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2021
Village Public Expenditure Management in Indonesia:
Towards Better Budgeting and Spending Findings from a Village Public Expenditure Review
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1
ACKNOWLEDGEMENTS
This assessment was led by Anna O'Donnell (Senior Social Development Specialist, World Bank), with
guidance and support from the Ministry of Home Affairs.
Analysis for the public expenditure review was conducted by Ihsan Haerudin and Andrew Laing, with
support from Findi Firmanliansyah. The report was written by Ihsan Haerudin, Tara Moayed, Alexander
B Setiadji, and Shah Zaman Farahi.
The authors would like to thank the team from MoHA’s Directorate of Facilitation for Village Finance and
Asset Management and the Siskeudes team, without whom this report would not be possible.
The report has benefited from useful comments by peer reviewers: Bert Hofman, Kathleen Whimp,
Jurgen Rene Blum, and Ahmad Zaki Fahmi.
This report was made possible through funding from the Australian Government Department of Foreign
Affairs and Trade (DFAT).
2
CONTENTS
Abbreviations ........................................................................................................................................................ 4 Executive Summary ............................................................................................................................................... 5
Summary of Findings ................................................................................................................................................. 6 Future Directions ....................................................................................................................................................... 8
1. Introduction .................................................................................................................................................. 9 2. Village Financial Management ..................................................................................................................... 10
Village Resources Since Introduction of Village Law .................................................................................. 10 Village Revenue Sources ............................................................................................................................ 12 Village Financial Management Regulations ............................................................................................... 13 Village Financial Reporting ......................................................................................................................... 13
3. Methodology ............................................................................................................................................... 15 4. Part 1: Village Reporting Analysis ................................................................................................................ 17
Finding 1. Nearly 95% of villages across Indonesia use Siskeudes, while data from nearly 60% of villages is submitted into the National Consolidation Application. .................................................................................... 17 Finding 2. Most village reports included both original budget and actual expenditure data, and the majority passed basic data validity tests; however, poor district guidance may impact reliability of reports. ....................................... 18
5. Part 2: Village Expenditure Analysis ............................................................................................................ 19 Finding 3. The largest share of village spending is for public works (36%), followed by salary and operations (26%), housing/sanitation (7%), health (4%), and education (4%). .................................................................... 19 Finding 4. Across all regions, the majority of village expenditures (80%) go toward capital and goods and services. .............................................................................................................................................................. 21 Finding 5. Village priorities vary significantly across provinces. ......................................................................... 21 Finding 6. Since 2016, villages have increased spending on housing/sanitation, education, and health, while reducing their share of spending on public works and salary and operations. .................................................. 23 Finding 7. 97% of villages invest in stunting-related activities, at an average rate of 12%. Papua has the highest spending share with nearly 30%, followed by NTT and Gorontalo at nearly 20% ................................. 24
6. Part 3: Village Revenue Analysis .................................................................................................................. 27 Finding 8. Dana Desa makes up just over half of total village resources. ........................................................... 27 Finding 9. Share of village revenues from Dana Desa Ranges from 23% in Bali to 81% in Papua. ..................... 27 Finding 10. Village Own-Source Revenue contributes 3% to overall village revenues, with most of this revenue coming from villages in Java and Bali. ................................................................................................................. 29 Finding 11. Spending priorities shift significantly between different fund sources. .......................................... 31
7. Part 4: Village Budget Credibility Analysis ................................................................................................... 32 Finding 12. 75% of villages receive an A or B grade in a modified PEFA assessment of budget reliability. ................ 33 Finding 13. There is a large variation in budget reliability between regions, with Sulawesi showing the best performance and Java the poorest. .................................................................................................................... 34 Finding 14. Predictable resourcing leads to better budgets. .............................................................................. 36
8. Future Directions ......................................................................................................................................... 37 Key Lessons from 2019 ViPER ................................................................................................................................. 37
Annex A: Village Reporting .................................................................................................................................. 39 Annex B: Village Expenditures ............................................................................................................................. 40 Annex C: Village Revenues ................................................................................................................................... 42 Annex D: Village Budget Credibility ..................................................................................................................... 45 Annex E: Dana Desa Financial Flow Mechanism (Fiscal Year 2020 as per PMK 205/2019) ...................................................... 47
3
List of Figures
Figure 1: Village revenues 2013 to 2019 (in trillion IDR, nominal) .............................................................................. 11
Figure 2: Village government expenditure as a share of national public spending (in trillion IDR)............................. 11
Figure 3: Villages Using Siskeudes and Report Availability in Siskeudes National Consolidation Application ................................. 16
Figure 4: Reporting completeness ............................................................................................................................... 18
Figure 5: Cut and paste test on revenue and expenditure reports ............................................................................. 18
Figure 6: Frequency of unreliable (Rev) reports by district .............................................................................................. 18
Figure 7: Village Expenditure by Sub-Bidang (2019) .................................................................................................... 20
Figure 8: Village spending by economic classification ................................................................................................. 21
Figure 9: Top five spending priorities by province....................................................................................................... 22
Figure 10: Village expenditure priority shift across major sub-Bidang (2016 and 2019) ............................................ 23
Figure 11: Percent of Villages With Stunting-Related Expenditures and Frequency Distribution by Spending ........................... 25
Figure 12: Village Stunting Expenditures by Province ................................................................................................. 26
Figure 13: Village Revenue by Source .......................................................................................................................... 27
Figure 14: Village Revenue Composition by Province ................................................................................................. 28
Figure 15: Village Own-Source Revenue Breakdown (2019) ....................................................................................... 29
Figure 16: PADes trend in nominal terms and as a share of total village revenue (2013-2019) ................................. 29
Figure 17: Village Own-Source Revenues by Province ................................................................................................ 30
Figure 18: Top Village Expenditure Categories by Source of Fund .............................................................................. 31
Figure 19: Modified PEFA Grades in Key Budget Reliability Indicators for 25,430 Villages ......................................... 33
Figure 20: Average Village PEFA Scores ....................................................................................................................... 33
Figure 21: PEFA Grades by Region Across 25,430 Villages - Count and Rate .............................................................. 34
Figure 22: Average Village PEFA Grade by Province for 25,430 Villages ..................................................................... 35
Figure 23: Distribution of Aggregate Revenue and Expenditure Scores as Percentage of Budget to Actuals ............................. 36
List of Tables
Table 1: Village revenue trends before and after the Village Law (in trillion IDR, nominal) ....................................... 10
Table 2: Description of Village Revenue Sources ......................................................................................................... 12
Table 3: Village Chart of Accounts Summary ............................................................................................................... 14
Table 4: Village-Level Stunting Priority Interventions ................................................................................................. 24
Table 5: Average and median of village spending on stunting-related interventions ................................................. 25
Table 6: Villages Using Siskeudes and Report Availability in Siskeudes National Consolidation Application .......................... 39
Table 7: Village Spending by Functional Classification (GFS) ....................................................................................... 40
Table 8: Village Spending by Economic Classification ................................................................................................. 40
Table 9: Village Spending by Economic Classification by Region ................................................................................. 40
Table 10: National estimates of Village Expenditure by Sub-Bidang & Infrastructure Content, 2019 ........................ 41
Table 11: Village Revenues by Fund Source by Province ............................................................................................. 42
Table 12: Top Village Expenditure Categories by Source of Fund ............................................................................... 43
Table 13: Financing contribution of multiple funds across sub-bidang ....................................................................... 44
Table 14: Average PEFA Scores by Province ................................................................................................................ 45
Table 15: PEFA Scoring Tables ..................................................................................................................................... 46
4
ABBREVIATIONS
ADD Village Fund Allocation (Alokasi Dana Desa)
APBDes Village Budget (Anggaran Pendapatan dan Belanja Desa)
BH-PDRD Shared Tax and Levies from District Government
BPD Village Council (Badan Permusyawaratan Desa)
BPK Audit Board of Indonesia (Badan Pemeriksa Keuangan)
BPS Statistics Indonesia (Badan Pusat Statistik)
BumDes Village-Owned Enterprise (Badan Usaha Milik Desa)
DAK Special Allocation Fund (Dana Alokasi Khusus)
DD Dana Desa (Village Fund)
DIY Daerah Istimewa Yogyakarta
ECD Early Childhood Development
FY Fiscal Year
GAKIN Poor Households (Keluarga Miskin)
GFS Government Finance Statistics
IDR Indonesian Rupiah
MoF Ministry of Finance
MoHA Ministry of Home Affairs
NGO Non-governmental Organization
NTB West Nusa Tenggara (Nusa Tenggara Barat)
NTT East Nusa Tenggara (Nusa Tenggara Timur)
OMSPAN Online Monitoring Application for the State Treasury and Budget System
OSR Village Own-Source Revenue (PADes)
PADes Village Own Source Revenue
PAUD Early Childhood Education Centre
PEFA Public Expenditure and Financial Accountability
PER Public Expenditure Review
Permendagri Minister of Home Affairs Regulation (Peraturan Menteri Dalam Negeri)
Polindes Village Maternity Hut (Pondok Bersalin Desa)
Posyandu Integrated Health Post (Pos Pelayanan Terpadu)
PP Government Regulation (Peraturan Pemerintah)
Puskesmas Community Health Clinics (Pusat Kesehatan Masyarakat)
RT/RW Neighborhood and Hamlet Heads
RTLH Unhealthy Households (Rumah Tidak Layak Huni)
Siskeudes Village Financial System (Sistem Keuangan Desa)
StraNas Stunting National Strategy to Accelerate Stunting Prevention
5
EXECUTIVE SUMMARY
Since the Government of Indonesia began implementation of the Village Law, more than IDR 547 trillion
(US$ 38 billion) has been transferred to Indonesia's nearly 75,000 villages. In 2020, intergovernmental
transfers to villages constituted 10% of subnational fiscal transfers, playing an important role in supporting
complementary activities for frontline services. The Village Law reaches 176 million people in Indonesia,
including 117 million people in rural areas, who constitute most of the country's poor. Village funds can
reach Indonesia's rural poor with improved access to infrastructure and basic services; help to reduce
stunting and improve village health, nutrition, and early childhood education; empower women, youth,
and vulnerable groups; provide "last-mile" rural connectivity; and strengthen local natural resource
management, disaster response, and climate resilience.
In 2019, for the first time, the Government of Indonesia began collecting financial data on how village
governments across the country were using their village funds. This data allows the government to
analyze village priorities, expenditures, revenues, and budget credibility. Prior to the implementation of a
unified village chart of accounts in 2018 and the roll-out of the village financial management system
(Siskeudes) National Consolidation Application, the government was not able to systematically access
village financial data. The data collected before 2019 only covered village activities under the Dana Desa
grant, transferred by the central government, accounting for only half of total village resources.
This report represents the largest assessment of village spending since the enactment of the Village
Law. The findings presented here are based on a public expenditure analysis of financial data from 45,625
rural villages across 248 districts and 33 provinces.1 This represents over 58% of all villages, although
coverage of villages by province varies between 5% in Papua Barat to 100% in Bali.2
The objective of this report is to provide an initial assessment of Indonesia's village spending and
budget credibility, which will in turn strengthen the ability of the Government of Indonesia and village
administrations to solve the pressing problems facing rural communities. The report is structured into
four parts: analysis of village reporting, expenditures, revenues, and performance. Each section aims to
answer the following questions:
• Reporting: Are villages submitting financial reports, and are reports credible?
• Expenditures: What are village spending priorities, how much do they spend, and how much do priorities vary across villages?
• Revenues: What is the composition of village revenues, how does it vary across villages, and how are villages spending revenues from different sources?
• Budget Credibility: Are village budgets credible, and are villages spending according to their plans? (Based on an adapted methodology from the PEFA framework on Budget Reliability)
1 33 provinces have rural villages in Indonesia. 2 Villages for the PER were not randomly selected, by include all villages for which financial data had been submitted into MOHA’s Siskeudes National Consolidation Application.
6
Summary of Findings
Part 1: Village Reporting Analysis
Finding 1. Nearly 95% of villages across Indonesia use Siskeudes, while data from nearly 60% of villages is submitted into the National Consolidation Application by district governments. The likely reasons for the gap in reporting are the lack of sanctions for districts that do not submit consolidated reports, limited capacity of district staff to use Siskeudes, and internet access and reliability.
