al.) were the most efficient (Negara, 2013).
Efficiency is one of the main
elements (besides economy and effectiveness) in the concept of value for money
when measuring the performance of public sector organizations (Erawan et
al., 2018). Efficiency is using as few
resources as possible to get maximum results (maximizing benefits and
minimizing costs) (Mardiasmo,
2021). In implementing the New Public Management (NPM),
efficiency is emphasized in all government organizations as a measure of the
performance of government organizations. Ministries/Institutions are directed
to improve the quality of spending that is more efficient but has an optimal
impact on the economy and people's welfare under government policy steps
contained in financial notes along with the state budget and income (Finance, 2021).
The Ministry of Public Works and Public Housing, as
one of the government institutions responsible for infrastructure development
in Indonesia, has to continue to improve the reliability of public works and
public housing infrastructure, which consists of the water resources sector,
the high-level development sector, and the creative works sector. In 2020 the
Ministry of PUPR managed a budget of IDR 107.1 trillion; this amount increased
by 50.6% in 2021 to IDR 161.3 trillion and decreased by 16.5% in 2022 to IDR
135.4 trillion. Accountability for relatively large budget management is an
important thing for the Ministry of PUPR to do. Management of this large budget
is expected to be able to fulfill aspects of good efficiency so that spending
sourced from state debt financing becomes meaningful in overcoming
infrastructure gaps which ultimately leads to the goal of building economic
growth.
Based on the background that has been explained, this
research was conducted aiming to evaluate the efficiency of infrastructure
development carried out by the Ministry of Public Works and Public Housing
during the 2020-2022 period and to examine the factors that influence the
efficiency of infrastructure spending in supporting economic growth in all
provinces in Indonesia. This research adapts previous research in analyzing the
efficiency of government capital spending on economic development in Aceh Province
(Chandra et al., 2022). Other research also examines the effect of fiscal capacity on the
efficiency of local government spending in provinces throughout Indonesia (Rambe, 2020). The differences in this
research from previous research are. First, this research looks at it from the
point of view of the central government in realizing infrastructure development
spending. Second, measuring the efficiency level using capital expenditure and
maintenance input variables. Third, this study adds the independent variables
of population and area as factors that influence the efficiency of government
spending.
METHODS
This study uses a
quantitative approach in which data is in the form of numbers or numbers that
can be processed and analyzed using statistical techniques (Bougie & Sekaran,
2019). Quantitative research can be used to explain and
predict certain conditions so that overall conclusions can be drawn.
The population in
this study are all provinces where the Ministry of Public Works and Public
Housing realized spending on infrastructure development in the Highways, Cipta
Karya, and Water Resources sectors in 2020-2022. Sampling in this study was by
using a census, where all population members were used as samples, so the
number of samples used in this study was 34 provinces.
This research uses
secondary data for 2020-2022 in fiscal capacity obtained through a Minister of
Finance Regulation issued annually by the Ministry of Finance. Data on the
realization of capital and maintenance expenditures per sector were obtained
from the Financial Report of the Ministry of PUPR. Data on per capita gross
regional domestic product, population, and area based on the Central Bureau of
Statistics are accessed via www.bps.go.id.
This study has two
stages of analysis, namely an analysis of the technical efficiency value of
infrastructure development spending during the 2020-2022 period measured using
the DEA model BCC (Banker et al.) approach through the input-oriented VRS
(Variable Return to Scale) assumption using MaxDEA software assistance. Lite
v12.0. The measurement of efficiency in this study uses the input variable to
realize capital expenditure and maintenance in the water resources, high
school, and creation sectors. In contrast, the output variable is Gross
Regional Domestic Income per capita. In the second stage, the effect of fiscal
capacity, population, and area on technical efficiency was tested using the
Tobit regression model with the help of EViews 10 software. Tobit regression
was used because the dependent variable data is censored in efficiency scores
ranging from 0 to 1.
RESULTS AND DISCUSSION
Efficiency
Analysis based on DEA
The first
stage of this research is to measure the technical efficiency of the Ministry
of PUPR's infrastructure spending in each province through input and output
using Data Envelopment Analysis (DEA) through the input-oriented Variable
Return to Scale (VRS) approach using MaxDEA Lite v12.0 software. A province is
considered technically efficient with an efficiency score of 100%.
