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aUNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

Universal Basic Income: Feasibility Application in Indonesia

b UNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

iiiUNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

Universal Basic Income: Feasibility Application

in Indonesia

United Nation of Development Program (UNDP) and Fiscal Policy Agency (BKF) Ministry of Finance Republic Indonesia

7-1-2020

iv UNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

TABLE OF CONTENTS

Table of Contents ....................................................................................................................................................2

List of Tables .............................................................................................................................................................3

List of Figures ...........................................................................................................................................................3

List of Appendices ................................................................................................................................................. 4

Abbreviations ..........................................................................................................................................................5

Chapter 1 Conceptual Framework of Universal Basic Income (UBI) ..............................................

1.1 What is UBI?...................................................................................................................................................... 7

1.2 Why Indonesia could to consider for implementing UBI? .......................................................... 7

1.3 What UBI offers and what might not? ................................................................................................. 8

1.3.1 Low transaction cost ........................................................................................................................... 8

1.3.2 Sustainability .......................................................................................................................................... 8

1.3.3 Expected impact conditional on budget neutrality ...............................................................9

1.3.4 General equilibrium and complementarity effect .................................................................9

1.3.5 Inflation and effect on prices ............................................................................................................9

1.4 Simulations, trials and experiment to introduce UBI around the world ............................10

1.4.1 Simulation-Indonesia ........................................................................................................................10

1.4.2 Simulation-India ..................................................................................................................................11

1.4.3 Simulation-Canada .............................................................................................................................11

1.4.4 Evaluation of UBI in Alaska’s Indigenous peoples .............................................................. 12

1.4.5 The Basic Income Experiment 2017–2018-Finland ............................................................ 12

1.4.6 Large scale unconditional cash transfer in Iran ................................................................... 12

1.5 Necessary and sufficient condition for UBI ...................................................................................... 13

1.5.1 Fiscal inclination, universality vs. generosity trade-off and UBI sustainability.... 13

1.5.2 Administrative capacity .................................................................................................................. 13

Chapter 2 The landscape of social protection and security in Indonesia ....................................

2.1 The development of Indonesia’s social protection system ........................................................ 15

2.1.1 Pre AFC 1997-Crisis Period ............................................................................................................ 15

2.1.2 Post Crisis until 2008 ........................................................................................................................ 16

2.1.3 The year of 2008–now ..................................................................................................................... 16

2.1.4 Local initiatives for universal children benefit .................................................................... 17

2.2 The development of Indonesia’s social security system ............................................................ 17

2.2.1 The period of 1945–1960s .............................................................................................................. 17

2.2.2 The period of 1960s–mid 1990s ................................................................................................... 17

2.2.3 Aftermath of the AFC in 1997–2004 ........................................................................................ 18

2.3.4 The year of 2004–now ................................................................................................................... 18

vUNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

2.3 Benefit Incidence of Social Assistances and Energy Subsidy ...................................................23

2.4 Stocktaking of impact evaluation on social protection and social security

in Indonesia ....................................................................................................................................................24

2.5 Remarks ............................................................................................................................................................ 25

Chapter 3 Potential of UBI in Indonesia’s Landscape ..............................................................................

3.1 Context ..............................................................................................................................................................26

3.2 General consideration of UBI: efficiency and equity trade-off ................................................26

3.3 Determining the context and the amount of budget ..................................................................27

3.4 A Quasi UBI: Reallocating fuel subsidy budget into a large-scale cash transfer amidst

Covid-19 outbreak .......................................................................................................................................30

3.5 Existing regulation in social protection and expenditure policies to support UBI

implementation ............................................................................................................................................33

3.6 Cost and administration challenges in administering UBI .......................................................34

3.7 Governance capacity in implementation ..........................................................................................34

3.8 Alignment with national development priorities......................................................................... 35

3.9 Macro policy considerations ...................................................................................................................37

Chapter 4 Case Study ..................................................................................................................................................

4.1 Context ..............................................................................................................................................................38

4.2 The local fiscal capacity of DKI Jakarta Province .........................................................................38

4.3 Types and coverage of the existing local social protection programs in DKI Jakarta ..39

4.4 Administrative capacity .......................................................................................................................... 40

4.5 Microsimulation results ............................................................................................................................41

Chapter 5 Conclusion .................................................................................................................................................

References ..............................................................................................................................................................46

Appendices ............................................................................................................................................................. 51

vi UNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

LIST OF TABLES

Table 1 The Summary of Social Assistance and Social Security in Indonesia ......................... 21

Table 2 Summary of impact evaluation of social protection in Indonesia ................................26

Table 3 The amount used for reallocation scenarios ...........................................................................28

Table 4 Total budget for energy and non-energy in APBN 2020 ..................................................33

Table 5 Generosity level by decile and commodity subsidy budget reallocated ....................34

Table 6 Revenue composition of DKI Jakarta and the national level ......................................... 40

Table 7 Spending composition of DKI Jakarta and the national level ........................................41

Table 8 Budget allocation for subsidy and social assistance in DKI Jakarta Province, 2020 .

42

Table 9 DKI Jakarta households and individuals in BDTKS 2019 ................................................ 44

Table 10 Summary of generosity and horizontal equity from microsimulations ..................46

viiUNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

LIST OF FIGURES

Figure 1 The Scheme of Social Protection in Indonesia .....................................................................23

Figure 2 Coverage and share of beneficiaries of social assistance programs and energy

subsidy .....................................................................................................................................................................24

Figure 3 Generosity level per household per year in rupiah across decile of inclusion (UBI

=10) .............................................................................................................................................................................28

Figure 4 Optimum social welfare with varying degrees of inclusion for PKH budget in

2018 ...........................................................................................................................................................................29

Figure 5 Horizontal equity with varying degree of inclusion for PKH budget in 2018 ......29

Figure 6 Implied marginal tax rate across household income level .............................................30

Figure 7 Benefit per household per year for selected commodity budget being reallocated

to cash transfer (in Rupiah) .............................................................................................................................32

Figure 8 Optimum social welfare with varying degrees of inclusion for total energy

subsidy budget in 2020 .....................................................................................................................................33

Figure 9 Horizontal equity with varying degree of inclusion for reallocation of budget for

energy into UBI ....................................................................................................................................................33

Figure 10 Scatterplot of provincial social protection spending per capita and total revenue

per capita during the period of 2001–2012 (average) ..........................................................................39

Figure 11 Benefit per individual, per adult individual and per household per year from

reallocating total social protection budget to UBI in DKI Jakarta (in Rupiah) ........................41

Figure 12 Number of households and individual in each decile, DKI Jakarta – 2019..........42

Figure 13 Optimum social welfare with varying degrees of inclusion for social protection

budget of DKI Jakarta in 2020 ......................................................................................................................43

Figure 14 Horizontal equity with varying degree of inclusion for social protection budget

of DKI Jakarta in 2020 ......................................................................................................................................43

Figure 14 Steps for implementing a full UBI in Indonesia ................................................................45

viii UNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

LIST OF APPENDICES

Appendix 1 Proxy Mean Testing Regression Results with SUSENAS 2018 .............................. 51

Appendix 2 The generosity level across different scenarios of fund reallocated at

national level microsimulation .....................................................................................................................54

Appendix 3 The social welfare across different scenarios of fund reallocated ..................... 55

ixUNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

ABBREVIATIONS

AFC Asian Financial Crisis

ASABRI Asuransi Sosial Angkatan Bersenjata Republik Indonesia

ASKESKIN Asuransi Kesehatan Keluarga Miskin

ASLUT Asistensi Sosial Lanjut Usia Telantar

ASPDB Asistensi Sosial Penyandang Disabilitas Berat

ASTEK Asurasni Sosial Tenaga Kerja

BDTKS Basis Data Terpadu Kesejahteraan Sosial

BKF Badan Kebijakan Fiskal

BKKBN Badan Kependudukan dan Keluarga Berencana Nasional

BKM Bantuan Khusus Murid

BLSM Bantuan Langsung Sementara Masyarakat

BLT Bantuan Langsung Tunai

BOS Bantuan Operasional Sekolah

BPJS Badan Penyelenggara Jaminan Sosial

BPNT Bantuan Pangan Non-Tunai

BPNT Bantuan Pangan Non-Tunai

BPS Badan Pusat Statistik

BPS Badan Pusat Statistik

CCT Conditional Cash Transfer

DASPERI Dana Kesejahteraan Pegawai Negeri

DFAT Department of Foreign Affairs and Trade

DKI Daerah Khusus Ibukota

ENAHO Encuesta Nacional de Hogares

GDP Gross Domestic Product

GMI Guaranteed Minimum Income

IDT Inpres Desa Tertinggal

ILO International Labour Organisation

JAMKESMAS Jaminan Sosial Masyarakat

JAMSOSTEK Jaminan Sosial Tenaga Kerja

JKN-KIS Jaminan Kesehatan Nasional-Kartu Indonesia Sehat

JKN-PBI Jaminan Kesehatan Nasional Penerima Bantuan Iuran

JPS Jaring Pengaman Sosial

JPS-BK Jaring Pengaman Kesehatan Bidang Kesehatan

KAT Pemberdayaan Komunitas Adat Terpencil

KJMU Kartu Jakarta Mahasiswa Unggul

KJP Kartu Jakarta Pintar

x UNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

KKS Kartu Keluarga Sejahtera

KLJ Kartu Lansia Jakarta

KPS Kartu Perlindungan Sosial

KTP Kartu Tanda Penduduk

KTP Kartu Tanda Penduduk

KUBe Kelompok Usaha Bersama

KUR Kredit Usaha Rakyat

LPG Liquified Petroleum Gas

LRT Light Rail Transit

MRT Mass Rapid Transit

NIK Nomor Induk Kependudukan

NRTC Non-Refundable Tax Credit

ODA Official Development Assistance

OECD Organisation for Economic Cooperation and Development

OPK Operasi Pasar Khusus

OPSM Operasi Pasar Swadaya Masyarakat

P2KP Program Penanggulangan Kemiskinan di Perkotaan

P3DT Proyek Pembangunan Prasarana Pendukung Desa Tertinggal

P4K Pembinaan Peningkatan Pendapatan Petani-Nelayan Kecil

PDF Permanent Dividend Fund

PDM-DKE Program Pemberdayaan Daerah dalam Mengatasi Dampak Krisis

Ekonomi

PDS Public Distribution System

PIP Program Indonesia Pintar

PKH Program Keluarga Harapan

PKKU Program Pendidikan Kecakapan Kerja Unggulan

PKPS BBM Program Kompensasi Pengurangan Subsidi Bahan Bakar Minyak

PKW Program Pendidikan Kecakapan Wirausaha

PKWU Program Pendidikan Kecakapan Wirausaha Unggulan

PMT Proxy Mean Testing

PNMPM Program Nasional Pemberdayaan Masyarakat

PPK Program Padat Karya

PPLS Pendataan Program Perlindungan Sosial

PPP Purchasing Power Parity

PSE05 Pendataan Sosial Ekonomi 2005

RASKIN Beras untuk Rakyat Miskin

RASTRA Beras Sejahtera

RS-RTLH Rehabilitasi Sosial Rumah Tidak Layak Huni

SCF Social Protection Floor

SIM Surat Izin Mengemudi

SUSENAS Survey Sosial Ekonomi Nasional

1UNIVERSAL BASIC INCOME: FEASIBILITY APPLICATION IN INDONESIA

TASPEN Tabungan dan Asuransi Pensiun

TEPAK Temu Penguatan Kapasitas Anak dan Keluarga

TNP2K Tim Nasional Percepatan Penanggulangan Kemiskinan

UBI Universal Basic Income

USD United States Dollar

UUD 1945 Undang-undang Dasar 1945

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CHAPTER 1CONCEPTUAL FRAMEWORK OF UNIVERSAL BASIC INCOME (UBI)

1.1 What is UBI?

Universal Basic Income (UBI), is a regular fixed transfer to individual citizens regardless of their income level (Hanna and Olken, 2018; Tondani, 2009). There are four features around the idea of UBI: universality, unconditionality, transfer-modality, and individuality (Gentilini et al., 2020a; Van Parijs, 2004). Universality refers to no exclusion as all citizens are eligible, although whether non-citizens are eligible or not is another consideration. Unconditionality means there is no requirement as, for example, the proxy mean-test does for anti-poverty program targeting. Individuality defines that the benefit is on an individual basis, not on the household. Last, transfer-modality refers to how the benefit is given; it is in the form of cash.

1.2 Why Indonesia could to consider for implementing UBI?

As one of the developing countries with an evolving social protection system, some unique UBI features have attracted the Indonesian government to explore UBI as one of the policy alternatives (Wibisono, 2017). The In her statement in 2017, the Minister of Finance attracted to the UBI because some of its main features work just like social protection programs. Among its key features; the universality element is the most appealing for Indonesia. The reason was the social protection programs have been facing inclusion and exclusion error for many years (Hanna and Olken, 2018). Moreover, the full considerations to adopt UBI should also to expect other beneficial features of UBI originated from its unconditionality and simplicity of modality. The idea is to enhance the system by integrating fragmented transfer programs that are currently being implemented.

Some studies on Indonesia’s conditional cash transfer, namely Program Keluarga Harapan (PKH)found mixture results on educational and health impact (Kusuma, Cohen, McConnell, & Berman, 2016; Kusuma, McConnell, Berman, & Cohen, 2017; Triyana & Shankar, 2017conducted in 2007 and 2009. This included 6869 pregnancies and 1407 midwives in 180 control subdistricts and 180 treated subdistricts in Indonesia. Outcome measures ANC component coverage index, a composite measure of each ANC service component as self-reported by women, and ANC provider quality index, a composite measure of ANC service provided as self-reported by midwives. Each index was created by principal component analysis (PCA,and Hadna & Kartika, 2017). The mixed results raise a doubt whether conditionality is the right way in ensuring the effectiveness of the programs. Hence, it stimulates rethinking


about relaxing the social protection conditionalities, which is the second feature of UBI. Further, recent policy effort to switch from in-kind nature of food assistance program (Raskin) into payment-based, namely Bantuan Pangan Non-Tunai (BPNT), is also another example for the demand for adopting cash-modality in social assistance program (TNP2K, 2017), the third feature of UBI. One of the argumentation is that cash transfer is superior in terms of making food consumption dietary diversity, apart from, objective to increase nutritional intake (see for example Hidrobo et al., (2014)).

Apart from these features, considerations to introduce UBI are not only about to improve social protection. UBI arguments cover three key narratives: social protection improvement, the fear of automation, and natural resource dividends (Gentilini et al., 2020). The first story is about a concern to improve social protections due to its complex and fragmented programs. Universality seems to be a panacea for targeting difficulty if the conditionality is fulfilled. The second narrative relates to the fear of induced unemployment from artificial intelligence emergence. Here, UBI is believed as a viable insurance instrument against this disruption. The last story is about the idea of natural resource is a collective wealth of citizens and is one of promising escapes from poverty. Last, with the health crisis of the Covid-19 outbreak, aspiration for universal transfer emerges due to its adverse economic effect affects all income groups, not only the lower income groups. On top of these narratives, how UBI redistribute income is universal and avoid exclusion. The promising outcome from universality is that it enhances horizontal equity as everybody gets the transfer.

Today’s social protection around the world is structured with various and mix of programs. One of the explanations for this arrangement is that the role of social protections primarily driven by major economic reforms, such as energy subsidy removal (Gentilini et al., 2020) and minor attention to the unified beneficiary database. One major challenge for developing economies is information about household income hardly presents (Olken, 2019). As for Indonesia, for example, in the absence of unified information on identified beneficiaries, multiple programs are offered by different government agencies with different client and objectives (Tohari et al., 2019). Hence, UBI is attractive because of its universality and conditionality feature. They could replace those complexities of conventional targeting. That is by lumping together these mix of programs into single cash transfer. Although, there might be concerns about costs associated with the universalness of the coverage and further, the potential reduced amount of benefit to the beneficiaries, apart from political acceptance.

