This chapter outlines the current state of carbon pricing and energy taxation and describes the methodology underpinning the Pricing Greenhouse Gas Emissions series. It provides an overview of the Carbon Pricing and Energy Taxation database including the coverage of instruments, countries and sectors. The chapter then details the methodology for computing the key indicators – Net Effective Carbon Rate and Net Effective Energy Rate – that are used to measure changes in global carbon pricing and energy taxation. The analysis covers carbon taxes, emissions trading systems, fuel excise taxes, electricity taxes and subsidies that lower pre-tax energy prices for 79 economies in this edition, representing 82% of global emissions. Last, the chapter outlines the methodologies for additional analyses presented in the subsequent chapters.
Pricing Greenhouse Gas Emissions 2024
Abstract
It is widely acknowledged that addressing the risks of climate change demands significant economic and structural transformations and these can be incentivised by the implementation of carbon pricing and other climate policies to steer economies towards a net-zero future. The IPCC, in their latest findings and with a high level of confidence, report that greenhouse gas (GHG) emissions have unequivocally caused global warming through unsustainable energy use, lifestyles and patterns of consumption and production (IPCC, 2023[1]). In response, the Paris Agreement offers countries the flexibility to chart their paths toward these ambitious goals and as a result, the global economy could be on track to reach peak emissions before 2030 (IEA, 2023[2]). In order to further reduce emissions while at the same time managing growth in total energy supply, governments must close the gap between existing policies and those under development (the ‘implementation gap’), as well as the gap between the current and necessary level of ambition required to meet global climate goals (the ‘ambition gap’) (Figure 1.1). As outlined in this report, in order to achieve climate goals, the need for a deep reductions in emissions – a period of rapid and drastic reductions in the generation of emissions through climate policies - is imminent (IPCC, 2023[1]).
Emissions and energy consumption pathways for net zero by 2050
Note: The IEA models three scenarios for the global energy sector. The Stated Policies Scenario (STEPS) gives a sense of the energy system progression, based on a detailed review of the current policy landscape and provides a conservative benchmark for the future by not taking for granted that governments will achieve all announced climate ambitions. The Announced Pledges Scenario (APS) illustrates the extent to which announced ambitions and targets can deliver the emissions reductions needed to achieve net zero emissions by 2050. The Net Zero Emissions by 2050 Scenario (NZE Scenario) is a normative scenario that shows a pathway for the global energy sector to achieve net zero CO2 emissions by 2050. (IEA, 2023[3]).
Source: (IEA, 2023[4]).
While Effective Carbon Rates have been increasing over recent years, in many countries rates remain low relative to the level needed to achieve upcoming climate targets (OECD, 2022[5]; Stiglitz et al., 2017[6]). Emissions trading systems (ETS) in particular are gaining traction, but still a large number remain in their pilot or transitory phases and offer high levels of free allocations that reduce incentives to invest in cleaner technologies (OECD, 2023[7]). Carbon pricing instruments can drive behavioural changes across industries and households, aligning economic activities with the urgent need to mitigate climate change impacts. The shift from preparation to action is critical as the window for preventing the most catastrophic outcomes of climate change narrows, requiring increasingly decisive action (IPCC, 2023[1]).
This report provides an in-depth analysis of the current global trends in carbon pricing and energy taxation based on 79 covered countries, shedding light on both the progress that characterise today’s carbon pricing and energy taxation landscape, as well as examining some pathways forward. By measuring the price and coverage of various carbon pricing and energy taxation instruments, the report aims to provide a clear picture of how these tools are being utilised. It highlights the uneven implementation of carbon pricing and energy taxation and the diversity in system design across different regions and sectors, underscoring the complex dynamics that may influence the effectiveness and efficiency of these measures in reducing emissions.
The report begins with an overview of the context that surrounds carbon pricing and energy taxation, followed by an explanation of the indicators and methodology of the analysis (Chapter 1). It then explores the trends in carbon pricing and coverage since 2021, an estimation of upcoming emissions coverage, and delves into the practical consideration for the implementation of carbon pricing and the role of revenues use in public and political feasibility (Chapter 2). Next, the report outlines trends in energy taxation, including coverage and price trends, and then explores how energy taxation can be better aligned with climate policy and other goals. This includes the role of energy affordability and security as well as transitioning tax bases as the energy mix shifts from combustibles to renewables (Chapter 3).