Figure 1. Graph of efficiency for the 2020-2021
period
Source: Processed data, 2023
Figure 1
shows the number of efficient provinces from 2020 to 2022 has fluctuated. In
2020 there are 18 provinces or 52.94% efficient (DI Yogyakarta, DKI Jakarta,
Banten, North Kalimantan, East Kalimantan, Central Kalimantan, South
Kalimantan, North Maluku, Maluku, Bali, West Papua, West Sulawesi, Central
Sulawesi, Southeast Sulawesi, Gorontalo, Riau Archipelago, Bengkulu, Bangka
Belitung). In 2021 there are 17 provinces or 50% efficient (DI Yogyakarta, DKI
Jakarta, Banten, North Kalimantan, Central Kalimantan, East Kalimantan, North
Maluku, Bali, West Nusa Tenggara, West Papua, West Sulawesi, Central Sulawesi,
Gorontalo, Southeast Sulawesi, North Sulawesi, Riau Archipelago, Bangka
Belitung). In 2022 it increased to 18 provinces or 52.94% efficient (DI
Yogyakarta, DKI Jakarta, Banten, North Kalimantan, East Kalimantan, Central
Kalimantan, South Kalimantan, North Maluku, Bali, West Nusa Tenggara, Papua,
West Papua, Sulawesi North, West Sulawesi, Central Sulawesi, Gorontalo,
Southeast Sulawesi, Riau Archipelago, Bangka Belitung, ). The province with the
lowest efficiency score (22.03%) in 2020 is South Sumatra Province; in 2021,
the lowest efficiency score (13.00%) is North Province, while in 2020, the
lowest efficiency score (18.27%) is North Sumatra Province.
Results of
Tobit Regression Analysis
Testing the hypothesis in this study on the Tobit regression model was carried out
using the Likelihood Ratio Test and the Wald Test with the Eviews10
application. The Likelihood Ratio test tests whether one or all of the
independent variables have a real contribution to the dependent variable. The
Wald test shows the significance value of the influence of one independent
variable in explaining the variation of the dependent variable, which assumes
that the other independent variables are unchanged (constant).
Likelihood
Ratio Test
The test results were carried out using the
Eviews program, as shown in Table 1. Based on the test results, the Likelihood
Ratio value was 59.74547 with a probability level ( α ) of 0.0000. So it can be concluded that
overall the independent variables (fiscal capacity, population, and area)
affect the dependent variable (Technical Efficiency) because the Likelihood
Ratio value > chi-square (x 2 = 7.815) and the probability value is less than
0.05.
Table 1. Likelihood Ratio Test
Results
|
|
Value
|
df
|
probability
|
|
|
59/74547
|
3
|
0.0000
|
|
LR test
summary:
|
Value
|
|
|
|
Restricted
LogL
|
-59.01438
|
|
|
|
Unrestricted
LogL
|
-29.14165
|
|
|
Source:
Processed data, 2023
Wald's test
Criteria for
decision-making to accept or reject the hypothesis can be done by looking at
the probability number (α) or p-value and the direction of the
variable coefficient value (positive/negative). If the number probability (significance) α <
5%, then the hypothesis is accepted. The hypothesis is rejected if the number
probability (significance) α > 5%. The following is the analysis results using
tobit regression with Eviews10 software.
Table 2. Significance Test Results
|
Variables
|
coefficient
|
std. Error
|
z-Statistics
|
Prob.
|
|
FIS
|
0.308973
|
0.080765
|
3.825573
|
0.0001
|
|
PEN
|
-0.647676
|
0.077408
|
-8.367031
|
0.0000
|
|
WIL
|
-0.131296
|
0.054346
|
-2.415941
|
0.0157
|
|
C
|
3.537173
|
0.381075
|
9.282097
|
0.0000
|
Source: Processed data, 2023
The Effect of Fiscal Capacity on the
Efficiency of Infrastructure Development Spending
The test
results through the Eviews program shown in Table 2 show that the coefficient
value of the FIS variable (positive) is 0.308973, and the significance is at
the 0.0001 level. These results mean that fiscal capacity positively affects
the efficiency of infrastructure development. The better the regional fiscal
capacity has the potential to increase the efficiency of infrastructure
development spending carried out by the Ministry of PUPR. The higher the fiscal capacity of a region, the fewer APBN
resources are realized by the Ministry of Public Works and Public Housing in
carrying out infrastructure development to support economic growth in certain
provinces.