Regarding the second narrative, artificial intelligence seems to be a real threat for restructuring job and its effects on worker displacement. See, for example, Arntz et al. (2016) for an optimistic view with OECD countries or Acemoglu and Restrepo (2019) with US data. One of the reasons for a positive trajectory is the estimated destroyed job by automation is often overstated, and not all jobs are destroyed by automation. Indeed, Acemoglu and Restrepo (2019) find that automation also creates new tasks in which labour has a comparative advantage. As for the case of Indonesia, the early diagnostic analysis predicts that the adverse effect of automation comes through its integration to the global value chain (Salam et al., 2018). On top of these, automation


effect to welfare seems to go through inequality as much of the affected employment segment are low skilled labours (World Bank, 2019). In this regard, the universality of UBI fits into contexts of the issue if the aims are equity.

The last narrative relates to the idea that natural resources are a form of wealth that no one has a claim to have produced. Hence, distributing natural resources’ rents to all citizens as a universal and unconditional cash transfer is the most transparent ways to comply with this perspective (Segal, 2011). He demonstrated that if each developing country adopted the policy, then the number of individuals living below $1 per day would be reduced by between 27% and 66%. In addition, similar promising ideas that have been implemented within a short time in Mongolia since 2010, The Islamic Republic of Iran since 2011 and two local initiative in the United States of Alaska (2012) and the Eastern Band of the Cherokee Nations featured this model.

The current outbreak of Covid-19 infection in more than 130 countries creates slowing down economy due to demand and supply shock due to social distancing and containment measures taken by government. The most severely affected would be lower income groups from this economic crisis induced by health crisis. Moreover, concerns also go to the aspiring middle income who are also vulnerable toward the slowing down economic activity in first impacted sectors such as tourism, transportation, and all types of activities that cannot be retained by working from home. As it is difficult to distinguish who are really impacted by the pandemic, thus a quick suitable response would be a universal transfer. In this situation, the aspiration to implement a universal-like transfer emerges. This specific narrative is a novel and recent motivation to make UBI as alternative policy in the affected countries by Covid-19 outbreak.

Indonesia is not the only country to open exploration to adopt UBI (Hanna and Olken, 2018). Other simulations intended to explore the possibility of adopting UBI were present in some countries, such as India (Coady and Prady, 2019, and that it can generate broad support for structural reforms. Using India as an illustration, the paper discusses the trade-offs that need to be recognized in adopting a UI in these contexts. It shows that replacing the 2011 Public Distribution System (PDSHernández, 2005). Currently, among initiatives, Iran and Mongolia are the only two countries that had implemented a full feature of UBI. The rest of the countries implemented variant-type or pilot type (See Table 1.1. of Gentilini, Grosh, Rigolini, & Yemtsov, 2019). In this regard, the bottom-line question is what UBI offers so that it moves from academic debate into a serious policy agenda or proposal. The next section overviews the advantages and disadvantages of introducing UBI.

1.3 What UBI offers and what might not?

There are at least three ways to look at this question. First is on the conceptual view. Second is on assessing the simulation-based comparison between instated UBI versus the existing social protection program. The third is by looking at some local or internal effect generated by trials and experiments in implementing UBI by some countries.


1.3.1 Low transaction cost

From the conceptual perspective, UBI has the core ensuring universality. That is to make every citizen within a political community covered by social protection. By this simplicity of its nature, universality offers some benefits in terms of targeting. With everyone is eligible for a transfer (except age limitation, such as above 18, as children often have their own dedicated programs), the universality bypasses inclusion and exclusion error that are inherent in needs-based approach such as proxy mean test (Hanna and Olken, 2018). Parallel with this benefit, the administrative costs associated with targeting (Kleven and Kopczuk, 2011) and utilising the benefits (Isaacs et al., 2016) can be significantly reduced. Moreover, as for the beneficiaries, there should be no case of stigma and psychological effect of becoming a targeted group that could affect their state of mental condition.

Moreover, universality avoids negative externalities associated with mistargeting, such as weakening social capital issue (Cameron and Shah, 2014). In sum, the benefit incidence of universality seem promising, but adding up the recipients of the status quo toward everyone to become eligible would be a major policy move. There are issues of budget neutrality, sustainability and relative effect by generosity level.

1.3.2 Sustainability

A large-scale basic income transfer could be financed by expanding tax, switching from other expenditures (price subsidy or other existing social protection), or any external funding. With 2016 figures, Banerjee et al. (2019) estimated that the percentage of existing Official Development Assistance (ODA) assistance of a set of Low-Income Countries to tax revenue in per capita and Purchasing Power Parity (PPP) terms is about 27%. Hence, any expansion toward universal coverage would require a substantial share of other resources. If this amount is obtained sustainably, one might expect the feature of continuous and long-term benefit as UBI proponents demand would have prevailed. Otherwise, it lasts in a short period. See, for example, the gradual decline in benefit dose followed by termination of the transfer only after few years as the case of Mongolia, which initiated in 2010 and the Islamic Republic of Iran in 2011 (Gentilini et al., 2020).

1.3.3 Expected impact conditional on budget neutrality

A further implication of switching toward UBI is that its conditionality on budget expansion, and this is related to dose or amount effect per individual of the recipient. If budget is neutral, the amount disbursed under UBI in contrast to the status quo would be significantly smaller as the case of Indonesia and Peru (Hanna and Olken, 2018). There are implications of this reduced amount per person. First is about gaining popularity and support among the beneficiaries of existing targeted programs, which primarily individuals at the bottom of income or expenditure distribution.


Furthermore, this circumstance leads to lower acceptance from the general public. In addition, the concern is also about to what extent small amount matters in changing the poverty when there is also a potential effect of induced inflation by massive positive income shocks (Gentilini et al., 2020). This concern is valid as, for example, the case of inflationary effect in the Islamic Republic Iran during the period of 2011-2014. In this occasion, as for the case of Indonesia and Peru, Hanna and Olken (2018) switching toward UBI entails a substantial trade-off between eliminating targeting error and giving smaller transfer on a per-beneficiary basis. In this regard, the UBI concept is closely related to the International Labour Organisation (ILO) concept of social protection floor (SCF). It ensures that anyone who needs social protection can access it at any time.1 The ultimate scrutiny is at the core of benefit incidence. That is to ensure that the most vulnerable groups receive adequate amount of benefit.

1.3.4 General equilibrium and complementarity effect

A unifying mixture of social assistances into a single lump sum per beneficiaries might create a distinct general equilibrium effect. Further, a distinct complementarity effect also might presence that is the absence in the fragmented social interventions. There are four relevant areas of effects: inequality, employment, wage, and prices.

By universality, the UBI shifts the dominating portion of targets population from the lower tail of income distribution toward the inclusion of the less poor segment of population. It might be the case the propensity to consume varies across income percentiles so that the general equilibrium effect might be pro to the welfare of the wealthier. This raises the ambiguity effect on inequality. In the first instance UBI might yield quality enhancing but then it followed by the opposite effect from the general equilibrium as simulation with France data by Magnani and Piccoli (2019) suggests. The general equilibrium framework also relevant to consider the classical question regarding the work incentive effect of UBI. At the individual level, microeconomics labour-leisure choice sense guides us a quick prediction of adverse labour incentive effect of giving negative income tax as UBI does. In the general equilibrium set up; however, the final effect is depending on the interaction of labour supply and income tax raised to finance the universal income. Reducing unemployment under unionised labour market with bargaining is present (Van der Linden, 2004). Last, the point is the impact if there is an interaction between ones’ additional income and their additional neighbourhood income induced by UBI (complementarity effect). Due to limited evidence on this case, there is little evidence about this at the moment (Banerjee et al., 2019).

Developing country-specific: the poor’s constraintDeveloping countries feature specific characteristics, especially on how the poor respond to universal income transfer. Banerjee et al., (2019) identify potential limitations of UBI in reaching the desirable development outcome

1 https://www.ilo.org/global/about-the-ilo/newsroom/news/WCMS_669390/lang--en/index.htm


for the poor in the developing countries. They argue two main points in which the constraints work. First is from the fact that developing countries’ market for the poor in developing income-generating opportunities are often missing. Second, there are some psychological burdens of being poor that can generate poverty traps through diminishing cognitive and aspiration toward productive activities. The study infers that giving the poor money is a necessary condition for empowerment, yet it is not a sufficient condition without the existence of one-on-one training programs as well as improving access to the credit market and insurance along with income transfers. Despite, some studies in contrast shows that giving cash transfer increases women empowerment and so do their economic and social outcomes (Fultz and Francis, 2013).

1.3.5 Inflation and effect on prices

One general equilibrium effect attributed to massive income transfers is inflation, especially in a short period. There are two mechanisms in which the price effect takes places. One is about how modality (i.e. cash injection, affects the economy through changes in household spending across the income distribution). Another mechanism is to what extent sourcing of UBI coming from an inflationary option such as subsidy reform. The recent empirical experiment shows that cash transfer, relative to in-kind modality, has an inferior inflationary effect on the local price (Cunha et al., 2019)which could lead to lower prices than under cash transfers. We test and confirm this prediction using a programme in Mexico that randomly assigned villages to receive boxes of food (trucked into the village. In addition, concern about the inflationary effect of introducing UBI can also be addressed to the financing source. If, for example, the budget is not neutral and an additional source of fund is coming from subsidy reform (removing existing fuel price subsidy), then the inflationary effect is apparent (Ter-Minassian, 2020).

Leisure and labour choiceOne of the concerning effects is, does UBI discourage works? The answer is on the work incentive that UBI provides concerning labour–leisure choice. It is shown that among programs reviewed covering conditional and unconditional cash transfer programs, there is no evidence that unconditional transfer discourages works (Banerjee et al., 2017; Bastagli, 2020). One of the fears about this adverse effect is because people often made a confusion between UBI and quasi-UBI, such as guaranteed minimum income (GMI) (Gentilini and Grosh, 2020). Indeed, a scheme like GMI discourages work as its definition suggests which ensures a minimum to any family that falls below a given income threshold.

The following section summarizes the simulation of switching into UBI from any existing social assistance programs in Indonesia, India, and Canada. From these reviews, it is shown that reallocating budged toward UBI entails concern about the benefit size per individual by imposing universality. In addition, the size can be increased by relying on saving from costs associated


with targeting problem as well as a distortionary allocation for commodity-based subsidy. Then it followed by a brief review on trials of UBI in some countries. In the form of local level UBI, experiences from Alaska shows that the program has a substantial mitigating effect on poverty for rural Indigenous families. At the country level, Finland’s experimental policy to introduce UBI with randomisation and Iran’s large-scale unconditional cash transfer show that there is no effect on employment. The effect on welfare and inflation are mixed. In Finland, there is an improvement in outcomes related to health and stress level, showing that UBI has a significant well-being effect. On, the other hand, the Iranian case showed a temporary welfare reduction due to a surge in inflation.

1.4 Simulations, trials and experiment to introduce UBI around the world

1.4.1 Simulation-Indonesia

Hanna and Olken (2018) simulate the trade-off between Universal Basic Income (UBI) and targeted transfers in two developing countries (Indonesia and Peru). Worldwide, targeted cash transfer is a famous government policy for poverty reduction. However, targeted cash transfers implemented in Indonesia and Peru, for example, have some problematic issues. They include a high cost of targeting, complex administration, inclusion error (people who are not entitled but get the transfer), or exclusion error (people who are entitled but not in the list of beneficiaries). This problem arises because of not well-developed population database in developing countries. Therefore, to overcome these problems, UBI deserves more attention.

In assessing the trade-off between UBI and targeted transfers, they conducted a simulation by using national household socio-economic surveys, SUSENAS for Indonesia and ENAHO for Peru. The simulation begins by determining targeted households by a proxy-means method (using household assets data to predict consumption /expenditure). Predicted income is then juxtaposed with actual income to identify potential inclusion and exclusion error. The magnitude of the two errors depends on the income cut-off level as a basis of eligibility requirement. The larger the cut-off value, the larger the inclusion error, then it leads to the implementation of the UBI (everyone gets the transfer).

The second simulation is conducted by evaluating the movement of benefits received by the household in line with a change in the cut-off level. At a certain budget level, with the larger cut-off value, the benefit that received by each household will be getting smaller. In other words, a very large cut-off (the UBI scheme is applied) will further reduce the value of the benefit received by households. For the record, the budget level has also been added with the targeting costs because with a large cut-off (UBI scheme), no additional costs are needed for targeting.

The third simulation is conducted by estimating the social benefits represented by the household utility. This simulation aims to determine the cut-off point/level, that provides a maximum utility (social benefit) for households. From the simulation, the


cut-off value that gives maximum utility is at a certain level and then decreasing along with the larger cut-off value. Therefore, it can be concluded that targeted transfers still provide higher utility than UBI schemes. Hence, based on the simulation, they infer that the targeted transfer scheme, although imperfect, will generate better benefit than the UBI scheme.

Hanna and Olken (2018) stated that the problem of targeted transfer is not only about inclusion and exclusion error. Other issues are the political support, horizontal equity2, transparency, and the potential labour market distortion. Although the last issue has been addressed somewhere else that might be less concerning, see, for example, Banerjee et al., (2017) or Bastagli (2020).

Considering the equity trade-off between social assistance and UBI in Indonesia, they suggest continuing the existing programs with targeting improvement. Hanna and Olken (2018) provide some recommendations for improving the targeting scheme. First is community-based targeting (the government involves the community in target setting). Second is self-targeting (the poor people can independently apply for the program, and then the government conducts assessments). The third is the conditional transfer (the beneficiaries are given specific targets (e.g. school attendance) as a condition for receiving assistance). The practicality that in principle, are diametral to UBI practice.

There are some potential consideration and exercise. First, the trade-off analysis only incorporates the reduction of administrative costs on poverty targeting for UBI. Indonesia’s budget for social assistance, however, comprises also allocations for the prices-subsidised commodities, especially energy. Adding up this allocation to UBI scheme simulation might have different trajectory on the amount disbursed for the universal coverage, and it turns out to open to discussion about the gain of political support from it. Second, the analysis is based on a scenario that the initiative is at the central government level. As seen below, some initiatives are at the local and decentralised unit of governmental administration. Thus, testing the simulation at the context of localities might have different implications on the trade-off, especially to the region with a quite non-neutral budget allocation for UBI scenario.

1.4.2 Simulation-India

Coady and Prady (2019)and that it can generate broad support for structural reforms. Using India as an illustration, the paper discusses the trade-offs that need to be recognized in adopting a UI in these contexts. It shows that replacing the 2011 Public Distribution System (PDS provide an update on the evaluation of social protection programs in India and then conduct a trade-off simulation if UBI is applied as a substitute for these programs. Public Distribution System (PDS) is a system used by the Indian government by providing subsidies on rice, wheat, sugar and kerosene for eligible households. In addition, the Indian government also provides subsidies on fuel oil. PDS has serious problems such as imperfect targeting and distribution due to weak governance.

2 With the switch from targeted social assistance to UBI, horizontal equity will initially decrease to a certain cut-off point then gradually increase along with the higher cut-off. In this regard, the UBI scheme becomes more attractive in the equity point of view.


The first simulation is conducted by comparing the benefit received between the PDS and UBI scheme. The benefits are assessed from the quality of coverage, targeting, and generosity. Based on the simulation, UBI will be superior in terms of coverage, but on the other hand, UBI will encourage a decrease in benefits received for low-income households. However, this decrease can be reduced if the operational costs of PDS and assistance for high-income households are eliminated to be transferred to low-income households.

Then, the second simulation is conducted by identifying the benefit if the energy subsidy program is reallocated to UBI. In contrast to the first simulation, the results of the second simulation show that UBI will provide larger benefits to lower income when compared to the subsidy scheme. In addition, it will also reduce fiscal pressures and promote energy efficiency related to environmental and health issues.

