Green Economic Growth in Indira Hapsari Ahya Ihsan Indonesia Anthony Obeyesekere Dwi Endah Abriningrum Muhammad Khudadad Chattha JAN.2024 This work is a product of the staff of The World Bank. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights & Permissions © 2024 The World Bank 1818 H Street NW Washington, DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org Some rights reserved. The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowl- edge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. All queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@world- bank.org. Please cite the work as follows: “Hapsari, AT T RI B U T I O N Indira, Ahya Ihsan, Anthony Obeyesekere, Dwi Endah Abriningrum, and Muhammad Khudadad Chattha. 2024. “Green Economic Growth in Indonesia.” © World Bank.” P. 1 Contents 06 0811 Executive Summary Summary Overview SECTION 1 Introduction 33 53 55 SECTION 2 Fiscal Policies to Support Low-carbon Growth in Indonesia SECTION 3 Summary and Conclusions Bibliography P. 2 Figures Figure 1 GHG EMISSIONS 14 Figure 2 GHG EMISSIONS IN PER CAPITA TERMS 14 Figure 3 PER CAPITA EMISSIONS IN LINE WITH STAGE OF DEVELOPMENT 14 Figure 4 CARBON INTENSITY OF GROWTH SLOWING 14 Figure 5 FOLU AND ENERGY ARE INDONESIA’S MAIN DRIVERS OF GHG EMISSIONS (A) . ELECTRICITY AND TRANSPORTATION ARE THE TWO LARGEST CONTRIBUTORS OF EMISSIONS FROM ENERGY (B) 15 Figure 6 COAL HAS BECOME THE HIGHEST CONTRIBUTOR TO ENERGY SUPPLY 16 Figure 7 … WHILE ENERGY SUPPLY FROM RENEWABLES HAS BEEN LIMITED 16 Figure 8 THERE ARE SIGNS OF RELATIVE DECOUPLING IN INDONESIA 18 Figure 9 MANY COUNTRIES HAVE MODERATE TO HIGH CONCENTRATIONS OF AMBIENT OZONE 19 Figure 10 WELFARE LOSS FROM PM2.5 EXPOSURE HAS BEEN RISING STEADILY 20 Figure 11 GLOBALLY, DEATHS RELATED TO EXPOSURE TO AIR POLLUTANTS HAVE BEEN INCREASING AND WERE MAINLY CAUSED BY PM2.5 20 Figure 12 DEATHS RELATED TO EXPOSURE TO AMBIENT OZONE AND PM2.5 IN INDONESIA ROSE SIGNIFICANTLY 21 Figure 13 NON-COMMUNICABLE DISEASES CONTRIBUTE THE MOST TO INDONESIA'S REDUCTION IN DALYS 22 Figure 14 WHILE AIR POLLUTION IS MORE CLOSELY LINKED TO DALYS IN INDONESIA COMPARED TO OTHER COUNTRIES 22 Figure 15 DESPITE BEING ON THE LOWER RANGE, INDONESIA’S FOREGONE PER CAPITA INCOME INCREASED BETWEEN 2000 AND 2019 23 Figure 16 INDONESIA HAS HIGH PER CAPITA HUMAN CAPITAL LOSS 24 Figure 17 INDONESIA’S TOTAL WEALTH GREW ON PAR WITH MOST OF ITS PEERS SINCE 1995 26 Figure 18 DESPITE THE GROWTH IN TOTAL WEALTH, PER CAPITA WEALTH HAS GROWN RELATIVELY SLOWLY 26 Figure 19 PER CAPITA WEALTH OF LOWER-INCOME COUNTRIES ARE CONVERGING WITH HICS 27 Figure 20 INDONESIA'S PATH OF CONVERGENCE IS SIMILAR TO THAT EXPERIENCED BY THE BOTTOM 25 PERCENT OF PEERS 28 Figure 21 INDONESIA’S EXPORTS ARE NOT COMMODITY DEPENDENT 29 Figure 22 INDONESIA’S WEALTH ASSETS ARE ALSO SLIGHTLY MORE DIVERSIFIED COMPARED TO PEERS 29 Figure 23 INDONESIA'S NONRENEWABLE NATURAL CAPITAL DEPLETION RATE HAS BEEN DECLINING DURING 1995-2018 30 Figure 24 INDONESIA’S NONRENEWABLE RENTS REACHED ABOUT 4 PERCENT OF ITS GDP 30 Figure 25 AMONG INDONESIA’S RENEWABLE ASSETS, CROPLAND INCREASED THE MOST, BOTH IN ABSOLUTE TERMS AND SHARE OF TOTAL RENEWABLE RESOURCES 31 Figure 26 NONRENWABLE NATURAL CAPITAL WEALTH PER CAPITA IS DECLINING; PRODUCED AND HUMAN CAPITAL IS INCREASING 32 Figure 27 INDONESIA HAS A STABLE TREND OF OVERALL FISCAL BALANCE 34 Figure 28 FISCAL CONDITIONS HAVE BEEN RESILIENT TO COMMODITY PRICE SHOCKS 34 Figure 29 PUBLIC SPENDING IS POSITIVELY CORRELATED TO COMMODITY CYCLE 35 Figure 30 THERE IS A HIGH GAP BETWEEN OVERALL AND PRIMARY BALANCE DURING COMMODITY BOOM AND BUST 35 Figure 31 HIGH BUT DECREASING FOSSIL FUEL SUPPORT 36 Figure 32 MUCH SUPPORT GOES TOWARD PETROLEUM 36 Figure 33 MOST SUPPORT IS GEARED TO CONSUMERS 36 Figure 34 RESULTING IN HISTORICALLY LOW PETROL END-USER PRICES 36 Figure 35 AND LOW RESIDENTIAL ELECTRICITY PRICES 36 P. 3 Figure 36 TAX INCENTIVES ARE TARGETED MOSTLY TOWARDS NON-GREEN SECTORS 38 Figure 37 MOST OF THE FISCAL SUPPORT TAKES THE FORM OF SUBSIDIES TO FOSSIL FUELS 47 Figure 38 THE NET FISCAL INCENTIVES IN INDONESIA SKEW TOWARDS ENCOURAGING EMISSIONS 51 Tables Table 1 MEASURING WEALTH PER CAPITA 25 Table 2 FISCAL FOOTPRINT OF POLICY INSTRUMENTS THAT SHAPE THE INCENTIVES FOR CARBON USE AND CO 2EQ EMISSIONS 42 Table 3 THE COVERAGE AND DIRECTION OF INDONESIA’S FISCAL INCENTIVES FOR EMISSIONS-INTENSIVE ACTIVITIES 44 Box Box 1 FISCAL INSTRUMENTS TO SUPPORT THE TRANSITION TO LOW-CARBON EMISSIONS 39 Box 2 THE EMISSIONS TRADING SCHEME: A NON-FISCAL INSTRUMENT FOR CUTTING EMISSIONS 48 Appendix Appendix 1 LEGAL BASIS OF THE FISCAL INSTRUMENTS 56 P. 4 This report is prepared by the Macroeconomics, Trade and Investment Global Practice and the Governance Global Practice of the World Bank, led by Indira Maulani Hapsari with core authors comprising Ahya Ihsan, Anthony Obeyesekere, Dwi Endah Abriningrum, and Acknowledgments Muhammad Khudadad Chattha. The analysis is conducted under the guidance of Lars Moller (Practice Manager) and Habib Rab (Lead Economist). Assyifa Szami Ilman, Innes Clara, and Kathleen Tedi provided excellent research assistance. The authors would like to thank Ralph Van Doorn for his support in designing the framework for fiscal instruments analysis. The analysis also benefitted from input and feedback from the reviewers, Apurva Sanghi, Hector Pollitt, David Kaczan, and Muthukumara S. Mani. Valuable comments were also received from the Fiscal Policy Agency of the Ministry of Finance. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors and do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors or the countries they represent. All errors are the authors’ responsibility. Financial support for this report was generously provided by the Australian Government through the Australia-World Bank Indonesia Partnership (ABIP). Financial support was also provided by the Climate Support facility Whole-of-Economy Program, administered by the World Bank. P. 5 Abbreviations and Acronyms ANS Adjusted Net Savings CAIT Climate Analysis Indicator Tools CWoN Changing Wealth of Nations DALY Disability-adjusted Life Year DBE Demand-based Emissions ETS Emissions Trading Scheme FOLU Forestry and Other Land Use GDP Gross Domestic Product GHG Greenhouse Gas GNI Gross National Income HHI Hirschman-Herfindahl Index HIC High-income Country IPPU Industrial process and product use LGST Luxury Goods and Services Tax LUCF Land Use Change and Forestry MoEF Ministry of Environment and Forestry MoEMR Ministry of Energy and Mineral Resources MoF Ministry of Finance NCD Non-communicable Disease OECD Organisation for Economic Co-operation and Development PBE Production-based Emissions PLN Perusahaan Listrik Negara (State-owned electricity company) PSO Public Service Obligation UNCTAD United Nations Conference on Trade and Development Executive P. 6 Summary P. 7 his paper provides a macro-fiscal overview of Indonesia’s progress along four dimensions of T green growth linked to each other from both the outcomes and policy perspectives: (i) car- bon use in the growth process; (ii) the impact of carbon use through pollution on human cap- ital; (iii) the consequence on national wealth; and (iv) fiscal policies to support the low-carbon transition. Although carbon emissions have risen in Indonesia, this paper notes that they have started to slow down—including signs of relative decoupling from growth in per capita income. This is mainly attributed to land use change and forestry reforms, including mora- toriums on land conversion—which has reduced deforestation rates. Reducing carbon emissions in Indonesia can have important local benefits through reduced pollution and its adverse effects on health and human capital. Indonesia’s total wealth has grown in line with other emerging markets, but per capita wealth has lagged that of peer countries, and the composition of the wealth stock raises con- cerns about the sustainability of growth. Sound macro-fiscal policies have helped manage commodity price volatility, but the fiscal frame- work overall could be better aligned with decarbonization objectives, which could help Indonesia to achieve long-term growth sustainability. Summary P. 8 Overview his paper provides a macro-fiscal overview of Indonesia’s progress along four interlinked T dimensions of green growth. The first three sections will discuss green growth from the out- comes perspective, while the last section will look at green growth from the policy perspec- tive: (i) carbon use in the growth process; (ii) the impact of carbon use through pollution on hu- man capital; (iii) the consequence of carbon use on national wealth; and (iv) the fiscal policies to support the low-carbon transition. The paper takes stock of Indonesia’s progress in decarbonizing growth. It then analyzes the extent to which fiscal policies are aligned with this overall objective. P. 9 Although greenhouse gas (GHG) emissions have risen in Indone- sia, this has started to slow down and there are signs of a rela- tive decoupling from growth in per capita income. Per capita emis- sion levels align with Indonesia’s development stage and other large emerging market economies. Unlike other emerging market econo- mies, Indonesia’s biggest GHG contributor is forestry and other land use (FOLU). The slowdown in CO2 emissions in recent years has been associated with reforms around LUCF, including moratoriums on land conversion—which have reduced deforestation rates. The energy sec- tor is Indonesia’s second largest contributor to emissions due to the significant use of fossil fuels in the energy mix. Reducing GHG emissions in Indonesia could have important local benefits through reduced pollution and associated negative effects on health and human capital. GHG emissions result in increased lo- cal air pollution. Forest fires and the use of fossil fuels—particularly coal for power generation and industry, and oil for transport—are sig- nificant sources of such pollution. In Indonesia, the casualties from air pollution have been rising rapidly. The number of deaths from am- bient ozone and fine particulate matter (PM2.5) in Indonesia was less than 60,000 in 2000 but had almost doubled by 2019. These have contributed to a decrease in disability-adjusted life years (DALYs) and thereby a lower life expectancy in Indonesia. For example, residents of Jakarta can expect to lose 2.3 years of their life expectancy if the pollution levels in 2016 are sustained over their lifetime. The carbon-intensive growth has consequences for Indonesia’s wealth, which although growing in line with other emerging mar- ket economies, has lagged peer countries on a per capita basis. The composition of the wealth stock raises concerns about the sus- tainability of growth. Indonesia experienced faster growth in per capi- ta gross domestic product (GDP) than in per capita wealth from 1990 to 2018, suggesting that, despite rapid short-term GDP growth, long- term growth could slow unless earnings can be better used to build up national wealth. Increasing human capital wealth will be essential for fulfilling Indonesia's ambition of becoming a high-income country (HIC) by 2045. Sound macro-fiscal policies have helped manage commodity price volatility, but the fiscal framework overall could be better aligned with decarbonization objectives. Indonesia’s fiscal policies P. 1 0 have historically incentivized fossil fuel consumption and GHG emis- sions, although ongoing reforms are trying to redress this issue. This paper considers how key fiscal instruments alter the incentives for carbon-intensive activities, and how they come together as an over- arching framework that promotes or discourages GHG emissions. It finds that fiscal instruments encourage more than they discourage polluting activities. For example, non-green sectors received almost 30 percent of tax expenditures. In this context, cross-sector coverage gaps in fiscal disincentives, conflicting incentives within sectors, and cross-sector inconsistencies in incentives are worth reviewing. 