Finding 2. The majority of village reports included both the original budget and actual expenditure data. Most village reports also pass basic data validity tests; however, poor district guidance may impact reliability of reports. While 92% of reporting village in FY 2019 submitted both original budgets and actuals, gaps remain in other data points, including revised budgets, outputs data, assets, and liabilities. Distribution analysis shows that villages with data validity errors are clustered in the same districts, suggesting poor policies or guidance from the district may impact village performance.
Part 2: Village Expenditure Analysis
Finding 3. The largest share of village spending is for public works (36%), followed by salary and operations (26%), housing/sanitation (7%), health (4%), and education (4%). The majority of public works expenditures were for construction, rehabilitation, and maintenance of roads and bridges. Village spending on salary and operations was 4% below the 30% limit set by national regulation. While housing and sanitation composed the third-largest category of spending, within this category, improved access to water only amounted to 1.7% of village spending, despite the major gap in access to potable water in Indonesia.
Finding 4. Across all regions, the majority of village expenditures (80%) go toward capital and goods and services. This pattern is consistent across all regions. Expenditure on personnel averages at 19% nationally, ranging from 16% in Papua to 20% in Java.
Finding 5. Village priorities vary significantly across provinces. Spending on public works ranges between 50% of total spending in Bengkulu and Banten to less than 7% in Papua Barat. Spending on housing and sanitation varies from a high of over 20% in Gorontalo and Papua Barat to less than 5% in Banten, Riau, and Yogyakarta.
Finding 6. Since 2016, villages have increased spending on housing/sanitation, education, and health, while reducing their share of spending on public works and salary and operations. Extrapolating spending shares to nominal spending for all villages suggests this represents a 130% increase in education spending and an 85% increase in housing/Sanitation, health, and Agriculture.
Finding 7. 97% of villages invest in stunting-related activities, at an average rate of 12%. Villages in most provinces with high stunting prevalence spent a relatively large share of their budget for stunting-related interventions. Papua has the highest share with nearly 30%, followed by NTT and Gorontalo at nearly 20%.
7
Part 3: Village Revenue Analysis
Finding 8. Dana Desa makes up just over half of total village resources. Despite the fact that most consolidated analysis of village revenues focused only on Dana Desa until 2019, central government transfers account for only half of total village revenues. However, inter-government transfers (including district and provincial transfers) account for nearly 97% of all village revenues.
Finding 9. Share of village revenues from Dana Desa Ranges from 23% in Bali to 81% in Papua. The Dana Desa is not a per capita allocation. Less populated areas with higher poverty rates receive higher per capita allocations. However, it is important to note that even in poor and lagging regions, villages still have significant revenues from other sources – highlighting the need for a holistic analysis of village spending.
Finding 10. Village Own-Source Revenue (PADes) contributes only 3% to overall village revenues, with most of this revenue coming from villages in Java and Bali. Even though most villages projected to raise own-source revenue in their original budget, 61% of all villages could not generate PADes. Between 2013 and 2019, PADes has declined both as a share of total revenues and nominally. The increasing inter-governmental transfers may disincentivize village governments from improving their PADes generation.
Finding 11. Spending priorities shift significantly between different fund sources. Currently, the central government and Ministry of Finance exclusively analyze village spending under Dana Desa. However, Dana Desa expenditures alone do not provide a complete picture of village spending and prioritization.
Part 4: Village Budget Credibility Analysis
Finding 12. 75% of villages receive an A or B grade in a modified PEFA assessment of village budget reliability, indicating high budget reliability and financial management capacity. Less than one-fifth of villages scored a C, and only 6% received a D score.
Finding 13. There is a large variation in budget reliability between regions. Over 70% of villages in Sulawesi received A and B grades, compared to less than 40% in Java. The five provinces with the highest share of villages with A and B grades are located in Sulawesi, Sumatra, and Papua.
Finding 14. Predictable resourcing leads to better budgets. Analysis of the distribution of average village expenditure and revenue scores shows that villages can develop credible budgets when village revenues are predictable. The revealed correlation between the budget revenue and expenditure execution performance aligns with Public Finance Theory, highlighting the importance of predictable resourcing.
8
Future Directions
The availability of village financial data provides the government with a unique opportunity for
evidence-based policymaking, targeted support to villages, and performance-based incentives to
villages and districts. This report serves as a first assessment of data from the Siskeudes National
Consolidation Application, but it also aims to demonstrate the opportunity to use village financial data to
measure the impact of village funds and inform future policy direction. The 2019 ViPER findings provide
some relevant policy indications for the government and its partners that support Village Law
implementation.
1. Improving the availability of complete consolidated village financial data will require better incentives
to districts and clear sanctions for non-compliance with reporting requirements.
2. Strengthening the financial performance of villages requires better support and monitoring of both
villages and districts.
3. Building a local-level interface to share information back to districts and villages can improve data
quality and support local planning.
4. Leveraging financial data for evidence-based policymaking requires a holistic analysis of all village
resources, not only Dana Desa.
5. Provincial spending patterns can inform sectoral technical assistance and allow for more strategic
targeting of village-level support by line ministries and directorates.
6. Institutionalizing village expenditure analysis, such as the ViPER methodology in this report, will
support policymaking for the Ministry of Home Affairs, the Ministry of Finance, and other government
institutions that focus on poverty reduction and frontline service delivery.
9
1. INTRODUCTION
Since 1999, Indonesia has undertaken an administrative and fiscal decentralization from the national
to district, and more recently, to the village level. This has led district and village governments to have
substantial financial resources and authority to oversee and deliver basic services, including health,
education, and infrastructure development.
In 2014, Indonesia's Village Law (No. 6/2014) ushered in a new chapter in the country's decentralization and rural development. One of the largest village decentralization programs globally, the Village Law substantially increases the autonomy, responsibilities, and funding transferred to Indonesia's nearly 75,000 villages, building on Indonesia's rich history of community-driven development. The Law states that the objective of village development is to improve villagers' welfare and quality of life and to alleviate poverty through fulfillment of basic needs, provision of village infrastructure, development of local economic potential, and sustainable utilization of natural resources and environment. The Village Law is a key instrument of the Government's National Medium-Term Development Plan (RPJMN) 2020 to 2024 to deliver basic services, increase accessibility, and contribute to national economic growth.
Since the Government of Indonesia began implementation of the Village Law, more than IDR 547 trillion (US$ 38 billion) has been transferred to Indonesia's nearly 75,000 villages.3 Despite the challenges, in the first year of Village Law implementation, the government successfully disbursed nearly 95% of village funds through inter-governmental transfer mechanisms.4 Over the next four years, transfers to villages more than doubled. During this period, the government introduced a new system for village public financial management, including a village-specific chart of accounts. The new classification system was integrated into a digital village financial management system (Siskeudes), which has helped improve and simplify the monitoring of village budgets and expenditures across Indonesia's nearly 75,000 villages.
In a relatively short time, the government has established the legal and regulatory framework for the Village Law, significantly increased transfers to the village level, mobilized large-scale capacity support, and upgraded policies and systems to monitor village performance. The government has allocated Dana Desa across villages based on a pro-poor formula, required villages to report on outputs in addition to expenditures, and is paying increasing attention to improve the quality of village spending. More than 25,000 facilitators are deployed by the Ministry of Village to support implementation, including technical infrastructure support. There has been significant and increasing high-level government attention on villages and Village Law implementation, including multiple cabinet and inter-ministerial meetings, presidential visits, and focus on Village Law implementation and its impact.
The Village Law reaches 176 million people in Indonesia, including 117 million people in rural areas, constituting
most of the country's poor.5 Village funds can reach Indonesia's rural poor with improved access to infrastructure
and basic services; help to reduce stunting and improve village health, nutrition, and early childhood education;
empower women, youth, and vulnerable groups; provide "last-mile" rural connectivity; and strengthen local
natural resource management, disaster management, and climate resilience.
As of 2019, with the adoption of the Siskeudes National Consolidation Application, the Government of
Indonesia has access to an unprecedented level of village financial information, including the activities
villages are prioritizing in their plans, village expenditures, and village revenues. With improved data and
3 World Bank estimation 4 Hans Antlöv, Anna Wetterberg, Leni Dharmawan, Village Governance, Community Life, and the 2014 Village Law in Indonesia, August 2016 5 World Bank, No One Left Behind, 2020
10
analysis of financial and non-financial data, the government will be able to better monitor and assess the
impact of village funds on national development objectives.
The objective of this report is two-fold: first, to provide a broad analysis of village budgets, and second
to provide a proof-of-concept for how village financial data can be used to assess village budget
reliability. This report summarizes findings from a public expenditure analysis based on 2019 village
financial data from 45,625 rural villages across 248 districts and 33 provinces.6 This represents the largest
assessment of village spending in Indonesia since the enactment of the Village Law.
2. VILLAGE FINANCIAL MANAGEMENT
Village Resources Since Introduction of Village Law
Between 2014 and 2019, village governments saw their budgets increase by 360 percent. The increase
in funding was driven, in large part, by the introduction of the Village Law and the Dana Desa inter-
governmental transfer in 2015. Since then, transfers to villages have been steadily increasing year-over-
year (Table 1 and Figure 1). In 2019, the Government of Indonesia transferred an average of nearly
IDR 1.6 billion (over US$107,000) to each village. The total value of fiscal transfers to villages was US$8.1
billion in 2019, 4.3% of the national budget, and 0.7% of the GDP (Figure 2).
Table 1: Village revenue trends before and after the Village Law (in trillion IDR, nominal) 7
2013 2014 2015 2016 2017 2018 2019
Village Own Source Revenue (PADes) 4.1 4.2 4.2 3.5 3.1 3.5 2.9
Transfer Revenue 17.5 21.3 47.2 78.3 96.7 98.0 113.4
Dana Desa (DD) - - 19.5 45.6 57.6 56.9 67.3
Shared Tax and Levies from District Govt (BH-PDRD) 0.6 0.9 1.7 2.0 2.5 3.0 3.6
Alokasi Dana Desa (ADD) 8.1 10.2 22.8 26.4 30.5 31.8 35.2
Financial Assistance (from Central/Province/District) 8.8 10.1 3.2 4.3 6.1 6.2 7.3
Other Revenue 1.0 1.1 0.6 0.5 0.5 0.7 1.2
Total Village Revenue IDR (trillions) 22.6 26.7 52.1 82.3 100.2 102.1 117.4
Total Village Revenue USD (billions) 1.6 1.8 3.6 5.7 6.9 7.0 8.1
6 33 provinces have rural villages in Indonesia. 7 The data for 2015-2019 is based on realized/actual revenue (BPS). The BPS does not record realized DD as separate item from realized bantuan keuangan in 2015. The DD data of 2015 in the table use Ministry of Finance (MoF) estimates of 93.8% of disbursed IDR 20.8 trillion of DD allocation, which in turn adjusts BPS data of bantuan keuangan of respected year from IDR 22.7 trillion to become IDR 3.2 trillion. The DD amount of 2016 , 2017, 2019 are BPS data which show smaller figures compared to MoF data on DD allocation at IDR 47 trillion (2016), IDR 60 trillion (2017), 60 trillion (2018), and 70 trillion (2019). The BPS estimates a smaller amount of ADD and BH-PDRD compared to MoF estimates. For ADD, MoF estimates at IDR 33.8 trillion, IDR 35,5 trillion, and IDR 34.1 trillion in 2015, 2016, and 2017 respectively, while for BH-PDRD the MoF estimates at 2.7 trillion, 2.8 trillion, and 3.2 trillion. The USD figure is based on exchange rate of 1 USD = 14.500 IDR
11
Figure 1: Village revenues 2013 to 2019 (in trillion IDR, nominal)
Figure 2: Village government expenditure as a share of national public spending (in trillion IDR)8
8 World Bank calculation based on LKPP (CG expenditure), DG Fiscal Balance Database (SNG expenditure), and BPS’s Financial Statistics of Village Government, multiple years. Village govt expenditure data of FY-2019 is provisional data.