The results
of research on fiscal capacity's effect on infrastructure development's
efficiency align with the research conducted (Rambe, 2020). Fiscal capacity has a positive and
significant effect on the efficiency of government spending in 34 provinces in
Indonesia (Rambe,
2020). Similar statements are also proven by
previous studies on research related to factors affecting government
performance in Portugal (Da Cruz &
Marques, 2014).
Provinces
with good fiscal capacity should be able to finance infrastructure development
in their territory. This can be used as a consideration for the Ministry of
PUPR in conditions of limited infrastructure development budgets to allocate
infrastructure development spending in each province. This research provides
evidence of the need for coordination between the central government and local
governments in infrastructure development to improve a province's economy. This
coordination allows the central government to use the available budget more
efficiently.
The Effect of
Area on the Efficiency of Infrastructure Development Spending
The test
results in Table 2 show that the coefficient value of the PEN variable
(negative) is 0.647676 and has significance at the 0.00000
level. These results indicate that the population harms the efficiency of
infrastructure development. This implies that the more the population will
increase the need to meet infrastructure for all people in a province. During
2020-2022 the population will always increase, followed by the amount of actual
infrastructure development spending in each province, but not all provinces
will experience an increase in GRDP. This condition illustrates that the level
of efficiency in infrastructure spending is getting smaller because high
infrastructure investment is not followed by increased economic growth in each
province.
The results of this study are supported by
several previous studies, which stated that in 31 provinces in China, they
found a significant effect of population on the efficiency of government
spending. A similar statement is also proven by research related to the
performance evaluation of public sector spending conducted in 18 OECD countries
during the 1995-2002 period that population size negatively influences the
efficiency of public sector spending in the health sector (Hsu &
Lee, 2014).
Concerning
the contingency theory, the results of this study prove that population size
should be an organizational consideration as a contingency factor in investing
in infrastructure development in a province. Efficiency in spending on
infrastructure development can be achieved if infrastructure provision can
support people's productivity in each province. So that in making investment
decisions for infrastructure development, it is necessary to pay attention to
external environmental factors of the population.
The Effect of
Area on the Efficiency of Infrastructure Development Spending
The test
results presented in Table 2 show the coefficient value of the WIL variable
(negative) of -0.131296 and significance at the 0.0157 level. These results
indicate that the area harms the efficiency of infrastructure development. The
total area of a province can affect the need to provide adequate public
facilities and infrastructure. If the province area is wider, it will cause the
distance between locations to be farther apart, so the need for accessibility
for the community to public facilities is getting higher.
Provinces
with a large area tend to have diverse geographical, natural conditions, such
as mountains and hills valleys,
rivers, or lakes. The diversity of natural conditions can potentially affect
the efficiency level of infrastructure spending. Infrastructure development in
hilly areas certainly requires a more complex design and higher costs compared
to lowland areas.
The results
of this study are supported by several previous studies, which state that area has a significant negative effect on the efficiency of
government spending in Indonesia AD (Prasetyo
et al., 2018). The determinants affecting government
performance in Portugal conclude that the area harms the efficiency of
government spending (Da Cruz &
Marques, 2014). This study's results align with previous
studies in Japan, which stated that the area has a negative effect on the
efficiency level of Nakazawa (2014).
The area size
factor is important as one of the considerations for investment in
infrastructure development in each province. Some regions have rich natural
resource potential, while others may have advantages in tourism or other
industries. So, to achieve efficiency in infrastructure development in certain
provinces, the infrastructure development must encourage economic growth,
maximize existing potential, and strengthen connectivity between regions.
CONCLUSION
Regions with high
fiscal capacity can better finance infrastructure provision in their regions
and are less dependent on the central government's APBN. This will have an
impact on the efficiency of spending on infrastructure development because
there are fewer input resources in the form of expenditure realization using
the APBN at the Ministry of Public Works and Public Housing, which is used for
infrastructure development in the province. An increase in population will
reduce the level of efficiency of infrastructure development. The more
population will increase the need to meet infrastructure for the whole
community. The increase in infrastructure needs will have an impact on
increasing costs which will ultimately affect the level of efficiency. The factor
of the province's area can reduce the efficiency of infrastructure development.