01 P. 1 1 P.11-32 INTRODUCTION limate action and sustainable use of nature in C Indonesia are intertwined with the country’s long-term growth prospects. Sustaining growth and improvements in the standard of living will require continued progress towards a low-carbon and climate-resilient economy. These shifts will require policies incentivizing more efficient use of natural resources and low-carbon production. Indonesia has experienced significant development transitions in the past 25 years, which have resulted in rising GHG emissions.1 As seen in many countries, economic growth has had negative im- pacts on climate and environmental sustainability. At the same time, Indonesia has made important commitments and actions to meet its climate and development targets. As stated in the Low Carbon Devel- opment Initiative (LCDI), Indonesia is looking for ways to “maintain economic and social growth through development activities with low GHG emissions and minimizing the exploitation of natural resources” (Bappenas 2021). Therefore, it is important to analyze green growth 1 In this note, we measure carbon emissions as net emissions developments in Indonesia and what policies, particularly from a which include emissions from forestry and other land use (FOLU). P. 1 2 macro-fiscal perpective, have and can be further implemented to support green growth. The paper draws upon on a clear definition of green growth. Spe- cifically, it uses the Organisation for Economic Co-operation and De- velopment (OECD) definition as laid out in its green indicators report (OECD 2011). Green growth is defined as “fostering economic growth and development while ensuring that the natural assets continue to provide the resources and environmental services on which our well-being relies. To do this, it must catalyze investment and innova- tion, which will underpin sustained growth and give rise to new eco- nomic opportunities” (OECD 2011). This paper provides a macro-fiscal overview of Indonesia’s progress on green growth, benchmarked against selected structural peer countries2 along four linked dimensions. The first three sections will discuss green growth from an outcomes perspective, while the last section will look at green growth from a policy perspective: • Carbon use in the growth process—including the sources of carbon emissions in the economy and the carbon intensity of growth. Both Indonesia’s emissions and global emissions negatively impact the country’s development through climate shocks, pollution, and the erosion of adaptation capacity. • Pollution and its impact on human capital—in particular, the detrimental effects on health, including respiratory problems, premature deaths, and loss of productive capacities and labor earnings. 2 This analysis uses a standard basket of peers where data allows. Structural peers are Nigeria, • Impact of carbon use on national wealth3—including human, China, India, Ukraine, Thailand, physical, and natural stocks. the Philippines, Mexico, the Arab Republic of Egypt, the Russian Federation, and Brazil, selected • Fiscal policies for the low-carbon transition and how they based on their statistical similarity in terms of population, GDP per affect household and firm incentives to reduce carbon-inten- capita, and total GDP. An additional set of aspirational peers is also sive consumption. used when relevant: Republic of Korea, Chile, Poland, and the Czech Republic. In some instances, The objective of the paper is to provide a snapshot of Indonesia’s developed countries are also used progress on these dimensions of green growth relative to other large as comparisons when discussing emissions levels and targets. emerging market economies. It draws on two frameworks and their 3 Definition of wealth and the associated datasets: (i) the OECD Green Growth Indicators framework; methodology to calculate wealth will be explained in the respective and (ii) the World Bank’s Changing Wealth of Nations (CWoN) framework section (Section 1.12). that measures a country’s natural, human, and physical capital stocks. P. 1 3 The Carbon Content of Growth in Indonesia Carbon Emission in the Growth Process ndonesia has experienced remarkable eco- nomic transformations since the early 1990s. I Its real income per capita more than doubled from US$1,488 in 1990 to US$3,757 in 2020 (constant 2015), with the poverty rate declin- ing from 19 percent in 2000 to 9.4 percent in 2019. Growth has been accompanied by rapid urbanization (from 36 percent of the population in 1995 to 66 percent in 2020) and improved access to services and development outcomes. Today, Indonesia is the 16th largest economy globally, accounting for 1.25 percent of global GDP, and the 4th most populous country globally. Economic transformation has come with rising GHG emissions, which (per capita) are broadly in line with Indonesia’s stage of economic development. Indonesia accounts for about 3.5 percent of global GHG emissions (Climate Watch 2023).4 Annual GHG emis- sions per capita have increased since the mid-2000s as income per capita increased. GHG emissions annually averaged 1,495 million tonnes of carbon dioxide equivalent (MtCO2eq), during 2018-2020 (Figure 1). However, it now shows signs of slowing (Figure 2). In re- cent years, per capita emissions in Indonesia have been in line with those of other large developing economies and lower than those of large, developed economies (Figure 3). No country has yet transi- tioned to high-income while reducing emissions. The high emissions base has meant that GHG emissions overall in- creased only moderately between 1990 and 2018 (by 35 percent). China and India saw much larger overall increases in GHG emissions (above 400 percent and 300 percent, respectively) but also have larger populations and economies and experienced faster economic growth. GHG emissions in Indonesia have translated to high but de- clining GHGs emitted per unit of GDP (Figure 4). GHG emissions from 4 Emissions for 2018 include forestry and land use, and all major greenhouse gases (link). P. 1 4 energy per unit of GDP have not increased as dramatically as in peer countries despite Indonesia's increased dependence on coal. FIG 1 GHG EMISSIONS FIG 2 GHG EMISSIONS IN PER CAPITA TERMS ANNUAL GHG EMMISIONS INTERQUARTILE RANGE ANNUAL GHG EMMISIONS INTERQUARTILE RANGE (ALL GHG, 3-YEAR MOVING INDONESIA PER CAPITA (ALL GHG, INDONESIA AVERAGE) 3-YEAR MOVING AVERAGE) 2.500 8 7 2.000 6 5 MTC0 2 EQ 1.500 4 1.000 3 2 500 1 0 0 1995 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 FIG 3 PER CAPITA EMISSIONS IN LINE WITH FIG 4 CARBON INTENSITY OF GROWTH SLOWING STAGE OF DEVELOPMENT PER CAPITA GDP (PPP CONSTANT 2017) VS. PER CAPITA CARBON INTENSITY OF INTERQUARTILE RANGE EMISSIONS (ALL GHG, TCO 2 EQ) (1990-2019) GROWTH (ALL GHG, 3-YEAR INDONESIA MOVING AVERAGE) 25 0,005 UNITED STATES PER CAPITA EMISSIONS MTC0 2 E/1000 USD GDP 20 0,004 15 0,003 NIGERIA 10 ITALY GERMANY 0,002 CHINA JAPAN INDONESIA THAILAND UNITED KINGDOM 5 0,001 INDIA BRAZIL FRANCE MEXICO PHILIPPINES 0 0,000 0 20.000 40.000 60.000 1995 2000 2005 2010 2015 2020 PER CAPITA GDP Sources: World Development Indicators (World Bank databank); Climate Notes: Interquartile range, the difference between the first quartile (lower Watch Data Explorer; Ministry of Environment and Forestry (MoEF) data; range) and the third quartile (upper range), refers to the performance of figures compiled by World Bank Group staff. structural peers (see Footnote 1). Figures include emissions from land use change and forestry. For the bottom left figure, lines show polynomial trends for 1990-2019 in per capita emissions. The main source of GHG emissions in Indonesia historically has come from FOLU, but land-based emissions have started to de- cline in recent years. FOLU accounted for the largest share of GHGs— about 40 percent of all GHGs on average between 2016-18 (Figure 5). Forest and peatland fires fueled GHG emissions, caused environ- P. 1 5 mental degradation, and imposed economic and health costs. The forest fires in 2015 burned approximately 2.6 million hectares of land and caused economic costs exceeding US$16 billion (or nearly 2 percent of GDP). However, in recent years, tightened forest and peatland protection from the authorities—along with other measures such as peatland rewetting and reduced impact logging, contributed to a slowdown in land-related emissions. Deforestation slowed from an average of 1.08 million hectares per year between 2000-07, to 0.61 million hectares per year between 2007-14 and to an average of 0.48 million hectares per year between 2014-21. Deforestation averaged 0.11 million hectares per year between 2019-21, its lowest rate since 1990. FIG 5 FOLU AND ENERGY ARE INDONESIA’S MAIN DRIVERS OF GHG EMISSIONS (A) . ELECTRICITY AND TRANSPORTATION ARE THE TWO LARGEST CONTRIBUTORS OF EMISSIONS FROM ENERGY (B) A. SECTOR CONTRIBUTION TO AGRICULTURE B. SECTOR CONTRIBUTION TO ENERGY GHG EMISSION ALL GHG EMISSIONS (PERCENT, FOLU (PERCENT, AVERAGE 2016-2018) AVERAGE 2016-2018) ENERGY BUILDING OTHER FUEL COMBUSTION MANUFACTURING/ INDUSTRIAL CONSTRUCTION FUGITIVE EMISSIONS ELECTRICITY/HEAT WASTE TRANSPORTATION 140 100 120 100 80 PHILIPPINES 80 INDONESIA 60 THAILAND 60 UKRAINE NIGERIA TURKEY MEXICO RUSSIA BRAZIL PHILIPPINES CHINA 40 INDIA INDONESIA 40 THAILAND 20 UKRAINE NIGERIA TURKEY MEXICO RUSSIA BRAZIL EGYPT CHINA 0 INDIA 20 -20 -40 0 C. GROWTH OF ALL GHG FOLU INDUSTRIAL D. GROWTH OF CO 2 ELECTRICITY/HEAT TRANSPORTATION EMISSIONS BY SECTOR WASTE AGRICULTURE EMISSIONS WITHIN ENERGY MANUFACTURING/CONSTRUCTION (1990=100) ENERGY SECTOR (1990=100) OTHER FUEL COMBUSTION FUGITIVE EMISSIONS 500 600 BUILDING 400 500 400 300 300 200 200 100 100 0 0 1990 1994 1998 2002 2006 2010 2014 2018 1990 1994 1998 2002 2006 2010 2014 2018 Sources: Climate Analysis Indicators Tool (CAIT) dataset, World Bank staff estimates. RENEWABLE COAL GAS OIL RENEWABLE GAS OIL COAL NUCLEAR 100 100 100 80 PHILIPPINES 80 INDONESIA 60 THAILAND 60 UKRAINE P . 16 The energy sector is the second largest contributor to GHG emis- NIGERIA TURKEY MEXICO RUSSIA BRAZIL PHILIPPINES CHINA 40 INDIA INDONESIA 40 sions in Indonesia due to the significant use of fossil fuels in the THAILAND 20 UKRAINE NIGERIA TURKEY MEXICO RUSSIA BRAZIL energy mix. Energy accounted for about 39 percent of GHG emis- EGYPT CHINA 0 INDIA 20 -20 sions in Indonesia between 2000 and 2020. About 93 percent of the -40 0 energy supply comes from fossil fuels, namely coal (43 percent), oil C. GROWTH OF ALL GHG FOLU INDUSTRIAL D. GROWTH OF CO ELECTRICITY/HEAT EMISSIONS BY SECTOR (31 percent), WASTE and gas (19 AGRICULTURE percent). EMISSIONS From WITHIN 1985 to ENERGY 2019, the share TRANSPORTATION 2 MANUFACTURING/CONSTRUCTION (1990=100) of coal in Indonesia’s SECTOR ENERGY energy (1990=100) mix increased dramatically (Figure OTHER FUEL COMBUSTION FUGITIVE EMISSIONS 500 6). Although the coal industry’s 600 BUILDING is less than share in the economy 2 percent and only employs 500 0.2 percent of the workforce, Indone- 400 sia has become the world’s second-largest coal exporter. About 400 300 80 percent of Indonesia’s coal is exported (coal briquettes account for 300 200 11.5 percent of total exports), while 90 percent of domestic coal consumption fuels more200 than 50 percent of electricity generation. The 100 share of renewables has 100remained relatively low (Figure 7). 0 0 1990 1994 1998 2002 2006 2010 2014 2018 1990 1994 1998 2002 2006 2010 2014 2018 FIG 6 COAL HAS BECOME THE HIGHEST FIG 7 … WHILE ENERGY SUPPLY FROM CONTRIBUTOR TO ENERGY SUPPLY RENEWABLES HAS BEEN LIMITED RENEWABLE COAL GAS OIL RENEWABLE GAS OIL COAL NUCLEAR 100 100 80 80 60 60 40 40 PHILIPPINES KOREA REP. 20 INDONESIA THAILAND UKRAINE TURKIYE POLAND MEXICO WORLD BRAZIL 20 EGYPT CHINA CHILE INDIA 0 OECD 1965 1968 1971 1974 1977 1980 1983 1986 1989 1990 1993 1996 1999 2001 2004 2007 2010 2016 2019 0 Source: BP Statistical Review of World Energy through OurWorldinData. Source: BP Statistical Review of World Energy through OurWorldinData. Note: Renewables include biofuels, solar, wind, hydro, geothermal, biomass, and others. Some high-income countries (HICs) have managed to reduce emis- sions while accelerating growth, although their per capita emis- sions remain higher than many large developing countries. GHG emissions have been strongly correlated with income—particularly at low-to-middle income levels. As a country’s income rises, it emits more GHG because of the higher use of energy, which often comes from fossil fuels. However, this relationship does not necessarily hold at high-income levels. Many countries have achieved econom- P. 1 7 ic growth while reducing emissions—known as absolute decoupling. One study (Hubacek et al. 2021) shows that 32 of 116 countries have decoupled production-based emissions (PBE) and GDP, 23 countries have decoupled demand-based emissions (DBE)5 and GDP, and 14 countries have decoupled both DBE and PBE from GDP. There are two main reasons: first, some countries have managed to decouple energy use and economic growth (GDP has increased while total en- ergy use has remained flat or even fallen), and second, countries are replacing fossil fuels with low-carbon energy. The challenge for Indonesia and other developing countries is that no country has transitioned to high income while simultaneously reducing emissions. This is the challenge implicit in the low-carbon transition. Although progress has been made in reducing emissions while growing, results at the country level have been mixed (Hubacek et al. 2021). For example, most EU countries and the US have seen absolute decoupling at high per capita GDP and emissions due to more efficient technology and improved energy mix. However, other countries have experienced no decoupling between GDP and emis- sions. It is also important to note that decoupling can also be tem- porary, and decoupled countries may revert to increasing emissions. Decoupling growth from emissions will be easier for developing coun- tries if the cost of low-carbon (cleaner) energy continues to fall. Nevertheless, there are encouraging signs of relative decoupling 5 Consumption-based emissions are emissions that have been in Indonesia (where the rate of emissions growth is slower than adjusted for trade (i.e., production emissions within the countries that of economic growth). Between 1990 and 2018, the growth of minus emissions embedded in exports plus emissions embedded real GDP (270 percent) surpassed the growth of all GHG emissions in