0
20
40
60
80
100
120
2013 2014 2015 2016 2017 2018 2019
DD ADD Financial Assistance BH-PDRD PADes Other Revenue
1.2% 1.3%
2.4%
3.8%
4.3%
4.0%4.3%
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
-
500.0
1,000.0
1,500.0
2,000.0
2,500.0
3,000.0
2013 2014 2015 2016 2017 2018 2019*
Village Govt Expenditure
Subnational Govt Expenditure (excluding transfer to other SNGs and villages)
Central Govt Expenditure (excluding transfer to SNGs and villages)
Share of Village Govt Expenditure (%, right axis)
12
Village Revenue Sources
Reporting on village resources to date has almost exclusively focused on Dana Desa spending, which
only makes up about half of total village revenues. However, village budgets consist of three revenue
categories: inter-governmental transfers, village own-source revenue, and other revenue. Table 2
describes these revenue sources. The breakdown of village revenues is further analyzed in Part 3.
Table 2: Description of Village Revenue Sources
Village Revenue Source Description
Transfer Revenue Revenue from inter-governmental transfers as listed below.
Dana Desa (DD)
Dana Desa ("village fund") is first mentioned in government regulation (PP) No. 60/2014 on Dana Desa to refer to the mandate of the Village Law on the transfer to villages from the central government budget. The Village Law states that this transfer should be 10% of, and in addition to, transfers to the regions (see Article 72 of the Village Law). Currently, the Dana Desa allocation formula includes a. Basic allocation (65%) distributed equally to all villages; b. Affirmative allocation (1%) given to lagging and extremely lagging villages; c. Performance allocation (3%) for top performing 10% of villages in each district; d. Formula allocation (31%) based on: population (10%), poverty rate (40%), village area (20%), and accessibility (30%).
Alokasi Dana Desa (ADD)
Alokasi Dana Desa ("village allocation fund") is a block grant transfer from the district government to village governments. ADD was established before the Village Law (Permendagri 37/2007). However, under the Village Law, a new provision requires districts to allocate 10% of balancing funds, excluding earmarked funds (such as Dana Alokasi Khusus/DAK), to villages.
Regional Tax Revenue Sharing and Regional Retribution (BH-PDRD)
BH-PDRD is local taxes and levies shared between districts and villages. Similar to ADD, BH-PDRD was established before the Village Law was enacted. However, districts must transfer at least 10% of district taxes and levies to villages under the Village Law.
Financial Assistance (Bankeu)
Financial Assistance constitutes transfers from central, provincial, and/or district governments that may be ad-hoc or based on local regulations and is additional to DD, ADD, and BH-PDRD.
Village Own-Source Revenue (PADes)
Village own-source revenue is generated directly by the village, including returns from village assets, investments, and community contributions. Village assets revenue includes rent from village land and revenue from village-owned enterprises (BumDes).
Other Revenue Other revenues include grants and contributions given to villages by third parties, including NGOs, the private sector, and other contributors.
13
Village Financial Management Regulations
In 2018, the Government of Indonesia updated the village public financial management system through
Permendagri 20/2018, which significantly improved village budget systems. The regulation provides three
functional classification levels for village expenditures. These are shown in Table 3.
a. Bidang: Based on village authorities as described under the Village Law.
b. Sub-Bidang: This classification was introduced in the new regulation. The Sub-Bidang is
harmonized with sectoral categories (Urusan) used by other levels of government. The village
expenditure can be classified and aggregated sectorally for education, health, public works, and
other functional sectors.
c. Activity: Activity-level classification was also introduced in the new regulation. This new
classification level allows village expenditures to be aggregated at a much more detailed level,
which was not previously possible.
Village Financial Reporting
Since 2019, the Ministry of Home Affairs has begun the full roll-out of the Siskeudes National
Consolidation Application to unify different reporting requirements and ensure the availability of
complete village financial data. Nearly all villages in Indonesia are now using Siskeudes to manage their
budget and expenditures. The new village chart of accounts has been integrated into Siskeudes and has
helped standardize budget classification and enable automated analysis of village financial data from 2019
onward.
Previously, consolidated village financial reports were only available for Dana Desa. Villages report all
budgets and expenditures to the district government, who then submit Dana Desa reports to the Ministry
of Finance (MoF) through OMSPAN (Online Monitoring for State Treasury and Budget System). OMSPAN
is a system used by MoF to monitor the budget and disbursement execution by all government entities,
including districts. This is the data used for verification of Dana Desa tranche transfers. The government
has developed a mechanism to allow districts and villages to use Siskeudes to produce the Dana Desa
reports that the district can then upload into OMSPAN. Until 2019, the only consolidated village financial
data available were Dana Desa reports through this system.
Villages must submit complete financial reports to the district government; however, until the
Siskeudes National Consolidation Application roll-out, these reports could not be consolidated and used
for meaningful analytics. Districts required all villages to submit their financial reports to be annexed to
district financial reports audited by Supreme Audit Board (BPK). Audited District Financial reports are
submitted to the District Parliament (DPRD) for accountability evaluation. These reports are still submitted
for each village and not consolidated. These reports may be attached as hard copies or in PDF format and
cannot be analyzed and consolidated. Some districts have already replaced this process by using
Siskeudes, but there is an opportunity to support more districts to adopt this practice, reduce reporting
requirements on villages, and streamline the overall data collection process.
14
Table 3: Village Chart of Accounts Summary
Bidang Sub-Bidang Summary of Select Activities
GO
VER
NM
ENT
AD
MIN
ISTR
ATI
ON
Provision of Fixed Income & Allowances, and General Village Government Operations
• Wages and salaries and social security for Village Heads and Apparat • Village government operations (equipment, utilities, allowances, etc.) • Allowances and operational cost for Village Council (BPD) and RT/RW heads
Village Administration, Facilities, and Infrastructure • Provision of fixed assets for village office • Construction, rehabilitation, maintenance of village office infrastructure
Civil Registration, Statistics, and Archives • Provision and community mobilization for civil registration
• Data collection and management, participatory mapping, and analysis of poverty
Village Planning, Budgeting, Accounting, Reporting • Village deliberations, such as MusDes and planning, including RPJMDes, APBDes
• Village Information System development
Land Administration • Land certification, registration, and conflict mediation
• Property tax administration (PBB) and village boundary development/determination
VIL
LAG
E D
EVEL
OPM
ENT
Education • ECD: operations, teacher allowances, equipment, construction, maintenance • Support and scholarships for students from poor households
Health • Operation, construction, maintenance of village health posts and Posyandu services • Community health education and training
Public Works and Spatial Planning • Construction and maintenance of village roads, bridges, community centers • Village social mapping and spatial planning
Housing/Sanitation • Construction and maintenance of village water and sanitation infrastructure • Construction and maintenance of parks and playgrounds
Forestry and the Environment • Environmental management and community awareness-raising
Transportation, Communication, and Information • Village signs, posters, public information material
Energy and Mineral Resources • Development and maintenance of alternative energy facilities and infrastructure
Tourism • Village-level tourism development
COM
MU
NIT
Y
DEV
ELO
PMEN
T Social Order and Community Protection • Village security posts, local disaster preparedness, village Satlinmas capacity building
Culture and Religion • Arts, cultural, and religious festivals, and management of cultural infrastructure
Youth and Sports • Support for infrastructure and operations of youth organization, sports, and clubs
Community Organization Empowerment • Development and operation of customary village organizations, such as PKK
COM
MU
NIT
Y EM
POW
ERM
ENT
Marine and Fisheries • Support for village fisheries, including construction of village-owned Karamba / fisheries ponds /
small river fishing ports.
• Training and technical assistance on fisheries and introduction of new technology
Agriculture and Livestock • Strengthening village-level food securities, including development of village granaries
• Maintenance of tertiary irrigation infrastructure • Support for agriculture and livestock programs, including input provision and training
Capacity Building for Village Apparatus • Training and capacity building for village head, officials, and BPD
Women's Empowerment, Family Planning, and Child Protection
• Training and community mobilization on women's empowerment, child protection, and support for people with disabilities
Coops, Micro, Small and Medium Enterprises • Development of micro, small, and medium enterprise infrastructure and cooperatives
Investment • Establishment and support for BumDes
Trade and Industry • Development and maintenance of village markets
DISA
STER
RESP
ON
SE Disaster Response • Disaster response
Emergency • Emergency
Contingency • Contingency
15
3. METHODOLOGY
The village public expenditure analysis, on which this report is based, is the largest assessment of village spending in Indonesia since the enactment of the Village Law. The data utilized to undertake this analysis covers 43,675 out of 74,957 villages in Indonesia, 58% of all villages. It presents data from villages across all 33 provinces and 287 districts out of 434 districts with rural villages. The analysis uses financial data from FY 2019 of all 43,675 villages reported in the system. The selection is not based on any random sampling method. The specific coverage and breakdown of 2019 Siskeudes data is further provided in Part 1 and shown in Figure 3. A complete breakdown of data coverage can be found in Annex A.
This analysis aims to assess the achievements and challenges of Indonesia's village fiscal performance in different dimensions and resolutions, which will, in turn, strengthen the ability of the Government of Indonesia and village administrations to solve the pressing problems facing the government and citizens. The report is structured into four parts: analysis of village reporting, expenditures, revenues, and budget credibility. Each section aims to answer the following questions:
1. Reporting: Are villages submitting financial reports, and are reports credible?
1. Expenditures: What are village spending priorities, how much do they spend, and how do priorities vary across villages?
2. Revenues: What is the composition of village revenues, how does it vary across villages, and how are villages spending revenues from different sources?
3. Budget Credibility: Are village budgets credible, and are villages spending according to their plans?
Part 1 of the report covers the current status of village financial reporting, both coverage and data credibility. The coverage compares the percentage of villages using Siskeudes and the number of districts reporting consolidated village data. All 43,675 village reports for FY 2019 are analyzed in this section. In this section, a "Cut and Paste" test was performed on data to identify whether villages had copied original budget data in place of actual expenditure data. The exercise was a simple test to assess the validity of actuals.
Part 2 summarizes village spending, compares 2019 spending with a public expenditure analysis of village funds conducted in 2016, and specifically analyses village spending related to stunting prevention. Findings are based on FY 2019 village expenditure realization reports from 36,242 villages. In Part 2 of the report, expenditure categories are based on village revenue realization, broken down by sub-Bidang classification used by villages are per village financial management regulation. However, expenditures were also cross-coded at the activity level with GFS standards (see Annex B) to conduct the modified PEFA analysis calculations. Expenditure analysis based on economic classification is also provided under finding 6, which is already embedded as part of the village chart of accounts.
Part 3 summarizes trends related to village revenues. A description of each revenue source and different inter-governmental transfers to villages is provided in Table 2. The analysis in Part 3 of this report is based on an analysis of 36,929 villages that had submitted complete revenue data for FY 2019.
Part 4 presents results from a modified PEFA assessment to review village budget reliability by comparing original budgets and expenditures. The Modified PEFA budget reliability assessment undertaken for villages is adapted from the 2016 PEFA Framework, using five standard PEFA indicators on budget reliability. The analysis has adjusted the time horizon of the analysis to one year, as at this time, village data is only available for FY 2019. The analysis in this section covers 33,220 villages that had
16
provided original and actual data for revenues and expenditures. Methodological details on this component are provided in Part 4, and the breakdown of scoring for each dimension is in Annex D.
The analysis is limited in some areas due to the lack of data availability. In terms of coverage, Figure 3 shows the coverage of villages by provinces (yellow bars). Findings from five provinces represent less than 50% of villages, including Papua Bara, Papua, Sulawesi Tenggara, Kamilantan Utara, and NTT. Therefore, future analysis will be required once data coverage for these provinces increases to ensure the accuracy of patterns identified in the current analysis. There are also limitations in the scope of data availability, including district budgets and output data. This prevents meaningful analysis on economic efficiency, complementarity of village and district spending, and reliability of district transfers.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Bali
Kep. Riau
Bengkulu
Kalimantan Selatan
Jambi
Riau
Kalimantan Barat
Gorontalo
Kalimantan Timur
Sumatera Barat
DIY
Sulawesi Tengah
Kep Babel
Sulawesi Barat
Jawa Barat
Jawa Tengah
Jawa Timur
Maluku
Sulawesi Utara
NTB
Kalimantan Tengah
National Average
Sulawesi Selatan
Maluku Utara
Banten
Lampung
Sumatera Selatan
Sumatera Utara
Aceh
NTT
Kalimantan Utara
Sulawesi Tenggara
Papua
Papua Barat
% of Villages Using Siskeudes % of Consolidated Data Submission
Figure 3: Villages Using Siskeudes and Report Availability in Siskeudes National Consolidation Application
17
4. PART 1: VILLAGE REPORTING ANALYSIS
Finding 1. Nearly 95% of villages across Indonesia use Siskeudes, while data from nearly 60% of
villages is submitted into the National Consolidation Application.