Here, UBI can be an efficient and straightforward policy alternative to reduce poverty and improve efficiency by removing distortionary subsidy on commodities. However, this policy requires an in close communication approach to gain political support. At methodological scope, the simulation that this current report will carry is a similar exercise to the above-mentioned Indian case.

1.4.3 Simulation-Canada

Stevens and Simpson (2017) documented the policy of social assistance in Canada through cash transfers and taxes. One of the issues is that the policy for granting tax credit, in general, cannot be applied for low income because the tax credit becomes non-refundable. Therefore, they tried to do a simulation by reallocating a portion of the non-refundable tax credit (NRTC) as a UBI financing. The simulation is carried out through three steps, 1) reallocation of Federal NRTC to UBI, 2) the reallocation of Provincial NRTC to UBI, and 3) combines Federal and Provincial NRTC to UBI.

From the simulation, the reallocation would be able to provide UBI funding of $51 billion from the federal government and $33 billion from the provincial government. Then, the beneficiaries can be received the transfer in the range of $8.755 per person in British Columbia to $13,983 in Quebec. The poverty rate will decrease by 57%, from 12% to 5.2%, and inequality (Gini ratio) decreased 6.8% from 41.3% to 38.5%. However, this cash transfer is limited to eligible people (not everyone). In addition, it should be noted that if most of the tax credit is reallocated into UBI, it will certainly affect the supply of labour, which may lead to disincentive condition. Therefore, determining the portion of the tax credit to be reallocated is important. The largest portion is only 38%; in this portion, the disruption effect on the labour supply will be the smallest one. The other issue that has not been resolved in this study is the cost of UBI implementation, which is estimated at $8.09 billion (9.7% of total UBI funding).


1.4.4 Evaluation of UBI in Alaska’s Indigenous peoples

Berman (2018) evaluates the impact of the implementation of UBI in Alaska or the Alaska Permanent Dividend Fund (PDF) on the poverty level, especially on Alaska Indigenous people. The national census conducted by the US Census Bureau has released data related to the poverty level in Alaska and other states. However, the data is a misinterpretation because the recording of household income tends to under/overvalue (e.g. PDF is not included as income), then the poverty level presented is not correctly stated. Therefore, to answer how the effect of PDF on poverty, he re-evaluates by describing income data in each household, and divide the income into two categories: without PDF and income with PDF, and then be compared with the income poverty threshold to get more accurate poverty level. In other words, he uses the counterfactual simulation to address the evaluation concern.

Based on the simulation, PDF can reduce the poverty level in Alaska, especially in Indigenous society. In more detail, this effect will be stronger in the poverty rates of children and the elderly: decreasing in the elderly but increasing in the child category.

1.4.5 The Basic Income Experiment 2017–2018-Finland

Kangas et al. (2019) conducted an experimental study to assess the effectiveness of UBI in Finland. Effectiveness is assessed from two aspects: the employment status and well-being by taking registration data and surveys (e.g. European Social Survey, International Social Survey Program, and others). Employment status is measured by the number of working days, while for well-being variables are measured by several aspects, such as social and financial well-being, subjective health, job-search activity and employment, and attitudes towards basic income. The object of the experiment is conducted on 2000 people included in the treatment group (receiving 560 euros monthly), 173.000 people included in the control group for employment outcomes, and 5000 people included in the control group for well-being outcomes. This experiment was carried out for one year in 2017.

Based on the empirical results, it is found that there is no significant difference between treatment and control groups in the aspect of employment status. From the perspective of well-being, the treatment group showed a significant improvement, as the decline in health problems, increasing the ability to concentrate, decreasing stress level, improving confidence about the future, and increasing the ability to deal with social issues. But from the aspect of trust to institutions, the existence of UBI does not have any significant effect.

1.4.6 Large scale unconditional cash transfer in Iran

Salehi-Isfahani and Mostafavi-Dehzooei (2018) conduct an empirical analysis to investigate the impact of large-scale cash transfer program in Iran on labour supply. In 2010, the President of Iran, Mahmoud Ahmadinejad, excise


and reallocate the subsidy in bread and energy to the unconditional cash transfer program that monthly distributed to the people at a fixed amount. This program is fully implemented in 2011 with the total cost 6.5% to GDP on 75 million individuals. The cash that monthly received is about 90 USD PPP per person or equal to 28% of the median per capita household income. This is one among two implementations of full-scale UBI in recent time, other than Mongolia (Gentilini et al., 2020).

In short, this policy makes a reduction on the poverty and inequality measure in the subsequent years because the poor get more benefits than the status quo subsidy program, however, the other potential adverse effects such as inflation and labour supply distortion worth to investigate. The effect of inflation had finally declined, and the effect on labour supply remains, there has been no general negative, adding a similar tone as the previous study provided.

Conceptually, the negative labour supply effect occurs when there is a high implicit marginal tax rate for the income near the limit related to income assistance, which is not happening in Iran because the program is universal. In addition, distortion in labour supply also depends on the condition of labour and credit market. The workers in Iran is constrained by rationed labour and credit market. The unemployment is high, so the leisure from the cash transfer may still less than if they are still on the job. Besides that, the workers are also constrained by their credit. This phenomenon may make the labour supply is at the current level or even increase.

1.5 Necessary and sufficient condition for UBI

1.5.1 Fiscal inclination, universality vs. generosity trade-off and UBI sustainability

To implement UBI, the essential infrastructure is administrative data. Implementing a large cash transfer means that the governments need to have access to by name, address and bank account of their citizen. However, this infrastructure is often hardly ready in most of the developing nations. As for example, the percentage of adult population who own account financial institution in 2017 is 48%.3 Frequently, the dataset is for the purpose of social protection targeting which only covers certain deciles of households from bottom income distribution. For example, Indonesia only covers bottom forty with its Unified Database or known as BDTKS. In addition, the tax registry also very low. For example, Indonesia only has slightly above ten percent of its labour force that has tax registration number which indicates a low potential coverage of existing database for implementing UBI. Also, Indonesia has a low coverage for its social security system for workers, namely BPJS Ketenagakerjaan. See Box 1.5 for a potential framework to prepare civil database merging for UBI implementation.

3 https://data.worldbank.org/indicator/FX.OWN.TOTL.ZS?name_desc=false


One of the most important consequences of introducing UBI is about benefit adequacy to fiscal space. Moving from targeting toward universal coverage is just simply multiplying the beneficiaries by many additional people. The political acceptance and public support then largely depend on how the government can increase the generosity of transfer and consequently considering the right financing. Accessing the fiscal space for UBI is one key first step (Ter-Minassian, 2020).

At the end, one of concerning outcomes from implementing UBI would be poverty incidence. Rigolini et al. (2020) suggest that the micro-simulation of replacing existing social assistance with UBI would not significantly reduce poverty without increasing generosity or the budget is neutral. The similar result is also true for inequality concern. The consequence emerges because with budget neutrality, per capita benefit would be lower, and individuals in the lower tails of the distribution are becoming worse off. The simulation found exception case in Russia. This is due to the existing condition where the poor receive a substantially lower share of cash transfers than the rich. The simulation results suggest that the societal preference toward equity and poverty reduction might need to be considered. Increasing generosity was the only way to make poverty reduction effect take place. In the case of a country like Indonesia, for example, increasing generosity to the level of currently received by the existing pool of beneficiaries still would not suffice to reduce poverty. In general, these differences in relative performance across countries reflect the progressivity of baseline programs. Thus, generosity and fiscal inclination is a real requirement for societal acceptance of switching existing social assistance toward UBI.

1.5.2 Administrative capacity

To implement UBI, the essential infrastructure is administrative data. Implementing a large cash transfer means that the governments need to have access to by name, address and bank account of their citizen. However, this infrastructure is often hardly ready in most of the developing nations. As for example, the percentage of adult population who own account financial institution in 2017 is 48%.

Frequently, the dataset is for the purpose of social protection targeting which only covers certain deciles of households from bottom income distribution. For example, Indonesia only covers bottom forty with its Unified Database or known as BDTKS. In addition, the tax registry also very low. For example, Indonesia only has slightly above ten percent of its labour force that has tax registration number which indicates a low potential coverage of existing database for implementing UBI. Also, Indonesia has a low coverage for its social security system for workers, namely BPJS Ketenagakerjaan. See Box 1.5 for a potential framework to prepare civil database merging for UBI implementation.

The next section provides the historical evolution of Indonesia’s social protection and social security system. The analysis intends to serve as


a stocktaking analysis about coverage and administrative capacity and readiness to implement UBI. The section shows that the existing transfer programs are quite extensive in terms of types, conditionality. The targeting improvement also impressive during the last five years marked by the establishment of a unified database. Yet, it only covers nearly half of the household from the bottom income distribution. On the other hand, the universally mandated social security system registry is recently only cover 80 percent of total adult population.

· The coverage of the current ID system. By 2020, the population in Indonesia is estimated to be close to 271 million (BPS, 2013). With this number,

Indonesia ranked fourth in the list of most populated countries in the world. The implementation of UBI needs personal data for every single citizen in a country. Hence, developing a valid data over 271 million may become the challenging issue. According to the recent data, the process of civil registration (e-KTP or citizen ID Card) in Indonesia was not finished. Up to 31 December 2019, the registration process reaches 98,7% of the total population that required to register or approximately 190 million people (Kemendagri, 2020). Meanwhile, the birth registration reaches 91,17% (Kemendagri, 2020). The complete coverage of citizens ID data is one of minimum requirements for UBI implementation. However, the high coverage remains insufficient if it is not accompanied by high validity.

· The plan of single identity number Government of Indonesia also plans to use the citizen identity number in e-KTP as a single identity that

can be utilized in anything such as economic activities, educations, legal works, public services, and so on. This plan is mandated in Law No. 23 of 2006. This mechanism is a powerful tool in promoting data validation. The individuals will have more awareness in civil registration process. Because, if he does not have a valid data, he will get a problem in his future activities. Nevertheless, this single identity concept is still far from ideal condition. The citizen does not only rely on e-KTP, but they can use another ID Card such as Driving License (SIM/Surat Izin Mengemudi) in their activity. This implies that there are many separated civil databases with at least two unique identity numbers basis (e-KTP and SIM). Besides that, e-KTP and SIM do not capture the socio-economic data. UBI implementation needs socio-economic data such as bank account or electronic pay system (e-money account) that used by the citizen. The other socio-economic data is also prominent in examining the complementarities of social protection programs and evaluating the impact of UBI in the future. Updated personal data is also important. It can be utilized to ensure the eligibility of the beneficiaries such as alive/death status.

· The necessary databases for UBI implementation Basically, the necessary databases for UBI implementation is three: 1) identity data such as unique identity

number, biometrics identity (fingerprint or iris eyes), alive/death status, and so on, to ensure the eligibility and validity of citizenship, 2) bank or e-money account to facilitate the payment process. 3) the other socio-economic data such as social protection beneficiary status, to ensure the complementarities of UBI with another social protection schemes. But there are two problems. First, the first database is not finished. Second, the first database is not completely integrated to the second and third database. The first problem might be solved by accelerating the registration process and aligning it with population census. The second problem might be solved by database merging scheme. However, this merging process needs more concern about security and legal basis.

· The Legal Issue of Civil Database Merging UBI is one of alternative public policy that can be utilized to create social welfare. But this policy needs

personal data usage to ensure the eligibility and the validity of UBI beneficiaries. Meanwhile, the ID system (civil database) in Indonesia cannot capture all data that needed in UBI implementation. Hence, the database merging strategy is one of the best alternative solutions. But the integration of separated database faces legal constraint. For example, Information and Electronic Transaction Law regulates that the usage of personal data by another parties can be conducted if it is determined by law or based on the owner approval (Law No. 11/2008). Then, Civil Administration Law regulates that the usage of civil database that produced by Ministry of Internal Affairs is limited only for public service, development planning, budget allocation, democracy development, and law enforcement. Bank Secrecy Law regulates that the banks are required to keep the customer information and limit the usage or exchange of bank customer only on certain conditions (Law No. 7/1992). Basically, there is no legal basis that supports civil database merging. Hence, to make it possible, the formulation of new laws might be needed. See details in Box 3.7 for potential database merging.

Box 1.5 Civil Database in Indonesia as a potential for UBI


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CHAPTER 2THE LANDSCAPE OF SOCIAL PROTECTION AND SECURITY IN INDONESIA

The previous chapter highlighted the necessary and a sufficient condition for implementing UBI concerning the fiscal space and generosity trade-off. The next chapter will examine the recent feasibility of fiscal space and calculate the generosity level of UBI. This chapter turns into an overview about Indonesia’s historical development of social protection assistance programs in which the direct cash transfers and insurance support are implemented. The overviews aim to know whether there was a basis in the form policy development and administrative capacity to consider a large-scale cash transfer as the initial condition needed to implement UBI. The overview started with the historical overview of social protection and security since Indonesia gained its independence in 1945, then it will be followed by a remark about whether the administrative readiness presents by looking at individual level or household level database developed by the country for its social protection and social security programs.

2.1 The development of Indonesia’s social protection system

Indonesia, like most of the developing nations, started its social program in an ad hoc manner at the time of responding economic crises. Most of these programs including food assistance, cash transfer and direct subsidy in health and education sector are continued as a broad set of social assistance programs. The administrative progress, however, gives a small room for implementing UBI scheme. First, the instrument that allows for the government to make direct payment to household as a result of the social protection programs is only partial. The existing database for social protection is limited to only up to 40% of total households. These households are the bottom deciles of the income distribution. Thus, to make the UBI implementation is feasible, the Indonesian government need to find another way to reach the gap of another 60% of population. The next section covers an alternative segment of social security dataset which has a larger coverage. The following sections overview the development of Indonesia’s social protection programs that generate the unified database (BDTKS) for anti-poverty targeting.

Most of Indonesia’s social protection programs, including the income or food assistance programs were introduced in responding to the economic crises in each respective time. For example, the Asian Financial Crisis (AFC) in 1998 has forced the country to introduce the food assistance which nowadays known as Raskin (rice for the poor). Or, the Global Financial Crisis in 2008 led to the introduction of the unconditional cash transfer of the BLT (Bantuan Langsung Tunai or the direct cash transfer) which later be renamed as BLSM (Bantuan Lansung Sementara Masyarakat


or the Temporary Direct Aid to People). All of these programs still present in different names or targeting coverage and its generosity level.

Among developing countries, Indonesia has been through several stages of its social protection and social assistance programs reform and development. Up to recently, the development stages of the social protection, or in general is also can be termed as anti-poverty programs, went through three main stages: first, second, and third generation (Tohari et al., 2019). Other authors such as Daly & Fane (2002) use three phases (pre-, during, and after the crises) for the phases.

2.1.1 Pre AFC 1997-Crisis Period

The first existence of social protection in the form of cash transfer was in the mid-1990s by the presence of BLT (Kwon and Kim, 2015). In this regard, if one would argue that whether the argument for having any universal income coverage on natural resource dividend-ground, it seems the justification was not evident enough in Indonesia’s history of its social protection development phases.

The major economic crises in 1997 triggered by twin crisis of the economy led to a different story of social assistance program. The crisis hit the economy badly and reversed the economic performance that previously had been achieved. The economy was contracted by 13.7% in 1998 (Suryahadi et al., 2012). The poor were among the severely affected by the contraction, along with the rapid rose in inflation by 78%. The poverty headcount went up from 23 million in 1996 to nearly 50 million people in 1998 (World Bank, 2012).

Given the situation, it was necessary for government to introduce set of packages of social safety net programs during the period of 1997–2001. The government introduced the JPS (Jaring Pengaman Sosial) consisting of subsidized rice (known as OPK), scholarship for elementary and junior high school students, block grants to school and health centres covering their expenses, nutritional supplements for infants and children, labour creation activities (public work), and regional development scheme (World Bank, 2012). These programs were ad hoc in nature responding the negative economic shock. Moreover, the program targeting was imperfect. The government relied on the database of families maintained by the family planning agency (BKKBN) that lacking precision in reaching the poor segment of population.