imports). Production-based (36 percent) and of emissions from energy (190 percent) during the emissions is production emissions within the countries, which do not same period—indicating relative decoupling but not absolute decou- account for emissions coming from traded goods and services. pling (Figure 8).6 It is worth noting that higher growth countries such 6 Decoupling occurs when the as China show stronger relative decoupling, although they also pro- growth rate of an environmental pressure (for example, CO2 duce higher emissions, while India shows weaker relative decoupling. emissions) is less than that of its economic driving force (for example, GDP per capita) over a given period. Decoupling can be either absolute or relative. Absolute decoupling is said to occur when CO2 emissions are stable or decreasing while the GDP per head is growing. Relative decoupling is when the growth rate of CO2 emissions is positive, but less than the growth rate of the GDP per capita (Link). P. 1 8 FIG 8 THERE ARE SIGNS OF RELATIVE DECOUPLING IN INDONESIA (GDP and Total GHG, Constant 2015 US$, MtCO 2eq) INDONESIA GDP (CONSTANT 2015 US$) CHINA GDP (CONSTANT 2015 US$) INDIA GDP (CONSTANT 2015 US$) ALL GHG (MtCO 2 EQ) ALL GHG (MtCO 2 EQ) ALL GHG (MtCO 2 EQ) 400 1400 600 350 1200 500 300 1000 400 250 800 200 300 600 150 200 400 100 200 100 50 0 0 0 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 Sources: CAIT dataset, World Bank staff estimates. The Impact of GHG Emissions and Pollution on Human Capital HG emissions result in increased pollution,7 which is indirectly detrimental to welfare and G productivity. Pollutants of major health concern include particulate matter (PM) or black carbon, methane, carbon monoxide (CO), ozone (O3), ni- trogen dioxide (NO2), and sulfur dioxide (SO2). The use of fossil fuels for power generation, in- dustry, and transport, as well as forest fires, are a significant sources of many of these pollutants. In addition, house- hold activities such as cooking and heating with solid fuels on open 7 Pollution is defined as the fires or traditional stoves, though excluded in the measurement of OZONE µG/M³ presence of substances and heat 0 TO <42 GHG emissions, can also contribute to air pollution. in environmental media (air, water, 42 TO <50 land) whose nature, location, or 50 TO produces quantity <58 undesirable Many countries—including Indonesia—have high concentrations of 58 TO <65 effects (UN environmental Database). 65 TO <73 pollutants8, where the air quality was rated moderately unsafe in NO DATA 8 Black carbon, a component 2020. This was due to a high annual mean concentration of PM2.5 at of fine PM, warms the earth’s 8.1 times above the WHO annual guideline (IQAir 2021). The mining atmosphere by absorbing sunlight and accelerating the melting and oil and gas industries, automobile manufacturing, vehicle emis- of snow and ice. Methane is a potent GHG that is 84 times more sions, and forest fires are all contributing factors to this poor air qual- powerful than CO2 and a precursor to the air pollutant ozone (WHO ity. The significant increases in electricity generation from coal-fired 2021). P. 1 9 power plants has been another significant contributor (Greenstone and Fan 2019). Seasonal air pollution variations also exist, with the INDONESIA levels of pollution highest CHINA GDP (CONSTANT 2015 US$) occurring during GDP (CONSTANT 2015 US$) INDIA the dry season (June to GDP (CONSTANT 2015 US$) ALL GHG (MtCO EQ) ALL GHG (MtCO EQ) ALL GHG (MtCO EQ) October). 2 2 2 400 1400 600 350 Air pollution contributes to welfare loss, although Indonesia’s 1200 500 300 welfare losses appear to be at the lower range of peer countries. 1000 250 Between 2000 and 2019, the welfare losses 400 from ambient ozone in 200 Indonesia grew by 10.2 percent. Similarly, 800 300 exposure to PM2.5 caused 150 rising welfare 600 losses in Indonesia between 2000 and 2019 (Figure 200 100 400 estimate, air pollution due to ambient ozone and PM2.5 10). By one 50 200 cost Indonesia about 4.5 percent could have 100 of GDP in welfare loss. 0 0 0 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 FIG 9 MANY COUNTRIES HAVE MODERATE TO HIGH CONCENTRATIONS OF AMBIENT OZONE (Population-weighted concentration of ambient air pollution to which the population is potentially exposed, 2019) OZONE µG/M³ 0 TO <42 42 TO <50 50 TO <58 58 TO <65 65 TO <73 NO DATA Source: https://www.stateofglobalair.org/data/#/air/map Note: 60µg/m³ represents the lower range of WHO recommendations for air pollution exposure over which adverse health effects are observed. P. 2 0 FIG 10 WELFARE LOSS FROM PM2.5 EXPOSURE HAS BEEN RISING STEADILY (Welfare loss from PM2.5 exposure, GDP equivalent) INTERQUARTILE OF TOP-10 POLLUTERS INDONESIA 9,0 8,0 7,0 6,0 5,0 4,0 3,0 Source: Green Growth Indicators, 2,0 OECD Stat, 2021. World Bank staff 1,0 calculations. 0,0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Note: Interquartile range includes both lower and upper ranges The consequence RESIDENTIAL RADON of air pollution on welfare loss takes the form AMBIENT OZONE LEAD PM2.5 of 6,0 health problems and premature deaths. Globally, in 2019, about 5.4 5,5 million deaths (9.6 percent of total deaths) were caused by air 5,0 pollution, 4,5 which is rising (Figure 11). Air pollution-related diseases in- 4,0 clude 3,5 respiratory infections and INTERQUARTILE OF TOP-10 POLLUTERS tuberculosis, neoplasms, cardiovas- INDONESIA 3,0 cular 2,5 9,0 diseases, chronic respiratory disease, cancers, diabetes, and 2,0 chronic 1,5 8,0 kidney disease. The burden of diseases attributable to air pollution 1,0 7,0 0,5 is estimated to be equivalent to other major global health risks, 0,0 6,0 such as unhealthy diets and tobacco smoking. In 2017, the 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 State 5,0 of Global Air ranked air pollution in the top five risk factors that 4,0 cause death, ranked by the total number of deaths from all causes 3,0 for all ages and both sexes. INDONESIA 2,0 INTERQUARTILE OF TOP-10 POLLUTERS 1,0 0,14 0,0 0,12 11 FIG GLOBALLY, DEATHS RELATED TO EXPOSURE TO AIR POLLUTANTS HAVE 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 BEEN INCREASING AND WERE MAINLY CAUSED BY PM2.5 0,10 (Number of deaths, millions) 0,08 RESIDENTIAL RADON AMBIENT OZONE LEAD PM2.5 0,06 6,0 0,04 5,5 5,0 0,02 4,5 4,0 0,00 3,5 3,0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2,5 2,0 1,5 1,0 0,5 0,0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Source: Green Growth Indicators, OECD Stat, 2021. 1,0 0,5 0,0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 P. 2 1 FIG 12 DEATHS RELATED TO EXPOSURE TO AMBIENT OZONE AND PM2.5 IN INDONESIA ROSE SIGNIFICANTLY (Number of deaths, millions) INTERQUARTILE OF TOP-10 POLLUTERS INDONESIA 0,14 0,12 0,10 0,08 0,06 0,04 0,02 Source: Green Growth Indicators, 0,00 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 OECD Stat, 2021. World Bank staff calculation. The casualties from air pollution, the byproduct of GHG emissions, have been rising rapidly in Indonesia. The number of deaths from ambient ozone and PM2.5 in Indonesia were less than 60 thousand in 2000, but this has increased rapidly (Figure 12). Chronic respira- tory disease from indoor air pollution has also increased the risks of premature deaths and deteriorating health conditions. Indoor air pollution contributed to higher respiratory infections and chronic ob- structive pulmonary disease, with those most at risk being women and young children who spend a large amount of time exposed to open fires (WHO). Indoor air pollution comes from cooking fuel—45 percent of households use kerosene as their source of cooking fuel. These ambient air pollutants have contributed to an increase in disability-adjusted life years (DALYs)9 and a lower life expectancy in Indonesia. According to Mboi et al. (2018), although health out- comes across many indicators had improved in Indonesia between 1990 and 2016, the improvements were partly offset by rising deaths and a growing burden of non-communicable diseases (NCDs). For the same period, total DALYs from NCDs rose—with a substantial in- crease linked to air pollution. The existing pollution levels in Indone- sia are estimated to have lowered life expectancy by an average of 1.2 years (Figure 13). For example, residents of Jakarta can expect to lose 2.3 years of their life expectancy if the 2016 pollution levels are sustained over their lifetime. 9 One DALY represents the loss of the equivalent of one year of full health. P. 2 2 Indonesia has lost a full-health year due to NCDs linked to ambient air pollution. Indonesia’s DALYs attributed to air pollution reached 7.6 percent of total DALYs—significantly higher than the average for aspirational peers10 and major global emitters (4.2 percent and 10 Aspirational peers are countries where Indonesia aspires 4.7 percent, respectively) (Figure 14). According to Gordon et al. to be, typically higher per capita (2017), people most affected by air pollution are children and the income countries. elderly, particularly in low- and middle-income countries. FIG 13 NON-COMMUNICABLE DISEASES FIG 14 WHILE AIR POLLUTION IS MORE CLOSELY CONTRIBUTE THE MOST TO INDONESIA'S LINKED TO DALYS IN INDONESIA REDUCTION IN DALYS COMPARED TO OTHER COUNTRIES (Rank of contributors to DALYs in 2016) (Contribution, percent, 2019) RANK 12,0% TOP-10 POLLUTERS ASPIRATIONAL 1 2 3-4 PHILIPPINES INDONESIA MALAYSIA THAILAND 5-7 8-12 >13 VIETNAM TURKEY BRAZIL INDIA HIGH SYSTOLIC BLOOD 1 1 4 1 3 5 3 2 10,0% PRESURE DIETARY RISKS 2 4 3 2 1 3 5 4 HIGH FASTING PLASMA 3 6 5 4 4 4 4 5 GLUCOSE TOBACCO 4 5 6 3 2 1 2 1 8,0% 7,6% CHILD AND MATERNAL 5 7 1 11 7 12 6 8 MALNUTRITION HIGH BODY-MASS INDEX 6 2 9 5 6 6 1 10 AIR POLLUTION 7 11 2 8 5 8 10 6 6,0% HIGH TOTAL CHOLESTROL 8 8 8 6 8 10 7 9 OCCUPATIONAL RISKS 9 9 12 9 11 7 8 7 4,0% IMPAIRED KIDNEY FUNCTION 10 10 11 10 10 9 9 11 UNSAFE WATER, SANITATION, 11 14 7 16 12 13 14 15 AND HANDWASHING ALCOHOL AND DRUG USE 12 3 10 7 9 2 11 3 2,0% LOW PHYSICAL ACTIVITY 13 13 13 12 13 14 12 13 UNSAFE SEX 14 12 15 13 14 11 16 12 LOW BONE MINERAL DENSITY 15 15 16 14 16 15 15 14 OTHER ENVIRONMENTAL 0,0% 16 16 14 15 15 17 13 16 INDIA CHINA INDONESIA UKRAINE RUSSIA BRAZIL JAPAN GERMANY US CANADA POLAND KOREA CZECH CHILE RISKS SEXUAL ABUSE AND VIOLENCE 17 17 17 17 17 16 17 17 Source: Mboi et al. June 2018. Source: World Bank 2021b. P. 2 3 The health impacts of air pollution in Indonesia also erode human capital, which is detrimental to the country’s potential output. In 2018, Indonesia lost 0.9 percent of per capita human capital due to air pollution (Figure 16). It is worth noting, however, that the relative impact of reducing air pollution-related deaths decreases as income levels increase, resulting in a smaller change in per capita human capital from decreased air pollution as total human capital increases due to economic growth (CwoN World Bank 2021). For example, some major global emitters such as Japan, Canada, Germany, and the US 11 Adjusted Net Savings is an indicator to measure a country’s experience lower per capita losses due to air pollution compared to particulate emission damage (in other top polluters such as Russia, Ukraine, Brazil, and China. current US$). In this note, the estimate is adjusted into per capita terms in current US$/capita. In addition, exposure to ambient pollutants also erodes Indone- Moreover, the database defines particulate emissions damage as sia’s Adjusted Net Savings (ANS).11 In 2019, the foregone per the damage due to exposure of a country’s population to ambient capita income due to exposure to air pollutants in Indonesia was concentrations of PM2.5, ambient ozone, and indoor concentrations of US$22.20—more than three times higher than US$7.30 in 2000 PM2.5 in households cooking with (Figure 15). This suggests that if there were no premature deaths solid fuels. Damages are calculated as foregone labor income due to resulting from exposure to air pollution, Indonesia’s per capita in- premature death. Estimates of health impacts from the Global come would have increased by about US$22.20 in 2019. The impact Burden of Disease Study 2013 are for 1990, 1995, 2000, 2005, of eliminating air pollution on per capita income was higher in 2019 2010, and 2013. Data for other than in 2000, indicating a deteriorating air quality trend in Indonesia years have been extrapolated from trends in mortality rates. between 2000 and 2019. FIG 15 DESPITE BEING ON THE LOWER RANGE, INDONESIA’S FOREGONE PER CAPITA INCOME INCREASED BETWEEN 2000 AND 2019 (Foregone labor income due to premature deaths attributable to air pollution, current US$/capita) INTERQUARTILE OF TOP-10 POLLUTERS INDONESIA 40 35 30 25 20 15 10 5 Source: World Bank 2021b. World 0 Bank staff calculation. 1990 2000 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Note: The indicator is ANS: particulate emission damage. 