With the development of Siskeudes, the Government of Indonesia now has access to an unprecedented
level of village financial information. Critically, because of a unified village chart of accounts, budgets and
expenditures can be aggregated and compared across villages. Siskeudes is the only means by which the
complete village budget (APBDes) is reported.
Across Indonesia, nearly 95% of villages are using Siskeudes as their financial management system.
Most provinces have nearly full coverage of Siskeudes, with only Papua, Papua Barat, Sumatera Barat, and
Kalimantan Utara falling below the national average of 95% coverage. Many villages use an offline version
of Siskeudes due to limitations with internet access and reliability. For villages using Siskeudes offline,
they submit financial reports to districts, who then submit them to the National Consolidation Application.
For the 2019 fiscal year, village financial reports from 58% of villages were available in the Siskeudes
National Consolidation Application. The data covers 100% of reporting provinces, 66% of reporting
districts, and 61% of reporting kecamatan. The coverage by province varies between 5 percent for Papua
Barat to nearly 100% in more than half of provinces (Figure 10). 20 out of 33 provinces have village
coverage above the national average of 58%. Four provinces remain below 25% village coverage (Papua,
Papua Barat, Sultra, and Kalut).
Figure 3 shows the gap between the adoption of Siskeudes by villages and the availability of financial
reports in the National Consolidation Application. While Siskeudes can support village financial
management, there is also an opportunity to improve district capacity to consolidate and report
comprehensive village financial data to MOHA.
The likely reasons for the gap in reporting are the lack of sanctions for districts that do not submit
consolidated reports, limited capacity of district staff to use Siskeudes, and internet access and
reliability. As discussed in section 2.4, Dana Desa tranche transfers are based entirely on financial data on
Dana Desa itself. Therefore, while many districts submit the data into the Siskeudes National
Consolidation Application, the regulatory requirement (see Permendagri 20/2018) is still weak and lacks
clear sanctions for districts that do not meet reporting requirements. In some cases, districts also have
difficulties managing the Siskeudes consolidated database using SQL due to lack of staff capacity;
however, as MOHA scales up district training for Siskeudes, the consolidated reporting should increase.
Finally, limited access to the online Siskeudes platform can create challenges for both villages and districts,
as the report sharing cannot be automated for villages using Siskeudes offline, which creates challenges
for districts with poor internet coverage and reliability.
18
Finding 2. Most village reports included both original budget and actual expenditure data, and the
majority passed basic data validity tests; however, poor district guidance may impact reliability of reports.
Most reporting villages (91.5%) submitted both original
budgets and actual expenditures for FY 2019 into Siskeudes.
This number is particularly impressive as 2019 was the first
year that most villages were reporting based on the new
financial management regulation and against the updated
village chart of accounts.
A "Cut and Paste" test of village revenues and expenditures
was performed to identify whether villages had copied original
budget data in place of actual expenditure data. The exercise
was a simple test to assess the validity of actuals. Less than 2%
of villages had identical budgets to actual expenditures, and
under 4% had identical budgets to actual revenues.
The distribution of invalid revenues by frequency (Figure 6)
shows that district policies may play a factor in the
reliability of village budgeting. This breakdown of findings
down to the district level shows that villages across each
district generally have similar budget reliability. Figure 6
shows that most districts had zero villages with unreliable
reports, while 110 districts had over 90% of villages with
unreliable reports.
However, there were gaps in village reports, particularly for
submission of revised budgets, output data, village assets,
and liabilities. Villages may need more support and
incentives to complete and submit these reports.
Budget and Expenditures
No Expenditure Data
No Original Budget
91.5%
of analyzed reports included budget and
expenditure data
Reliable Unreliable
96%
of villages passed revenue data test
98%
of villages passed expenditure data test
Figure 5: Cut and paste test on
revenue and expenditure reports
Figure 6: Frequency of unreliable (Rev) reports by district
0
50
100
150
200
Nu
mb
er o
f D
istr
icts
Percentage of Unreliable Reports
Figure 4: Reporting completeness
19
5. PART 2: VILLAGE EXPENDITURE ANALYSIS
Finding 3. The largest share of village spending is for public works (36%), followed by salary and
operations (26%), housing/sanitation (7%), health (4%), and education (4%).
New nomenclature for village financial management has allowed the Government of Indonesia to
analyze village budgets based on priority investment areas. Expenditure analysis based on sub-Bidang
describes the purpose of spending, rather than economic classifications. Table 3 provides more detail on
the activities that fall under each sub-Bidang.
The largest share of village spending was on public works and spatial planning category, which
constituted over one-third of all village expenditures (36%). The majority of these expenditures were for
construction, rehabilitation, and maintenance of roads, bridges, and road-related infrastructure (such as
culverts, road drainage, and ditches). This category also includes other infrastructure spending, such as
community centers, cemeteries, and village-owned historic sites. Infrastructure content makes up 90
percent of the share in this spending category. Non-infrastructure spending (which makes up 10% of this
component), such as spatial planning and social maps, is also categorized here.
Villages spent less than 26% of their total spending on Village Apparatus Salary and Operations, 4% below
the 30% cap set by the central government in 2019. This component consists of the wages and salaries for
village government officials, including the village head; allowances for village council representatives (BPD);
allowances for neighborhood and hamlet heads (RT/RW); operation costs for the village government and
BPD – including office supplies, office equipment, uniforms, and utilities such as electricity, internet, and
telephone. In 2019, the central government mandated that villages only spend a maximum of 30% of total
spending to finance salaries and allowances for village government officials and allowances and operational
cost of the village council (BPD).9 However, the average village spending on Village Apparatus Salary and
Operations was more than 4% below the limit set by government regulation.
The third-largest spending category was housing and sanitation at 7% of total village spending. One-
quarter of this spending (25%) was for poor households (GAKIN) under the Rumah Tidak Layak Huni (RTLH)
program, providing beneficiaries with in-kind assistance to improve their housing conditions, such as roofs,
floors, and walls. Excluding RTLH spending, the total portion of funds villages spent on improving housing,
sanitation, and access to clean water comes to just over 5 percent of total expenditures. Total spending on
clean water projects amounted to 1.7% of village funds and 2.23% on sanitation. Nearly half of the sanitation
component consisted of the construction or maintenance of public toilets. The low levels of spending on
water and sanitation contrast with village prioritization in past community-driven programs, where water
supply and sanitation investments consisted of more than double the current share of expenditures.10
Additional qualitative analysis may provide insight on lower village spending in these sectors, particularly
9 Based on PP 11/2019, Second Revision on PP No. 43/2014 on Implementation of Village Law. Note: calculation of village spending under the regulation excludes income from village-owned land. 10 PNPM Rural Annual Report 2007
20
considering the low rural access to drinking water and improved sanitation in Indonesia (nearly 20% of
households lack access to drinking water, and 36% lack access to basic sanitation).11
The next two largest expenditures were for health and education, accounting for 8.3% of all village
expenditures. Under health, the largest share of spending (nearly 41%) was for Posyandu services,
including supplementary feeding programs, incentive for Posyandu Cadre, and classes for pregnant
women. The next largest category is construction or rehabilitation of village health infrastructure (26% of
health spending), such as Posyandu and Polindes. This is followed by the implementation of public health
campaigns and messaging (11%). Under the education sub-Bidang, the largest categories of investments
are construction and rehabilitation of Early Childhood Development (ECD) facilities, including PAUD (34%)
nearly equal to expenditure on the operation of ECD facilitates (34%), including teacher honorarium,
supplies, and utilities. Overall, infrastructure spending makes up 47% of village education spending and
29% of village health spending.
Figure 7: Village Expenditure by Sub-Bidang (2019)
11 WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene
36.01%
25.93%
7.06%
4.28%
4.00%
3.30%
3.06%
2.49%
2.14%
2.04%
2.03%
1.25%
0.86%
0.80%
0.56%
0.55%
0.54%
0.54%
0.53%
0.44%
0.42%
0.42%
0.34%
0.27%
0.06%
0.03%
0.02%
0.02%
Public Works and Spatial Planning
Village Apparatus salary and operations
Housing/Sanitation
Health
Education
Culture and Religion
Village Office Facilities and Infrastructure
Village Planning, Budgeting, and Reporting
Agriculture and Livestock
Community Organization Empowerment
Youth and Sports
Capacity Building for Village Apparatus
Social Order and Community Protection
Trade and Industry
Tourism
Women's Empowerment & Child Protection
Energy and Mineral Resources
Marine and Fisheries
Transportation and ICT
Investment
Land Administration
Coops and MSME
Civil Registration, Statistics, and Archives
Forestry and the Environment
Disaster Response
Contingency
Emergency
Others
21
Finding 4. Across all regions, the majority of village expenditures (80%) go toward capital and
goods and services.
80% of village expenditures go toward capital investments and goods and services, a pattern that is
consistent across all regions. There is, however, greater variation between the share of capital compared
investments to goods and services expenditures between regions. Capital investments make up more than
55% of expenditures in Java compared to less than 35% in Bali and Nusa Tenggara. In contrast, spending
on Goods and Services is lowest in Java at under 25%, and highest in Bali and Nusa Tenggara at over 46%.
Expenditure on personnel is similar across regions, averaging at 19%. The exception is in Papua, where
spending on personnel makes up a smaller share of the total budget, at 16%, than in other regions.
Between all other regions, the share ranges from 20% in Java to 17% in Sumatra.
Less than 0.2% of village budgets go toward contingency spending. The highest percentage is in Papua,
where contingency spending accounts for 0.17% of total spending. Bali and Nusa Tenggara have the
lowest share of contingency spending, at only 0.04%.
Figure 8: Village spending by economic classification
Finding 5. Village priorities vary significantly across provinces.
Village priorities vary across provinces, but in most provinces, public works has the largest share,
followed by spending on village apparatus salary and office operation. There is significant variation for
the third-largest priority, ranging from housing/sanitation, education, health, or agriculture. In Figure 8,
provinces listed between Sumatera Barat to Gorontalo spend a larger share of their budget on salary and
operations than public works. In Papua, the largest share of the spending is devoted to agriculture (36%),
followed by housing and sanitation (15%). In Papua Barat, the largest share is devoted to housing and
sanitation (25%). Villages in Papua Barat and Maluku also invested a significant portion of their budget on
marine and fisheries (19%). Villages in Bali spent the largest share of their budget on Culture and Religion
(25%), much of which may be from provincial allocation designated specifically for such activities.