Post crisis period has brought Indonesia into a more reformist development agenda including social protection. The cash transfer, food assistance, scholarships to students and grants to schools have been continued since 2001. In the case of cash transfers, it was more noticeable to be reinstated in the two events of structural adjustment by removing gradually fuel subsidies in 2005 and 2008. Hence, the social assistance has been in the form of from responding to crisis to structural adjustment. Along with this, government also made the database of the recipient targeting to be more reliable.


Indonesia’s first anti-poverty program was the IDT program, Presidential Instruction for Underdeveloped Village. Overall, during the pre-crisis, the anti-poverty programs took forms of in-kind benefit in education and health sector, lagging village transfer (IDT), and village infrastructure program and loan scheme (Daly and Fane, 2002). In 1998, a subsidised rice (OPK) added up the lines of the program and had a major share on total government budget for anti-poverty programs. Some of these programs had been continued until 2004 with the share of budget for OPK declined along with a shift toward education and health sector anti-poverty programs. This period constitute what in general it is known as the first generation of Indonesia’s social protection programs (Tohari et al., 2019). In this period, the OPK was renamed toward Raskin, rice for the poor and used the household data from the central planning agency, BKKBN, as the means of targeting.

2.1.2 Post Crisis until 2008

The second generation of the programs run between the period of 2004–2008. To provide economic cushion from the increase of fuel price by the removal of its subsidy, the government launched a compensation package, namely PKPS BBM. Not much different in term of coverage to the first generation, the package includes scholarship and operational aid in education sector, health insurance (Askeskin), village infrastructure program, and the cash transfer program (BLT). In subsequent time, BLT was renamed toward BLSM. One of notable milestone in this period was that the government through BPS conducted a census for poor household for the first time. It was known as PSE05, Socio-economic Data Collection of the Population, aimed at replacing the use of BKKBN data (Tohari et al., 2019).

2.1.3 The year of 2008–now

In 2008, the government restructured the program and conducted a major change and for updating the list of program beneficiaries. This period become the flagship of the current landscape of the social protection program in which the Unified Database (BDTKS) was established. This is the third-generation phase in which the latest social protection programs are administered: Rastra or rice for the poor, JKN-PBI or subsidized social health insurance, PKH or the conditional cash transfer, and PIP or scholarship for student at risk. Data Collection for Targeting Social Protection Programs or PPLS08 is the updated version of PPSE05. However, the problem faced by PPSE05 was not completely removed by PPLS08. In 2011, the BDTKS, a harmonised and standardised list of intended beneficiaries that cover up to 40% bottom of income distribution was established.

Along these milestones of the first to the third generation of social protection program, one of the key changes is the refinement of the targeting mechanism. The attempts to examine the precision of anti-


poverty targeting program have been extensive, see for example an analysis by Alatas, Banerjee, Hanna, Olken, & Tobias (2012). Despite these efforts, inclusion and exclusion error remain valid concern in the discussion of how the government target the beneficiaries of the programs in Indonesia. One of negative externality associated with the mistargeting is social disharmony (Cameron and Shah, 2014). On top of these, two important highlights can be taken. First, the types and composition of the intervention has not evolved much, they are cash, food, education and health. Second, there has been a major improvement in administrative capacity in the form of perfection of database for intended beneficiaries.

The introduction of unified database (BDTKS/Basis Data Terpadu) was one of the most important targeting milestones for Indonesia’s social protection development. Formed in 2011, TNP2K, the national team for poverty reduction acceleration is the executive body under the Vice President office who responsible to design anti-poverty policy including for developing the BDTKS. BDTKS is based on census approach of poverty targeting by BPS known as PPLS (Pendataan Program Perlindungan Sosial or the Data Collection for Social Protection Programs). Recently, BDTKS covers bottom 40% of welfare distribution of Indonesian households. This decile accounts for about 30 out of 72 million households for social protections targeting.

The formation of TNP2K and the introduction of BDTKS can be said as the landmark for the latest generation of the Indonesia’s social protection programs. In 2013, the Indonesian government introduced the social protection card (KPS or Kartu Perlindungan Sosial) and recently renamed toward Kartu Keluarga Sejahtera (KKS) which makes the holder are eligible for social protection program of cash transfers (BLSM, PKH), food assistance (BPNT), health (JKN-PBI) and education (PIP). In addition to improvement in the targeting by the dedicated database, the current state of Indonesia’s social protection is more institutionalised.

However, in relation to UBI necessary condition that the government needs to have access to all citizens, the situations left a big administrative gap. First is that the government needs to cover the 60% gap of household database. Second, the completed dataset is still at household level and it should be expanded further to the individual level if UBI is going to be implemented.

2.1.4 Local initiatives for universal children benefit

There are also sub-national government initiatives in implementing universal child benefit in Papua and Aceh. The name of this program reflects the proudness and is the abbreviation of Bangun Generasi dan Keluarga Papua Sejahtera. Stipulated based on Government Regulation Number 23 Year 2018, Bangga Papua is a strategic program of local government in which supported by some development partners, including DFAT Australia. It covered 28,409 children in 3 districts: Paniai, Lanny Jaya, and Asmat. Bangga Papua uses


the universal child grant and unconditional cash transfer scheme, in which every child aged 0–4 years old is eligible for the grant. Cash transfer is paid through Bank of Papua account to mother (or female guardian), strengthening financial inclusion in Papua. The grant amounted Rp200,000 each month for each child aimed to help household to provide the adequate nutrition to ensure their child’s growth, reducing malnutrition, while also to support their education and healthcare needs. In Aceh, Geunaseh-Sabang is eligible for all local children from 0–6 years old (covered more than 5000 children). The grant delivered monthly amounted Rp150,000 for each child, transferred through the local bank account of their mother or caregiver. Number of total children involved was 4,850 of children aged 0–6.

2.2 The development of Indonesia’s social security system

Similar to social protection development, social security in Indonesia also have went through stages of progress. Suryahadi et al. (2017) outlines six stages for the development of Indonesia’s social protection system. It started with the post-independence period to recent time, especially the period after 2010. Similar to the time framework that was used to describe the Indonesia’s long-term development of its social protection program, the phases for the social security system can be divided into parts: the 1945–1960s, the 1960s–mid 1990s, aftermath of the AFC in 1997–2004, and 2004–now.

The current structure of Indonesia’s social security regime can be traced back to its early stage of the country’s economic development subsequent to its independence in 1945. The bottom line is that, the dynamics of the state’s intervention by promoting social security largely depend on the stage of the economic development. Mainly, the influential factor is external shock conditional on the economic growth and the fiscal space of the government. In this report, this sub-section is divided the long-term phases into three parts: the 1945–1960s, the 1960s–mid 1990s, aftermath of the AFC in 1997–2004, and 2004–now. The different phases contains two things: (i) to show the absence of resource dividend argument for UBI feasibility in Indonesia and (ii) to indicate the administrative readiness.

2.2.1 The period of 1945–1960s

During the period of the 1945–1960s, Indonesian economy was in a recovery mode from war to gain independence and was in a shape of an infant economy. Despite the potential speedy growth due to two main commodities’ boom, oil and rubber, Indonesian economy were not growing much in this period. Moreover, the political instability in the period of 1958–1965 made the economic growth even slower. As the country with high population growth after a war, Indonesia’s economic growth in this period was remarkably low. It was no more than 1%, less than the international performance for similar country at the time (Suryahadi et al., 2017, 2012). During this period, the social security for civil servant and their family for natural disaster (DASPERI) and pension (TASPEN) were established.


2.2.2 The period of 1960s–mid 1990s

During the period of 1960s–mid 1990s, Indonesian economy were under New Oder era with a pragmatic developmentalist approach. The world witnessed a tremendous economic performance of the country as shown by the average economic growth of 4.6% annually and the rose of income per capita from $50 in 1967 to $610 in 1991 (Suryahadi et al., 2017). The good performance of the economy was also benefited from two commodity booms period of 1973–1974 and 1978–1979. During this period, however, the social security system was minorly expanded by the establishment of pension program for military personnel, ASABRI. In this period, the DASPERI program was discontinued and merged with TASPEN.

2.2.3 Aftermath of the AFC in 1997–2004

Despite the state had ensured that all citizens had the right to decent work and livelihood as well as social protection for the poor and vulnerable as stipulated in the 1945 Constitution (Article 27, Subsection 2 and Article 34), Indonesia had never formed any administrative capacity for social protection and assistance program since its independence. Nor until the fourth amendment made in 2002 that explicitly mentioning the state obligation to form social national social security system.

The development health component of social security system marked by the establishment of PT ASKES in 1992. This type of health insurance is only for civil servant. As for private sector, were also started to present in this period by the ASTEK in 1977 and later to be developed to workers’ social security (JAMSOSTEK) in 1992. As for the poorer segment of population, the social security system does not have any health insurance until the introduction of Askeskin in 2005. The key milestone for the development of recent Indonesia’s health insurance system is the aim for a universal coverage of the insurance system by the establishment of BPJS in 2011.

The outline provides important highlights. First, the initial development for the modern Indonesia’s social security system can be traced back to 1963 when the country had for the first time its social security program for civil servant. This system then developed and accompanied by advancement of the types, coverage and benefit bot for civil servants and military personnel within subsequent decades. Second, the fourth constitutional amendment in 2002 provided a key milestone for a universal coverage of the social security system by asserting that “The state shall develop a social security system for all the people and shall empower the vulnerable and poor people in accordance with human dignity” (Article 34, Subsection 2).

2.3.4 The year of 2004–now

The implementing law of the constitutional mandate, the SJSN Law No. 40/2004, was enacted in 2004 and formed its implementing agency of BPJS


in 2011. The BPJS Law demands two administrative bodies: BPJS Health and BPJS Employment. All operating public agencies in the health and employment insurance will be transformed into the BPJS. They include PT ASKES, PT JAMSOSTEK, PT TASPEN and PT ASABRI. Amalgamation of these existing institution, at practical, provides a massive registry data of Indonesian. Despite the issue of missing middle (individuals at the middle of income distribution are missing) due to self-enrolment, the BPJS registry data is the largest available information about individual’s membership in health, employment, and social security.

Indonesia’s social security system also provide a baseline for administrative data needed for UBI implementation. It covers about 84% of the population or it equals to about 221 million individuals (Jakarta Post, 2019). This section explores to what extent this enormous registry data useful for exploring the feasibility of administering UBI with those registry data.

Other than programs mentioned above, the Indonesian government through line ministries such as Ministry of Social Affairs, Ministry of Education and Culture, and Ministry of Religious Affairs have been provided other various type of social protections, along with the major ones are summarized in Table 2.


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2.3 Benefit Incidence of Social Assistances and Energy Subsidy

Annually, the Government of Indonesia allocates social assistance spending and energy subsidies in the budget. The purpose of this budget allocation is to maintain households’ consumption, especially of the poor and vulnerable households. Ultimately, the objective of this budget policy is to reduce poverty and to redistribute income. In 2019, about 9.22% of the population lived below the national poverty line, while Gini coefficient was about 0.380%. The 9.22% poverty rate in 2019 was a slight improvement compared to the rate in 2018 which stood at 9.66%. In order to achieve lower poverty rate, or even zero poverty rate, Indonesia needs to increase the budget allocation for social assistance, as well as improving the quality of its implementation. The social assistance spending is targeting the bottom 40% of the income distribution while energy subsidies are provided by the government to maintain low and stable price of vital commodities and to maintain purchasing power of the middle and the lower income households. The social protection scheme in Indonesia is summarized in the figure below.

Figure 1 The Scheme of Social Protection in Indonesia

The energy subsidy is not an effective policy since all level of the population in the income distribution can have the same access to consume the subsidized commodities. The social assistance has a better targeting performance than the energy subsidy in targeting the bottom 40% of the income distribution. Hence, almost all social assistance programs such as the PKH (Program Keluarga Harapan), PIP (Program Indonesia Pintar, which is scholarships program for the poor), BPNT (Non-Cash Food Assistance) and health insurance for the poor and the vulnerable are more progressive schemes than the energy subsidy. Although the inclusion and exclusion error still exist in the implementation, the pattern shown in the chart below implies that with the social assistance programs, the poorer households obtain more beneficiaries coverage. In contrast the energy subsidy has relatively flat pattern, showing all level of income distribution obtain similar benefit, where in the case of 3 kg LPG subsidy, the pattern shows a regressive pattern. See Figure 2 for reference.


Figure 2 Coverage and share of beneficiaries of social assistance programs and energy subsidySource: Susenas 2018, author’s calculation

2.4 Stocktaking of impact evaluation on social protection and social security in Indonesia

Indonesia’s recent experiences to administer some of its social assistance programs yield a mix results about its effectiveness in reaching the expected outcome. Bazzi et al., (2015) evaluates the impact of the timing of the unconditional cash transfer in 2005 and they find no significant different between those who already had received it and those who had not at the setting of staggered implementation. Another example, the conditional cash transfer, namely PKH, also has different impacts across outcome of interests. See for example Kusuma et al., (2017)this paper provides evidence on the impact of household cash transfer (PKH who show that it increases nutritional status of the children but not for the health outcome of mother (Kusuma et al., 2016; Triyana and Shankar, 2017b)303,000 maternal deaths still occurred globally in 2015. One explanation is a considerable inequality in maternal mortality and the sources such as nutritional status and health utilization. One strategy to fight health inequality due to poverty is conditional cash transfer (CCT. Hadna and Kartika, (2017), on the other hand, shows that the CCT improves educational outcomes. Similar positive outcomes in education also shown by Cahyadi et al., (2018) apart from its positive cumulative effect on health utilisation and outcomes. As for the Askeskin program, Sparrow et al., (2013) show that the program improves public health care utilisation yet it increases out of pocket spending for health in the urban area. As for the Raskin program, the effectiveness is to be less pronounced as show by the regressiveness of the take up by the poor (Satriawan and Shrestha, 2018)a national rice price subsidy program for the poor. Using a household panel from the 2000 and 2007 rounds of the Indonesian Family Life Survey (IFLS. The other three studies that use non-impact


evaluations indicates the positive effect of PIP and JKN.

Table 2 Summary of impact evaluation of social protection in Indonesia

Program Nutrition Health Education Consumption Overall or welfare

PKH + (Kusuma et al. 2017, Cahyadi et al. 2018)

No effect mother health (Kusuma et al. 2016)

+ (Cahyadi et al. 2018)

Askeskin + and – (Sparrow et al. 2013)

Subsidi Rastra/Bantuan Pangan

- (Satriawan and Shrestha, 2018)

JKN + (Agustina et al. 2019)

BLT No effect Bazzi et al., (2015)

Complementarity effect and integration

+ (Tohari et al., 2019)

Source: Author’s compilation from various sources.

2.5 Remarks

Outlining the development of Indonesia’s social protection and social security system provides two important highlights:1. The landscape of the social protection and social security comprises a mixture of

direct and indirect transfers with gradual coverage from civil servant, military personnel, formal private sectors and finally the poor segment of the population.

2. The presence of social assistance for the poor were mainly crisis driven or in the form of social safety net at the time of economic downturn. The types and number of programs varies by year and could results in overlapping programs objectives and further it creates inefficiencies.

3. Despite of the crisis driven, the generations of social protection system has been evolved and bring a major administrative capacity to perform anti-poverty targeting program in a more precise way. However, the administrative capacity and database is still far from an ideal condition to implement a large-scale cash transfer as UBI required. The current anti-poverty database for intended beneficiaries only covers bottom 40% of the household income.

4. The subscription to the universal health and employment social insurance system, BPJS, might provide a better coverage in which it includes more than 80% of the population. Integrating the database with BDTKS and further with civil registration unique ID (NIK) might provide a more feasible avenue for the fulfilment of administrative capacity for implementing UBI.


CHAPTER 3POTENTIAL OF UBI IN INDONESIA’S LANDSCAPE

3.1 Context

The previous chapter provides an assessment in administrative capacity as a consideration to implement UBI in Indonesia. There is a gap for the government to reach all individuals in the economy in order to make a massive and radical move of a universal transfer. This chapter focuses on examining the various scenarios concerning the fiscal capacity in implementing UBI in Indonesia.