0 1990 2000 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 P. 2 4 FIG 16 INDONESIA HAS HIGH PER CAPITA HUMAN CAPITAL LOSS (X axis: per capita human wealth, log, 2018 US$; Y axis: hypothetical human capital wealth per capita, percent from base) 15 STRUCTURAL AND TOP-10 POLLUTERS India STRUCTURAL BENCHMARK TOP-10 POLLUTERS Philippines Egypt ASPIRATIONAL 10 Indonesia Nigeria 5 China Ukraine Thailand Poland Turkey Mexico Czech Rep Germany Russia Japan Brazil Chile United States Korea Rep Canada 0 2 3 4 5 6 7 Source: Global Burden of Disease Study and World Bank 2021b. World Bank staff calculation. The Consequence of Carbon-Emitting Growth on the Accumulation of Wealth he carbon content of growth, which is the flow of national income, has implications for na- T tional wealth accumulation, which is the stock of human, physical, and natural resources in the country. National wealth is central to long- term growth. The wealth accounting methodol- ogy tries to quantify the lifetime earnings of a country’s assets and considers the sustainabili- ty of natural, produced, and human capital (World Bank 2021b). For example, human capital is calculated as a population’s discounted expected lifetime earnings. A similar approach applies to fossil fuel wealth, estimated as the discounted value of future resource rents until these assets are depleted. The methodology tries to provide a more complete picture of an economy than traditional GDP accounts by covering issues such as depletion of subsoil assets, loss of ecosys- tems, or agricultural damage resulting from extreme weather events (Table 1). P. 2 5 TABLE 1 MEASURING WEALTH PER CAPITA Wealth per capita, beginning of period Factor Minus Plus Produced capital Normal depreciation Investment in produced capital: buildings, Not included: catastrophic losses from natural structures, machinery, intellectual property disasters or civil conflicts, obsolescence Nonrenewable Extraction Increase in proven reserves and production; natural capital Other reductions in proven reserves and increase in unit rent due to: production volume • Lower market price Decrease in unit rent due to: • Higher production cost • Lower market price Accelerated extraction path • Higher production cost Not included: the impact of changes in Extended extraction path future prices and policies, because these are unknown Not included: the impact of changes in future prices and policies, because these are unknown Renewable natural Extraction greater than natural regeneration Increase in harvestable extent, improved capital Degradation condition, increase in unit rent due to: Decrease in unit rent due to: • Lower market price • Lower market price • Higher production cost • Higher production cost Not included: the impact of changes in future prices and policies, because these are Not included: the impact of changes in unknown future prices and policies, because these are unknown Human capital Decline and/or aging of the labor force, Growth of the labor force through growth of declining wage rates, decline in education the domestic population, increased labor force Changing wage growth trajectory due to participation, or migration (gain to one country, economic shocks as COVID-19 loss to another) Not included: loss of human capital from Increasing wage rates; increasing education missed schooling and health damages from COVID-19 Loss of human capital via migration Net foreign assets Foreign liabilities Foreign assets Population change Mortality Births Out-migration Immigration Wealth per capita, end of period Source: World Bank (2021b). Indonesia’s total wealth growth has been lagging behind its structural peers, though it remains faster than the global rate. Between 1995 and 2018, wealth almost doubled globally, reach- ing US$1,152 trillion, while Indonesia’s wealth more than doubled— reaching US$12.9 trillion in 2018 (averaging 4 percent growth an- nually) (Figure 17). This increase is on par with some of Indonesia’s peers, such as Egypt, Nigeria, and the Philippines. On the other hand, it is slower than China, Turkey, Chile, the Republic of Korea, and India, where human capital contributed the most to wealth accumulation. P. 2 6 In Indonesia, both human capital and physical capital are closely associated with commodity price trends. Both accelerated during the commodity boom in 2003 and decreased during the price down- turn in 2012. This was in line with a decline in labor earnings, one of the key components in human capital estimates, particularly in agriculture and mining (Allen 2016). FIG 17 INDONESIA’S TOTAL WEALTH GREW ON PAR FIG 18 DESPITE THE GROWTH IN TOTAL WEALTH, WITH MOST OF ITS PEERS SINCE 1995 PER CAPITA WEALTH HAS GROWN (Average growth of wealth, 1996-2018, RELATIVELY SLOWLY percent) (Increase in per capita wealth, 1996-2018, thousands) INTERQUARTILE RANGE OF PEERS INDONESIA 9 120 8 100 7 6 80 5 60 4 40 3 SOUTH KOREA 20 PHILIPPINES 2 CZECH REP. INDONESIA THAILAND NIGERIA POLAND TURKEY MEXICO RUSSIA BRAZIL 1 0 EGYPT CHINA CHILE INDIA IRAN 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 0 Source: World Bank 2021b. World Bank staff calculation. Source: World Bank 2021b. World Bank staff calculation. P. 2 7 Indonesia’s per capita wealth has not grown as quickly as in peer countries since 1995 (Figure 18). Per capita wealth INTERQUARTILE RANGE OF PEERS INDONESIA increased for 9 during this period. Indonesia experienced a most countries globally 120 8 faster per capita GDP growth than per capita wealth growth, suggest- ing that, despite rapid short-term 100 GDP growth, long-term growth could 7 slow unless earnings can be used more to build up national wealth. 6 80 This has resulted in a relatively slow convergence of wealth per capita between Indonesia 60 and HICs. Per capita wealth growth was 5 4 the slowest for high-income OECD countries compared to others, but per capita wealth growth 40in lower-income countries also stagnated 3 (Figure 19). Indonesia’s per capita wealth convergence has been SOUTH KOREA 20 slow relative to high-income economies (US), staying almost flat be- PHILIPPINES 2 CZECH REP. INDONESIA THAILAND tween 1995 and 2018 and at the bottom end of the interquartile NIGERIA POLAND TURKEY MEXICO RUSSIA BRAZIL 1 0 EGYPT CHINA CHILE INDIA range of its structural peers (Figure 20). China and India have con- IRAN 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 0 verged faster. FIG 19 PER CAPITA WEALTH OF LOWER-INCOME COUNTRIES ARE CONVERGING WITH HICS (Growth of per capita wealth from 1995 to 2018) LOW-INCOME HIGH-INCOME: OECD LOWER-MIDDLE INCOME HIGH-INCOME: NON-OECD UPPER-MIDDLE INCOME 500 % GROWTH IN TOTAL WEALTH PER CAPITA 1995-2018 400 300 200 100 0 -100 2.000 20.000 200.000 2.000.000 TOTAL WEALTH PER CAPITA, 1995 (2018 US$, LOG SCALE) Source: World Bank 2021b. WDI, World Bank staff calculations. P. 2 8 FIG 20 INDONESIA'S PATH OF CONVERGENCE IS SIMILAR TO THAT EXPERIENCED BY THE BOTTOM 25 PERCENT OF PEERS (Per capita wealth excluding nonrenewable source, convergence to US, index 1=total convergence) INTERQUARTILE RANGE OF PEERS INDONESIA 0,14 0,12 0,10 0,08 0,06 0,04 0,02 0,00 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 Source: World Bank 2021b. WDI, World Bank staff calculations. The composition of Indonesia’s wealth is relatively diversified, with human capital remaining the largest asset category, but its share has been declining over time. The share of human capital decreased from 62 percent in 1995 to 53 percent in 2018, while Indonesia’s physical capital increased. Natural capital is the smallest asset cate- gory. Although commodity-related exports account for 55 percent of total exports, they are lower than many countries in Africa or South America (Figure 21). Indonesia’s asset diversification increased be- tween 1995 and 2018 (Figure 22). Indonesia’s natural wealth is high in absolute terms due to large endowments of fossil fuels, forests, and agricultural lands. In re- cent years, Indonesia has reduced its rate of nonrenewable natural resource depletion as it has transitioned toward increased production of renewable natural capital (Figure 23). The nonrenewable natural 0-20 capital share of total wealth typically changes as a country develops. 20-40 As countries experience rising incomes, nonrenewable natural capital 40-60 60-80 first increases, then declines. 80-100 P. 2 9 FIG 21 INDONESIA’S EXPORTS ARE NOT COMMODITY DEPENDENT (Share of commodity export product to total merchandise exports, percent) 0-20 20-40 40-60 60-80 80-100 Source: UNCTAD Commodity State of Dependence, 2020. Note: Data is for 2018-19. A country is considered to be commodity-export dependent when more than 60 percent of its total merchandise exports are composed of commodities. FIG 22 INDONESIA’S WEALTH ASSETS ARE ALSO SLIGHTLY MORE DIVERSIFIED COMPARED TO PEERS Herfindahl Index of Asset Diversification, Indonesia and peers BRAZIL 6500 INDIA MEXICO 6000 RUSSIA CHINA 5500 INDONESIA NIGERIA THAILAND 5000 EGYPT IRAN 4500 PHILIPPINES TURKEY 4000 3500 3000 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 Source: World Bank 2021b. World Bank staff calculations. Note: Hirschman Herfindahl Index (HHI) is the quadratic sum of each share of asset class to total assets. It ranges from 0-10,000, where HHI of less than 1,500 is considered a highly diversified assets base, an HHI of 1,500 to 2,500 is moderately concentrated, and an HHI of 2,500 or greater is highly concentrated. BRAZIL CONGO, DEM REP GHANA COAL RENTS NATURAL GAS RENTS INDONESIA RUSSIAN FEDERATION MINERAL RENTS OIL RENTS P. 3 0 Resource rents from nonrenewables in Indonesia are small and be- BRAZIL 6500 low the average of its peers. In 2018, they accounted for 4 percent INDIA of GDP, while average peers stood at 5.7 percent (Figure 24). Indone- MEXICO 6000 RUSSIA sia’s large share of nonrenewable natural capital and rents pose risks CHINA INDONESIA 5500 to the country from several challenges that are typical for countries NIGERIA with a high share of fossil-fuel capital: (i) high exposure to low-carbon THAILAND 5000 EGYPT transition risks; (ii) high potential for reduced government revenues IRAN 4500 derived from fossil fuel wealth; (iii) policies and investments that PHILIPPINES TURKEY might further increase low-carbon transition risk; and (iv) the difficul- 4000 ty of diversifying away from nonrenewable natural capital (Cust and 3500 Manley 2018). FIG 23 3000NONRENEWABLE NATURAL INDONESIA'S FIG 24 INDONESIA’S NONRENEWABLE RENTS CAPITAL DEPLETION RATE HAS BEEN REACHED ABOUT 4 PERCENT OF ITS GDP 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 DECLINING DURING 1995-2018 (Nonrenewable natural capital rents, (Nonrenewables capital depletion, percent of GDP, 2018) percent of Gross National Income-GNI) BRAZIL CONGO, DEM REP GHANA COAL RENTS NATURAL GAS RENTS INDONESIA RUSSIAN FEDERATION MINERAL RENTS OIL RENTS 10 IRAN RUSSIA 9 NIGERIA 8 EGYPT 7 INDONESIA 6 BRAZIL MEXICO 5 UKRAINE 4 INDIA 3 THAILAND 2 CHINA 1 PHILIPPINES TURKEY 0 1995 2000 2005 2010 2015 2018 0% 5% 10% 15% 20% 25% Source: World Bank 2021b. World Bank staff calculation. Source: World Bank 2021b. WDI, World Bank staff calculation. P. 3 1 Meanwhile, between 1995 and 1998, renewable natural capital 12 Renewable natural capital assets such as cropland, pastureland, protected areas, mangroves, remains important even as countries grow and develop. and forest timber resources saw increases in absolute value12 Developing an economy requires (Figure 25). These were driven by increases in physical quantities efficient use of natural capital and managing it sustainably. in some cases (e.g., for cropland), as well as in monetary unit value It is, therefore, important to invest in renewable capital (e.g., for mangroves, which protect increasingly valuable coastal as- to build other asset types as the country’s economy grows. sets). The rising trends in agricultural capital are similarly observed Globally, there is a positive in Indonesia's structural peers. relationship between renewable capital and a country’s total wealth. Renewable capital grows as a country develops, also suggesting that renewable capital is complementary to other capital such as produced and human capital. FIG 25 AMONG INDONESIA’S RENEWABLE ASSETS, CROPLAND INCREASED THE MOST, BOTH IN ABSOLUTE TERMS AND SHARE OF TOTAL RENEWABLE RESOURCES A. CHANGE IN RENEWABLE CAPITAL (US$ MN) B. SHARE OF RENEWABLE RESOURCES FORESTS, TIMBER PROTECTED AREAS FISHERIES PASTURELAND FORESTS, TIMBER PROTECTED AREAS FISHERIES PASTURELAND MANGROVES FORESTS, ECOSYSTEM CROPLAND MANGROVES FORESTS, ECOSYSTEM CROPLAND SERVICES SERVICES 1.200.000 100% 90% 1.000.000 80% 70% 800.000 60% 600.000 50% 40% 400.000 30% 20% 200.000 10% 0 0% AVG 2000-2003 AVG 2015-2018 AVG 2000-2003 AVG 2015-2018 Source: World Bank 2021b. World Bank staff calculation. INDONESIA PHYSICAL CAP HUMAN CAP BRAZIL PHYSICAL CAP HUMAN CAP Indonesia has exploited its natural capital, particularly nonrenew- RENEWABLES NON RENEWABLES NON RENEWABLES RENEWABLES 400 able resources, to produce 700 physical and human capital. Natural 350 capital, particularly nonrenewables, 600 has declined since 2013 (due 300 to both physical exploitation 500 and variation in global commodity pric- 250 200 es which are reflected in natural capital values). Human capital has 400 150 increased after declining300during the Asian Financial Crisis in 1997 100 due to earning losses; the 200 accumulation rate since then has been 50 slow although from a higher base than produced capital and natural 100 0 0 capital. Human capital accumulation started to accelerate in 2002 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 with the onset of the commodity boom period but declined again in IRAN 2011 PHYSICAL CAP(Figure 26). HUMAN CAP NIGERIA PHYSICAL CAP HUMAN CAP RENEWABLES NON RENEWABLES RENEWABLES NON RENEWABLES 250 350 600.000 50% 40% 400.000 40% 30% 400.000 30% 20% P. 3 2 200.000 200.000 FIG 26 NONRENWABLE NATURAL 20% PRODUCED AND HUMAN 10% CAPITAL WEALTH PER CAPITA IS DECLINING; CAPITAL IS INCREASING 0 10% 0% AVG 2000-2003 (Annual Indexed Per Capita Wealth, AVG 2015-2018 Indonesia vs Select AVG 2000-2003 Structural AVG 2015-2018 0 Peers, 1995 = 100) 0% AVG 2000-2003 AVG 2015-2018 AVG 2000-2003 AVG 2015-2018 INDONESIA PHYSICAL CAP HUMAN CAP BRAZIL PHYSICAL CAP HUMAN CAP INDONESIA RENEWABLES PHYSICAL CAP NON RENEWABLES HUMAN CAP BRAZIL RENEWABLES PHYSICAL CAP NON RENEWABLES HUMAN CAP RENEWABLES NON RENEWABLES RENEWABLES NON RENEWABLES 400 700 400 350 700 600 350 300 600 500 300 250 500 400 250 200 400 200 300 150 300 150 200 100 200 100 50 100 50 100 0 0 0 0 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 IRAN PHYSICAL CAP HUMAN CAP NIGERIA PHYSICAL CAP HUMAN CAP IRAN RENEWABLES PHYSICAL CAP NON RENEWABLES HUMAN CAP NIGERIA RENEWABLES PHYSICAL CAP NON RENEWABLES HUMAN CAP RENEWABLES NON RENEWABLES RENEWABLES NON RENEWABLES 250 350 250 350 300 200 300 200 250 150 250 200 150 200 100 150 100 150 100 50 100 50 50 50 0 0 0 0 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 1995 1997 2001 2003 2005 2007 2009 2011 2013 2015 2017 Source: World Bank 2021b. World Bank staff calculation. 