55%
54%
53%
49%
44%
35%
25%
28%
29%
31%
41%
46%
20%
17%
18%
19%
15%
19%
0% 20% 40% 60% 80% 100%
Java
Sumatra
Kalimantan
Sulawesi
Papua
Bali & Nusa Tenggara
Capital Goods and Services Personnel Contingency
22
Figure 9: Top five spending priorities by province
6.5%
9.3%
15.0%
15.2%
15.7%
18.2%
20.7%
23.8%
24.7%
25.1%
27.4%
27.4%
27.7%
28.0%
29.0%
30.5%
31.8%
32.3%
34.0%
34.7%
34.9%
36.1%
36.6%
37.4%
39.2%
39.5%
39.9%
40.4%
44.1%
44.2%
46.2%
48.6%
49.9%
13.2%
8.1%
23.5%
26.2%
28.7%
23.4%
27.5%
28.4%
29.4%
28.5%
29.0%
28.7%
18.5%
23.9%
24.4%
29.0%
23.2%
27.3%
29.7%
27.9%
24.2%
27.8%
26.6%
26.0%
29.5%
23.8%
28.1%
23.9%
21.9%
23.9%
22.4%
25.3%
24.0%
24.7%
15.3%
20.4%
14.2%
4.6%
9.8%
9.5%
4.6%
6.9%
5.6%
13.2%
10.3%
9.2%
4.8%
16.6%
10.2%
4.9%
5.1%
5.6%
6.0%
6.0%
8.1%
5.2%
9.0%
6.0%
6.2%
7.6%
6.5%
7.3%
4.3%
6.5%
7.7%
7.4%
5.3%
6.2%
6.7%
8.0%
5.3%
5.3%
4.7%
5.6%
5.2%
7.8%
4.3%
6.0%
3.9%
5.7%
4.5%
10.9%
5.9%
7.8%
5.0%
4.2%
3.7%
6.8%
3.8%
5.5%
4.7%
6.7%
4.4%
3.9%
4.5%
4.6%
5.5%
3.3%
3.0%
36.0%
7.2%
4.5%
4.9%
6.0%
4.3%
3.6%
6.6%
4.7%
4.8%
4.6%
4.8%
4.9%
4.0%
3.4%
7.8%
24.5%
6.5%
4.3%
9.4%
18.9%
7.1%
5.2%
4.6%
4.6%
4.0%
4.4%
3.3%
3.1%
6.7%
6.5%
5.4%
4.7%
29.1%
20.5%
27.8%
32.0%
37.6%
23.8%
28.1%
26.1%
30.0%
30.2%
29.1%
26.0%
26.9%
26.1%
27.1%
25.2%
15.6%
21.6%
21.0%
21.6%
22.8%
21.2%
18.1%
20.1%
17.8%
18.9%
18.0%
21.6%
18.2%
14.2%
17.5%
10.9%
12.2%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Papua Barat
Papua
Gorontalo
Maluku
Kep. Babel
Bali
Sulawesi Tengah
NTB
Kep. Riau
Kalimantan Utara
Kalimantan Timur
Sumatera Barat
Aceh
Maluku Utara
Sulawesi Tenggara
DIY
NTT
Sulawesi Utara
Riau
Kalimantan Tengah
Jambi
Kalimantan Barat
Kalimantan Selatan
Sulawesi Selatan
Jawa Timur
Sulawesi Barat
Jawa Barat
Sumatera Selatan
Sumatera Utara
Lampung
Jawa Tengah
Banten
Bengkulu
Public Works and Spatial Planning Village Apparatus salary and operations Housing/Sanitation
Education Health Agriculture and Livestock
Village Office Facilities and Infrastructure Culture and Religion Marine and Fisheries
Youth and Sports Village Planning, Budgeting, and Reporting Land Administration
Energy and Mineral Resources Community Organization Empowerment Capacity Building for Village Apparatus
Others
23
Finding 6. Since 2016, villages have increased spending on housing/sanitation, education, and
health, while reducing their share of spending on public works and salary and operations.
In 2016, the World Bank conducted a Village Expenditure analysis, using data from 1,868 villages across
Indonesia, translating activities into functional classification, which now align with the sub-Bidang
categories. The re-classification was used to analyze thousands of spending line items contained in village
budgets into functional categories. Beyond looking at how villages used resources in FY2016, the study
offered recommendations to improve classification and reporting to better analyze future spending.
Based on these recommendations and the government's own analysis, the village chart of accounts was
updated in the new financial management regulation. This analysis is used here to draw some
comparisons on how the composition of village budgets has shifted between 2016 (the second year of
Village Law implementation) to 2019. However, it is important to note that the 2016 data covers a much
smaller number of villages.
Between 2016 and 2019, the share of spending on village apparatus salary and operations, and public
works has been reduced, whereas spending on housing/sanitation, health, education, agriculture, and
youth and sports has increased. Although declining as a share of spending, in 2019, public works replaced
village apparatus spending as the largest expenditure category compared to 2016.
Extrapolating spending shares to total village revenues across the country suggests that the nominal
spending on village apparatus salary and operations, and culture and religion, both reduced, while
nominal spending for all other sub-Bidang increased. This represents a 130% increase in nominal spending
on education and an 85% increase in housing/Sanitation, health, and Agriculture. Nominal spending for
public works and spatial planning increased by 30%, well youth and sports increased by 180%.12
Figure 10: Village expenditure priority shift across major sub-Bidang (2016 and 2019)
12 Estimated nominal spending is based on total national village spending of DR 117.4 trillion (BPS’s finance statistics of village, 2020). Calculation is based on available data from 36,242 villages, rather than on statistical sampling methods.
38.1%
39.0%
5.2%
3.2%
2.4%
5.8%
1.6%
1%
3.7%
36.0%
25.9%
7.1%
4.3%
4.0%
3.3%
2.1%
2.0%
15.2%
Public Works and Spatial Planning
Village Apparatus Salary and Operations
Housing/Sanitation
Health
Education
Culture and Religion
Agriculture
Youth and Sports
Others
VIPER World Bank 2016
SISKEUDES 2019
24
Finding 7. 97% of villages invest in stunting-related activities, at an average rate of 12%. Papua has
the highest spending share with nearly 30%, followed by NTT and Gorontalo at nearly 20%
In August 2017, the Government of Indonesia launched its 2018-2024 National Strategy to Accelerate
Stunting Prevention (StraNas Stunting). The StraNas Stunting is centered on the understanding that
reduction in stunting requires a coordinated effort across different government agencies and levels of
government, including villages. As most services are delivered to citizens at the local level, villages have a
critical role in delivering last-mile services to help reduce stunting in Indonesia. Activities toward reducing
stunting can be divided into nutrition-specific and nutrition-sensitive interventions. Nutrition-specific
interventions improve the quality of nutrition for mothers and children, including micronutrient
supplementation programs and operation of Posyandu. Nutrition-sensitive interventions create an enabling
environment that can impact nutrition, including access to health care for mothers and infants, food security
and agriculture activities, water and sanitation, and early childhood education (see Table 4).13
Table 4: Village-Level Stunting Priority Interventions
Function Activities
Spec
ific
Health
• Operational cost of village health posts (Posyandu)
• Posyandu services (supplementary feeding, classes for pregnant mothers, incentive for Posyandu Cadre)
• Health education and training for Posyandu Cadre
• Joint-Caring for Toddler Family Development (BKB)
Sen
siti
ve
Education
• Operational cost of early childhood development (ECD) facilities (including teacher honorariums)
• Equipment and supplies for ECD facilities
• Construction and maintenance of ECD Facilities
Health
• Implementation of Village Health Alert
• Guidance and supervision for traditional health efforts
• Construction and maintenance of village health facilities
Housing/Sanitation
• Construction and maintenance of village drinking water infrastructure
• Construction and maintenance of village sanitation infrastructure, including drainage and wastewater disposal
• Construction and maintenance of public toilets
Forestry and Environment
• Training, socialization, and awareness-raising about environment and natural resources
Community Organization Empowerment
• Support and service of Family Welfare Movement (PKK)
Agriculture and Livestock • Strengthening food security, including development of village granaries
Women's Empowerment, Child Protection
• Child protection training and counseling
13 Lancet, Maternal and child nutrition series, 2013.
25
In total, 97.4 percent of villages spend on stunting-related interventions, with average investments of
12%. The vast majority of villages (86%) spend on both nutrition-specific and nutrition-sensitive
interventions. Breaking down the levels of investment shows a wide variance between villages (Figure 11).
10% of villages spent 4% or less on stunting-related interventions, while at the same time, the highest
decile spent over 26% of their total budget. The median expenditure was 8.6%, with the share of stunting-
related spending clustered at the left tail of the distribution. Despite this, nearly 1% of villages spent 54%
or more of their total budget on stunting-related interventions.
Table 5: Average and median of village spending on stunting-related interventions
Average Median
SENSITIVE Intervention Spending Share 10.0% 6.3%
SPECIFIC Intervention Spending Share 2.6% 2.0%
Overall Stunting Spending Share 12.0% 8.6%
Figure 11: Percent of Villages With Stunting-Related Expenditures and Frequency Distribution by Spending
2.6%
8.9%
14.2%
13.0%
10.2%
8.1%
6.5%
5.8%
5.0%
4.1%
3.7%
3.0%
2.6%
2.3%
1.7%
1.5%
1.2%
1.1%
0.7%
0.6%
0.6%
0.5%
0.4%
0.4%
0.3%
0.2%
0.2%
0.2%
0.8%
None
2% - <4%
6% - <8%
10% - <12%
14% - <16%
18% - <20%
22% - <24%
26% - <28%
30% - <32%
34% - <36%
38% - <40%
42% - <44%
46% - <48%
50% - <52%
54% or more
None
Comprehensive (Both Sensitive
and Specific)
Sensitive Only
Specific Only
26
Figure 12: Village Stunting Expenditures by Province
In most provinces with high stunting prevalence (Papua, NTT, Gorontalo, Sulbar, NTB, and Lampung),
villages spent a relatively large share of their budget for stunting-related interventions (Figure 12). On
average, villages in Papua spent almost 9% of their budget for nutrition-specific interventions and nearly
30% on all nutrition-related activities. Villages in Java and Bali generally spent less on such interventions.
Excluding villages in Java and Bali, the average village spending on stunting interventions increases to 14%
(compared to 12%), and the mean increases to 13% (compared to 9%).
0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0%
Papua
NTT
Gorontalo
Sulawesi Barat
NTB
Lampung
Kalimantan Selatan
Sulawesi Tengah
Maluku Utara
Aceh
Kep. Babel
Jambi
Sulawesi Selatan
Sulawesi Utara
Kalimantan Tengah
Kalimantan Barat
Sumatera Selatan
Sumatera Barat
Kalimantan Utara
Bengkulu
Maluku
Riau
Kep. Riau
Sumatera Utara
Jawa Barat
Sulawesi Tenggara
Kalimantan Timur
Jawa Timur
Papua Barat
Bali
Jawa Tengah
Banten
DIY
Sensitive Intervention Specific Intervention
27
6. PART 3: VILLAGE REVENUE ANALYSIS
Finding 8. Dana Desa makes up just over half of total village resources.
Nearly half of village revenues are from sources other than Dana Desa, although inter-governmental
transfers account for 97% of all revenues (Figure 13). Dana Desa transfers contribute more than half of
overall village revenues (53%), followed by ADD (31%), financial assistance from district and provincial
governments (9%), and shared revenue from district taxes and levies (4%). Financial Assistance (Bankeu)
consists of assistance from districts and provinces, with a slightly larger share from districts (4.4%)
compared to provinces (4.1%).
Figure 13: Village Revenue by Source
Finding 9. Share of village revenues from Dana Desa Ranges from 23% in Bali to 81% in Papua.
There is a large variation in the share of village revenue from Dana Desa between provinces, ranging from
23% in Bali to 81% in Papua (Figure 14). In 23 provinces, Dana Desa accounts for more than 50% of total
village revenues. In Papua, Dana Desa accounts for 81% of village revenues, followed by Aceh (79%) and NTT
(74%). By contrast, in Bali, Dana Desa is only the third-largest revenue source at 23%. In 10 provinces, Dana
Desa accounts for less than 50% of total village revenues. The revenue trend from Dana Desa is in line with
the allocation formula, which provides a fixed base allocation for all villages. It includes affirmative
allocations for lagging villages and areas with higher poverty rates (See Table 2 for a detailed breakdown of
the Dana Desa allocation formula). However, it is important to note that even in poor and lagging regions,
villages still have significant revenues from other sources – highlighting the need for a holistic analysis of
village resources.
The share of ADD from districts ranges from 59% of total revenues in Kalimantan Timur to 19% in Papua.
In two additional provinces, ADD accounts for more than 50% of total revenues. In Kalimantan Utara and
Kepulauan Riau, ADD contributes 56% and 54% of revenues, respectively. In six provinces, ADD accounts
for less than one-quarter of revenues, with the lowest in Papua, followed by Aceh (20%), Jawa Tengah
(21%), Bali (23%), and Banten (24%).