The fiscal feasibility analysis consists of two steps of analysis. It starts with performing a general case of reallocating any fiscal space of the existed cash transfer toward a UBI scheme. In this regard, the approach follows a similar method used by Hanna & Olken (2018). Then, the analysis uses a stylized scenario that is country specific case which provides a higher feasibility on fiscal ground. Nevertheless, our exercise shows that an innovative financing and a non-neutral budget is required if the government decide to revising the existing social protection programs toward UBI.

Gentilini, Grosh, Rigolini, & Yemtsov (2020) provides a comprehensive framework for navigating UBI decision making. The framework prescribes setting up the initial context as the key important primary move. Indonesia could use three contexts for the government to consider implementing UBI. First is to switch the existing cash transfer program into UBI. Second is to reallocating budget for fuel subsidy to UBI. Third, is a subnational context of switching local government budget of the existing social protection and subsidies to UBI.

As a result of applying the first context to examine the feasibility of UBI, the budget consequence is non-neutral, or an innovative financing is needed. As for the second context, the crucial consideration of which one is more dominant, political support from the public is important. The nature of benefit incidence for fuel subsidy in Indonesia is known to be progressive. Transforming the price subsidy into UBI will flatten the benefit incidence and certainly benefits more the poor than the richer. The most important strategy attached to the context is to avoid public discontent. Fear of poverty effect originated from the inflationary effect of removing price subsidy and make it cash transfer should be addressed carefully.

The second context might have a favourable expected outcome in relation to country’s effort to reach the SDG target. However, the financing consequence is not


neutral. The government needs to find additional financing either from increasing income tax or consumption tax which in nature progressive to justify the equity argumentation. Despite the promising economic and political avenue for the two contexts mentioned above, the administrative constraint seems to be existed for both scenario of introduced UBI in Indonesia as it had been highlighted in the previous chapter.

3.2 General consideration of UBI: efficiency and equity trade-off

This subsection advances and replicates the simulation done by Hanna & Olken (2018) in examining the trade-off faced by the government in switching targeted social protection into UBI. There are three main indicators for the purpose of analysis. First is the generosity level of the amount of universal basic income. This indicator is important because it determines the efficiency of an anti-poverty program between using the conventional instrument and the universal basic income. In addition, the amount of the universal basic income will determine the attractiveness of the reform. The second indicator is the socio-welfare level. Imposing universality will create a different profile of the aggregate social welfare. Therefore, simulating universality level concerning their social welfare is also important. The third indicator is the horizontal equity. Transforming the existing program into universal basic income and entails changes in the horizontal equity. Hence, simulating different level of universality by looking at the horizontal equity is the last part of the analysis.

The calculation of the generosity level uses two information. The first one is the amount of budget available for the purpose of universal basic income. The second information is the number of recipients. There are two options of units for beneficiary: The individual level and the household level. Our calculations reveal that the adequacy level of universal basic income at individual level is very low in Indonesia given the space of fiscal at national level. Therefore, the following analyses focus on the household level. The generosity level is calculated by the amount of budget available by the number of households in each decile of welfare level. The number of households refer to the approximation of total household in Indonesia in 2019 by Statistic Indonesia (BPS). The entire exercises also simulate the alternative scenarios for budget availability in 2018 as presented in the following table.

Table 3 The amount used for reallocation scenarios

Nominal Rp (Triliun) 2016 2017 2018 2019 (APBN)

PKH 8.5 12.5 19.2 34.3

PIP 10.8 10.7 11.0 11.2

JKN 24.8 25.4 25.5 26.7

Bidik Misi 3.2 3.7 3.4 4.9

Subsidi Rastra/Bantuan Pangan 22.1 19.5 19.3 20.8

Subsidi Mitan 2.2 1.7 3.4 4.2

Subsidi Solar 15.3 6.6 35.5 26.8

Subsidi LPG 24.9 38.7 58.1 69.6

Subsidi Listrik 63.1 50.6 56.5 59.3

Total Subsidi NonEnergi 67.4 68.7 63.3 64.3

Source: BKF, Ministry of Finance.


The calculation of the level of social welfare uses a similar formula by Hanna & Olken (2018) of the following:

(3.1)Where U is the total utility function of individuals in each decile of inclusion or universality. is the level of expenditure and is the level of transfers received. is the risk aversion parameter. The higher value of this parameter puts higher weights on transfers received by the very poor.

Horizontal equity measures how equal is individual treated to get transfer in each income decile based on asset data. There are steps to calculate the horizontal equity by Hanna & Olken (2018). First step, for each cut-off value , is to assign which households receive the transfer and which do not. For each household income level-proxied by expenditure, the second step then is to calculate the percentage of households 5 percentiles above or below who have the same outcome. That is, for households receiving the transfer, the percentage of households 5 percentiles above and below who also would receive the program. As for households not receiving the program, the percentage of households 5 percentiles above and below who do not receive the transfer. For each cut-off , the last step is then to average these two percentages over all households to get a measure of horizontal equity. The steps repeat this exercise for each possible value of .

Finally, the analysis also deal with the implied tax rate across income level. Universality ensures that all individuals receive the same benefit regardless of their income level. In contrary, with targeting and PMT, everyone’s chance to receive transfer is decreasing with respect to income. Thus, PMT is an imposed “a tax rate” relative to UBI. The nominal taxed is measured by of how much subject’s probability to receive transfer declines as their income increases times the nominal benefit that UBI offers. The simulation for the implied tax rate by switching from UBI to PMT is then calculated by local regression of probability receiving transfer with household survey data on income level with SUSENAS. The probability weights the benefit incidence. The expectation is that the rate is declining over income level as the conceptutal framework suggests.

To mimic the factual targeting process, the exercise replicates the same steps of creating two datasets from national socio-economic survey (SUSENAS) 2018, each for calculating the proxy mean test parameter and for applying the parameter. The analysis focus on household level simulations as the ex-ante generosity level is very low for simulation at the individual levels. The subnational simulation, especially in calculating the generosity, uses both individual and household level as the fiscal space is larger and thus the generosity level. Horizontal equity and social welfare pattern are simulated with household level as the general pattern would not differ from individual level simulations.

3.3 Determining the context and the amount of budget

In 2019, there official cash transfer existed is the conditional cash transfer program


or the PKH. The total budget allocated in the corresponding year is Rp34.3 trillion covering about 10 million households in 2018 (World Bank, 2017). Each household receives at the range of USD 60–220 a year as the benefit (Kusuma et al., 2017)this paper provides evidence on the impact of household cash transfer (PKH. The program context is used for exercising the conversion from targeted policy into a UBI. The simulation is a switching from this program into a universal income transfer at household level for 70.1 million household.

29

Figure 3 Generosity level per household per year in rupiah across decile of inclusion (UBI =10) The calculation across decile of coverage of imposing universality gradually declines the value of generosity. At 20% of inclusion, the available fund can make total benefit per household per year at the amount of Rp2.4 million rupiah and it becomes only Rp0.49 million rupiah for UBI. All alternative scenarios for budget availability corresponding generosity is presented by Graph A1 in the Appendix. Certainly, in terms of poverty reducing effect, the generosity level offered by existing PKH scheme with Rp37.8 million per household per year (The World Bank, 2019), the UBI generosity needs to expand almost eight times to reach the same poverty effect. Another illustration is as follow. Let assume an addition of the budget of PIP and Rastra into the simulation. The amount in Table 3 shows a multiplication of the reallocation amount by 1.5. Thus, the generosity level would be around Rp0.74 million. The current PIP and Rastra combined benefit incidence are about Rp2.4 million rupiah (The World Bank, 2019). Still, the generosity level of UBI needs to multiply to maintain poverty reducing effect. Similar to conclusion of Hanna & Olken (2018), universality will require an innovative financing to make UBI performance for anti-poverty objective as good as the existing targeting programs. When the analysis extends into individual level, the demand for innovative financing also increases. Aiming horizontal equity (i.e. everybody gets benefit or decile of inclusion equals to 10) is at the cost of weakening effectiveness of poverty alleviation purpose if the budget is neutral. Next, equation 3.1 applies to calculate the social welfare function in aggregate for each level of inclusion decile. Eventually, the optimal inclusion level that maximise the social welfare for the entire population in Indonesia is at around 3% of decile given the available budget. This inclusion level is very low and not desirable for making anti-poverty program also to be effective.

4.892.857

2.446.428

1.630.952

1.223.214 978.571

815.476 698.980 611.607 543.651 489.286

-

1.000.000

2.000.000

3.000.000

4.000.000

5.000.000

6.000.000

1 2 3 4 5 6 7 8 9 10

Figure 3 Generosity level per household per year in rupiah across decile of inclusion (UBI =10)

The calculation across decile of coverage of imposing universality gradually declines the value of generosity. At 20% of inclusion, the available fund can make total benefit per household per year at the amount of Rp2.4 million rupiah and it becomes only Rp0.49 million rupiah for UBI. All alternative scenarios for budget availability corresponding generosity is presented by Graph A1 in the Appendix. Certainly, in terms of poverty reducing effect, the generosity level offered by existing PKH scheme with Rp37.8 million per household per year (The World Bank, 2019), the UBI generosity needs to expand almost eight times to reach the same poverty effect. Another illustration is as follow. Let assume an addition of the budget of PIP and Rastra into the simulation. The amount in Table 3 shows a multiplication of the reallocation amount by 1.5. Thus, the generosity level would be around Rp0.74 million. The current PIP and Rastra combined benefit incidence are about Rp2.4 million rupiah (The World Bank, 2019). Still, the generosity level of UBI needs to multiply to maintain poverty reducing effect.

Similar to conclusion of Hanna & Olken (2018), universality will require an innovative financing to make UBI performance for anti-poverty objective as good as the existing targeting programs. When the analysis extends into individual level, the demand for innovative financing also increases. Aiming horizontal equity (i.e. everybody gets benefit or decile of inclusion equals to 10) is at the cost of weakening effectiveness of poverty alleviation purpose if the budget is neutral.


Next, equation 3.1 applies to calculate the social welfare function in aggregate for each level of inclusion decile. Eventually, the optimal inclusion level that maximise the social welfare for the entire population in Indonesia is at around 3% of decile given the available budget. This inclusion level is very low and not desirable for making anti-poverty program also to be effective.

Figure 4 Optimum social welfare with varying degrees of inclusion for PKH budget in 2018

The last parameter to show is the horizontal equity. Figure 5 shows the result of calculation of horizontal equity framework mentioned above. Technically, horizontal equity is achieved when decile of inclusion is either 0 or 1. That is to say, the horizontal equity achieved optimally if everyone gets the same amount (c = 1) or nobody does (c=0). Our calculation with SUSENAS 2018 with its inclusion and exclusion nature, gives us the U-shaped pattern. In which, the lowest horizontal equity is at inclusion level about 30% saying that the current inclusion level of about 20% is also socially less optimum on horizontal equity ground.


Figure 5 Horizontal equity with varying degree of inclusion for PKH budget in 2018

The implied marginal tax rate from imposing PMT relative to implementing UBI is provided by the following figure. It is effectively affected by how precise is the PMT or how asset information predict income and it turns predict the probability of receiving transfer. It shows that the implied marginal tax rate of imposing PMT declines as income rises. The interpretation is that the lower income borne loses larger from switching from UBI to PMT than the richer ones. It declines from about 15% for the bottom ten percent toward nearly zero for the top ten. The red line shows a slightly different pattern when the targeting error existed. For an example, the red line describes the decline of the implied marginal tax rate of PMT when the accuracy of asset data is weaker. Therefore, the availability and accuracy of asset information at household level largely determines the implied tax rate of imposing targeting with PMT relative to UBI.

Figure 6 Implied marginal tax rate across household income level


Up to this point, the analysis demonstrated the efficiency and equity trade-off in imposing universality. It measures the efficiency as the effectiveness of anti-poverty objective measured by generosity level. Indeed, imposing universality yields a greater horizontal equity or fairness, however, it has a clear effect on the declining of benefit per household per year by significant amount. To make the anti-poverty objective is not hampered when universality takes place, the reversed calculation recovers the needed budget. The calculation implies that, to make 20%-equivalent poverty level benefit is maintained, the government needs to collect five times additional budget or about Rp172 trillion for the UBI. This amount is approximately 1.1% of Indonesian nominal GDP in the corresponding year.4 Currently, as the country has maintained in the last five years, the share of social protection budget to GDP is at around 0.7%. This means that the additional required allocation is about twice as current social assistance spending. A large amount that is not easy to fulfil by reallocations of other budget programs, it requires an innovative financing.

3.4 A Quasi UBI: Reallocating fuel subsidy budget into a large- scale cash transfer amidst Covid-19 outbreak

Currently, Indonesia and more than 130 countries in the world have been coping with health and economic crisis as the result of the outbreak of infection caused by SARS-CoV-2 virus or Covid-19 infections. The demand side and supply side negative shock to the economy is a clear effect of natural physical distancing and containment measures implemented by the authority in each country. One of the emerging disaster relief effort advocated is the UBI. This part shows a second simulation motivated by such necessity and at the same time to provide a more feasible implementation of UBI in a form of a quasi-version with specific context of reallocating Indonesia’s state budget for fuel subsidy into cash transfer. As the formal analysis assesses the following conceptual concerns:1. The motivating context to implement such quasi UBI is for two considerations.

First, the existing trials and exercise shown that implementing a full UBI with a neutral fiscal space requires a careful examination toward anti-poverty effectiveness. Second, at the time of this report is being written, the burden for Indonesia’s state budget to fuel subsidy is relaxed by two events: the decrease in the transportation sector activity due to containment policy and natural physical distancing effect associated with Covid-19 and the sharp decline in world oil price.

2. There is a strong pressure to expand the existing cash transfer coverage to include the missing middle-income group as the potential list of beneficiaries. This is due the adverse effect of Covid-19 health crisis to economic crisis that make the middle-income deciles as the vulnerable group.

3. The Indonesia’s fiscal policy long term goal is to convert its inefficient fuel subsidy benefit incidence from a price based to direct subsidy. The fuel subsidy is progressive in nature for benefit incidence. By the means of economic access to fuel product, the richer household accumulate more subsidy benefit from consumption than the poorer.

4. Providing a cash transfer following the increase of fuel price as the result of subsidy removal is not new for Indonesia. The similar policy in 2005 and 2008 shows a general takeaway that the policy taken was economically superior. This

4 According to Statistics Indonesia, the nominal GDP in 2018 is Rp14,837 trillion, see https://www.bps.go.id/pressrelease/2019/02/06/1619/ekonomi-indonesia-2018-tumbuh-5-17-persen.html.


conclusion emerges as the transfer provided can mitigate the inflationary pressure to poverty acceleration. Therefore, any further repetition of similar policy should also be evaluated at the same ground, how the transfer works against adverse inflationary effect. On the other hand, the motivation to provide a larger scale due to demand for disaster relief for Covid-19 is new one.

The exercise starts by looking at the amount of money available at the government budget to be reallocated from fuel subsidy to a cash transfer program. The following table present the potentially reallocated resources in 2020 for the purpose of such exercise. Depending the amount choice, the available budget can be comparable to the existing announced cash transfer. On March 31st, the Indonesian government announced its fiscal stimulus package amount to Rp405.1 trillion. It covers the cash transfer program at the amount of total Rp17.58 trillion. This transfer accounts for 29.3 million households with generosity level of Rp600.000 per household per year (the cash transfer is distributed within three months). For example, the reallocation of subsidy for diesel and kerosene would be comparable to this cash transfer budget.

Table 4 Total budget for energy and non-energy in APBN 2020

Commodity Amount (in trillion Rp) % to total

Diesel fuel (solar) 15.31 8%

Kerosene (minyak tanah) 3.391 2%

LPG 49.386 27%

Electricity 54.785 30%

Non energy subsidy 62.264 34%

Total 185.136 100%

Source: BKF, Ministry of Finance.