1.2.1. Overview of the report series, databases and covered policy instruments
The Pricing Greenhouse Gas Emissions report – first published in 2022 – is an evolution from the Taxing Energy Use report and includes data and findings from the Effective Carbon Rates report which together make up the OECD Series on Carbon Pricing and Energy Taxation. The respective databases of the two series have been merged to form the Carbon Pricing and Energy Taxation database (CPET) (Figure 1.2). Although the Pricing Greenhouse Gas Emissions series draws on the most up-to-date data from the Effective Carbon Rates series, the data collection exercises and focus of the reports differ. The Effective Carbon Rates series comments on changes related to the Effective Carbon Rates indicator, mainly focussing on those resulting from developments in ETSs, including the interaction between free allocations and Effective Carbon Rates (OECD, 2023[7]). The Pricing Greenhouse Gas Emissions series is broader and collects data on carbon taxes, fuel excise taxes, energy taxes and complements this with the OECD’s Effective Carbon Rates database on ETSs, the OECD’s Inventory of Fossil Fuel Support database on fossil fuel subsidies and other emissions and energy use data from the IEA. Due to a time lag in fossil fuel subsidy data (2022 data in this case), this edition notes that the ongoing changes in subsidy measures sometimes may not reflect the most up-to-date policy measures. These main data sources are used to produce two distinct indicators, the Net Effective Carbon Rate (Net ECR) and Net Effective Energy Rate (Net EER). They are the basis to produce a comprehensive analysis of the latest development in carbon pricing and energy taxation policies across the world.
A timeline of the OECD’s Taxing Energy Use, Effective Carbon Rates, and Pricing Greenhouse Gas Emissions reports
Source: Authors.
1.2.2. Coverage update
The CPET database focuses on pricing instruments that apply to a base that is proportional to an energy or GHG emissions base (Table 1.1). It therefore excludes taxes and fees that are only partially correlated with energy use or GHG emissions. Common examples of policy instruments that fall outside the scope of the database include vehicle purchase taxes, registration or circulation taxes, and taxes that are directly levied on non-GHG emissions. Some countries also apply production taxes on the extraction or exploitation of energy resources (e.g., severance taxes on oil extraction). Since these supply-side measures are not directly linked to domestic energy use or emissions, the database does not cover them.
Similarly, the database does not include value added taxes (VAT) or sales taxes as in principle these rates apply equally to a wide range of goods and therefore do not change the relative prices of products or services. In practice there are some exceptions to these whereby preferential rates are applied to products such that they change the relative price of carbon- or energy-intensive products, compared to less carbon- or energy-intensive products. Although this does not warrant including VAT explicitly in the database, it is explored briefly in this report to demonstrate how VAT rates can play a role in carbon pricing in some specific cases.
In addition, explicit carbon pricing and energy taxation are not the only instruments necessary or available to achieve net-zero. Many countries are opting for a complex mix of policies that do not directly price emission or energy bases, such as subsidies for low-emission investment. These policies can also influence the relative prices of emissions and energy products through other channels and, in turn, the behaviour of households and firms. Such policies must be acknowledged as part of the climate policies package, along with carbon pricing and energy taxation, that will lead to the climate goals with different considerations and means for different countries.
Note: Data on the tax policy instruments are collected via publicly available official sources; government officials are provided with the opportunity to review and refine the data. Excises are taxes levied as a product specific tax on a predefined limited range of goods (OECD, 2023[8]). For details on emissions trading systems, see the OECD’s (2023[7]) Effective Carbon Rates 2023. For details on fossil fuel and electricity subsidies, see (OECD, 2023[9]; Garsous et al., 2023[10]).
Source: (OECD, 2022[5]).