13 Growth sustainability can be The pace of wealth accumulation may need to accelerate for Indo- measured by ANS as it measures nesia to each high-income status by 2045. With a higher accumula- how a nation’s assets can turn into income. The World Bank in tion of wealth, Indonesia will have the potential to increase its output the 1990s also introduced ANS as a proxy of change in wealth, and thus boost its economic growth. Economic growth remains sus- represented by savings. ANS is measured as gross national saving tainable, with the share of ANS to GNI increasing.13 Indonesia’s ANS minus depreciation of produced capital, depletion of subsoil assets as a share to GNI has increased by 4.3 percentage points despite and timber resources, and air GDP per capita increasing by more than 100 percentage points. Sim- pollution damage to human health, plus a credit for expenditures on ilarly, in China, GDP per capita almost tripled while the share of ANS education. A country is considered consuming more than it is saving in GNI increased by 6.9 percentage points. Indonesia has reduced if the ANS as a percentage of GNI is negative, risking its long-term its natural resource depletion rate in recent years (Figure 26), which sustainability. If ANS is positive, led to an increase in ANS. However, further increasing human capital then it is increasing its wealth and future economic well-being. wealth will be essential for reaching HIC by 2045. 02 P. 3 3 P.33-52 FISCAL POLICIES TO SUPPORT LOW-CARBON GROWTH IN INDONESIA Macro-fiscal Policy Framework and Commodity Price Volatility verall, macro-fiscal policy in Indonesia has O helped the country to manage commodity price volatility. Countries with higher exposure to nonrenewable wealth per capita had higher fiscal deficits during the 2015-18 period when commodity prices fell. Despite Indonesia’s ex- posure to commodity prices, it performed rel- atively well in terms of macro-fiscal outcomes, with a lower decrease in overall fiscal balance during the commodity bust period (Figure 27). This could partly be because its natural re- source rents during commodity boom and bust periods have been relatively low and stable, compared to other countries (Figure 28). P. 3 4 FIG 27 INDONESIA HAS A STABLE TREND OF OVERALL FISCAL FIG 28 FISCAL CONDITIONS HAVE BEEN RESILIENT TO COMMODITY PRICE SHOCKS BALANCE (Change in rent per capita, constant (Overall fiscal balance and 2018 US$) wealth per capita, 2000- 2018) A. OVERALL BALANCE VERSUS WEALTH B. CHANGE IN RENT PER CAPITA 2000-2003 TO 2004-14 PER CAPITA, 2000-2018 2004-14 TO 2015-18 CASE STUDY COUNTRY GABON SIMILAR GDP PER CAPITA COMPARTOR CHILE RUSSIAN FEDERATION HIGHER GDP PER CAPITA COMPARTOR MEXICO DECLINING OR STAGNANT WEALTH SOUTH AFRICA PER CAPITA COUNTRY MALAYSIA NIGERIA 10 EGYPT, ARAB REP. PERU COLOMBIA 5 BRAZIL OVERAL BALANCE (% OF GDP) INDONESIA VIETNAM COD THA THAILAND 0 TUR GAB MOROCCO MDG VNM MEX RUS BGD PER CHL LIBERIA MAR IDN COL MYS LBR NGA TURKEY -5 BDI PAK BEN ZAF PAKISTAN GHA KEN BANGLADESH BRA KENYA -10 MADAGASCAR EGY BURUNDI BENIN -15 CONGO, DEM. REP. 10,000 100,000 GHANA -2,000 -1,500 -1,000 -500 0 500 1000 1,500 TOTAL WEALTH PER CAPITA (CONSTANT 2018 US$, LOG SCALE) RENT CHANGE (CONSTANT 2018 US$) Source: World Bank CORRELATION 2021b. World BETWEEN Bank staff estimates. COMMODITY Source: CHANGE World Bank 2021b. IN GDP, World Bank 2000-2003 TO staff estimates. OVERALL BALANCE PRICES AND SPENDING 2015-18 PRIMARY BALANCE 0,35 In the past, public spending GABON NIGERIA has been positively correlated with 0,3 commodity prices. However,KENYA the link has waned over time thanks to RUSSIAN FEDERATION prudent macro-fiscal policies—especially BRAZIL cutbacks in fossil-fuel sub- 0,25 LIBERIA sidies (Figure 29). In other TURKEYwords, as commodity prices rise, current EGYPT, ARAB REP. 0,2 expenditure accelerates. The SOUTH correlation is positive and significant. AFRICA PAKISTAN 0,15 of spending from the commodity price cycle The gradual decoupling INDONESIA PERU CHILE prudence measures and prioritization of has been attributed to fiscal EXPENDITURE EXPENDITURE EXPENDITURE MOROCCO 0,1 spending towards development. During more recent commodity price CURRENT VIETNAM CAPITAL rallies, declining subsidies BENIN (especially after 2015) and offsetting rev- TOTAL 0,05 COLOMBIA enues have helped keepMEXICOthe primary balance in check. Moreover, the BANGLADESH 0 overall balance deteriorated GHANA by less than the primary balance when MADAGASCAR -0,05 compared to the commodity boom (2000-2003) and bust (2015- CONGO, DEM. REP. BURUNDI 2018) periods (Figure 30). This is due to sound macro-fiscal policies THAILAND MALAYSIA -0,1 that enabled debt to decline by gradually decoupling -12 -10 -8 -6 -4 -2 spending 0 2 4 6 from 8 the commodity price cycle, reducing interest burden, and increasing PERCENTAGE POINT CHANGE spending on development (see World Bank 2020b). KEN BANGLADESH OVERAL B BRA KENYA -10 MADAGASCAR EGY BURUNDI . 35 P -15 FIG 29 PUBLIC SPENDING IS POSITIVELY CORRELATED TO FIG 30 BENIN THERE IS A HIGH GAP BETWEEN OVERALL AND PRIMARY BALANCE DURING CONGO, DEM. REP. 10,000 COMMODITY CYCLE 100,000 GHANA COMMODITY BOOM AND BUST -2,000 -1,500 -1,000 -500 0 500 1000 1,500 (Correlation coefficient, 1 = TOTAL WEALTH PER CAPITA (Change in GDP, 2000-2003 to 2015-2018) completely correlated) (CONSTANT 2018 US$, LOG SCALE) RENT CHANGE (CONSTANT 2018 US$) CORRELATION BETWEEN COMMODITY CHANGE IN GDP, 2000-2003 TO OVERALL BALANCE PRICES AND SPENDING 2015-18 PRIMARY BALANCE 0,35 GABON NIGERIA KENYA 0,3 RUSSIAN FEDERATION BRAZIL 0,25 LIBERIA TURKEY EGYPT, ARAB REP. 0,2 SOUTH AFRICA PAKISTAN INDONESIA 0,15 PERU EXPENDITURE EXPENDITURE EXPENDITURE CHILE MOROCCO 0,1 CURRENT VIETNAM CAPITAL BENIN TOTAL 0,05 COLOMBIA BANGLADESH MEXICO 0 GHANA MADAGASCAR CONGO, DEM. REP. -0,05 BURUNDI THAILAND -0,1 MALAYSIA -12 -10 -8 -6 -4 -2 0 2 4 6 8 PERCENTAGE POINT CHANGE Source: Haver Analytics. World Bank staff estimate. Source: World Bank 2021b. World Bank staff estimate. Aligning Fiscal Policy to the Low- carbon Transition ndonesia’s fiscal policies have historically incentivized carbon consumption, although I ongoing reforms are trying to redress this. In- centives are driven by low taxation of, and subsi- dies for, fossil fuels. Support for fossil fuels as a share of tax revenue in Indonesia has declined, with a sharp drop in 2015 (Figure 31). This drop was driven by ambitious transport fuel subsidy 14 As per the 2020 national reform in 2014-15. Petroleum received nearly one-half of total fossil budget. This includes reported fuel support although this has declined over the 20 years to 2020 direct subsidy spending and estimated implicit subsidies (Figure 32). Cuts in full support (from 3.9 percent of GDP in 2000 to accruing as payment obligations to Pertamina, the state-owned oil and 1.8 percent in 2020)14 created space for higher spending on health, gas enterprise. P. 3 6 infrastructure, and social assistance. Social assistance increased from 0.3 percent of GDP in 2004 to 1.5 percent in 2021. Total fuel subsidy expenditure rose because of the energy crisis in 2022, al- though the government has increased administered prices to contain these pressures. FIG 31 HIGH BUT DECREASING FOSSIL FUEL FIG 32 MUCH SUPPORT GOES TOWARD PETROLEUM SUPPORT TOTAL FOSSIL FUEL SUPPORT INTERQUARTILE RANGE PETROLEUM SUPPORT INTERQUARTILE RANGE INDONESIA INDONESIA 35 100 % TOTAL FOSSIL FUEL SUPPORT 30 % OF TOTAL TAX REVENUE 80 25 20 60 15 40 10 20 5 0 0 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 FIG 33 MOST SUPPORT IS GEARED TO CONSUMERS FIG 34 RESULTING IN HISTORICALLY LOW PETROL END-USER PRICES FOSSIL FUEL CONSUMER SUPPORT INTERQUARTILE RANGE PETROL END-USER SUPPORT INTERQUARTILE RANGE INDONESIA INDONESIA 100 35 % TOTAL FOSSIL FUEL SUPPORT 80 USD PER LITRE 25 60 40 10 20 0 0 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 FIG 35 AND LOW RESIDENTIAL ELECTRICITY PRICES RESIDENTIAL ELECTRICITY PRICE INTERQUARTILE RANGE INDONESIA 0,5 0,4 USD PER KWH 0,3 0,2 0,1 0 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Sources: OECD Green Growth Data, figures compiled by World Bank Group staff. Note: Interquartile range refers to equivalent data for the 25th and 75th percentile of structural peers (see Footnote 1). P. 3 7 Historically, most fossil fuel support is poorly targeted and does not benefit those who need it the most. Most fossil fuel support is targeted at consumers rather than producers (Figure 33). This results in low petrol end-user prices (Figure 34) designed to assist house- holds. However, benefits accrue more to the better-off households because they are more significant fuel consumers than the poor. In the power sector, electricity tariffs are set below cost recovery under a Public Service Obligation (PSO) arrangement (Figure 35). Although efforts have been made (especially between 2015 and 2017) to re- assign consumers to non- or less-subsidized tariff classes through means testing, many relatively better-off households still benefit from the PSO tariff. Approximately 45 percent of the PSO is used to sub- sidize households that do not fall within the database for poor and vulnerable households. The current economic environment creates challenges for the re- duction of fossil fuel subsidies, but there are steps that can be taken to help gradually move the process forward. Authorities in a range of countries sometimes decide to choose fuel price subsi- dies over targeted transfers at a time when energy prices are high because: (i) many poor households may not receive social transfers sufficient to compensate for higher fuel prices; (ii) price controls can shield producers from higher input costs; and (iii) price controls help keep inflation expectations in check. This occurs despite evi- dence showing that targeted transfers are more cost-effective in mit- igating the poverty impacts of price increases (World Bank 2022b). Addressing and re-targeting subsidies will require sustained efforts to strengthen the delivery infrastructure for social protection and devise transfers consistent with political imperatives—such as time- bound transfers to affected households. Steps can also be taken to redirect tax incentives directed to- wards ‘non-green sectors.’ A significant proportion of Indonesia’s tax expenditure is shown to be targeted at non-green sectors. Some 29 percent of Indonesia’s tax expenditures are targeted at these sec- tors (Figure 36)—amounting to 0.46 percent of GDP. These incentives are primarily targeted at mining oil, gas, and coal via exemptions on import duties and property taxes. P. 3 8 FIG 36 TAX INCENTIVES ARE TARGETED MOSTLY TOWARDS NON- GREEN SECTORS (Tax incentives by sector, share to total, percent) SHARE OF NON-GREEN TAX INCENTIVES IN TAX EXPENDITURE (%) 2% GREEN TAX INCENTIVES NON-GREEN TAX INCENTIVES OTHER 29% 69% Sources: Ministry of Finance (MoF) Tax Expenditure Data 2018; World Bank staff calculation. 