To assess whether such a budget provides a meaningful generosity level in the form of cash transfer program, the calculation needed is the benefit incidence along the universality level. That is by varying the cut-off level of , from 1st to 10th deciles. The following table provides the simulated benefit incidence at the household level by deciles across amount of budget available in the state budget 2020 for energy sector. For the purpose of the analysis, the number of household equals to 73.25 million based on Susenas 2019 is applied.


Table 5 Generosity level by decile and commodity subsidy budget reallocated

Deciles Diesel fuel Kerosene LPG Electricity All energy All non-energy

Diesel + Kerosene

UCT (BLT) 2020

10 2,090,102 462,935 6,742,116 7,479,181 16,774,471 8,500,205 2,553,038 2,400,000

20 1,045,051 231,468 3,371,058 3,739,590 8,387,235 4,250,102 1,276,519 1,200,000

30 696,701 154,312 2,247,372 2,493,060 5,591,490 2,833,402 851,013 800,000

40 522,526 115,734 1,685,529 1,869,795 4,193,618 2,125,051 638,259 600,000

50 418,020 92,587 1,348,423 1,495,836 3,354,894 1,700,041 510,608 480,000

60 348,350 77,156 1,123,686 1,246,530 2,795,745 1,416,701 425,506 400,000

70 298,586 66,134 963,159 1,068,454 2,396,353 1,214,315 364,720 342,857

80 261,263 57,867 842,765 934,898 2,096,809 1,062,526 319,130 300,000

90 232,234 51,437 749,124 831,020 1,863,830 944,467 283,671 266,667

100 209,010 46,294 674,212 747,918 1,677,447 850,020 255,304 240,000

Source: Author’s calculation.

Figure 7 presents the pattern of the generosity level by decile for selected commodity budget being reallocated.

The variations in the generosity in Table 6 demonstrate that the amount reallocated from solar plus kerosene toward a cash transfer program is comparable to the existing cash transfer as a response to Covid-19 outbreak. Moreover, the amount would be significantly decreasing as the universality level shifts to 100. With the available budget, the generosity is only around Rp250 thousand per household, which is less than half of the existing cash transfer. Thus, to maintain the generosity and attractiveness of the amount, the government needs a larger budget. For example, shifting the amount equals to the subsidy budget of electricity or LPG with full universality would yield a comparable amount of generosity as the existing cash transfer with universality equals to bottom 40%.

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Table 5 Generosity level by decile and commodity subsidy budget reallocated Deciles Diesel fuel Kerosene LPG Electricity All energy All non-

energy Diesel + Kerosene

UCT (BLT) 2020

10 2,090,102 462,935 6,742,116 7,479,181 16,774,471 8,500,205 2,553,038 2,400,000

20 1,045,051 231,468 3,371,058 3,739,590 8,387,235 4,250,102 1,276,519 1,200,000

30 696,701 154,312 2,247,372 2,493,060 5,591,490 2,833,402 851,013 800,000

40 522,526 115,734 1,685,529 1,869,795 4,193,618 2,125,051 638,259 600,000

50 418,020 92,587 1,348,423 1,495,836 3,354,894 1,700,041 510,608 480,000

60 348,350 77,156 1,123,686 1,246,530 2,795,745 1,416,701 425,506 400,000

70 298,586 66,134 963,159 1,068,454 2,396,353 1,214,315 364,720 342,857

80 261,263 57,867 842,765 934,898 2,096,809 1,062,526 319,130 300,000

90 232,234 51,437 749,124 831,020 1,863,830 944,467 283,671 266,667

100 209,010 46,294 674,212 747,918 1,677,447 850,020 255,304 240,000 Source: Author’s calculation. Figure 7 presents the pattern of the generosity level by decile for selected commodity budget being reallocated. The variations in the generosity in Table 6 demonstrate that the amount reallocated from solar plus kerosene toward a cash transfer program is comparable to the existing cash transfer as a response to Covid-19 outbreak. Moreover, the amount would be significantly decreasing as the universality level shifts to 100. With the available budget, the generosity is only around Rp250 thousand per household, which is less than half of the existing cash transfer. Thus, to maintain the generosity and attractiveness of the amount, the government needs a larger budget. For example, shifting the amount equals to the subsidy budget of electricity or LPG with full universality would yield a comparable amount of generosity as the existing cash transfer with universality equals to bottom 40%.

Figure 7 Benefit per household per year for selected commodity budget being reallocated to cash transfer (in Rupiah) The next parameter to calculate and present is the total welfare by decile of universality coverage. Given the amount of total subsidy for diesel and kerosene, the level of universality that maximise social welfare is very low.

-

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

0 10 20 30 40 50 60 70 80 90 100

Selected benefit per households

Diesel fuel Kerosene Diesel + Kerosene UCT (BLT) 2020

N=73,250,000


Figure 7 Benefit per household per year for selected commodity budget being reallocated to cash transfer (in Rupiah)

The next parameter to calculate and present is the total welfare by decile of universality coverage. Given the amount of total subsidy for diesel and kerosene, the level of universality that maximise social welfare is very low. Nonetheless, allocating all of energy subsidy budget results in maximum social welfare at universality level of 20%. As aforementioned interpretation, there would be a much larger budget needed to maximise social welfare or to maintain the same level of anti-poverty decelerating magnitude. Figure 8 describe the social welfare maximisation given the scenario that all of energy subsidy in 2020 is allocated for cash transfer.

Figure 8 Optimum social welfare with varying degrees of inclusion for total energy subsidy budget in 2020

As for the horizontal equity, similar graph produces pattern that yield the maximum horizontal equity level, either everybody gets (c=1) or nobody gets (c=0) the cash transfer. With the amount equals to total subsidy budget for energy, the coverage of universality equals to 30% has the lowest horizontal equity. In other words, to improve the horizontal equity that represent public support in general based on equity sense, the universality level should be increased. For example, imposing a quasi UBI at 60% of universality might yield a higher horizontal equity at around 75% of its maximum value. Consequently, the additional budget is needed to maintain generosity level for this purpose, otherwise an intensive public communication is needed whenever the universality level at 40% is chosen.


Figure 9 Horizontal equity with varying degree of inclusion for reallocation of budget for energy into UBI

3.5 Existing regulation in social protection and expenditure policies to support UBI implementation

The social contract between the states and citizen of the right to have a decent live —the ultimate goal of any social protection system as well as UBI, is preserved in the constitution (Article 27, Subsection 2 UUD 1945). The article states that “Tiap-tiap warga negara berhak atas pekerjaan dan penghidupan yang layak bagi kemanusiaan”, meaning that every citizen has right over decent occupation and livelihood for humanity”. In other articles, the contract specifically regulates about citizen’s right over social security service (Article 28G, Subsection 3 and Article 34, Subsection 2). The article states explicitly that the states has obligation to develop social security system that empower every citizen (“Negara mengembangkan sistem jaminan sosial bagi seluruh rakyat dan memberdayakan masyarakat yang lemah dan tidak mampu sesuai dengan martabat kemanusiaan”) and they has the right to it in a universal manner (“Setiap orang berhak atas jaminan sosial yang memungkinkan pengembangan dirinya secara utuh sebagai manusia yang bermartabat”).

Moreover, the specific contexts of the contract were stipulated in another article, social security in health (Article 28H, Subsection 1) and poverty (Article 34, UUD 1945). The spirit of universality be made explicit in providing social security as the contract between the states and citizens. This is one fundamental legal basis for implementing UBI as it be one of forms of social protection mechanism. The general umbrella for any social protection programs in Indonesia is Law No. 11/2009 about Social Welfare.

The most recent operating regulation to implement the mandates mentioned above, such as for social security in health sector is the Law No. 40/2004 about the national social security and the Law No. 24/2011 about the implementing body, BPJS (Badan Penyelenggara Jaminan Sosial). As for other social protection programs implemented


by line ministries (see Table 2), the legal basis is varying from Presidential Decrees up to Ministerial decrees. BLT for example, were implemented by Presidential Decrees (No. 12 in 2005 and No. 3 in 2008). To sum up, most of operational of the social protection programs and the social insurance program can be implemented under the umbrella of both laws, either Law No. 40/2004 or Law No. 11/2009. Therefore, any implementation of cash transfer aimed to enhance social welfare, including UBI, without doubt can be attributed to these laws.

3.6 Cost and administration challenges in administering UBI

When the governments implement UBI, they can save money because administration cost to do targeting can be avoided. Mainly, the costs are associated with administrating the database and updating them. The larger share of this cost is to implement poverty census or in Indonesia context known as PPSE05 and PPLS08 (see section 2.1.3). In terms of amount, for example, the 2015 Indonesian poverty census cost the government about Rp900 billion (Olken, 2019); increase by a half than the amount in 2011 which was Rp600 billion (Booth et al., 2019). Out of total budget for main programs such as PKH, Raskin, PIP and Jamkesmas; the poverty census cost constitutes about 0.5% of the budget. Note that, due to small portion of administrative cost for targeting, adding up this cost to increase generosity yield marginally trivial benefit.

Another part of the cost is the operational and administrative costs associated with the program monitoring and evaluation. These costs are usually embedded in each responsible line ministries such as Ministry of Social Affairs. The data from state budget (APBN) in 2018 illustrates that the amount varies from Rp36 billion (monitoring) to Rp332 billion (support for management and program implementation). This money be an opportunity gain for doing universality as the government does not require poverty census every year and to monitor the programs on the beneficiaries on yearly basis.

When the government implement UBI, one large fixed cost would be to set up a universal coverage of individual subscription to UBI. But the government just need this to occur once, at the onset of UBI implementation. As the discussion in the section 1.5.2 shows, the government might use the existing social assistance database (DTKS) and the existing social security database (BPJS) as the basis, for example, to avoid incurring a larger cost of build from scratch the database. Subsequently, the costs associated with updating the database would be quite low as it deals with partial updating and not census as the poverty census requires. Furthermore, the Indonesian tax office or the Directorate of General Taxation could see the upscaling the UBI database as an opportunity to integrate it with the taxation registration. Indonesia’s tax system, especially income tax, relies much on corporate income tax than personal income tax. Thus, implementing UBI is also be an opportunity to expand the registration of personal income tax in Indonesia by requiring individuals’ subscription to UBI is tied to tax registration. See box 3.7 for detail discussion on how to integrate some potential database with tax and financial account data.


3.7 Governance capacity in implementation

The landscape of social assistance and social insurance programs in Indonesia provides a mixture of types, benefit and coverage of each programs. The fragmented structure of the programs implies that the unification of those items of program into a single and cash-based transfer when the full UBI feature is implemented would not be easy. The first obvious challenge is the assignment of the agency who will take responsibility implying some loses of role by some line ministries who previously implemented the various programs.

Second, as mentioned in section 1.5.2 administrative capacity is the sufficient condition to make full UBI implementation is feasible. The ultimate data would be by name, by address and banking account of the entire eligible population. However, Indonesia has only fragments of those required dataset. For example, the targeted beneficiaries of BDTKS or the subscription to BPJS are the readiest dataset. Each of this dataset consists only 40% of households and about 80% of individuals and both are not yet integrated. Therefore, the ideal step would be to first prepare the integration of the dataset if a full UBI wanted to be implemented. An alternative route would be a quasi-UBI version of expanding the current social assistance recipients into higher income distribution level.

Last, a potential good implementing capacity would be no doubt presents in Indonesia. This optimism is based on the country experience in administering cash transfer in crises situation successfully. The BLT implementation in 2005 and 2008 provide baseline on how well the government capacity in planning and executing the transfer. The ultimate step is now how to integrate the database with other databases and to expand the coverage. See Box 3.7 for the details about merging civil databases in Indonesia.

3.8 Alignment with national development priorities

Among SDG goals, to end poverty is the number one agenda of the global economy. Like this tone, in its long-term development plan or RPJMN 2020-2024, Indonesia puts the poverty alleviation as one of the national priorities under the agenda of to increasing quality of human resources and competitiveness. The Indonesian government targets the poverty rate at 6.5–7% by 2024 (National Planning Agency, 2020). To achieve this goal, the direction of policy and the development strategy was to strengthen the social protection system. There are two specific strategy in the five years period towards 2024, to strengthen the social security programs and to strengthen the social assistance targeting and benefit distribution.

The prolonged Covid-19 health crises is expected to occur in Indonesia. As a result of this situation, there will be of adverse distributional effect in the form of accelerated poverty and changing inequality figures as a result of sectoral job losses and sharp decline in economic activity. Suryahadi et al., (2020) estimate that the poverty rate would be around 12.4% by the end 2020 under the most severe scenario of the economy only grows by 1%. This figure implies that new additional population living under poverty line accounts for 8.5 million people wiping out the poverty reduction


progress in the last decade. With this situation, the policy making needs a careful realignment of social assistance programs to decelerate the hike of poverty incidence. Section 3.2 demonstrated that switching a targeted cash transfer into a full UBI in normal situation with a neutral budget leads to undermining poverty reduction effort due to drop in generosity. The generosity would be slightly different (higher) as for the context of adverse poverty effect by Covid-19 crisis if the benefit incidence can be increased with an additional funding dedicated to the pandemic.

Hence, one possible and suitable application would be, first is a quasi-UBI in the form of expanding the existing cash transfer to cover the missing aspiring middle class. This segment is the new vulnerable group during this crisis. As section 3.4 highlighted, the form of the UBI adoption context is to reallocate the fuel subsidy budget into a cash transfer in the large scale to mitigate the adverse income shock. Second, a longer-term version of the UBI would be the ideal fully implemented UBI as the instrument to increase the number of people in the tax registry. The next section discusses this issue.

To deal with database integration, identification of the other potential databases that support the UBI implementation need to be conducted. The identified potential databases are as follows.

a. Unified Database (Basis Data Terpadu/BDT)The BDT (explain now is under kemensos and the name is already change) is individual socio-economic database that managed by The National Team for The Acceleration Poverty Reduction (TNP2K/Tim Nasional Percepatan Penanggulangan Kemiskinan). The coverage of BDT is 40% of the population with the lowest welfare status. It consists of approximately 24 million households or 96 million individuals. This database is used to enhance the quality of targeting performance in social protection programs and promote the complementarities between the programs.

This 40% population is divided into three clusters, 1) 11.37% is the poor group, 2) 13.36% is the near-poor group, and 3) 15% is the vulnerable group. The social protection package for each group varies. For example, vulnerable groups only get the health insurance program (Jaminan Kesehatan Masyarakat/Jamkesmas), while the poor group get all packages.

Source: Tohari, et. al (2019)

This existing social protection package can be used to learn on how the payment/transfer scheme that has been conducted so far, how much people that used bank account as a payment system, or whether there is another payment scheme (e.g. e-money or direct payment). However, due to its limit on 40% population, this DBT cannot be used to provide all necessary data for UBI implementation.

Box 3.7 The potentiality of civil database merging


b. JKN-KIS DatabaseJKN-KIS database is one of the largest health insurance databases in Indonesia. Up to 31 December 2019, the member of JKS-KIS is about 208 million people (BPJS Health, 2018). The member of JKN-KIS includes the 1) Jamkesmas beneficiaries, 2) formal workers and his/her family such as politician, civil servants, private workers, so on, 3) nonformal/informal/self-employed workers and his/her family, and 3) not a worker and his/her family such as investor, pensionary, veteran, and so on. The qualification for membership is not only limited to the citizen, but also the foreigner that works in Indonesia for a minimum of 6 months. Basically, the registration mechanism is self-enrolment except for the civil servant and military personnel.