This edition of the CPET database covers 79 countries, an increase in geographic coverage from 71 in 2022, and from 44 in 2019. The database coverage has been expanded to additional countries including Croatia, Bulgaria, Romania, Kazakhstan, Malta, Mauritius, Singapore and Zambia. This edition includes all OECD and G20 countries except Saudi Arabia, and for the first time, also covers all European Union (EU) member states. As a result, the database covers approximately 82% of global GHG emissions (excluding emissions from land use change and forestry). Where time trends with regard to previous editions are presented (concerning data for 2018 and 2021), the coverage and country composition of the database differs year-by-year, which sometimes does not allow for direct comparisons.
As in previous editions, the database covers six economic sectors that account for CO2 emissions from energy use in road transport, off-road transport, industry, agriculture and fisheries, buildings, electricity (Table 1.2). GHG emissions and energy use are assigned to the sector in which the primary energy is consumed. A seventh sector captures other GHG emissions, which are separated due to data limitations and to facilitate comparisons with previous vintages. Table A.1 in the Annex contains further details on how energy products are aggregated in the database. In line with previous editions, this report presents results that exclude emissions from the combustion of biofuels, consistent with the practice that the other GHG emissions (emissions from CH4, N2O, F-gases and process CO2 emissions) that were added to the emissions base exclude LUCF.
Note: Estimates of primary energy use are based on the territoriality principle, and include energy sold in the territory of a country but potentially used elsewhere (e.g. because of fuel tourism in road transport).
Source: Own classification based on information on energy flows contained in the IEA’s (2023[11]) extended world energy balances and “other GHG” reported in Climate Watch’s (2024[12]) GHG emissions dataset.
Indicators of Pricing Greenhouse Gas Emissions and their components
Pricing Greenhouse Gas Emissions features two main indicators – the Net Effective Carbon Rate (Net ECR), representing the effective tax rate on GHG emissions (measured in EUR/tCO2e), and the Net Effective Energy Rate (Net EER), representing the effective tax rate on energy use (measured in EUR/GJ), both net of subsidies. Although these indicators are related through the overlap in policy instruments included, the rates collected under these indicators apply to different bases – emissions versus energy. These different bases do not cover the same economic activities and therefore cannot be directly compared or converted into each other, even though energy use and emissions are correlated. As a result, the Net ECR and Net EER indicators cannot be compared to each other (Figure 1.3). For this reason, this report discusses the indicators separately, with Chapter 2 focussing on the Net ECRs and related developments in carbon pricing policies, while Chapter 3 focussing on Net EERs and related trends in energy taxation.
Both indicators are a representation of effective rates, meaning tax exemptions, rate reductions and refunds and other preferential tax treatment are accounted for in the final estimate. These measures are common in carbon pricing and energy taxation systems, as certain emitters or energy users often receive preferential treatment that reduces the effective tax paid on emissions or energy use.
The net effective rates take into account negative carbon pricing or energy policy instruments resulting from consumption subsidies that lower pre-tax energy prices below reference prices. Changes in subsidies result from not only from policy changes, such as changes in the regulated pre-tax price, but also from changes in the reference price and therefore fluctuate with market conditions (e.g. an increase in the reference price, all else equal, would result in an increase in the subsidy amount and thus a higher negative price). This is unlike instruments such as carbon taxes and fuel excise taxes, which are not normally driven by broader market forces, but more by policy intervention. Together with preferential treatment, subsidies lower the price paid on emissions and energy.
The Effective Carbon Rate (ECR) and the Net Effective Carbon Rate (Net ECR)
The ECR is the sum of carbon taxes, ETS permit prices and fuel excise taxes, representing the aggregate Effective Carbon Rate paid on emissions. To combine the marginal price signals of the various instruments, fuel excise tax and fuel-based carbon tax rates (which are typically expressed in physical units such as litres or kilogrammes) are converted into tax rates per tonne of CO2-equivalent based on the carbon content of the fuels that they apply to. Other emission-based carbon taxes, as well as ETS permit prices do not need to be converted, as they are typically expressed in tonne of CO2-equivalent.
The ECR indicator in this report is primarily the Effective Marginal Carbon Rate (EMCR, referred to as ECR in this report unless otherwise noted), which is distinct from the Effective Average Carbon Rate (EACR). The difference between these two measures is that the EACR accounts for free allocation of permits in ETSs by including emissions that are covered with free allocations as part of the total emissions base. This reduces the average permit price across the emissions base, compared to EMCR. This is further outlined in detail in the Effective Carbon Rates 2023 report (OECD, 2023[7]).