52.6%
30.8%
8.6%
4.1%
3.1%
0.7%
Dana Desa (DD)
Alokasi Dana Desa (ADD)
Financial Assistance (Bankeu)
Shared Revenue (BH-PDRD)
Village OSR (PADes)
Other Revenue
Government transfers to villages
96.7%
28
Financial Transfers (Bankeu) from provinces and districts make up a large share of revenues in select
provinces. In Bali, Bankeu from the provincial government accounts for 19% of total revenues. Provincial
transfers also make significant contributions to total revenues in Riau (11%), Jawa Tengah (10%), and Jawa
Barat (7%). Six provinces do not provide Benkeu, Kalimantan Utara, Papua Barat, Maluku, Maluku Utara,
NTT, and Papua. District Bankeu makes up 14% of total revenues in DI. Yogyakarta , followed by 11% in Jawa
Tengah, and 8% in Jawa Timur. In 20 provinces, District Bankeu contributes less than 1% of total revenues.
Figure 14: Village Revenue Composition by Province
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Papua
Aceh
NTT
Gorontalo
Lampung
Sumatera Utara
Bengkulu
Sumatera Selatan
Maluku
Kalimantan Tengah
Sulawesi Utara
Sulawesi Barat
Sulawesi Tengah
Kalimantan Barat
Maluku Utara
Sulawesi Tenggara
Kalimantan Selatan
NTB
Banten
Papua Barat
Sulawesi Selatan
Jambi
Sumatera Barat
Jawa Timur
Jawa Barat
Jawa Tengah
Kalimantan Utara
DIY
Kep. Riau
Kep. Babel
Riau
Kalimantan Timur
Bali
DD ADD Bankeu of Province Bankeu of District BH-PDRD PADes Other Village Revenue
29
4.1 4.2 4.2
3.5
3.1
3.5
2.9
18%16%
8%
4%3% 3%
2%
0%
5%
10%
15%
20%
0
1
2
3
4
2013 2014 2015 2016 2017 2018 2019
Trill
ion
IDR
PADes Nominal (left axis) PADes as Share of Total Village Revenue (right axis)
Finding 10. Village Own-Source Revenue contributes 3% to overall village revenues, with most of
this revenue coming from villages in Java and Bali.
Village Own-Source Revenue (PADes) contributes only 3% to overall village revenue. The majority of
PADes, 2.4% of total revenues, comes from the rent of village land (Figure 15). Even though most villages
projected to raise own-source revenue in their original budget, 61% of all villages could not generate
PADes (Figure 17). About 15% of villages generated PADes of less than 1% as a share of total revenue. In
nominal terms, 27% of villages generate PADes less than IDR 100 million a year. While most villages in
Java-Bali (excluding Banten) could generate their own revenue, villages in other regions could not do so.
Across all villages, the BUMDes return on investment contributes less than 0.1% to village revenue.
Figure 15: Village Own-Source Revenue Breakdown (2019)
Figure 16: PADes trend in nominal terms and as a share of total village revenue (2013-2019)
2.6%
0.2%
0.1%
0.2%
Returns on Village Asset
Returns on VillageInvestment
Community contribution
Other OSR
Rent from village land asset
Return from other asset utilization
Other ROI
BUMDes ROI
30
Between 2013 and 2019, PADes has declined both as a share of revenue and in nominal terms (see Figure
16). The decrease in share of revenue is expected with the significant increase of inter-governmental
transfers, decreasing from a high of 18% of total revenues to 2% in 2019. Perhaps more surprisingly, PADes
is also on a declining trend in nominal terms, going from a high of IDR 4.2 trillion in 2014 and 2015 to IDR 2.9
trillion in 2019. The increasing size of inter-governmental transfers may disincentivize village governments
from improving their PADes generation. The government may want to consider options for incentivizing
PADes generation for the long-term sustainability of village-level infrastructure projects.
Figure 17: Village Own-Source Revenues by Province
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Papua Barat
Papua
Maluku Utara
Sulawesi Tenggara
Maluku
Kalimantan Utara
Kalimantan Barat
Sulawesi Barat
Sulawesi Tengah
Sumatera Utara
NTT
Bengkulu
Sulawesi Utara
Kalimantan Timur
Aceh
Banten
Kalimantan Selatan
Kalimantan Tengah
Lampung
Kep. Riau
Jambi
Gorontalo
Sumatera Selatan
Sumatera Barat
Kep. Babel
Sulawesi Selatan
Riau
NTB
Jawa Barat
DIY
Jawa Tengah
Bali
Jawa Timur
No OSR Less than 1% OSR 1% - <10% OSR 10% or more OSR
31
Public Works and Spatial Planning
Housing / Sanitation
Health
Education
Agriculture and Livestock
Others
Apparatus Salary and Office Operations
Village Office Facilities and Infrastructure
Culture and Religion
Community Organization Empowerment
Public Works and Spatial Planning
Others
Public Works and Spatial Planning
Village Planning, Budgeting, Reporting
Housing / Sanitation
Village Office Facilities and Infrastructure
Apparatus Salary and Office Operations
Others
Public Works and Spatial Planning
Culture and Religion
Housing / Sanitation
Village Office Facilities and Infrastructure
Community Organization Empowerment
Others
Figure 18: Top Village Expenditure Categories by Source of Fund
DD
ADD
District Financial
Assistance
Provincial Financial
Assistance
Finding 11. Spending priorities shift significantly between different fund sources.
Spending priorities shift significantly between different fund sources. Currently, the central government
and Ministry of Finance exclusively analyze village spending under Dana Desa. However, Dana Desa
expenditures alone do not provide a complete picture of village spending and prioritization. With
improved data availability for all revenue sources, the government can now conduct a much deeper
analysis of spending patterns.
Alokasi Dana Desa (ADD) contributes the most toward Salary and Office Operations14, while it is also a
major contributor for financing village office facilities and infrastructure, social order/security, and civil
registration. The shared district tax and levies (BH-PDRD) and own-source revenue (PADes) contribute the
most to the financing of land administration. The financial assistance from districts complements the ADD
to finance the majority of village planning, budgeting, and reporting. Financial assistance from provinces
contributes to activities in culture and religion.
14 Note that villages are not allowed to use Dana Desa to cover salary and office operations costs.
32
7. PART 4: VILLAGE BUDGET CREDIBILITY ANALYSIS
Assessment of the village level data is vital to improve public financial management at the lower tier of
the governance and improve service delivery. The extension of PEFA to the subnational level can help
understand PFM capacity at the village level and assess budget credibility. However, the PEFA assessment
(2016 framework) does not cover the assessment of the subnational or village-level public financial
management operations. The assessment is undertaken at the central level to assess the public finance
management operations of the government using Government Finance Statistics (GFS) definitions, which
covers ministries and extra-budgetary units at the central level.
The PEFA framework has been adapted to assess the performance at the village level based on the
Budget Reliability pillar. The budget reliability measures the accuracy of the budget by comparing the
composition of expenditures and revenues to the year-end outrun. The scores measure the strength of
the budget forecast, the establishment of a consistent budgeting framework, and revenue mobilization.
Basing the budget on the previous year's actual expenditure enhances the consistency and provides a
realistic baseline for next year's budget formulation.
The analysis for budget reliability uses five standard PEFA indicators and applies two additional
indicators that are non-standard PEFA indicators. 15
1.1 Aggregate expenditure outturn (and by Fund)
2.1 Expenditure composition outturn by function
2.2 Expenditure composition outturn by economic type
2.3 Expenditure composition outturn by Fund - Non-Standard PEFA
3.1 Aggregate revenue outturn (and by Fund)
3.2 Revenue composition outturn by economic type
3.3 Revenue composition outturn by Fund – Non-Standard PEFA
The analysis has also adjusted the time horizon of the analysis to one year, as at this time, village data
is only available for FY 2019. PEFA for most indicators uses three years of data to score an indicator and
two years where necessary to eliminate a one-off effect of an external shock. As data becomes available
for additional fiscal years, MOHA will update the analysis.
The analysis presented in this section cover 33,220 villages across all 33 provinces with rural villages for
which original and actual budgets were available, including data on revenues and expenditures. While the
assessment covers 45% of all villages, it is not a drawn sample from all villages and therefore may not
represent budget credibility of all villages across the country. The process serves as a proof-of-concept to
demonstrate the possibility of leveraging the newly available data to develop performance-based metrics
on village financial management. It is important to note that these grades are not representative of the
national average but only of the assessed villages. It is likely that in provinces with lower levels of reporting
(see Part 1) – such as Papua (6%) and Sulawesi Tenggara (22%) – the average grades may shift. On the
other hand, 98% of villages from Bengkulu were included in the modified PEFA assessment, and 92% of
those villages received A and B grades.
15 Please refer to PEFA Guidelines for details on the dimensions, scoring scale, and calculation of averages.
33
Figure 20: Average Village PEFA Scores
Finding 12. 75% of villages receive an A or B grade in a modified PEFA assessment of budget reliability.
Across the country, 75% of villages scored A or B grades on the overall PEFA average score, indicating
high budget reliability and financial management capacity. Less than one-fifth of villages scored a C, and
only 6% received a D score. As Figure 19 shows, more than half of villages received an A when analyzing
Expenditure and Revenue grades separately. The same pattern holds for villages that received a D, with a
higher percentage of villages receiving a D in the Expenditure Grade and Revenue Grade. This shows that
while some villages perform poorly on analyzing their revenues or expenditures, they usually make up for
the poor performance in the other category. This may suggest that, in general, budget reliability is high
across villages, and external factors – such as district regulations or predictability of funds may contribute
to lower performance in some areas. However, additional analysis is required to test this hypothesis.
Figure 19: Modified PEFA Grades in Key Budget Reliability Indicators for 25,430 Villages
52%
14%
10%
24%
A B C D
34%
41%
19%
6%
61%10%
14%
15%
Expenditure Grade
Average PEFA Grade
Revenue Grade
34
Finding 13. There is a large variation in budget reliability between regions, with Sulawesi showing
the best performance and Java the poorest.
Regional analysis of grades shows a large variation between regions (Figure 21). Over 70% of villages in
Sulawesi received A and B grades, compared to less than 40% in Java. Papua and Maluku had the highest
share of villages scoring D – at over 30%. However, looking at provincial analysis (Figure 22) shows that most
lower grades are from villages in Papua Barat and Maluku. Villages in Sulawesi and Sumatra were the highest
performing, followed by Bali & Nusa Tenggara and Kalimantan, followed by Papua & Maluku and Java.
Figure 21: PEFA Grades by Region Across 25,430 Villages - Count and Rate
0 2000 4000 6000 8000 10000 12000 14000
Papua & Maluku
Bali & Nusa Tenggara
Sulawesi
Kalimantan
Sumatra
JavaA
B+
B
C+
C
D+
D
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Papua & Maluku
Bali & Nusa Tenggara
Sulawesi
Kalimantan
Sumatra
Java
35
Figure 22: Average Village PEFA Grade by Province for 25,430 Villages
Bengkulu
Southeast Sulawesi
Lampung
West Sulawesi
Papua
Jambi
North Sumatra
Riau
South Sumatra
North Kalimantan
North Sulawesi
West Sumatra
Central Sulawesi
South Sulawesi
Bali
West Nusa Tenggara
Central Kalimantan
West Java
Gorontalo
Riau islands
South Borneo
Banten
East Kalimantan
West Kalimantan
East Nusa Tenggara
Bangka Belitung Islands
North Maluku
West Papua
East Java
Central Java
Aceh
Maluku
D.I. Yogyakarta
A B+ B C+ C D+ D
36
The five provinces with the highest share of villages with A and B grades are located in Sulawesi,
Sumatra, and Papua. Nearly 92% of villages in Bengkulu, Sumatra with received A or B grades; Sulawesi
Tenggara had 90%; Lampung, 89%; Sulawesi Barat, 84%; and Papua, 81%. In contrast, DI Yogyakarta had
the lowest share of villages with A and B grades at just over 12%, followed by Maluku with 24%; Aceh,
25%; Jawa Tengah, 30%; and Jawa Timur, 33%.
Finding 14. Predictable resourcing leads to better budgets.