The member of JKN-KIS cannot always be straightforwardly used as a basis to UBI implementation due to the involvement of kids and foreigners. However, this big data can be used to learn on how the payment system of insurance premium. It becomes useful additional data to know the insurance health status. The disadvantage of this database is lack on the socio-economic data, especially for non-formal or informal or self-employed workers.

c. Taxpayer DatabaseThe number of taxpayers in Indonesia is 38,7 million as individual taxpayer and 3.3 million as corporate taxpayer (National Budget-Financial Note, 2020). The taxpayer database uses unique taxpayer identification number as a basis (Nomor Pokok Wajib Pajak/NPWP). This database is important in UBI implementation, because it provides the level of tax compliance and the tax payment system. The integration with taxpayer database can also be used to enhance the tax base if NPWP becomes one of requirements to get UBI benefit.

d. Population Census 2020In 2020, Government of Indonesia through Statistic Agency (BPS) is conducting the population census. This census covers all major indicators in socio-economic data at individual and household level (see Population Census 2020 Form). This database will be the largest and updated database in Indonesia. It can be used to conduct validity check for ID system. The integration and alignment between e-KTP database and population census will generate more valid civil database.

e. The Other Potential Databases DBT, JKN-KIS, and Population Census have the same drawback. These databases cannot be used to ensure the feasibility of payment system. Bank account or electronic payment system is not completely available in these databases. Hence, we need additional data sources to develop a complete database that meets the necessary condition for UBI implementation. The only possible data source is from banking and e-commerce sector. From banking sector, we will get the bank account for individuals and from the e-commerce sector, we will get the electronic payment system that used by individuals in their daily activity. However, this merging process is very sensitive to privacy, legality, and security issue. Even if by legality and security, Government of Indonesia has a capacity to make the merging process occurs, the database remains incomplete due to the low participation in bank account registration. The portion of adult citizen in Indonesia that has a bank account is only 49% (Global Findex Database, 2017).

f. Self-Enrolment ExperienceThe integration of all available database may still leave an exclusion error. Besides that, the integration process does not always produce valid data. A risk of redundancy, incorrect, and missing data remains and become the challenging issue. Hence, we need self-enrolment mechanism as a complementary database collection. However, due to the experience of JKN-KIS program, the self-enrolment scheme also cannot stimulate a high participation in JKN-KIS membership (missing middle problem).


3.9 Macro policy considerations

The implementation of UBI in a low tax registry regime would create an undesirable state of fairness. If a full UBI is implemented, most of Indonesian in the informal sectors, the one with income under threshold, and all workers outside the tax registry are enjoying the transfer funded by the minority number of income earner in the tax registry. There are two ways of looking at this issue. First is to avoid a full implementation of UBI if there is no strategic agenda to expand the tax registry coverage. Second is to use the momentum of social protection reform to full UBI feature to design a more progressive taxation system with enrichment in the tax registry coverage.

In the medium term, the Indonesian government aims to integrate the social protection database (BDTKS) and the social security database (BPJS) (National Planning Agency, 2020). An integrated data has been a major concern for Indonesia in order to make its social protection systems works perfectly, especially for targeting. Apart from this, the data issue is also an important avenue for reforming the tax inclusion or registry. This study argues that an integrated data by the NIK (single ID) would be an open opportunity to advance the tax registry (not yet collection) when it becomes the necessary condition to implement UBI. Given that this agenda presents in the medium-term program, the feasibility of implementing a full UBI in the future will be largely be supported by this databasing agenda.


CHAPTER 4CASE STUDY

4.1 Context

This chapter takes a smaller coverage as a case of study. The selection of DKI Jakarta Province as the study case because as capital city, it meets the fiscal consideration as well as the administrative requirement to implement UBI. The analysis starts by highlighting the fiscal capacity of the province and then outlining the existing social protection programs as a potential context for the status quo for the transformation toward UBI scheme. An assessment on local administrative capacity to implement a full UBI is also covered. Last, the analysis involves a microsimulation result comparing the benefit incidence between the three scenarios: status quo, a quasi-UBI and full UBI. Overall, the feasibility for DKI Jakarta to adopt a quasi UBI is well supported by both administrative and fiscal condition. Specifically, to fully implement a UBI scheme, DKI Jakarta has a stronger local fiscal capacity and to expand the registration system is not as challenging to the case of the national level.

4.2 The local fiscal capacity of DKI Jakarta Province

The fiscal space of the local government budget of DKI Jakarta over the last four years available data provides overview about the feasibility of introducing a full UBI or a quasi-UBI. There are two dimensions covered: revenue and types of spending. In 2019, the total revenue of DKI Jakarta is Rp89 trillion or about Rp8 million rupiah per capita making the figure as the largest one among provinces in Indonesia. With this fiscal capacity, DKI Jakarta is arguably among provinces in Indonesia which has potential to implement UBI or a quasi-UBI. In addition, the less dependency toward national transfer makes the feasibility is even stronger. The following table shows that relative to national pattern, the total own revenue of DKI Jakarta is about 150% above the national average. The main source for total own revenue is local tax. At the time of pandemic, however, the 2020 or the current budget predicts that the local tax receipt would be drop significantly to about only 47% of the planned5.

5 https://jakarta.bisnis.com/read/20200507/384/1237458/disunat-apbd-dki-jakarta-tinggal-separuh


Table 6 Revenue composition of DKI Jakarta and the national level

National (%) DKI Jakarta (%)

Type of revenue 2016 2017 2018 2019 2016 2017 2018 2019

Local tax 40.89 38.89 40.55 39.23 58.80 56.33 60.86 59.14

Retribution 0.68 0.54 0.47 0.51 1.25 0.96 0.92 0.95

Local SOE profit 1.15 1.07 1.09 1.24 0.56 0.74 0.96 1.00

Others 5.61 5.66 5.19 5.05 7.98 9.69 7.48 6.65

Total own revenue 48.33 46.16 47.3 46.03 68.58 67.73 70.21 67.75

Tax revenue sharing 8.05 8.07 7.35 7.55 22.38 25.62 24.36 24.11

Revenue sharing other 3.08 2.29 3.12 3.36 0.67 0.37 0.29 0.17

DAU 13.98 17.24 16.87 15.98 0.00 0.00 0.00 0.00

DAK 16.16 18.55 18.04 19.57 5.36 3.27 4.28 4.22

Total transfer 41.27 46.15 45.38 46.46 28.40 29.26 28.93 28.50

Other 10.4 7.69 7.32 7.51 0.03 0.04 0.01 0.05

Grand total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00

Source: BPS, 2020.

On the spending side, DKI Jakarta’s share of its social protection spending to total spending also extraordinary at national level. Compared to national pattern, the share is five times larger than other provinces. During the period 2016–2019, the share ranges from 5.2–6.6% and it equals to amount between Rp2.4 to 4.4 trillion rupiah a year. The generous spending on social protection in this province is clearly supported by the fiscal capacity mentioned above making the poverty rates of DKI Jakarta be the lowest at national level. In 2019, the poverty rate was only 3.47% with the national poverty rate was 9.41%. Figure 10 shows,the social protection spending per capita of DKI Jakarta over the period 2001–2012 is the second largest along with its revenue per capita. DKI Jakarta is an exception in the sense that the high coverage of social protection is due to the availability of fiscal space rather than the low denominator i.e. population as the case of, for example, West Papua. Hence, reallocation of spending which financed independently from local taxation would be a feasible scenario for the province seeking the possibility of implementing UBI.


Table 7 Spending composition of DKI Jakarta and the national level

National (%) DKI Jakarta (%)

Type of spending 2016 2017 2018 2019 2016 2017 2018 2019

A. Indirect spending 59.8 60.75 60.89 57.27 48.37 46.50 49.49 42.67

Personnel 15.69 23.61 24.57 23.31 36.18 34.53 35.60 26.49

Interest 0.02 0.02 0.02 0.05 0.02 0.06 0.07 0.09

Subsidy 0.36 0.48 0.88 1.32 1.91 2.74 4.30 5.99

Grant 20.38 15.25 15.91 13.16 4.59 2.18 2.31 2.84

Social protection 1.29 1.35 1.52 1.4 5.20 6.27 6.62 5.52

Revenue sharing 13.53 13.03 12.54 12.08 0.00 0.00 0.00 0.00

Financial grant 8.51 6.95 5.41 5.65 0.45 0.67 0.55 1.04

Other 0.02 0.06 0.04 0.3 0.00 0.02 0.00 0.68

B. Direct spending 40.2 39.25 39.11 42.73 51.68 53.54 50.56 57.38

Personnel 2.79 2.72 1.79 2.61 4.90 5.13 0.00 4.14

Good and services 20.46 21.11 21.54 23.39 27.73 26.77 27.55 30.51

Capital 16.95 15.42 15.78 16.73 19.02 21.63 22.99 22.70

Total 100 100 100 100 100 100 100 100

Source: BPS, 2020.

Figure 10 Scatterplot of provincial social protection spending per capita and total revenue per capita during the period of 2001–2012 (average)

Source: INDODAPOER, 2019. Processed by author. Note: The social protection only covers direct transfer and not including price-based subsidies programs.


4.3 Types and coverage of the existing local social protection programs in DKI Jakarta

Similar to the types of direct and indirect transfers provided by the central government, DKI Jakarta Province also provides price subsidy and social protection programs. Up to 2020, the province has maintained 5 price-based subsidy programs of both targeted and non-targeted and 7 social assistance programs. Overall programs cover about 6 million people and use Rp12,65 trillion yearly budgets in 2020. Out of this budget, the composition consists of 45% for price-based subsidies and 55% for social assistance programs in the forms of direct transfers. Within the social assistance programs, the province also provides the special transfer for marginalised group (people with disability) and aid for basic need for children. Each program constitutes a small portion in the total budget for subsidy and social assistance, yet, their presence showing advance level of program development that hardly exist in other provinces.

Among the programs, education (i.e. Kartu Jakarta Pintar Plus or KJP Plus) and the bus transportation subsidy (i.e. TransJakarta) constitute the largest share in the government budget. The two program has a distinct target and benefit incidence. While KJP plus is aimed for improving human capital development and special only for DKI Jakarta residence (people with KTP DKI Jakarta), subsidy for TransJakarta is subsidy for daily mobility and commuting that benefit larger segment population covering Greater Jakarta area, not exclusive to DKI Jakarta residence. Like this program’s benefit incidence, LRT and MRT subsidies also are non-exclusive to DKI Jakarta residence. Thus, at the onset of simulation toward UBI it is expected that some welfare gains shifts out from the existing programs for non DKI Jakarta residence. Such welfare change might induce less incentive to stay within DKI Jakarta administrative boundary while they are not DKI Jakarta residence. Other more complex responses also might emerge such as less use public transport by non DKI Jakarta residence and so on.


Table 8 Budget allocation for subsidy and social assistance in DKI Jakarta Province, 2020

Programs Budget (billion Rp)

Budget (%) Beneficiaries (# of people)

Food subsidy 1,013.00 8.01%

Transportation subsidy

a. LRT 439.62 3.47%

b. MRT 825.00 6.52%

c. TransJakarta 3,291.57 26.02%

Housing subsidy 0.00 0.00%

Septic tank revitalisation 10.00 0.08%

JKN-BPJS subsidy 2,268.00 17.93% 5,000,000

Kartu Jakarta Pintar (KJP) Plus 3,975.27 31.42% 870,565

Kartu Jakarta Mahasiswa Unggul (KJMU) 192.28 1.52% 9,145

Kartu Lansia Jakarta (KLJ) 558.17 4.41% 77,524

Disability Card 41.12 0.32% 11,422

Aid for basic need for children 34.31 0.27% 9,531

Aid for disability 3.83 0.03%

COVID-19 Aid on plan on plan 12,000,000

Total 12,652.17

Source: DKI Jakarta Province, 2020.

4.4 Administrative capacity

The database for social assistance program in DKI Jakarta Province consists of two types administrative data: the DTKS or BDTKS as part of central government database and the existing local government database of programs in Table 4.3 At best of our knowledge, these two datasets were not well integrated. Similar to situation at the national level, the local government seems not in a state of better readiness in terms of administrative capacity. Especially, it is a question about how among databases are integrated or not and when they want to be expanded into full coverage of residence. The beneficiary’s database of programs in Table 4.3 such as KJP Plus is administered by DKI Jakarta Education Office (Dinas Pendidikan Provinsi DKI Jakarta) with registration held at school level. The program uses BDTKS only for the purpose of including the children that are not attending school. Such fragmentation of database management would require a significant administration preparation for implementing a full UBI later on.

4.5 Microsimulation results

This section provides the analysis whether implementing a full UBI is feasible in DKI Jakarta on fiscal consideration. Otherwise, the analysis further asks what level of incidence benefit offered if the scenario is a quasi-UBI. The analysis uses both the individual level and the household level of beneficiaries targeting. Note that, the same SUSENAS data of 2018 is applied for the simulation of the 2020 budget profile of DKI Jakarta.


There are three important points to note at the beginning. First, the choice of DKI Jakarta as case study is based on the local fiscal capacity as was explained in section 4.2 in which DKI Jakarta has the most potential to provide an adequate generosity for implementing UBI and thus make the simulation result attractive. Indeed, the microsimulation shows the potential. Second, poverty incidence in DKI Jakarta is relatively low and it is the lowest among provinces at national level. In March 2019, the poverty rate was only 3.47% and it accounts for 365,550 people. Given this situation, switching from status quo social protection program to UBI with a neutral budget entails a less riskier harms to population living under poverty. The needed budget to make top up and halt harming for them is more affordable.

4.5.1 Generosity level

The information about the total budget available for a UBI simulation comes from the DKI Jakarta Government data on social protection and its budget in 2020. The total amount used for the simulation is Rp12.65 trillion rupiah. Part of this budget is price-based subsidy that is not easy to transform. However, the simulation keeps include them to give an upper bound the maximum generosity whenever the political support allows for it. The population data comes from Dinas Kependudukan DKI Jakarta in which there are 11,063,324 people, 7,854,960 adult population and 2,911,401 households in 2020. The following graph shows the variations of generosity by level of inclusion (decile 1 to 10 in which 10 equals to UBI).

11,436,141

5,718,071 3,812,047 2,859,035 2,287,228 1,906,024 1,633,734 1,429,518 1,270,682 1,143,614

16,107,241

8,053,621

5,369,080 4,026,810 3,221,448 2,684,540 2,301,034 2,013,405 1,789,693 1,610,724

43,457,337

21,728,669

14,485,779

10,864,334 8,691,467

7,242,890 6,208,191 5,432,167 4,828,593 4,345,734

1 2 3 4 5 6 7 8 9 10

all population adult population household levelFigure 11 Benefit per individual, per adult individual and per household per year from reallocating total

social protection budget to UBI in DKI Jakarta (in Rupiah)

At household level, the yearly generosity offered by the simulation for DKI Jakarta (Rp4.3 million) is seven times higher than the current targeted UCT that central government offers (Rp600 thousand per year). Moreover, the generosity level is still adequate when it uses the general population or adult population as the targeting definition. The UBI generosity equals to Rp1.6 million with adult population and equals to Rp1.4 million with all population. It is approximately twice of the current poverty line of DKI Jakarta. All these magnitudes are higher than any generosity produced by simulation with the central government budget in Chapter 3. These


figures imply that local level UBI is more feasible with the reference to DKI Jakarta Province on fiscal consideration. The number of households and individuals in each decile are provided in the following Table 9.

Nevertheless, the benefit incidence concerning the poverty reduction is higher for existing targeting program such KJP and KLJ relative to UBI. As for an illustration, a family with two children with elementary and junior high school attendance and an elderly, will get Rp1.15 million per month or equals to Rp13.8 million per year. The generosity and budget for UBI needs to expand about three times in this case to maintain the equal level of benefit as the existing program. In addition, some local government program provides benefit on top of the central government transfer. For an example, the KIP or KLJ program eligibility requires household to be listed in DTKS or an equivalent database, the same requirement as central government program of PKH or Rastra. Hence, the benefit received by a household even could be larger in total by these combined benefits. In this regard, the local government benefit incidence is a ‘top up’ to the national program’s benefit. Considering this circumstance, a UBI generosity needs to expand more to meet the same level of benefit incidence of the combined value of central and local government cash transfers.