The Net ECR is a different indicator that attempts to account for negative carbon prices in the form of fossil fuel subsidies that decrease pre-tax prices of domestic fossil fuel use and may counteract the price signals from fuel excise taxes, carbon taxes and ETS permit prices. These subsidies are collected through the CPET database, drawing on direct budgetary transfer data of the OECD Inventory of Fossil Fuel Support Measures database for OECD and G20 countries, and other desk research. They are mapped onto the CO2 emissions from domestic energy use that are directly affected by the measures and are then converted into a negative tax rate per tonne of CO2. This process excludes tax expenditures on taxes that are already recorded as the effective rates through tax reductions, exemptions and refunds in the CPET database, but adds budgetary transfers to fuel suppliers, electricity suppliers and end users (Garsous et al., 2023[10]).
This creates a distinct indicator from the ECR, where the Net ECR includes policy instruments applying to a base not strictly proportional to emissions, and estimates the negative prices resulting from subsidies and how these evolve over time across countries, fuels and sectors.
The Effective Energy Rate (EER) and Net Effective Energy Rate (Net EER)
The EER is composed of carbon taxes, ETS permit prices, fuel excise taxes and electricity excise taxes that are applied to an energy base that results in an effective rate. The rates are converted into tax rates per gigajoule of energy, based on the energy content of the energy product of which they apply. Like the previous ECR indicator, the rates used in this report, unless otherwise stated, are marginal effective rates and therefore do not account for free allocation.
The Net EER is a distinct indicator that attempts to estimate and account for fossil fuel subsidies and electricity subsidies as negative energy rates. In general, electricity excise taxes and subsidies tend to not treat fossil fuels in a differential manner compared to lower-emitting energy sources and are typically also applied to energy sources that do not emit CO2 emissions such as hydro, solar, as well as nuclear (OECD, 2019[13]; OECD, 2022[5]). Altogether, the Net EER captures the interaction of both positive and negative price signals on energy use, including electricity, but does not include the comprehensive range of levies that apply to electricity.
The components and the different bases used
Source: Authors.
1.2.3. Mapping tax rates to their respective GHG emission and energy bases
The first step of the methodology is collecting data on carbon pricing and energy taxation rates, as detailed above. The second step is to map tax rates and subsidies to their respective emissions and energy bases, in order to compute both the ECR and EER, and then the Net ECR and Net EER. This is done through assigning tax rates to the latest available information on energy use, by energy product, adapted from the IEA’s World Energy Statistics and Balances (2023[11]). This is also used to calculate CO2 emissions from energy use, together with non-CO2 GHG emissions from energy use sourced from Climate Watch (2024[12]). To produce the final indicators, for the Net ECR, all positive components including rates from carbon taxes, ETS and fuel excise taxes, are summed with the negative pricing components resulting from fossil fuel subsidies. For the Net EER, the positive components also include electricity taxes and the negative components also include electricity subsidies. After mapping of net tax rates to the emissions/energy bases, the weighted rates can be aggregated to create net effective rates by country, instrument, and sectors. All rates are therefore in EUR/tCO2e for the Net ECR or EUR/GJ for the Net EER based on the carbon content and energy content of the product, respectively. Official OECD exchange rates and inflation data are used to express all prices in real 2023 euros.
The mapping accounts for overlaps between policy instruments, which is common across countries and instruments. In some cases, policies are implemented to take effect together (e.g. a carbon tax applied to emissions that are also covered by an ETS, as in the case of the United Kingdom), whereas in other cases, policies are implemented to cover specific sectors or uses (e.g. a carbon tax applied only to emissions that are not already covered by an ETS, as in the case of France). Ignoring such interactions, which vary across countries and levels of governance (supranational, national, subnational), would be an inaccurate representation of the coverage and prices of countries’ carbon pricing and energy taxation policies.