4,000,000 Note: Green sectors are sectors with renewable energy, such as geothermal and low-emissions vehicles. Non-Green sectors include those with fossil fuel energy, such as oil, gas, coal, and electricity consumption. Other sectors, such as 3,500,000 books, post services, insurance, and others, are not explicitly classified into those two. SUB BUSINESS AND INDUSTRY 3,000,000 2,500,000 Fiscal Instruments and Incentives for ELECTRICITY SUBSIDY: ELECTRICITY SUBSIDY: a Low-carbon Transition FUEL TAX: PERTALITE PERTALITE SUBSIDY CPO EXPORT TAXES SUB HOUSEHOLDS 2,000,000 VAT EXEMPTIONS: FUEL TAX: DIESEL COAL ROYALITIES DIESEL SUBSIDY 1,500,000 LPG SUBSIDY CARBON TAX ELECTRICITY closer look at Indonesia’s fiscal instruments 1,000,000 presents opportunities to navigate the above A 500,00 challenges and help the government achieve 0 its climate ambitions. This section considers In- donesia’s specific INSTRUMENTS THAT DECREASE THE COST OF EMISSIONS THAT instruments fiscal INSTRUMENTS that INCREASE THE COST shape OF EMISSIONS GHG emissions incentives. It begins by invento- rying Indonesia’s relevant fiscal instruments and then investigates the fiscal framework for GHG emissions that they collectively represent—focusing on budgetary impacts, coverage, inconsistencies. Fiscal policy offers a range of instruments that can support the government’s efforts on decarbonization. Fiscal instruments have their effect by incentivizing businesses and households to reduce their carbon footprint, whether by discouraging emissions-intensive activities or promoting activities with a lower or zero carbon footprint (see Box 1). For instance, taxes can be used to penalize the use of emissions-intensive fossil fuels, subsidies can encourage consum- P. 3 9 ers to switch to greener options, and tax expenditures can promote renewable energy investments. Fiscal instruments can, however, also shape incentives in ways that obstruct a country’s green transition. Several of Indonesia’s current fiscal instruments, originally imple- mented with other policy objectives in mind, are already impacting In- donesia’s green and climate objectives, not always in favorable ways. BOX 1 FISCAL INSTRUMENTS TO SUPPORT THE TRANSITION TO LOW- CARBON EMISSIONS I ndonesia has over a dozen fiscal instruments that influence the incentives for emitting GHGs. These instruments take the form of taxes and excise duties, activity-specific licenses, direct and indirect subsidies, and tax expenditures arising from preferential tax treatment. They target both the consumers and producers of emissions-intensive goods and services and the consumers and producers of greener alternatives. They have been implemented for various reasons (for example, industry promotion, revenue collection, or social protection), none of which typically relate to emissions mitigation. This is unsurprising, given the government’s diverse objectives, which evolve. Therefore, it would be unreasonable to expect that these instruments would constitute a coherent and effective overarching fiscal regime for pricing emissions and achieving the government’s mitigation goals. The following inventory briefly introduces Indonesia’s most noteworthy fiscal instruments, categorizing them by the primary direction in which they currently shift emitter incentives.15 Fiscal instruments that primarily discourage emissions • Palm oil export taxes: An export levy and an export duty are levied on palm oil exports. Both are progressive, in that they tend to be higher when global prices are higher, although the levy does have a stipulated maximum rate. Derivative palm oil products have related but typically lower levy and duty rates. Land conversions for expanding palm oil plantations are a significant source of GHG emissions. 15 The legal basis for these instruments is documented in Appendix 1. P. 4 0 • Forestry license: Forestry licenses are required by subnational governments for activities such as collecting timber or non-timber forest products, using forest areas, and using environmental services. There are significant emissions of GHGs during deforestation. • Coal royalties: Coal miners are subject to a royalty on their sales. The applicable royalty rate depends on the type of license the mining firm holds but can be up to 13.5 percent before any allowable deductions. Coal is one of the most GHG-emissions-intensive fossil fuels, and Indonesia is the world’s third-largest producer. • Carbon tax: Indonesia has planned a phased introduction of a tax on carbon-dioxide-equivalent (CO2eq) emissions. It was scheduled to commence in 2022, with initial implementation in the coal-fired power sector, but has been postponed. The carbon tax will work together with an emissions trading scheme in this sector. • Fuel tax: There is a provincial government tax on motor vehicle fuels (for example, diesel and gasoline). Although an ad-valorem rate of up to 10 percent is permitted, almost all provinces apply a rate of 5 percent. The transport sector accounts for about 27 percent of Indonesia’s total energy-related CO2eq emissions. • Luxury goods and service tax (LGST) incentives: LGST reductions are offered for fuel-efficient and battery- powered vehicles and implemented through reductions in the applicable LGST tax base. LGST is reimbursed or not collected on sales to businesses engaged in exploration and exploitation in the oil, gas, and geothermal sectors. • Income tax borne by government: The government’s tax dues from geothermal firms’ proceeds, from geothermal energy that is supplied to power plants, is borne by government up to annual limits designated in the national budget. This only applies to geothermal operations that have been operating since 2002. P. 4 1 Indonesia has the world’s largest potential for geothermal power generation, an important substitute for fossil fuels. Fiscal instruments that primarily encourage emissions • Zero royalty on coal value addition: Coal miners are potentially eligible for a zero-rate coal royalty on coal that they use for domestic value-added activities. Such activities include the use of coal-fired power plants. • VAT exemptions: VAT is exempted from electricity sales for residential connections less than 6600 VA capacity. • Fuel subsidies: There is an explicit, fixed, per liter subsidy on diesel fuel of IDR 500/liter. There are also subsidies on a popular brand of gasoline (Pertalite) and on LPG when sold in 3kg cannisters; both are implemented by setting administered retail prices below the cost of supply. The government reimburses the supplier for corresponding losses. • Electricity subsidy: An electricity subsidy is implemented through administered below-cost retail prices for low-voltage connections. The government reimburses the supplier for corresponding losses. Indonesia’s grid-connected electricity is predominantly generated by high-emitting coal-fired power plants. • Fertilizer subsidy: There is a subsidy on fertilizers to the agriculture sector, implemented through below-cost pricing of fertilizers. The government reimburses the supplier for corresponding losses. Fertilizers account for about 10 percent of emissions from the agriculture sector (Savelli et al. 2021). • Import duty exemptions: Import duty is exempted on imported goods for businesses engaged in exploration and exploitation in the oil, gas, and geothermal sectors. • Land and building tax exemptions: Land and building tax is fully deductible for businesses engaged in P. 4 2 exploration in the oil, gas, and geothermal sectors. • Capital injections into the national electricity company: Perusahaan Listrik Negara (PLN), the national electricity company, has received annual capital injections from the central government since 2019. These assist PLN in raising finance by maintaining key metrics, such as debt service coverage ratio, within loan covenants. Overall, fiscal policies that encourage GHG emissions are more sig- nificant than those that discourage GHG emissions. Fiscal policies encouraging GHG emissions may have been equivalent to 1.5 percent of GDP in 2019, while policies discouraging emissions might have reached about 0.5 percent of GDP (Table 2). Most instruments have a relatively minor fiscal footprint, while just a few are particularly large. Moreover, energy subsidies alone might have amounted to double the fiscal footprint of all other relevant instruments in 2019. The implica- tion is twofold. First, Indonesia’s fiscal regime potentially lowers the price of carbon and, therefore, acts counter to decarbonization efforts. Second, significant headway on greening the fiscal regime may be possible through renewed reform efforts focused on energy subsidies. TABLE 2 FISCAL FOOTPRINT OF POLICY INSTRUMENTS THAT SHAPE THE INCENTIVES FOR CARBON USE AND CO 2EQ EMISSIONS Fiscal Instrument Fiscal Gain / Burden (Rp) Fiscal Gain / Burden (% of GDP) Fiscal instruments that primarily discourage emissions Palm oil export taxes Levy: Rp 20.2 T (2020) Levy: 0.1 % (2020) Duty: Data not available Duty: Data not available Forestry license Forestry revenues:(a) Rp 5.0 T (2019), Rp 4.4 Forestry revenues: 0.0% (2019), 0.0% T (2020) (2020) Coal royalties Production contribution and royalties: Rp Production contribution and royalties: 0.1% 12.6 T (2020) (2020) Carbon tax Estimated at: Rp 0.2 T for first full year 0.0% (2022) Fuel tax Rp 21.2 T (2019), Rp 18.1 T (2020) 0.1% (2019), 0.1% (2020) LGST incentives Rp 2.3 T (2019), Rp 1.2 T (2020) 0.0% (2019), 0.0% (2020) Income tax borne by Rp 2.2 T (2019), Rp 3.0 T (2020) 0.0% (2019), 0.0% (2020) government Import duty exemptions Rp 0.0 T [36 billion] (2020)(b) 0.0% (2020) (geothermal) Land and building tax Rp 0.0 T (2019), Rp 0.0 T (2020) 0.0% (2019), 0.0% (2020) exemptions (geothermal) P. 4 3 Fiscal Instrument Fiscal Gain / Burden (Rp) Fiscal Gain / Burden (% of GDP) Fiscal instruments that primarily encourage emissions Zero royalty on coal Initiated in 2021. Data not available. Data not available. value addition VAT exemptions Rp 6.0 T (2019), Rp 6.0 T (2020) 0.0% (2019), 0.0% (2020) Fuel subsidies (c) Rp 89.7 (2019), Rp 2.7 (2020), Rp 151.4 (d) 0.6% (2019), 0.0% (2020), 0.9% (2021) (2021) Electricity subsidy(e) Rp 103.8 (2019), Rp 78.4 (2020), 94.4% 0.6% (2019), 0.4% (2020), 0.5% (2021) (2021) Fertilizer subsidy Rp 27.2 T (2021) 0.2% (2021) PLN capital injections Rp 6.5 (2019), Rp 5.0 (2020), Rp 5.0 (2021) 0.0% (2019), 0.0% (2020), 0.0% (2021) Import duty exemptions Rp 0.8 B (2020) 0.0% (2020) Land and building tax Rp 0.1 T (2019), Rp 0.0 T (2020) 0.0% (2019), 0.0% (2020) exemptions Income tax holiday Data not available(f) Data not available Sources: MoF; Ministry of Energy and Mineral Resources (MoEMR); Pertamina; and World Bank staff estimates. Notes: (a) Comprising of income categories as: reforestation fund; forest resources; forest product utilization business permit fee; use of forest areas for development purposes outside forestry activities; (b) Before 2020, there is no sectoral split. In 2019, the total was Rp 0.4 T; (c) Includes both implicit and explicit subsidies for Premium, Pertalite, and Pertamax gasoline; (d) Does not include subsidies on Pertalite and Pertamax due to data limitations; (e) Includes both implicit and explicit subsidies; and (f) four of 96 companies that received a tax holiday in 2020 were classified as coal products industry or oil and gas drilling industry. However, the tax expenditures data on tax holiday does not provide a breakdown at the sectoral level. There are three characteristics where fiscal instruments could support the government’s climate targets: coverage, coordination, and alignment. First, fiscal instruments that are comprehensive and cover the entire economy—except in those sectors where instruments already exist to ensure appropriate incentives for emitters. Second, fiscal instruments are coordinated so they do not needlessly offset each other within the same sector. Third, there should be an alignment of fiscal incentives for emitters across the economy wherever possible so that significant differences between sectors do not unintentionally distort the allocation of resources. These principles can be illustrated through a simple framework that summarizes how and where fiscal instruments have been implement- ed, based on resource supply and demand across the economy. For each fiscal instrument discussed above, the matrix below (Table 3) identifies the sectors to which it applies and the direction in which it shifts incentives to emit, whether encouraging or discouraging. Fiscal instruments that discourage greater emissions are represented in green, whereas those that encourage it are colored red. The columns of the table cover the major emitting sectors of the economy. P. 4 4 TABLE 3 THE COVERAGE AND DIRECTION OF INDONESIA’S FISCAL INCENTIVES FOR EMISSIONS-INTENSIVE ACTIVITIES Resource Supply Resource Demand Coal Other Geother- Land House- Industri- Trans- Electric Agricul- Fiscal fossil mal and hold and al pro- port vehicles ture instrument fuels forests busi- cesses fuels ness energy(1) Tax and non-tax Palm oil export tax Forestry license Coal royalties Carbon tax(2) Fuel tax (provincial government) Tax expenditure LGST incentive for fuel-efficient vehicles VAT exemptions Zero royalty on coal value addition Import duty exemptions Land and building tax exemptions Income tax holiday Expenditure and capital injections Diesel subsidy (explicit and implicit) Petrol subsidy (implicit) LPG subsidy Electricity subsidy (explicit and implicit) PLN capital injections Fertilizer subsidy Source: World Bank staff estimates. Note: (1) For conciseness, this category is defined to include household energy demand, including electricity, LPG, and kerosene, as well as business demand for electricity. (2) Not yet implemented. P. 4 5 The framework can be useful to start a discussion on green fiscal incentives settings but should be treated with a caveat. A core be- lief underpinning the following discussion is that GHG emissions have negative externalities; hence, goods and services with an emissions footprint should be subject to policy-induced