43

Nevertheless, the benefit incidence concerning the poverty reduction is higher for existing targeting program such KJP and KLJ relative to UBI. As for an illustration, a family with two children with elementary and junior high school attendance and an elderly, will get Rp1.15 million per month or equals to Rp13.8 million per year. The generosity and budget for UBI needs to expand about three times in this case to maintain the equal level of benefit as the existing program. In addition, some local government program provides benefit on top of the central government transfer. For an example, the KIP or KLJ program eligibility requires household to be listed in DTKS or an equivalent database, the same requirement as central government program of PKH or Rastra. Hence, the benefit received by a household even could be larger in total by these combined benefits. In this regard, the local government benefit incidence is a ‘top up’ to the national program’s benefit. Considering this circumstance, a UBI generosity needs to expand more to meet the same level of benefit incidence of the combined value of central and local government cash transfers.

Figure 12 Number of households and individual in each decile, DKI Jakarta – 2019 The generosity level provided by the simulation above use hypothetical situation as if the local government has access to all household or all individual in the region. This is not the case. The available access to current beneficiaries of social protection program in DKI Jakarta refers to the same Unified Database (BDTKS) as the central government has. In addition to this, the local government maintain semi-community level targeting called Dasa Wisma. With reference to the BDTKS of Ministry of Social Affair, the coverage of social protection in DKI Jakarta is only 11% of its total household or individual, despite that the national level coverage is the bottom 40%. This means that the share of total poverty incidence in DKI Jakarta to national level is relatively low as previous section pointed out. If the administrative feasibility is using BDTKS database only, the second scenario would be a quasi-UBI for the bottom 11% of the household and individuals. In this scenario, the generosity level would be equals to Rp40 million rupiah per household per year. Or it equals to a monthly transfer of Rp3.4 million per household. Or, it equals to a monthly transfer of Rp890 thousand per individual. A very generous amount that not only can make people out of poverty but also generously well off on top up of any anti-poverty transfer administered by the central government. Thus, it is quite clear that a quasi-UBI with adequate generosity level will have a clear positive effect on poverty alleviation. Table 9 DKI Jakarta households and individuals in BDTKS 2019

Deciles 1 2 3 4 Total Number of households 58,090 80,675 109,612 62,053 310,430 % of household to total household 2% 3% 4% 2% 11% Number of individual 255,373 312,175 394,444 225,524 1,187,516 % of individual to total individual 2% 3% 4% 2% 11%


-

2.000.000

4.000.000

6.000.000

8.000.000

10.000.000

12.000.000

1 2 3 4 5 6 7 8 9 10

total population adult population (19 or older)

number of households

Figure 12 Number of households and individual in each decile, DKI Jakarta – 2019

The generosity level provided by the simulation above use hypothetical situation as if the local government has access to all household or all individual in the region. This is not the case. The available access to current beneficiaries of social protection program in DKI Jakarta refers to the same Unified Database (BDTKS) as the central government has. In addition to this, the local government maintain semi-community level targeting called Dasa Wisma. With reference to the BDTKS of Ministry of Social Affair, the coverage of social protection in DKI Jakarta is only 11% of its total household or individual, despite that the national level coverage is the bottom 40%. This means that the share of total poverty incidence in DKI Jakarta to national level is relatively low as previous section pointed out.


If the administrative feasibility is using BDTKS database only, the second scenario would be a quasi-UBI for the bottom 11% of the household and individuals. In this scenario, the generosity level would be equals to Rp40 million rupiah per household per year. Or it equals to a monthly transfer of Rp3.4 million per household. Or, it equals to a monthly transfer of Rp890 thousand per individual. A very generous amount that not only can make people out of poverty but also generously well off on top up of any anti-poverty transfer administered by the central government. Thus, it is quite clear that a quasi-UBI with adequate generosity level will have a clear positive effect on poverty alleviation.

Table 9 DKI Jakarta households and individuals in BDTKS 2019

Deciles 1 2 3 4 Total

Number of households 58,090 80,675 109,612 62,053 310,430

% of household to total household 2% 3% 4% 2% 11%

Number of individual 255,373 312,175 394,444 225,524 1,187,516

% of individual to total individual 2% 3% 4% 2% 11%


The potential adverse consequence of such attractiveness is inducing in migration to DKI Jakarta. The local government needs to carefully address the in-migration issue, especially during the normal time. On the other hand, the huge generosity that only applies to residence might not solving the current problem of welfare decline for the poor and the middle during the Covid-19 pandemic.

4.5.1 Horizontal equity and social welfare

The simulation results also provide us information about the maximum social welfare attained and the measure of horizontal equity in every decile of expansion toward UBI for DKI Jakarta as so for the national level. The social welfare becomes maximum at much higher level of inclusion compared to the national level analysis. The distinction is attributed to the available fiscal space in DKI Jakarta that is much larger than the national level. While the national level simulation yields inclusion level of less than 5%, the DKI Jakarta simulation by reallocation the existing local social protection budget yields inclusion level of around 10% to make the maximum social welfare (see Figure 13).


Figure 13 Optimum social welfare with varying degrees of inclusion for social protection budget of DKI Jakarta in 2020

The horizontal equity profile of the simulation yields not much different pattern of the U-shaped measure of horizontal equity across the decile of inclusion. No transfer at all or a full UBI is a desirable option if it is refer to this measure. The choice of implementing a quasi-UBI at inclusion rate of 11%, for example, is still worse than expanding it further so that adequate to increase the horizontal equity. If the local government of DKI Jakarta wants to obtain a better horizontal measure, for example inclusion of 60% or above will make horizontal equity at 80% or more (Figure 14). Consequently, the generosity would fall. However, given the more flexible space of generosity, this level of inclusion still provides a sizeable amount of yearly transfer to household level (Rp7,2 million) or to individual (Rp1.9 million). See Figure 11 for reference.

Figure 14 Horizontal equity with varying degree of inclusion for social protection budget of DKI Jakarta in 2020


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CHAPTER 5CONCLUSION

This chapter highlight the general conclusion of feasibility in implementing full UBI in combining information from literature review on UBI around the world, landscape of Indonesia social protection and the microsimulation. The conclusion is mainly about the synthesise of what kind of way forward for implementing a full UBI scheme in Indonesia.

To examine the possibility of implementing UBI in Indonesia, the steps involves, first by looking at the generosity level of recent scenario. The result is comparable to Hanna and Olken ( 2018) with a newer dataset and recent context of budget reallocation consisting budget for social protection and the budget for fuel subsidy. The main point is that the generosity level needs to expand by a budget increase in social protection. Moreover, at international comparison, relative to Iran Salehi-Isfahani and Mostafavi-Dehzooei (2018), Indonesia’s benefit incidence with status quo budget is less generous. This is due to the larger amount of budget in Iran relative to current simulation in Indonesia. In PPP term, Iran offers about 90 USD PPP per month while Indonesia only about 12 USD PPP. This led to the following overall conclusion about feasibility of implementing a UBI in Indonesia. The summary of generosity and horizontal equity of main selected scenarios is provided in Table 10.

Table 10 Summary of generosity and horizontal equity from microsimulations

Case study DKI Jakarta Province*

National level simulation switching social protection budget**

National level simulation reallocating fuel subsidy***

Generosity per year at inclusion 100% (in rupiah)

- Household 4,345,734 489,286 255,304

- Individual 1,143,614

80% of horizontal equity obtained at … inclusion.

78% 75% 75%

Note: * with subsidy and social protection program’s budget in 2020, **with PKH Budget in 2018, *** with diesel and kerosene fuel subsidy budget in 2020.

First, at a national level, concerning both administrative readiness and fiscal space, Indonesia needs some stages of preparation to allow for implementing a full UBI in the medium-term. One of avenues to implement UBI in Indonesia is at the context of replacing the existing social protection and social security with a large cash transfer. Despite that the existence of social assistance in Indonesia was motivated by crisis response, the administrative capacity had been evolving and the development has been at its early maturity by the landmark of improved targeting. A dramatic switch toward unconditional and universal transfer will create a major shock in the system in which the administrative coverage is still low. Therefore, a further development of targeting database coverage toward higher inclusion is needed. On fiscal consideration, to implement a full UBI with


attractive generosity level, Indonesia needs a large outside financing from the existing toward the innovative ones. On the generosity calculation, the non-neutral budget will potentially slow down the poverty alleviation if a universal coverage implemented without an innovate financing.

Second, another feasible and attractive scenario is a quasi-UBI in the medium term by reallocating non-efficient fuel price subsidy into large cash transfer. The argumentation might similar to the exercise done by Coady and Prady (2019)and that it can generate broad support for structural reforms. Using India as an illustration, the paper discusses the trade-offs that need to be recognized in adopting a UI in these contexts. It shows that replacing the 2011 Public Distribution System (PDS in India arguing the progressive nature of factual benefit take up across income decile. The benefit for implementing this scenario is also in the form of environmental externality and reduced burden of fuel subsidy in the time of high fuel demand and price. In addition, like the first avenue mentioned above, the existing administrative database has its potential to be improved by a reforms and integration to make it ready for a full UBI. Current coverage of social protection by name and address of the bottom forty of the income (expenditure) distribution needs to expand. Expanding the existing social protection program database at national level into sixty percent coverage would be a desirable option for this scenario to work. The subsequent process after the expansion of the beneficiary database is to expand the inclusion in the taxation system. Indonesia has been in the low tax collection regime. Thus, implementing UBI might give a room to increase tax registration and the tax reporting as for the additional benefit in the future.

Third, local level UBI is more feasible. In addition to a subsidy reform as a second-best avenue to implement a quasi-UBI, a local level study case in DKI Jakarta Province provide a more promising avenue to implement local level basic income. The local government might see the exclusivity of UBI toward their citizen as the mechanism to maintain the speed of immigration to big cities which had been heavily burdened by urbanisation problem. Moreover, some region also has potential fiscal space. Therefore, the generosity level provides a good condition on political feasibility as it is attractive enough given the fiscal space available for existing social protection programs. While at national level exercise shows that the switch from social protection toward UBI potentially harms the poor, in DKI Jakarta it is not case. The generosity per household by switching the current subsidy and social protection budget into UBI is as higher as seven times of the poverty line making the potential harm to the poorer does not present. However, the administrative capacity to reach the large inclusion level is still far from ideal like the national level situation.


Local level quasi-UBI

(expanding local coverage)

National level quasi-UBI (expanding

national level coverage)

National level full UBI (expanding full national coverage and tax

registration expansion)

Figure 14 Steps for implementing a full UBI in Indonesia

Last, the overall exercise of literature review and the microsimulation suggests that implementing a full UBI in Indonesia involving several stepwise phases. 1. A local level quasi-UBI for subnational level with adequate fiscal capacity also a

desirable pathway to exercise how it works in a smaller scale level. The central government thus, can learn what work and what does not work to implement the quasi-UBI at national level.

2. Along with this move, one of the few options at the national level in the immediate term is to reframe the price-based subsidy at the national level into a quasi-UBI by gradually expanding the existing coverage of database. Switching social protection program would-be second-best alternative compared to this option.

3. Finally, a wider coverage of large cash transfer with a serious reform in the taxation system and to enhance the national room for fiscal capacity for a full UBI would be a desirable medium- or longer-term agenda for Indonesia.

The first and second step gives Indonesia with a temporary and not permanent UBI as the fiscal space suggest but not for local level quasi-UBI which has a better fiscal space. Lesson learned from Mongolia suggest that unsustain large cash-transfer would create political distress due to harming effect from the discontinuation and managing people’s expectation. Thus, implementing the national level quasi-UBI by removing fuel subsidy for example need a careful public communication so that the government does not create over expectation from public about its continuity. Managing this expectation is important to avoid unnecessary political distress associated with the quasi-UBI implemented.


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APPENDICES

Appendix 1 Proxy Mean Testing Regression Results with SUSENAS 2018

VariablesDependent variable: Log (per capita

consumption)

HH head age 31-50 -0.029***

(0.005)

HH head age 51+ -0.073***

(0.005)

HH is male 0.131***

(0.006)

HH is married -0.151***

(0.006)

Household size 0-2 0.490***

(0.006)

Household size 3-4 0.156***

(0.004)

1 dependent child -0.130***

(0.004)

2 dependent children -0.281***

(0.004)

3 or more dependent children -0.376***

(0.006)

Dependent older than 65 -0.135***

(0.004)

Highest ed HHH: None -0.044***

(0.005)

Highest ed. level of HH head: elementary -0.031***

(0.004)

Highest ed. level of HH head: high school 0.036***

(0.005)

Highest ed. level of HH head: tertiary 0.101***

(0.007)

Highest ed. level of anyone in HH: junior high 0.017**

(0.007)

Highest ed. level of anyone in HH: high school 0.029***

(0.007)

Highest ed. level of anyone in HH: SD 0.007

(0.006)

Highest ed. level of anyone in HH: tertiary 0.083***

(0.008)

1 child in tertiary ed 0.019***

(0.006)


2 child in tertiary ed -0.024

(0.017)

3 or more children in tertiary ed -0.036

(0.049)

HHH works in industry sector 0.049***

(0.004)

HHH works in service sector 0.086***

(0.003)

HHH self employed -0.137***

(0.007)

HHH self-employed with unpaid employment -0.164***

(0.007)

HHH employee -0.108***

(0.007)

Unpaid family worker -0.135***

(0.014)

Freelance or casual laborer -0.195***

(0.007)

Roof: Beton -0.116***

(0.013)

Roof: Genteng -0.026**

(0.013)

Roof: Asbes -0.005

(0.013)

Roof: Seng 0.058

(0.036)

Roof: Kayu, sirap, lainnya 0.046***

(0.015)

Walls: Tembok 0.023**

(0.010)

Walls: Kayu 0.099***

(0.006)

Wall:bambu atau lainnya -0.117***

(0.011)

Floor: not soil 0.084***

(0.006)

Milik Sendiri -0.061***

(0.010)

Kontrak/Sewa 0.001

(0.011)

Bebas Sewa -0.090***

(0.010)

Drinking water: air kemasan 0.104***

(0.004)


Drinking water: sumur bor -0.038***

(0.005)

Drinking water: sumur terlindungi -0.069***

(0.005)

Drinking water: sumur tak terlindungi -0.079***

(0.006)

Drinking water: lainnya -0.038***

(0.005)

Toilet: private 0.070**

(0.032)

Toilet: shared/public 0.034

(0.032)

Toilet: others -0.018

(0.032)

Septic tank 0.015***

(0.003)

PLN electricity with meter 0.055***

(0.005)

non-PLN electricity 0.179***

(0.007)

Gas, candles, other 0.133***

(0.008)

HH has a fridge 0.147***

(0.003)

HH has a 5.5 kg or more gas tube 0.165***

(0.005)

HH has a motorcycle 0.140***

(0.003)

HH has a AC 0.249***

(0.006)

HH has a car 0.344***

(0.005)

HH has a TV 0.179***

(0.004)

HH has a computer/laptop 0.142***

(0.004)

Urban-1, Rural-0 -0.022***

(0.003)

Obs. 129274.000

R2 0.553

Note: Standard errors in parentheses with * p < 0.1, ** p < 0.05, *** p < 0.01.


A. PKH and Energy Subsidy B. PKH and Non-energy subsidy

C. PKH and all subsidy D. PKH and all programs

E. Energy subsidy F. Non-energy subsidy

All subsidy

Appendix 2 The generosity level across different scenarios of fund reallocated at national level microsimulation


A. PKH and Energy Subsidy B. PKH and Non-energy subsidy

C. PKH and all subsidy D. PKH and all programs

E. Energy subsidy F. Non-energy subsidy

All subsidyAppendix 3 The social welfare across different scenarios of fund reallocated

Gd. R.M. NotohamiprodjoJl. Dr. Wahidin Raya No. 1 Jakarta Pusat - 10710Tel: +62 21 3441484

Website: http://fiskal.kemenkeu.go.id/

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