OECD global long‑run economic scenarios

Annex A. Additional methodological information

1. This Annex provides an overview of the core features of the Long-Term Model (LTM). See Annex B for more details on the revisions to the framework relative to previous iterations of these scenarios and Annex C for more details on the new climate damage channel in the LTM.

A1. Geographical coverage and definition of aggregates

2. The LTM comprises 139 individual countries, with 55 others modelled as part of three regions (Table A A.1). These are Other Asia (code OTHERASIA), Other Africa (code OTHERAFRIC) and Other Latin America (code OTHERLATIN). Altogether the LTM covers more than 99% of global GDP at purchasing power parity exchange rates.

Table A A.1. Main aggregates in the LTM

Aggregate	Code	Individual members
OECD members	OECD	AUS AUT BEL CAN CHE CHL COL CRI CZE DEU DNK ESP EST FIN FRA GBR GRC HUN IRL ISL ISR ITA JPN KOR LTU LUX LVA MEX NLD NOR NZL POL PRT SVK SVN SWE TUR USA
Euro area OECD members	EA17	AUT BEL DEU ESP EST FIN FRA GRC IRL ITA LTU LUX LVA NLD PRT SVK SVN
G20 advanced	G20ADV	AUS CAN DEU FRA GBR ITA JPN KOR USA
G20 emerging	G20EME	ARG BRA CHN IND IDN MEX RUS SAU TUR ZAF
G20	G20	G20ADV G20EME
World Bank regions
East Asia and Pacific	EAP	AUS CHN HKG IDN JPN KHM KOR LAO MMR MNG MYS NZL PHL SGP THA VNM OTHERASIA
Europe and Central Asia	ECA	ALB ARM AUT AZE BEL BGR BIH BLR CHE CYP CZE DEU DNK ESP EST FIN FRA GBR GEO GRC HRV HUN IRL ISL ITA KAZ KGZ LTU LUX LVA MDA MKD MNE NLD NOR POL PRT ROU RUS SRB SVK SVN SWE TJK TKM TUR UKR UZB
Latin America and Caribbean	LAC	ARG BOL BRA CHL COL CRI DOM ECU GTM HND HTI JAM MEX NIC PAN PER PRY SLV SUR TTO URY OTHERLATIN
Middle East and North Africa	MNE	ARE BHR BRN DZA EGY IRN IRQ ISR JOR KWT LBN LBY MAR MLT OMN QAT SAU SYR TUN
North America	NAR	CAN USA
South Asia	SAR	BGD IND LKA NPL PAK
Sub-Saharan Africa	SSA	AGO BEN BWA CIV CMR COD COG ETH GAB GHA GNQ KEN MDG MOZ MUS NAM NER NGA RWA SDN SEN SWZ TGO TZA UGA ZAF ZMB ZWE OTHERAFRIC
World	WLD	EAP ECA LAC MNE NAR SAR SSA

Note by the Republic of Türkiye: The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Türkiye recognizes the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of United Nations, Türkiye shall preserve its position concerning the “Cyprus” issue.

Note by all the European Union Member States of the OECD and the European Union: The Republic of Cyprus is recognised by all members of the United Nations with the exception of Türkiye. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

3. Individual-country projections are normally shown for the 38 OECD member countries, some selected non-OECD economies that are G20 members (Argentina, Brazil, China, India, Indonesia and South Africa) and accession or partner countries (Bulgaria, Croatia, Peru, Romania and Thailand). A decomposition of global outcomes into regions is also shown following World Bank conventions as much as possible, the exception being that the LTM’s Other Asia region is allocated to East Asia and Pacific, even though some individual countries should belong to South Asia as per World Bank nomenclature.

A2. Exchange rates for currency conversions

4. When comparing or aggregating across countries, GDP and GDP per capita are expressed in United States dollars (USD) at fixed 2021 prices and Purchasing Power Parity (PPP) exchange rates, based on estimates from the International Price Comparison Programme’s latest round.

A3. Primary energy consumption, energy mix and GHG emissions projections

5. The energy mix in individual countries is represented in the model as shares of total primary energy coming from eight sources (coal, oil, gas, nuclear, hydro, solar, wind and a residual category called other renewables). Total primary energy covers all energy use, including power generation, transport, heating and cooling. Different energy transition scenarios are then expressed as assumptions regarding how these primary energy shares might evolve over time. The historical data source is the International Energy Agency’s World Energy Balances database.

6. Total energy consumption per capita is projected based on the evolution of GDP per capita and that of the energy mix itself. Higher GDP per capita leads to higher energy consumption per capita, but less than one-for-one, leading to gains in energy efficiency (measured as primary energy consumed per unit of output). This is consistent with recent history, as energy efficiency has improved substantially in many countries in recent years. It also implies that, all else equal, countries where growth is projected to be relatively strong in the decades ahead show higher gains in energy efficiency than countries where growth is weaker. The evolution of energy consumption in the LTM is also a function of the evolution of the energy mix itself, not as a causal mechanism, but to ensure that energy efficiency gains are larger in energy transition than in no-transition scenarios. It is natural to suppose that in a scenario where policy discourages carbon emissions, reductions would occur on both carbon and energy intensity margins simultaneously. Initial cross-country differences in energy efficiency levels are partly preserved in the projections, as these reflect differences in industrial mix, geography, etc. that are implicitly assumed to persist.

7. CO₂ emissions from energy use and industrial processes are projected at the country level for both scenarios. This is done by, first, combining projections of total energy use with the energy mix assumptions just described to project energy supply from individual sources; second, applying CO₂ emissions coefficients specific to each energy source; and third, aggregating the resulting CO₂ emissions over energy sources. GHG emissions other than CO₂ (but excluding land use change and forestry) are projected on the basis of population, living standards and a time trend. Historical data on CO₂ and other GHG emissions are from a variety of sources via Our World in Data.

8. See section 2 of Annex B in Guillemette and Château (2023[1]) for additional methodological details on energy and emissions projections.

A4. Caveats regarding the interpretation of projections and scenarios

9. The scenarios generated with the LTM are meant to illustrate some of the forces that could shape the medium and long-term outlook for the world economy and can serve as building blocks for other work. However, they are highly stylised, conditional on a number of hypotheses, omit some potentially important factors and, for all these reasons, are subject to enormous uncertainty. In addition to those mentioned in introduction of the main part of the paper, the following caveats apply:

• As regards missing elements, the projections should generally be seen as incorporating the implicit assumption that they remain unchanged from their current states.

• Long-run scenarios are useful, but not always sufficient, to provide country-specific policy recommendations, which must take account of particular economic and policy contexts that cannot be fully incorporated into such a stylised exercise.

• Differences in economic outcomes between business-as-usual and alternative scenarios incorporating policy changes should not be interpreted as reflecting pure one-way causation from policies to outcomes. In reality, causation typically runs both ways, so the coefficients linking policies and outcomes incorporated in the LTM should be understood as attempts to add realism to the scenarios, in the sense of respecting estimated historical correlations.

The long-run scenarios focus on GDP per capita as a measure of living standards and leave out many other dimensions of well-being. They can and should be considered in conjunction with other projection exercises – for the environment, income inequality, health, etc. – to get a full picture of the likely evolution of well-being.