In most countries, carbon pricing and energy taxation is applied at the national level. However, there are some exceptions, such as the United States, Canada, Mexico and China, where subnational instruments play a significant role and are included. To assign subnational rates to their corresponding emissions or energy use bases, it is necessary to split countries’ emissions and energy bases by subnational jurisdictions, as the IEA’s World Energy Statistics and Balances report energy use data at the country level.1 Where possible, CPET relies on energy use data from official sources, however simplifying assumptions are required to account for some of these instruments.
In addition to the main indicators, this edition of Pricing Greenhouse Gas Emissions presents several counterfactual exercises, bringing together data from the CPET database with other policy developments in carbon pricing and energy taxation (Table 1.3). These exercises include an estimate of changes to the coverage of Effective Carbon Rates resulting from policies that are currently under development; revenue potential from comprehensive carbon pricing reform (including phasing out free allocation, fossil fuel subsidies, and setting a minimum Effective Carbon Rate); and effects on revenue through a shift in the tax base from combustibles to electricity in the road transport sector. These counterfactual scenarios provide an in-depth exploration of a selection of possible developments across carbon pricing and energy taxation and demonstrate the potential for further analysis that can be conducted using this database.
Outline of additional quantitative analyses undertaken
1.3.1. Emissions coverage from carbon pricing instrument under development
With countries progressing carbon pricing at different rates, there are a large number of instruments, mostly ETSs, that have not been implemented but are still under development and likely to take effect in the coming years. To illustrate the ongoing efforts in carbon pricing policies, this edition of Pricing Greenhouse Gas Emissions estimates the change in the share of emissions subject to a positive price that could result from these instruments being implemented.
A stocktake of instruments that are under development are drawn from the World Bank’s State and Trends of Carbon Pricing Dashboard, whereby instruments are categorised as such if the country’s government is actively working towards the implementation of the instrument, a mandate may have been established, but regulated entities do not yet face compliance obligations, and this has been formally confirmed by government sources (The World Bank, 2024[14]). Instruments at the regional, national and subnational level for countries covered by the CPET database, are considered. Available details on the planned coverage of these instruments, primarily in terms of fuels and sectors, are matched to the IEA’s (2023[11]) World Energy Balances and Statistics and Climate Watch (2024[12]) data as is done in the general methodology of Pricing Greenhouse Gas Emissions. While some countries have more granular information on the planned emissions threshold determining which entities are covered by the instrument, these are not accounted for in this exercise due to data constraints. Where there is a lack of information on planned implementation, additional assumptions are made to be able to model the instrument. Overlaps between the emissions coverage of new instruments and existing explicit carbon pricing instruments are accounted for. All policies are assumed to be implemented under the current environment, although the timeline of implementation is not finalised for most of the instruments covered.
Given the variability in available information and assumptions made, the estimates should be interpreted as an upper bound of the expected change in emissions coverage as some instruments under development may not be implemented or the actual implementation may result in smaller changes than estimated in this exercise due to the assumptions made. However, it is possible that additional new schemes are also implemented. Nevertheless, the analysis can provide an indicative quantitative estimate of the ongoing developments in carbon pricing around the world, which are otherwise not captured by the standard indicators of this report.
1.3.2. Revenue from carbon pricing policy reform
Current revenue from current carbon pricing policies
The Net ECR and Net EER indicators can be used to estimate government revenue from carbon pricing and energy taxation policies, including for different benchmark prices. To calculate total revenue from current carbon prices and energy taxes, each positive pricing component of the respective indicator is multiplied by the coverage base that it applies to, and then summed with the other components to capture all prices paid on the base.
To calculate net revenue, the sum is adjusted to account for free allocation of permits in ETS and fossil fuel subsidies (and electricity subsidies for the Net EER). Free allocation refers to the allocation of emission permits to certain entities or sectors without charge and are generally used to address competitiveness concerns for entities that are deemed vulnerable to the increased production costs resulting from carbon pricing policies. As this reduces the size of the emissions base subject to a price, it lowers the average price of permits in an ETS. It is also relevant to include in these estimates as free allocations represent revenue foregone compared with the auctioning of permits. Thus, to calculate net revenue, revenues from ETS are multiplied by only the share of permits that are auctioned, rather than total permits allocated. Due to accounting for free allocation, the net effective rates presented in revenue estimates represent an average, rather than marginal rate, as is used elsewhere in the report. In addition, the fossil fuel (and electricity) subsidies are subtracted from the respective effective carbon (and energy) rates and the resulting net effective rate is multiplied by its coverage base. All components are then summed to compute total net revenues.
