IEA (2023), Global Energy and Climate Model, IEA, Paris https://www.iea.org/reports/global-energy-and-climate-model, License: CC BY 4.0
The Global Energy and Climate Model (GEC Model) uses macro drivers, techno-economic inputs and policies as input data to design and calculate the scenarios. The values for the different data categories and scenarios used in the GEC Model 2023 can be downloaded here.
Economic activity and population are the two fundamental drivers of demand for energy services in GEC Model scenarios. Unless otherwise specified, these are kept constant across all scenarios as a means of providing a starting point for the analysis and facilitating the interpretation of the results.
The projections are based on the average retail prices of each fuel used in final uses, power generation and other transformation sectors. These end-use prices are derived from projected international prices of fossil fuels and subsidy/tax levels and vary by country.
We use the medium variant of the United Nations projections as the basis for our population growth. In this variant, global population growth slows over the coming decades, but the total population nonetheless rises from 8 billion in 2022 to 9.7 billion in 2050. Population growth in the medium variant is not linear, and the rate of growth slows over time.
Demographic trends differ by country and region. Ageing populations and slowing fertility rates mean the size of the population in 2050 is expected to be smaller than today in the European Union, Russia, Japan and China. In contrast, the United Nations projects a billion more people in Africa by 2050, accounting for three-fifths of the global population increase. India’s population is overtaking that of China and is projected to reach almost 1.7 billion by 2050, some 360 million people more than in China. In the past, the development of economies has typically been associated with the migration of rural workers to towns and cities in search of better paying jobs. This pattern of development is assumed to continue over the period to 2050. In fact, in most regions the change in the population is entirely concentrated in urban areas. Only Africa is expected to experience an increase in the size of its rural population by the middle of the century, and even there it is dwarfed by a much larger increase in the urban population.
In GEC Model 2023 scenarios, the global economy is assumed to grow by 2.6% per year on average over the period to 2050. This is broadly in line with trend growth, but varies by country and by region and over time, reflecting investment dynamics, employment rates and changes in terms of trade. The initial years in the Outlook are shaped by countries exposure and resilience to shocks and by where they are currently positioned in the economic cycle. The reverberations from the pandemic and the global energy crisis are being felt across the broader economy as household purchasing power is eroded by higher inflation and as business investment is restrained by rising borrowing costs (although clean energy appears, in some cases, to be bucking this trend).
The assumed rates of economic growth are held constant across the scenarios, which allows for a comparison of the effects of different energy and climate choices against a common backdrop.
International prices for coal, natural gas and oil in the GEC Model reflect the price levels that are needed to stimulate sufficient investment in supply to meet projected demand. They are one of the fundamental drivers for determining fossil fuel demand and supply projections in all sectors and are derived through iterative modelling.
The supply modules calculate the production of coal, natural gas and oil that is stimulated under a given price trajectory, considering the costs of various supply options and the constraints on resources and production rates. If prices are too low to encourage sufficient production to cover global demand, the price level is increased and energy demand is recalculated. The new demand resulting from this iterative process is again fed back into the supply modules until a balance between demand and supply is reached for each projected year.
The price trajectories do not attempt to represent the fluctuations and price cycles that characterise commodity markets in practice. The potential for volatility is ever present, especially in systems that are undergoing a necessary and profound transformation.
CO2 price assumptions are one of the key inputs into the GEC Model, as the pricing of CO2 emissions affects demand for energy by altering the relative costs of using different fuels.
An increasing range and variety of carbon pricing schemes are coming into operation around the world. There are 73 direct carbon pricing instruments existing today, covering around 40 countries and over 30 subnational jurisdictions.
The STEPS includes only existing and scheduled initiatives, whereas in the APS and NZE Scenario additional measures of varying stringency and scope are assumed to be introduced. In the NZE Scenario, for example, carbon prices are in place in all regions, rising by 2050 to an average of USD 250/tonne CO2 in advanced economies, to USD 200/tonne CO2 in emerging market and developing economies with net zero emissions pledges, and to lower levels elsewhere.