price-based disincen- tives that help internalize those externalities. It should be recognized that fiscal incentives per unit of emissions are not a perfect basis for assessing the adequacy of carbon pricing across goods and services. There is no reason why this indicator should be exactly equal across sectors. There can be reasonable justifications for maintaining differ- ent levels of this indicator across various goods and services, such as due to non-GHG externalities and other public policy objectives. Nevertheless, the framework presented above and in the following discussion draws attention to important gaps and inconsistencies to trigger a conversation about whether the existing settings are appro- priate. The findings from this framework are presented below. Cross-sector Coverage Gaps in the Fiscal Regime everal sectors in the framework lack direct fiscal instruments that discourage emissions. S The supply of non-coal fossil fuels, such as oil and gas, is not subject to any fiscal disincentives for its emissions footprint. On the demand side, the same is true for household and business en- ergy use and industrial process and product use (IPPU). Even household consumption of LPG and kerosene is not discouraged. In contrast, household electricity may be indirectly exposed to the proposed carbon tax on coal-fired power plants, if administered electricity prices are allowed to adjust. While IPPU is also a major consumer of electricity from coal-fired power plants, the sector’s emissions outside of energy use account for al- most 4 percent of Indonesia’s total emissions and face no fiscal dis- incentives. Coverage gaps could also be more prevalent than what the frame- work may suggest. The presence of an instrument in any sector nei- ther means that all that sector’s emissions fall within the scope of P. 4 6 the instrument nor that within-scope emissions are even adequately managed by the instrument. For example, the carbon tax will penalize coal-related emissions generated by coal-fired power plants but will not tax most of Indonesia’s coal. About 80 percent of Indonesia’s coal is exported, and companies will avoid the tax on exports. Most of the remainder will be consumed domestically within the power sector. Where it is instead used directly in industrial processes, it will avoid the tax. Even within coal-fired power plants, if those power plants have a generation capacity below 100 MW, or if those pow- er plants directly service the industrial sector (for example, smelting or concrete production), their coal-related emissions will be beyond the initial remit of the tax. In agriculture, palm oil export taxes im- pose higher costs but not on domestically consumed palm oil. These export taxes also do not differentiate between high-emissions and low-emissions production, a difference which can be large. Emissions may also be covered by other non-fiscal policy instru- ments, which could help offset the lack of fiscal disincentives. Large sources of emissions across the economy remain outside the scope of any fiscal or other instrument that would directly or indirectly discourage emissions. Box 2 discusses Indonesia’s proposed emis- sions trading scheme (ETS). The ETS is a non-fiscal carbon pricing instrument that, if implemented broadly and effectively, can signifi- cantly expand the disincentives to GHG emissions across the Indone- sian economy. Emissions from FOLU are most directly influenced by regulatory limitations, such as the moratorium on clearing peatland and primary forests. Another dimension of coverage is the materiality of the incentives generated by these fiscal instruments where coverage does exist. Figure 37 illustrates the size of fiscal incentives per ton of CO2eq emissions for those instruments with amenable data. This offers rich- er insight into how the fiscal regime influences behavior at the level of a marginal unit of emissions. Analogous to the comparative fiscal footprint discussed earlier, a clear picture emerges that the fiscal re- gime, on an emissions basis, leans heavily in favor of emissions. P. 4 7 FIG 37 MOST OF THE FISCAL SUPPORT TAKES THE FORM OF SUBSIDIES TO FOSSIL FUELS (Fiscal support per ton of CO 2eq emissions*, Rp) 4,000,000 3,500,000 SUB BUSINESS AND INDUSTRY 3,000,000 2,500,000 ELECTRICITY SUBSIDY: ELECTRICITY SUBSIDY: FUEL TAX: PERTALITE PERTALITE SUBSIDY CPO EXPORT TAXES SUB HOUSEHOLDS 2,000,000 VAT EXEMPTIONS: FUEL TAX: DIESEL COAL ROYALITIES DIESEL SUBSIDY 1,500,000 LPG SUBSIDY CARBON TAX ELECTRICITY 1,000,000 500,00 0 INSTRUMENTS THAT DECREASE THE COST OF EMISSIONS INSTRUMENTS THAT INCREASE THE COST OF EMISSIONS Sources: MoF; MoEMR; Pertamina; and World Bank staff estimate. Note: *Data on fuel subsidies are estimates for 2022. All others are 2021. It is also important to consider which stage of the supply chain the fiscal instrument is imposed on. Implementation at an earlier or upstream stage of the supply chain typically makes it adminis- tratively easier to achieve broader coverage, though this is primarily relevant for emissions from fossil fuels. For example, consider tax- ing carbon at its source of entry into the economy, such as when fuel imports enter the country or when domestically produced coal leaves the mine. This reduces the number of entities that need to be monitored by the government and helps to ensure that the price dis- incentive propagates throughout the rest of the supply chain regard- less of distribution channels and types of use. Disincentivizing coal upstream means the government does not have to monitor the coal use or emissions of the much larger number of downstream users. The disincentive is either absorbed by upstream entities or included in the price and passed down the supply chain. P. 4 8 BOX 2 THE EMISSIONS TRADING SCHEME: A NON-FISCAL INSTRUMENT FOR CUTTING EMISSIONS A n emissions trading scheme (ETS) is one type of non-fiscal policy instrument that governments use to curtail GHG emissions in the economy. ETSs create a market for emissions by requiring that emitters hold tradable emissions permits and limiting the market supply of these permits. Market demand and supply then come together to determine a price for the tradable permits and, equivalently, a price for the underlying permissible emissions. Whenever an emitter has too few permits to account for anticipated emissions, it can attempt to either purchase more permits, reduce emissions, or in some schemes, undertake other eligible avenues for offsetting emissions. Penalties are imposed upon emitters that fail to acquire sufficient permits to meet their obligations. Emitters with excess permits can attempt to sell the excess back to the market. The government’s initial allocation of emission permits may take place through various arrangements, including grandfathering legacy emissions, open auctions, or a combination of the two. The Government of Indonesia plans to set up a wide-ranging domestic ETS by 2025, with implementation across several economic sectors. It is currently developing the design and institutional infrastructure of the ETS and implementing regulations, which requires considerable inter-ministry coordination and agreement. It is not clear which sectors of the economy will eventually come under the purview of the ETS, but the government has signaled an intention to make the ETS the primary emissions pricing mechanism in Indonesia. The government’s sectoral and design choices for the ETS will partly depend on early experiences combining the new carbon tax with a pilot ETS in the coal-fired power sector. The pilot ETS has been operational since 2021, covering about 80 percent of GHG emissions from coal-fired grid-connected power plants. However, the implementation of the carbon tax, which was initially expected to be introduced in this sector no later than October 2022, has so far been postponed. In the P. 4 9 proposed combined implementation of the ETS and carbon tax, the ETS's market price for emissions will be capped at the prevailing carbon tax rate. The latter will commence at just Rp 30,000 per ton of CO2eq, which is very low by international standards. While the MoF has the authority to raise the carbon tax rate, such increases are expected to be modest in the initial years of implementation. This will limit the ETS’s ability to generate a significantly stronger emissions price, even if the demand for permits is high. The pilot ETS also employs significant emission permit grandfathering, which is expected to continue under the combined approach. The grandfathering entitles emitters to an allocation of free annual permits of a magnitude that primarily reflects their historical emissions. Given these drawbacks, even this deliberate combination of fiscal and non-fiscal instruments is unlikely to create an adequate disincentive for emissions. In the remaining sectors, the government can still decide to implement just one of an ETS or a carbon tax, reducing the policy and administrative complexity of the carbon pricing mechanism. The ETS and carbon tax have their unique characteristics, including advantages and weaknesses, which lead to variation in their respective suitability for any given sector. Careful consideration of these is critical when deciding which instrument to employ in each sector. Unless significant weaknesses in the recently proposed approach in the power sector are addressed, it is likely preferable that just a single choice of instrument—that is, either an ETS or a carbon tax— be implemented for each of the remaining sectors. P. 5 0 Conflicting Incentives Within Sectors here are instances where fiscal instruments impose conflicting incentives on emitters. In T the area of coal supply, royalties and the upcom- ing carbon tax combine to discourage the supply of coal. Simultaneously, however, a zero-royalty policy on coal used for downstream activities (particularly coal gasification) and exemptions on import duties in the sector act in the opposite direction. In agriculture, where fertilizers account for over 10 percent of agriculture-related emissions, fertilizers (and thereby their emissions) are encouraged through fertilizer subsidies. At the same time, palm oil export taxes aimed at securing domestic supply and improving downstream development implicitly discourage agricultural emissions from the second-largest consumer of agricultural fertilizers. Energy subsidies are the primary source of fiscal incentive incon- sistencies for emitters. In household and business energy, all grid users enjoy some degree of subsidized emissions-intensive, primarily fossil-fuel-generated electricity. These subsidies are implemented by holding administered electricity tariffs below the supply cost, with the government compensating PLN for related losses. These supply costs will increase once a carbon tax is in place. The interaction between the administered electricity tariffs (subsidies) and the new carbon tax is, therefore, expected to force the supply side to absorb much of the tax—thereby triggering larger government subsidies to PLN. In transport,16 provincial government taxes on motor vehicle fuels, which discourage emission-intensive fossil fuels, are countered by much larger central government subsidies on the same fuels. For the energy products just described, Indonesia’s net fiscal incen- tive ultimately promotes a larger emissions footprint. In other words, if the existing fiscal regime were replaced with an equivalent carbon tax, the tax on these products would be negative. It is possible to estimate this net tax for several energy products. Figure 38 reveals the essentially 16 In 2018, the transport sector accounted for about 27 percent negligible disincentive that the provincial fuel tax and the carbon tax— of Indonesia’s energy-related GHG emissions, with the latter if eventually allowed to pass through into electricity prices—can impose accounting for a little under when confronted with Indonesia’s energy subsidy regime. one-half of Indonesia’s total GHG emissions. P. 5 1 FIG 38 THE NET FISCAL INCENTIVES IN INDONESIA SKEW TOWARDS ENCOURAGING EMISSIONS (Equivalent net taxes per ton of emissions, Rp) SUBSIDY EQUIVALENT NET TAX ELECTRICITY SUBSIDY: ELECTRICITY SUBSIDY: DIESEL SUBSIDY PERTALITE SUBSIDY SUBSIDIZED SUBSIDIZED 500,00 HOUSEHOLDS BUSINESS & INDUSTRY 0 PROVINCIAL PROPOSED -500,00 FUEL TAXES CARBON TAX -1,000,000 -1,500,000 -2,000,000 VAT EXEMPTIONS ON -2,500,000 SUBSIDIZED HOUSEHOLD ELECTRICITY -3,000,000 -3,500,000 Source: MoF; MoEMR; Pertamina; and World Bank staff estimates. Note: Data on fuel subsidies are estimates for 2022. All others are 2021. Electricity and fuel subsidy reforms have been a recurring reform agenda in Indonesia for the two decades leading up to 2022. Re- forms have been primarily motivated by evidence that subsidies are expensive and inefficiently targeted at their principal intended bene- ficiaries: the poor. The need for green fiscal reform should add impe- tus to these efforts. These conflicting incentives are mainly due to the government’s intention to promote other policy objectives. Faced with multiple objectives, there are sensible justifications for implementing such fis- cal instruments, even when they are expected to have countervailing effects on the incentives