World Energy Projection System (WEPS): 

Global Activity Module

Independent Statistics & Analysis

www.eia.gov

U.S. Department of Energy

Washington, DC 20585

Last Updated 2023 
U.S. Energy Information Administration | World Energy Projection System: Global Activity Module i 

This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and 

analytical agency within the U.S. Department of Energy. By law, EIA’s data, analyses, and forecasts are 

independent of approval by any other officer or employee of the United States Government. The views 

in this report therefore should not be construed as representing those of the U.S. Department of Energy 

or other federal agencies.
U.S. Energy Information Administration | World Energy Projection System: Global Activity Module 1 

Contents

1. Model System Overview ........................................................................................................................... 2

1.1. GLAM components........................................................................................................................... 2

1.2. Oxford Economics Global Economic Model (GEM) .......................................................................... 2

1.3. Oxford Economics Global Industrial Model (GIM)............................................................................ 7

2. The GLAM Interface with WEPS................................................................................................................ 9

2.1. Relationship to WEPS........................................................................................................................ 9

2.2. Relationship to other WEPS modules............................................................................................... 9
U.S. Energy Information Administration | World Energy Projection System: Global Activity Module 2 

1. Model System Overview

1.1. GLAM components 

The Global Activity Module (GLAM) in the World Energy Projection System (WEPS) projects economic 

driver variables for the supply, demand, and conversion modules of WEPS. GLAM’s baseline economic 

projection contains the economic assumptions used in WEPS to help determine energy demand and 

supply. GLAM can also provide WEPS with alternative economic assumptions representing a range of 

uncertainty about economic growth. The economic impacts of these assumptions become inputs for the 

remaining supply and demand modules of WEPS. 

The GLAM is made up of two models:

• Oxford Economics Global Economic Model (GEM)

• Oxford Economics Global Industrial Model (GIM)

GEM is the same model that Oxford Economics uses to produce its economic forecasts for the 

company’s monthly assessment of the global economy. GIM provides the industrial output detail that 

WEPS requires. The GEM and GIM releases we use for a particular International Energy Outlook (IEO) 

varies by IEO. GEM and GIM are linked to provide a fully integrated approach to estimating economic 

activity at the country, regional, and industrial levels. 

GEM projects each national economy's growth path and the final demand mix. GIM ensures that supply 

by industry is consistent with the final demands (consumption, investment, government spending, 

exports and imports) calculated in GEM. Together, GEM and GIM constitute the GLAM of the WEPS. 

To execute its two models, GLAM uses energy prices and quantities as inputs. In the current version, 

GLAM extracts oil and natural gas prices and demands, natural gas supply, electricity prices, and coal 

demand from the output of the demand and supply modules of WEPS. These data from WEPS are

transformed into more aggregated data for GLAM. GEM and GIM execute in sequence to produce

consistent estimates of macroeconomic and industrial activity. GLAM passes the economic driver 

variables for this output to the supply, demand, and conversion modules of WEPS, and the system reacts 

to the new economic activity assumptions. 

1.2. Oxford Economics Global Economic Model (GEM)

Key inputs: National population by age cohort, total factor productivity, tax rates and nominal 

expenditures, money supply, and energy prices and quantities

Key outputs: Final demands (consumption, investment, government purchases, exports, imports), 

inflation, foreign exchange and interest rates, incomes, employment, and balance of payments

1.2.1. Overview

The Oxford Economics Global Economic Model (GEM) is an international macroeconomic model that

covers 80 countries or territories and six additional regions and includes projections through 2050. 

Countries are modeled similarly, but larger economies have greater disaggregation and more financial 

sector detail. All territories have forecasts for gross domestic product (GDP), consumer prices, exchange 
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rates, and the current account. Each of the countries, territories, and regions is fully linked through 

trade, prices, exchange rates, and interest rates.

The structure of each country and regional submodel in GEM is based on standard economic theory. In 

the long run, population growth and productivity drive economic activity, but the business cycles 

fluctuate in the short run. These business cycles arise from a number of factors, including wages and 

prices that do not adjust over short periods, non-competitive behavior by firms, and regulations, to 

name a few.