For fuel end-use prices, for each sector and GEC Model region, a representative price (usually a weighted average) is derived taking into account the product mix in final consumption and differences between countries. International price assumptions are then applied to derive average pre-tax prices for coal, oil, and gas over the projection period which are used in the model for the technology choice. Excise taxes, value added tax rates and subsidies are taken into account in calculating average post-tax prices for all fuels. In all cases, the excise taxes and value added tax rates on fuels are assumed to remain unchanged over the projection period. Governmental actions to shield consumers are also taken into account.
We assume that energy-related consumption subsidies are gradually reduced over the projection period, though at varying rates across the GEC Model regions and the scenarios. In the APS the oil price is lower than in the STEPS. In order to counteract a rebound effect in the transport sector from lower gasoline and diesel prices, a CO2 tax is introduced in the form of an increase of fuel duty to keep end-user prices at the same level as in the STEPS. All prices are expressed in US dollars per tonne of oil equivalent and assume no change in exchange rates.
For electricity end-use prices, the model calculates prices as a sum of the wholesale electricity price, system operation cost, transmission and distribution costs, supply costs, and taxes and subsidies. Wholesale prices are calculated based on the costs of generation in each region, under the assumption that all plants recover their variable costs and that new additions recover their full costs of generation, including their capital costs.
System operation costs are taken from external studies and are increased in the presence of variable renewables in line with the results of these studies. Transmission and distribution tariffs are estimated based on a regulated rate of return on assets, asset depreciation and operating costs. Supply costs are estimated from historic data. Taxes and subsidies are also taken from the most recent historic data, with subsidy phase-out assumptions incorporated over the projection period in line with the relevant assumptions for each scenario.
There is no single definition of wholesale electricity prices, but in the GEC Model the wholesale price refers to the average price (across time segments) paid to generators for their output. They reflect the region-specific costs of generating electricity for the marginal power plants in each time segment, plus any capital costs that are not recovered. The key factors affecting wholesale prices are therefore:
- The capital cost of electricity generation plants;
- The operation and maintenance costs of electricity generation plants; and
- The variable fuel cost and, if applicable, CO2 cost of generation plants’ output.
The derivation of the wholesale electricity price for any region makes two fundamental assumptions:
- Electricity prices must be high enough to cover the variable costs of all the plants operating in a region in a given year.
- If there are new capacity additions, then prices must be high enough to cover the full costs – fixed costs as well as variable costs – of these new entrants.
For each region, GEC Model breaks the annual electricity demand volume down into four segments: baseload demand, low-midload demand, high-midload demand and peakload demand. For a fuller discussion of load-duration curves and how they are derived, please refer to the methodology document on the calculation of capacity credit for renewables.
Demand must be met by the electricity generation capacity of each region, which consists of variable renewables – technologies like wind and solar PV without storage whose output is driven by weather – and dispatchable plants (generation technologies that can be made to generate at any time except in cases of technical malfunction). In order to account for the effect of variable renewables on wholesale prices, the model calculates the probable contribution of variable renewables in each segment of the simplified load-duration curve. Subtracting the contribution of renewables from each segment in the merit order leaves a residual load-duration curve that must be met by dispatchable generators.
The IEA measures fossil fuel consumption subsidies using a price-gap approach. This compares final end-user prices with reference prices, which correspond to the full cost of supply, or, where appropriate, the international market price, adjusted for the costs of transportation and distribution. The estimates cover subsidies to fossil fuels consumed by end-users and subsidies to fossil-fuel inputs to electricity generation.
The price-gap approach is designed to capture the net effect of all subsidies that reduce final prices below those that would prevail in a competitive market. However, estimates produced using the price-gap approach do not capture all types of interventions known to exist. They, therefore, tend to be understated as a basis for assessing the impact of subsidies on economic efficiency and trade. Despite these limitations, the price-gap approach is a valuable tool for estimating subsidies and for undertaking comparative analysis of subsidy levels across countries to support policy development.