for GHG emissions. These other objectives can in many cases, however, be achieved using instruments that do not generate steep favorable incentives for specific emissions-inten- sive activities. The administrative burden of conflicting instruments also needs to be recognized: there may be more efficient ways to employ fiscal policy than simultaneously taxing and subsidizing the same good or service. Moreover, it can become problematic when fiscal instruments begin to counteract each other, if this is due to a failure to take a systemwide perspective to the incentives being gen- erated, and hence where such conflicts are not the result of a care- ful assessment of tradeoffs. In that case, in addition to generating P. 5 2 administrative inefficiencies, such conflicts may hamper the govern- ment’s ability to ensure the overall fiscal regime is set up to achieve its chief policy priorities. Cross-sector Inconsistencies in Emitter Incentives here is no consistency in the incentives creat- ed by the fiscal regime for emissions across T sectors. Variations in the emissions coverage of fiscal instruments, differences in the size of the corresponding incentives, and offsetting impacts due to instruments that lean in opposite directions set the stage for significant differences in the price of emissions across sectors. Individuals or firms with the same GHG footprint but in different sectors can, therefore, face entirely different incentives and disincentives to emit. Different emitter incentives across sectors can be justified from a climate policy perspective (Bataille et al. 2018). In some sectors or activities, emitter behavior may be quite unresponsive to changes in such incentives, or there may be little or no available opportunities for emitters to transition towards greener alternatives (Hayes and Hafstead 2020). Higher emissions disincentives might lead to lower sector output and profitability or lower consumer welfare. They might have a limited impact on the government’s goal of reducing emissions. Higher emitter disincentives may, therefore, be more appropriate in sectors that are more amenable to green transitions after also con- sidering the government’s other policy objectives. However, in the present Indonesian context, cross-sector variation in fiscal emitter incentives is not based on carefully considered rationale. A consequence is that the optimal rate of emissions miti- gation is not being achieved, and consumption, business, and invest- ment decisions that respond to prevailing incentives are likely to be distorted—thereby reducing the allocative efficiency of the economy. Moreover, such a regime is also unlikely to give many investors in new green industries the confidence and policy coherence they require before they proceed with investments. 03 P. 5 3 P.53-54 SUMMARY AND CONCLUSIONS his paper provides a macro-fiscal overview of Indonesia’s progress along four dimensions of T green growth, which are linked to each other from both the outcomes and policy perspec- tives: (i) carbon use in the growth process; (ii) pollution and its impacts on human capi- tal; (iii) the impact of carbon use on national wealth; and (iv) fiscal policies for the low car- bon transition. The paper takes stock of Indonesia’s progress on de- carbonizing growth. It then analyzes the extent to which fiscal policies are aligned with this overall objective. Although GHG emissions have risen in Indonesia, they have started to slow down—including signs of relative decoupling from growth in per capita income. GHG emissions align with Indonesia’s stage of development and other large emerging market economies. The slow- down in carbon emissions in recent years has been associated with reforms around FOLU, including moratoria on land conversion—which have reduced deforestation rates. The energy sector is Indonesia’s second largest contributor to GHG emissions due to the significant use of fossil fuels in the energy mix. P. 5 4 Reducing GHG emissions in Indonesia could have important lo- cal benefits through reduced pollution and its negative effects on health and human capital. Forest fires and the use of fossil fuels for power generation, industry, and transport are significant sources of pollution. In Indonesia, the casualties from air pollution have been rising rapidly. The number of deaths from ambient ozone and PM2.5 in Indonesia was less than 60,000 in 2000, but this has increased rapidly. These have contributed to increased DALYs and a lower life expectancy in Indonesia. Indonesia’s total wealth has grown in line with other emerging market economies. However, per capita wealth has lagged that of peer countries, and the composition of the wealth stock raises con- cerns about the sustainability of growth. Indonesia experienced fast- er per capita growth in GDP than per capita growth in wealth—which suggests that, despite rapid short-term GDP growth, long-term growth could slow unless earnings can be better used to build up national wealth. Increasing human capital wealth will be essential for reach- ing HIC status by 2045. Sound macro-fiscal policies have helped manage commodity price volatility, but the fiscal framework overall could be simplified and better aligned with decarbonization objectives. Indonesia’s fiscal policies have historically incentivized carbon consumption, although ongoing reforms are trying to redress this. This paper considers how key fiscal instruments alter the incentives for carbon-intensive activ- ities, and how they come together as an overarching framework that promotes or discourages CO2eq emissions. It finds that fiscal instru- ments encourage more than they discourage carbon consumption. In this context, cross-sector coverage gaps in fiscal disincentives, conflicting incentives within sectors, and cross-sector inconsisten- cies in incentives are worth reviewing. A complex fiscal instrument system calls for simplification to make it easier to assess whether it is aligned with greener growth goals. Moreover, exploring other fis- cal instruments that encourage emission reduction is also import- ant. Given how decentralization plays an important role in Indone- sia and how transfers account for a significant share of the budget, ‘ecological fiscal transfers’ could be an example. This would provide transfers to local government for activities that could have positive environmental and climate impacts. P. 5 5 Bibliography Allen, E.R. 2016. “Analysis of Trends and Challenges in the Indonesian Labor Market.” ADB Papers on Indonesia. Manila: ADB. Bataille, C., C. Guivarch, S. Hallegatte, J. Rogelj, and H. Waisman. 2018. “Carbon prices across countries”. Nature Climate Change 8: 648–650. Cust, J., and D. Manley. 2018. “The Carbon Wealth of Nations: From Rents to Risks.” In The Changing Wealth of Nations 2018: Building a Sustainable Future, edited by G-M. Lange, Q. Wodon, and K. Carey, 97–113. Washington, DC: World Bank. Greenstone, M., and C. Fan. 2019. “Air Quality Life Index® Indonesia’s Worsening Air Quality and its Impact on Life Expectancy.” Hayes, K., and M. Hafstead. 2020. “Carbon Pricing 103: Effects across Sectors.” Resources for the Future. Haver Analytics, Haver database Hubacek, K., X. Chen, K. Feng, T. Wiedmann, and Y. Shan. 2021. “Evidence of decoupling consumption-based CO2 emissions from economic growth.” Advances in Applied Energy Vol. 4: 100074, ISSN 2666-7924 (link). ———. 2021. “Not Yet on Track to Net Zero: The Urgent Need for Greater Ambition and Policy Action to Achieve Paris Temperature Goals.” IMF Staff Climate Note 2021/005. Washington, DC: IMF. Mboi, N., IM..Surbakti, I. Trihandini, I. Elyazar, K. Houston Smith, P.B. Ali, S. Kosen, K. Flemons, S.E. Ray, J. Cao, S.D. Glenn, M.K. Miller-Petrie, MD. Mooney, J.L. Reid, D.N.A. Ningrum, F. Idris, K.N. Siregar, P. Harimurti, R.S. Bernstein, T. Pangestu, Y. Sidharta, M. Naghavi, C.J.L. Murray, and S.I. Hay. 2018. “On the road to universal health care in Indonesia, 1990– 2016: a systematic analysis for the Global Burden of Disease Study 2016.” Lancet 392: 581–91. (link). Ministry of Environment and Forestry (Pusarpedal). 2015. (link). New Zealand Ministry for the Environment. 2020. “Measuring emissions: A guide for organisations – 2020 Detailed Guide.” OECD. 2011. “Towards Green Growth” Paris: OECD Publishing. (link). ———. 2020. “Indicators to Measure Decoupling of Environmental Pressure from Economic Growth.” The OECD Environment Programme. Oficina Catalana del Canvi Climatic. 2019. “Practical Guide for Calculating GHG Emissions.” Savelli, A., M. Atieno, J. Giles, J. Santos, J. Leyte, N.V.B. Nguyen, H. Koostanto, Y. Sulaeman, S. Douxchamps, and G. Grosjean. 2021. “Climate-Smart Agriculture in Indonesia.” CSA Country Profiles for Asia Series. Hanoi (Vietnam): The Alliance of Bioversity and CIAT, The World Bank Group. Tanjungpinang City Environment Service. 2019. “Inventory of Greenhouse Gas Emissions, Tanjungpinang City” (link). United Nations Conference on Trade and Development (UNCTAD). 2020. “The State of Commodity Dependence 2020.” ———. 2020b. “Indonesia Public Expenditure Review 2020: Spending for Better Results.” Washington, DC: World Bank. ———. 2021b. The Changing Wealth of Nations 2021: Managing Assets for the Future. Washington, DC: World Bank. ———. 2022b. “East Asia Pacific Economic Update (October 2022).” Washington, DC: World Bank World Health Organization (WHO). 2014. “Burden of diseases of ambient air pollution.” ———. 2021. “WHO global air quality guidelines: particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide.” Geneva: World Health Organization. P. 5 6 Appendix 1 Legal Basis of the Fiscal Instruments Fiscal instrument Legal Basis Palm oil export tax Regulation of the Minister of Finance (PMK) No. 76/2021 on the Second Amendment to PMK No. 57/2020. Forestry licenses Law No. 41/2009 on Forestry. Government Regulation No. 6/2007 on Forest Management and Preparation of Forest Management Plans and Forest Utilization. Regulation Of The Minister Of Forestry P.15/Menhut-II of 2009 amending Regulation of The Minister of Forestry P.32/Menhut-II of 2007 on Procedures for Imposition, Collection, And Payment of Business License Contributions for Utilizing Forests in Production Forests. Regulation Of The Minister Of Forestry P.76/Menhut-II of 2014 on Determination of The Amount of Contribution Forest Utilization Business License. Coal royalties Government Regulation No. 25/2021 on Implementation of the Energy and Mineral Resources Sector. Law No. 4/2009 on Mineral and Coal Mining. Government Regulation No. 81/2019 on Types And Prices For The Types Of Non-Tax State Revenue Apply To The MoEMR. More recently: Government Regulation No. 15/2022, on the Treatment of Taxes and/or Non-Tax State Revenues in the Coal Mining Business Sector. Carbon tax Law No. 7/2021 on Harmonization of Tax Regulations – Article 13. Presidential Regulation No. 98/2021 on Implementation of NEK – Article 58. Another six interrelated implementing regulations from the Fiscal Policy agency (MoF), Directorate General of Tax, MoEMR, and MoEF. Fuel tax Law No. 28/2009 amending Law No. 34/2000 on Regional Taxes and Regional Levies. VAT exemptions Government Regulation No. 12/2001 as amended by Government Regulation No. 31/2007 and Government Regulation No. 81/2015 LGST incentive Government Regulation No. 73/2019 amending Government Regulation No. 74/2021 on Taxable for fuel efficient Goods Categorized Luxury In The Form Of Motor Vehicles Subject To Sales Tax On Luxury Goods - vehicles Article 36. LGST incentive for Government Regulation No. 73/2019 amending Government Regulation No. 74/2021 on Taxable goods resulting Goods Categorized Luxury In The Form Of Motor Vehicles Subject To Sales Tax On Luxury Goods – from mining, Article 36. excavation, and drilling Zero royalty on coal Government Regulation No. 25/2021. value addition Import duty PMK No. 217/2019, which regulates the exemption of import duty and not being levied tax in exemptions the context of the import of goods for upstream oil and gas business activities. Also, PMK No. 259/2016; PMK 7No. 8/2005; PMK No. 20/2005. For geothermal, PMK No. 177/2007, PMK No. 21/2010. For power generation industries, some set of the following: Section 26, paragraph 1, clause a, b, and c of Law No. 17/2006 on Customs; PMK No. 176/2009; PMK No. 76/2012; PMK No. 188/2015; PMK No. 66/2015. Land and building PMK No. 267/2014 (oil & gas). tax exemptions PMK No. 172/2016 (geothermal). Income tax borne PMK No. 179/2013 (geothermal; income tax borne by govt). by government Income tax holiday Government Regulation No. 94/2010. for pioneer industry PMK No. 130/2011, as last revised by PMK No. 129/2014. (incl. oil refinery PMK No. 159/2015 as last revised by PMK No. 103/2016. industry) P. 5 7 Fiscal instrument Legal Basis Diesel subsidy (on Decree of Ministry of Energy and Mineral Resources No. 29.K/HK.02/MEM.L/2021 on the and off-budget) provision of a stimulus for PT PLN’s consumer electricity tariffs to deal with the impact of COVID-19. Petrol subsidy (off- budget) LPG subsidy Electricity subsidy (on and off-budget) Fertilizer subsidy Minister of Agriculture Regulation No. 41/2021 which determinates the highest allocation and retail price of subsidized fertilizer in the agricultural sector.