Analysis of the distribution of average village expenditure and revenue scores shows that villages can
develop credible budgets when village revenues are predictable. Figure 23 shows the correlation
between village aggregate revenue scores (y-axis) and aggregate expenditure scores (x-axis), with colors
representing average PEFA budget reliability scores (where A is dark green, and D is bright red). The x-
and y-axes represent the percentage of budget to actuals, with 100% significating a full match at the
middle of the graph. The revealed correlation between the budget revenue and expenditure execution
performance aligns with Public Finance Theory and highlights the importance of predictable resourcing.
This means that when villages receive what they think they will get, and put that in their budget, they will
spend their budget as planned – delivering a reliable budget.
Figure 23: Distribution of Aggregate Revenue and Expenditure Scores as Percentage of Budget to Actuals
37
8. FUTURE DIRECTIONS
Through Siskeudes, the Government of Indonesia has unprecedented access to comprehensive village
financial data that can help measure the impact of village transfers and inform future policy direction.
This data can help the government measure results, ensure value for money, monitor village and district
performance, flag corruption risk, and make better policy decisions. In the process of conducting this
expenditure analysis, the World Bank has worked with MOHA to develop a proof-of-concept application
that has automated many of the key processes for multi-year trend analyses.
MOHA has already begun work to take critical next steps to strengthen both the application of
Siskeudes and the processes that can improve village reporting. These next steps include increasing
uptake of villages and districts to report through the Siskeudes National Consolidation Application; sharing
information and analysis back down to local governments so they can compare their performance with
others; leverage Siskeudes to support District Inspectorate with village oversight and audit; and use
findings from village performance to better target capacity building and technical assistance to villages;
and link Siskeudes with other data systems, including SIPADES (Village Asset Management System).
Complete village financial data availability provides the government with a unique opportunity for
evidence-based policymaking, targeted support to villages, and performance-based incentives to
villages and districts. As the quality of input data improves, the government can undertake economic
efficiency analysis of village investments. By pairing this data with district budgets, the government can
analyze frontline service delivery and identify critical gaps. In the area of stunting, the government can
link data from BPS with village and district spending to better understand the impact of investments. This
data can also improve financial management and oversight of supra-village governments, such as
implementing risk-based audits.
Key Lessons from 2019 ViPER
1. Improving the availability of complete consolidated village financial data will require better
incentives to districts and clear sanctions for non-compliance with reporting requirements. The
government can expand disbursement requirements for Dana Desa to require districts to submit
complete village financial reports (APBDes), not only for a single revenue source. There is also an
opportunity to include reporting requirements as a component of the performance-based Dana Desa
allocation, holding back a certain portion of allocations for non-compliance to reporting requirements.
A key consideration for this should be that the reporting bottleneck is often at the district level, not
at the village level. Therefore, incentives and sanctions should also target district governments, such
as conditionality for part of DAU.
2. Strengthening the financial performance of villages requires better support and monitoring of both
villages and districts. The modified PEFA assessment and "cut and paste" test show that village
performance depends on district performance. Findings from these analyses can be used to directly
work with districts where regulations and guidelines lead to poor financial management. This includes
requirements for expenditure reports to match original budgets – even where this means numbers
do not report actual spending. It also includes delays in informing villages about annual transfer
38
ceilings and delays in disbursements. Analysis of village financial data can help the government
identify regions with suboptimal performance and provide needs-based training and refresher
courses to the relevant village or district government officials.
3. Building a local-level interface to share information back to districts and villages can improve data
quality and support local planning. Village financial data presented here can play an important role in
evidence-based policymaking for the central government. However, this data can also be of equal
importance for district and village governments to improve their performance. Currently, districts and
villages do not have the capacity to analyze the financial data they submit to the central government.
As with most other data in Indonesia, financial data collection is an extractive process where local
governments do not see the results and findings of their reports. Building an interface that allows local
governments to see this data in a meaningful format will both help with local planning, particularly in
targeting capacity building support, and can also help to improve the quality of data as villages and
districts will be able to see where incorrect inputs have impacted their performance on key indicators.
4. Leveraging financial data for evidence-based policymaking requires a holistic analysis of all village
resources, not only Dana Desa. Currently, the MoF is only analyzing reports from Dana Desa. As articulated
in this report, this hides some important trends. A more holistic analysis of resources can help ensure
better complementarities between different revenue sources; ensure fiscal fairness in the distribution of
resources as a whole; and improve oversight and monitoring for the nearly US $4 billion annually spent by
villages from revenues outside of Dana Desa. As the availability of consolidated data increases across the
country, the Ministry of Finance will also be able to use wholistic financial data from the National
Consolidation Application to update and refine the current performance-based incentive methodology for
the Dana Desa allocation formula, to make transfers contingent on performance on all village revenues.
5. Spending patterns can inform sectoral technical assistance and allow for more strategic targeting of
village-level support by line ministries and directorates. The variation in village spending patterns
between provinces shows how communities prioritize activities based on the local context. This data can
help inform sectors about opportunities for better collaboration between village governments and local
service delivery systems. For example, data from 2019 shows that there is potential for the Ministry of
Fisheries to work closely with village governments in Papua Barat and Maluku, where villages are
spending a significant portion of their budget on activities in that sector. Similarly, the Ministry of
Agriculture has an opportunity to work closely with villages in Papua, which spend 36% of their total
village revenue on agriculture activities. To improve access to water and sanitation, the Ministries of
Health and Public Works have the opportunity to coordinate more closely with villages in Papua Barat
and Gorontalo, where villages are spending over 20% of their funds toward WASH activities. Better
targeting of technical support and village-district coordination can help ensure complementarity of
spending between different levels of government and help progress toward sectoral targets.
6. Institutionalizing village expenditure analysis, such as the ViPER methodology in this report, will
support policymaking for MOHA, the Ministry of Finance, and other government institutions that
focus on poverty reduction and frontline service delivery. As a part of this PER, an automated
interface has been developed that can help government routinely monitor the use of resources under
the Village Law. Regularly providing such analysis can help institutions across government better
understand the capacity and opportunities available through village-level delivery mechanisms.
39
ANNEX A: VILLAGE REPORTING
Table 6: Villages Using Siskeudes and Report Availability in Siskeudes National Consolidation Application
Province Total Villages # of Villages Using Siskeudes
% of Villages Using Siskeudes
# of Villages Reporting in Siskeudes
% of Villages Reporting in Siskeudes
Aceh 6496 6461 99% 2741 42%
Bali 636 636 100% 635 100%
Banten 1238 1238 100% 666 54%
Bengkulu 1341 1341 100% 1316 98%
DIY 392 392 100% 315 80%
Gorontalo 657 657 100% 556 85%
Jambi 1399 1399 100% 1265 90%
Jawa Barat 5312 5312 100% 3920 74%
Jawa Tengah 7809 7573 97% 5740 74%
Jawa Timur 7724 7535 98% 5453 71%
Kalimantan Barat 2031 2031 100% 1812 89%
Kalimantan Selatan
1864 1862 100% 1737 93%
Kalimantan Tengah
1433 1432 100% 917 64%
Kalimantan Timur 841 841 100% 698 83%
Kalimantan Utara 447 406 91% 109 24%
Kep Babel 309 309 100% 246 80%
Kep. Riau 275 275 100% 274 100%
Lampung 2435 2435 100% 1232 51%
Maluku 1198 1198 100% 795 66%
Maluku Utara 1063 1063 100% 603 57%
NTB 1005 995 99% 652 65%
NTT 3026 3026 100% 871 29%
Papua 5411 2679 50% 346 6%
Papua Barat 1742 1317 76% 84 5%
Riau 1591 1591 100% 1422 89%
Sulawesi Barat 575 575 100% 457 80%
Sulawesi Selatan 2255 2255 100% 1306 58%
Sulawesi Tengah 1842 1842 100% 1479 80%
Sulawesi Tenggara 1908 1876 98% 416 22%
Sulawesi Utara 1507 1507 100% 980 65%
Sumatera Barat 928 806 87% 757 82%
Sumatera Selatan 2853 2852 100% 1392 49%
Sumatera Utara 5417 5410 100% 2492 46%
40
ANNEX B: VILLAGE EXPENDITURES
Table 7: Village Spending by Functional Classification (GFS)
GFS Classification Actuals Final (%) Original Budget (%)
Housing and community amenities 37.78% 37.26%
Economic affairs 35.66% 34.96%
Recreation, culture, and religion 10.03% 10.29%
General public services 4.76% 5.41%
Health 4.13% 4.12%
Education 3.96% 3.97%
Environmental protection 2.37% 2.43%
Public order and safety 0.83% 1.02%
Social protection 0.48% 0.53%
Table 8: Village Spending by Economic Classification
Type Average
Capital 52.33%
Goods and Services 28.70%
Personnel 18.89%
Contingency 0.08%
Table 9: Village Spending by Economic Classification by Region
Region Capital Goods and Services Personnel Contingency
Java 55.05% 24.57% 20.31% 0.08%
Sumatra 54.32% 28.23% 17.34% 0.10%
Kalimantan 53.11% 29.06% 17.77% 0.06%
Sulawesi 49.20% 31.46% 19.27% 0.08%
Papua 43.53% 40.80% 15.50% 0.17%
Bali & Nusa Tenggara 34.94% 46.43% 18.59% 0.04%