Revenue potential from carbon pricing reform
The report then estimates revenue potential – the additional revenue that could be earned from raising the tax rates (or reducing subsidies) of countries’ carbon pricing and energy taxation policies under different scenarios. This is broken down into several measures including: the phasing out of free allocation, phasing out of fossil fuel (and electricity) subsidies and setting a minimum Effective Carbon Rate. Benchmark values for a carbon rate follow the recommendations of the High Level Commission on Carbon Prices, which concluded that carbon prices must reach a level of at least EUR 60/tCO2 to EUR 120/tCO2 by 2030 (converted to real 2023 EUR and rounded) for countries to remain on track with keeping global warming to below 2 degrees Celsius (Stiglitz et al., 2017[6]). These values provide an indicative range of revenue potential if countries pursue their targets under the Paris Agreement using carbon pricing policies, noting that other policy mixes of price-based and non-priced based measures can also be used to achieve emissions reductions targets
To calculate the additional revenue potential from phasing out free allocation, the ETS permit price is multiplied by the respective emissions base as before, and then multiplied by the share of free allocations. The phasing out of free allocations is assumed to not lead to a short-term behavioural change. Calculating the revenue potential from phasing out subsidies and setting a minimum carbon price requires more steps to account for the emissions elasticity to carbon prices (i.e. emissions responsiveness leading to behavioural change). The OECD ECR dataset is used to estimate long-run elasticities (separate for OECD and non-OECD countries) capturing the responsiveness of emissions to carbon pricing.2 The elasticities are then used to compute a reduction factor for the coverage base of the indicator, before being multiplied by the respective ECR (adjusted for phasing out fossil fuel subsidies or minimum rate). In this exercise, the reforms are implemented sequentially, beginning with the phase out of fossil fuel (and electricity) subsidies, followed by the phase out of free allocations and then raising the Effective Carbon Rate.
Revenues presented in this report are based on bottom-up estimations using carbon rates and emissions coverage and hence may differ from actual revenue figures collected by public authorities. In addition, the scenario analysis is an indication of the level of revenue potential from carbon pricing reform and does not represent a dynamic revenue forecast, which requires more complex considerations of changes over time in economic conditions, supporting policies, technological developments and behavioural responses, among others.
1.3.3. Revenue impacts from shifting energy tax bases in road transport
Section 3.5 in Chapter 3 includes an in-depth assessment of revenue impacts from the road transport sector’s electrification. Assuming that every electric vehicle sold displaces the purchase of a comparable vehicle with an internal combustion engine (ICE), charging this electric vehicle with electricity also displaces the diesel or gasoline consumption of the replaced ICE vehicle. Such a counterfactual analysis requires taking into account differences and improvements in fuel economy across all vehicle types. Data on projected electricity consumption in the road transport sector and resulting displaced oil consumption is taken from the IEA’s Global EV Outlook 2024 (IEA, 2024[15]). The IEA dataset covers for the years 2025, 2030 2035, the four vehicle segments, cars, vans, buses and trucks, while excluding two- and three-wheelers due to modelling uncertainties. Data is grouped in five geographical regions: Europe, China, India, the United States (US) and the rest of the world. Impacts on the revenue generation potential of specific taxes on energy use are estimated by applying Effective Marginal Energy Rates, aggregated by fuel and country, to the projected electricity demand and displaced oil consumption. The revenue impacts are then converted to shares of GDP using 2023 data from the IMF (International Monetary Fund, 2023[16]) and does not attempt to forecast or account for future growth in GDP. The analysis does not provide information on the impact on emissions due to data limitations on the carbon intensity of electricity generation and upstream losses of electricity and petroleum products (i.e. through transmission and distribution grids as well as pipelines).
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← 1. China’s subnational ETS is able to be modelled without the disaggregation of the national energy use data, under the assumption that the local energy mix is representative of the national energy mix.
← 2. See reference for detailed information on methodology (D’Arcangelo et al., 2022[17]).