The territory of a province has geographical characteristics that are different
from one another. The wider the province tends to have different geographical,
natural conditions. Infrastructure development in difficult geographical
conditions such as hills requires a more complex design and higher costs than
in lowland areas.
REFERENCES
Bougie, R., & Sekaran, U. (2019). Research methods for
business: A skill building approach. John Wiley & Sons.
Chandra, C. P. S., Darwanis, D., & Ibrahim, R. (2022).
Efisiensi Belanja Modal Pemerintah Daerah: Studi Pada Kabupaten/Kota di
Provinsi Aceh. AFRE (Accounting and Financial Review), 5(2), 222�232.
Da Cruz, N. F., & Marques, R. C. (2014). Revisiting the
determinants of local government performance. Omega, 44, 91�103.
Erawan, P. A., Santosa, M. D. S. W. A. D. I., Budiartha, D.
K. B., & Wahyudi, P. T. A. (2018). Peranan Value for Money Untuk Mengukur
Kinerja Pemerintahan Kabupaten Buleleng. Jurnal Ilmiah Akuntansi Dan
Humanika, 8(3). ������������� https://doi.org/10.23887/jinah.v8i3.20010
Gunawan, I., & Maryoni, H. S. (2017). Dinamika Penetapan
Kawasan Ekonomi Khusus Dalam Mempengaruhi Kebijakan Wilayah Desa. Jurnal
Sungkai, 5(1), 69�95. https://doi.org/10.30606/js.v5i1.1210
Hsu, Y.-C., & Lee, C.-C. (2014). Performance measurement
in public spending: evidence from a nonparametric approach. Romanian Journal
of Economic Forecasting, 3, 136�159.
Keuangan, K. (2021). Buku II - Nota Keuangan beserta
Anggaran Pendapatan dan Belanja Negara Tahun Anggaran 2022.
Luter, M., Indrocahyo, I., & Resti, I. L. V. (2019).
Pengaruh Belanja Infrastruktur terhadap Pertumbuhan Ekonomi Provinsi Nusa
Tenggara Timur. Jurnal Ekonomi Pembangunan, 17(2), 38�48.
Mardiasmo, M. B. A. (2021). Akuntansi Sektor Publik-Edisi
Terbaru. Penerbit Andi.
Merini, D. (2013). Analisis Efisiensi Pengeluaran
Pemerintah Sektor Publik di Kawasan Asia Tenggara: Aplikasi Data Envelopment
Analysis�. Universitas Brawijaya.
Negara, P. K. A. P. dan B. (2013). Kajian Evaluasi
Efektivitas dan Efisiensi Belanja Kementerian/Lembaga Tahun 2011: Belanja
Infrastuktur.
https://fiskal.kemenkeu.go.id/kajian/2012/06/29/140331171835037-kajian-evaluasi-efektivitas-dan-efisiensi-belanja-kementerianlembaga-tahun-2011-belanja-infrastuktur
Prasetyo, A. D., Mulyono, N. B., & Nugroho, L. I. (2018).
Local governments� expenditures efficiencies and determinants: the case of
Indonesia. International Journal of Trade and Global Markets, 11(3),
160�177. https://doi.org/10.1504/IJTGM.2018.095820
Ramadhan, M. (2019). Analyzing public infrastructure and
economic growth in Indonesia. International Journal of Scientific and
Technology Research, 8(11), 1144�1148.
Rambe, R. A. (2020). Inefisiensi Belanja Pemerintah Daerah di
Indonesia: Pendekatan DEA dan Regresi Logit. Indonesian Treasury Review:
Jurnal Perbendaharaan, Keuangan Negara Dan Kebijakan Publik, 5(4),
311�324. https://doi.org/10.33105/itrev.v5i4.175
Ram�rez, L. E. R., & Vargas, A. M. (2018).
Infraestructura p�blica y su importancia para el crecimiento econ�mico: El caso
de Oaxaca (M�xico). Ecos de Econom�a, 22(46), 4. DOI:10.17230/ecos.2018.46.1
Sukwika, T. (2018). Peran Pembangunan Infrastruktur terhadap
Ketimpangan Ekonomi Antarwilayah di Indonesia. Jurnal Wilayah Dan Lingkungan,
6(2), 115. https://doi.org/10.14710/jwl.6.2.115-130