41
Table 10: National estimates of Village Expenditure by Sub-Bidang & Infrastructure Content, 2019
Sub-Bidang Share
coefficient
Total Spending Infrastructure Content
trillion IDR billion USD*
% trillion IDR billion USD*
Public Works and Spatial Planning 36.0% 42.30 2.92 90.6% 38.31 2.64
Village Apparatus salary and office operations
25.9% 30.46 2.10
Housing/Sanitation 7.1% 8.29 0.57 90.2% 7.48 0.52
Health 4.3% 5.03 0.35 28.5% 1.43 0.10
Education 4.0% 4.70 0.32 47.0% 2.21 0.15
Culture and Religion 3.3% 3.88 0.27 22.2% 0.86 0.06
Village Office Facilities and Infrastructure
3.1% 3.59 0.25 42.6% 1.53 0.11
Village Planning, Budgeting, and Reporting
2.5% 2.92 0.20 1.4% 0.04 0.00
Agriculture and Livestock 2.1% 2.51 0.17 10.8% 0.27 0.02
Community Organization Empowerment
2.0% 2.40 0.17
Youth and Sports 2.0% 2.39 0.16 70.7% 1.69 0.12
Capacity Building for Village Apparatus
1.3% 1.47 0.10
Social Order and Community Protection
0.9% 1.01 0.07
Trade and Industry 0.8% 0.94 0.06 69.9% 0.65 0.05
Tourism 0.6% 0.66 0.05 70.5% 0.47 0.03
Women's Empowerment & Child Protection
0.6% 0.65 0.04
Energy and Mineral Resources 0.5% 0.63 0.04 74.3% 0.47 0.03
Marine and Fisheries 0.5% 0.63 0.04 12.4% 0.08 0.01
Transportation and ICT 0.5% 0.62 0.04
Investment 0.4% 0.52 0.04
Land Administration 0.4% 0.50 0.03
Coops and MSME 0.4% 0.49 0.03
Civil Registration, Statistics, and Archives
0.3% 0.40 0.03
Forestry and the Environment 0.3% 0.32 0.02
Disaster Response 0.1% 0.07 0.00
Contingency 0.0% 0.03 0.00
Emergency 0.0% 0.02 0.00
Others 0.0% 0.02 0.00
42
ANNEX C: VILLAGE REVENUES
Table 11: Village Revenues by Fund Source by Province
DD ADD Bankeu of Province
Bankeu of District
BH-PDRD PADes Other
Aceh 78.8% 19.7% 0.1% 0.0% 0.7% 0.2% 0.4%
Bali 22.6% 23.4% 19.1% 6.1% 27.1% 0.9% 0.7%
Banten 57.1% 23.5% 4.1% 6.7% 6.7% 0.2% 1.6%
Bengkulu 67.6% 31.5% 0.0% 0.1% 0.3% 0.1% 0.4%
DIY 40.7% 28.3% 0.9% 13.8% 7.8% 7.2% 1.3%
Gorontalo 70.2% 27.8% 0.0% 0.5% 0.8% 0.2% 0.5%
Jambi 56.2% 34.3% 4.8% 2.6% 1.1% 0.5% 0.5%
Jawa Barat 46.1% 28.8% 6.8% 6.1% 10.1% 1.3% 0.8%
Jawa Tengah 45.6% 20.6% 9.9% 11.2% 2.2% 9.5% 0.9%
Jawa Timur 47.3% 30.5% 0.9% 7.9% 2.9% 9.5% 1.0%
Kalimantan Barat 62.2% 34.0% 0.1% 0.7% 2.2% 0.5% 0.3%
Kalimantan Selatan 58.6% 38.7% 0.0% 0.0% 1.6% 0.3% 0.7%
Kalimantan Tengah 64.1% 34.1% 0.1% 0.1% 1.1% 0.2% 0.4%
Kalimantan Timur 37.4% 59.1% 0.0% 1.9% 1.0% 0.2% 0.4%
Kalimantan Utara 40.9% 56.1% 0.0% 0.0% 1.7% 0.3% 1.2%
Kep. Babel 39.0% 47.8% 2.7% 1.2% 5.4% 1.2% 2.7%
Kep. Riau 39.1% 53.8% 0.0% 0.3% 6.3% 0.1% 0.4%
Lampung 69.1% 26.9% 0.5% 1.4% 1.4% 0.4% 0.4%
Maluku 64.2% 35.1% 0.0% 0.0% 0.3% 0.1% 0.3%
Maluku Utara 61.0% 33.9% 0.0% 0.0% 0.2% 0.1% 4.8%
NTB 58.4% 35.9% 0.3% 1.8% 2.6% 0.4% 0.6%
NTT 73.8% 24.0% 0.0% 0.0% 1.0% 0.8% 0.4%
Papua 80.9% 19.1% 0.0% 0.0% 0.0% 0.0% 0.0%
Papua Barat 56.6% 42.7% 0.0% 0.0% 0.7% 0.0% 0.0%
Riau 38.9% 43.3% 10.9% 3.3% 2.6% 0.5% 0.5%
Sulawesi Barat 62.6% 34.9% 1.7% 0.0% 0.4% 0.0% 0.3%
Sulawesi Selatan 56.4% 40.1% 0.0% 0.5% 1.8% 0.6% 0.6%
Sulawesi Tengah 62.6% 33.4% 0.0% 0.1% 2.4% 0.1% 1.4%
Sulawesi Tenggara 60.0% 37.1% 0.0% 2.3% 0.3% 0.1% 0.3%
Sulawesi Utara 63.7% 34.9% 0.1% 0.2% 0.6% 0.2% 0.4%
Sumatera Barat 52.1% 44.5% 0.0% 0.3% 2.0% 0.4% 0.6%
Sumatera Selatan 66.7% 30.4% 2.0% 0.0% 0.4% 0.2% 0.3%
Sumatera Utara 68.2% 30.4% 0.0% 0.2% 0.8% 0.1% 0.3%
43
Table 12: Top Village Expenditure Categories by Source of Fund
Dana Desa
1 Public Works and Spatial Planning 57.51%
2 Housing / Sanitation 10.92%
3 Health 6.75%
4 Education 6.37%
5 Agriculture and Livestock 3.58%
6 Others 14.87%
ADD
1 Apparatus Salary and Office Operations 71.30%
2 Village Office Facilities and Infrastructure 5.60%
3 Culture and Religion 3.90%
4 Community Organization Empowerment 3.60%
5 Public Works and Spatial Planning 3.50%
6 Others 12.20%
District Financial Assistance
1 Public Works and Spatial Planning 48.62%
2 Village Planning, Budgeting, Reporting 15.72%
3 Housing / Sanitation 10.56%
4 Village Office Facilities and Infrastructure 4.62%
5 Apparatus Salary and Office Operations 3.70%
6 Others 16.77%
Provincial Finance Assistance
1 Public Works and Spatial Planning 46.47%
2 Culture and Religion 17.05%
3 Housing / Sanitation 9.98%
4 Village Office Facilities and Infrastructure 6.35%
5 Community Organization Empowerment 5.40%
6 Others 14.76%
44
Table 13: Financing contribution of multiple funds across sub-bidang
Sub-Bidang Share Total Spending
Sources of Fund
DD ADD BH-PDRD Bankeu Districts
Bankeu Provinces
PADes Others Total
Public Works and Spatial Planning
36.0% 85.5% 3.1% 0.8% 5.5% 4.1% 0.4% 0.7% 100%
Village Apparatus salary and operations
25.9% 0.6% 88.0% 3.6% 0.6% 0.6% 6.1% 0.5% 100%
Housing/Sanitation 7.1% 82.9% 3.7% 1.3% 6.1% 4.5% 0.4% 1.1% 100%
Health 4.3% 84.4% 7.9% 3.2% 1.2% 2.0% 0.5% 0.8% 100%
Education 4.0% 85.2% 9.2% 1.8% 1.8% 0.5% 0.8% 0.8% 100%
Culture and Religion 3.3% 19.3% 37.7% 14.4% 4.5% 16.5% 5.3% 2.3% 100%
Village Office Facilities and Infrastructure
3.1% 6.4% 58.6% 15.5% 6.2% 6.7% 3.0% 3.6% 100%
Village Planning, Budgeting, and Reporting
2.5% 10.3% 43.4% 9.0% 25.7% 0.7% 7.7% 3.2% 100%
Agriculture and Livestock
2.1% 89.8% 2.5% 0.6% 3.4% 1.5% 1.0% 1.3% 100%
Community Organization Empowerment
2.0% 16.6% 56.3% 11.4% 4.0% 8.5% 2.3% 1.0% 100%
Youth and Sports 2.0% 70.1% 17.9% 6.3% 2.6% 0.9% 1.1% 1.1% 100%
Capacity Building for Village Apparatus
1.3% 52.1% 35.5% 8.8% 0.4% 0.3% 1.3% 1.6% 100%
Social Order and Community Protection
0.9% 21.2% 54.6% 14.3% 2.5% 2.8% 3.0% 1.6% 100%
Trade and Industry 0.8% 87.6% 2.3% 1.0% 3.4% 2.2% 1.9% 1.6% 100%
Tourism 0.6% 85.0% 3.0% 1.2% 5.0% 0.8% 1.7% 3.2% 100%
Women's Empowerment & Child Protection
0.6% 82.2% 7.4% 2.9% 2.5% 2.8% 1.1% 1.1% 100%
Energy and Mineral Resources
0.5% 88.5% 5.8% 0.7% 2.3% 1.4% 0.1% 1.0% 100%
Marine and Fisheries 0.5% 92.4% 4.2% 0.5% 0.7% 0.5% 0.2% 1.4% 100%
Transportation and ICT 0.5% 82.4% 9.0% 2.6% 3.0% 1.0% 0.8% 1.2% 100%
Investment 0.4% 82.5% 3.1% 1.0% 1.5% 8.3% 0.6% 3.0% 100%
Land Administration 0.4% 4.0% 14.5% 33.2% 3.2% 0.4% 30.4% 14.3% 100%
Coops and MSME 0.4% 76.4% 5.6% 1.4% 8.7% 5.8% 0.4% 1.7% 100%
Civil Registration, Statistics, and Archives
0.3% 25.5% 55.5% 13.4% 0.9% 1.3% 2.1% 1.2% 100%
Forestry and the Environment
0.3% 74.8% 8.4% 9.9% 3.8% 0.3% 1.2% 1.6% 100%
Disaster Response 0.1% 52.9% 18.8% 10.0% 6.0% 1.9% 6.2% 4.1% 100%
Contingency 0.0% 65.6% 12.6% 5.7% 0.3% 0.5% 12.5% 2.9% 100%
Emergency 0.0% 44.6% 23.6% 9.5% 0.7% 0.8% 15.4% 5.4% 100%
Others 0.0% 86.0% 14.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100%
45
ANNEX D: VILLAGE BUDGET CREDIBILITY
Table 14: Average PEFA Scores by Province
Province A B+ B C+ C D+ D Total
Aceh 129 41 366 327 468 794 10 2135
Bali 160 55 124 56 35 50 11 491
Bangka Belitung Islands 21 9 70 63 27 14 3 207
Banten 116 24 45 61 65 28 6 345
Bengkulu 496 39 140 22 15 22 2 736
Central Java 368 216 816 1027 966 880 397 4670
Central Kalimantan 227 40 245 136 100 105 5 858
Central Sulawesi 342 42 321 104 110 74 2 995
D.I. Yogyakarta 7 5 23 36 32 112 66 281
East Java 196 95 1113 962 682 707 490 4245
East Kalimantan 70 18 184 85 71 93 5 526
East Nusa Tenggara 29 7 227 73 68 117 9 530
Gorontalo 10 1 218 105 42 31
407
Jambi 342 43 496 140 40 33 2 1096
Lampung 129 6 439 40 13 18 2 647
Maluku 35 5 92 58 121 246 2 559
North Kalimantan 1 1 51 15 3 3
74
North Maluku 95 20 143 54 79 134 10 535
North Sulawesi 288 44 225 79 50 99
785
North Sumatra 804 98 244 140 54 90 1 1431
Papua 126 1 20 6 3 26
182
Riau 80 288 461 161 78 39 3 1110
Riau islands 19 5 103 64 28 12
231
South Borneo 268 88 498 363 172 174 11 1574
South Sulawesi 222 46 546 119 64 69 87 1153
South Sumatra 453 35 114 141 36 42 2 823
Southeast Sulawesi 216 13 88 18 5 13
353
West Java 971 142 655 430 285 358 148 2989
West Kalimantan 382 67 386 134 268 383 13 1633
West Nusa Tenggara 169 17 108 53 31 63 8 449
West Papua 10 3 18 45 2 6
84
West Sulawesi 264 11 108 27 27 17
454
West Sumatra 223 90 135 126 44 10 4 632
Grand Total 7268 1615 8822 5270 4084 4862 1299 33220
46
Table 15: PEFA Scoring Tables
Dimension 1.1. Aggregate Expenditure Outturn
Score Scoring Scale
A Aggregate expenditure outturn was between 95% and 105% of the approved aggregate budgeted expenditure in at least two of the last three years.
B Aggregate expenditure outturn was between 90% and 110% of the approved aggregate budgeted expenditure in at least two of the last three years.
C Aggregate expenditure outturn was between 85% and 115% of the approved aggregate budgeted expenditure in at least two of the last three years.
D The performance is less than required for a C score
Dimension 2.1. Expenditure composition outturn by function16
Score Scoring Scale
A Variance in expenditure composition by program, administrative or functional classification was less than 5 percent in at least two of the last three years.
B Variance in expenditure composition by program, administrative or functional classification was less than 10 percent in at least two of the last three years.
C Variance in expenditure composition by program, administrative or functional classification was less than 15 percent in at least two of the last three years.
D The performance is less than required for a C score
Dimension 2.2. Expenditure composition outturn by economic type17
Score Scoring Scale
A Variance in expenditure composition by economic classification was less than 5% at least two of the last three years.
B Variance in expenditure composition by economic classification was less than 10% at least two of the last three years.
C Variance in expenditure composition by economic classification was less than 15% at least two of the last three years.
D The performance is less than required for a C score
Dimension 3.1. Aggregate revenue outturn
Score Scoring Scale
A Actual revenue was between 97 percent and 106 percent of budgeted revenue in at least two of the last three years.
B Actual revenue was between 94 percent and 112 percent of budgeted revenue in at least two of the last three years.
C Actual revenue was between 92 percent and 116 percent of budgeted revenue in at least two of the last three years.
D The performance is less than required for a C score
Dimension 3.2. Revenue composition outturn18
Score Scoring Scale
A Variance in revenue composition was less than 5 percent in two of the last three years.
B Variance in revenue composition was less than 10 percent in two of the last three years.
C Variance in revenue composition was less than 15 percent in two of the last three years.
D The performance is less than required for a C score
16 2.1 composition is done at the high (10 functions) level of COFOG. 17 2.2 is at GFS 2-digit level (economic classification). The same formula is used for the composition according to Fund DD, ADD, etc) 18 3.2 composition is at GFS 2-digit level (economic classification). The same formula is used for the composition according to Fund
47
ANNEX E: DANA DESA FINANCIAL FLOW MECHANISM (FISCAL YEAR 2020 AS PER PMK 205/2019)
2021
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