The long-run price depends on monetary policy, which does not affect economic activity over this time

period. Monetary policy does, however, have a short-run impact on output, which also affects the price.

Consumption in each country or region depends on income, wealth, interest rates, and inflation. 

Investment varies, based on its risk-adjusted after-tax return, and exports are a function of world 

demand and the real exchange rate. Imports are determined by domestic demand and competitiveness.

1.2.2. Coverage of GEM

GEM covers 80 territories in depth and provides high-level details in six regional groupings, including 

OPEC (Organization of the Petroleum Exporting Countries). Territories covered in detail include:

Table 1. Territories analyzed by the Oxford Economics Global Economic Model

Europe Americas Asia Middle East and Africa

Austria Argentina Australia Algeria

Belgium Brazil China Angola

Bulgaria Canada Hong Kong Bahrain

Croatia Chile India Egypt

Cyprus Colombia Indonesia Ghana

Czech Republic Ecuador Japan Iran

Denmark Mexico Malaysia Iraq

Estonia Peru New Zealand Israel

Finland United States Philippines Kenya

France Uruguay Singapore Kuwait

Germany Venezuela South Korea Mauritius

Greece Taiwan Morocco

Hungary Thailand Namibia

Ireland Vietnam Nigeria

Italy Oman

Latvia Pakistan

Lithuania Qatar

Luxembourg Saudi Arabia

Malta South Africa

Netherlands Tunisia

Norway Uganda

Poland United Arab Emirates

Portugal Zambia
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Romania Zimbabwe

Russia

Slovak Republic

Slovenia

Spain

Sweden

Switzerland

Türkiye

United Kingdom

Source: Oxford Economics

GEM also includes global and multiregion variables such as oil and commodity prices, world GDP and 

industrial production, OECD (Organization for Economic Cooperation and Development) average 

inflation, and others.

Most of the countries and territories map directly into one of the WEPS regions listed below:

• Single-country regions: Brazil, Canada, China, India, Japan, Mexico, Russia, South Korea, and the 

United States

• Multicountry regions: Africa, Australia and New Zealand, Eastern Europe and Eurasia, Middle 

East, Other Americas, Other Asia-Pacific, and Western Europe

For example, Argentina falls under Other Americas, and Germany is under Western Europe. The Oxford 

regions are broken up where appropriate (according to their shares of economic activity within the

region) and assigned to the WEPS regions. For example, Syria is in Oxford’s Rest of the World region, but 

we separate it from that region and assign to the WEPS Middle East region. 

We followed the same procedure for all territories that make up the remaining regional groups in GEM. 

The Rest of the World and Rest of OECD aggregations consist of all territories within those two groupings 

that are not already in the model.

1.2.3. Detailed model structure

1.2.3.1. Model variables

Model variables are divided into demand and supply as well as core and non-core. Coverage of core 

variables is standard across all country submodels; non-core coverage is determined by data availability 

and country-specific requirements. 

Core demand variables include all the aggregate expenditure components—consumption, investment, 

government spending, and net exports—at constant and current prices, monetary policy variables, and 

financial variables. The demand non-core variables include disaggregated consumption and investment, 

as well as important indicator variables such as retail sales and car sales. 

Core supply variables include variables that determine output, unemployment, and real wages. Prices 

are also disaggregated within core supply. Non-core supply variables include disaggregated employment 
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and nominal earnings. Other variables related to government, personal, and corporate sector flow 

accounts are based on relationships outside of demand and core supply.

The model variables are expressed either in units of the local currency that most of the country or 

region uses or in rates or ratios that have no units. The data sets we used to estimate the model 

parameters also vary by country.

1.2.3.2. Projecting consumption

For each region and projection year, the model estimates the natural logarithm of energy consumption 

by a two-stage least squares (2SLS, described in Section B1) time series regression.

In the first stage, the model estimates a function of the following instrumental variables: 

• Natural logarithm of energy consumption in the previous year

• A weighted average of the following:

– Natural logarithm of real income during the previous year

– Ratio of financial wealth to income during the previous year

• Real interest rate in the previous year

In the second stage, the model estimates the natural logarithm of year-to-year change in energy

consumption as a function of the following variables:

• Year-to-year change in the natural logarithm of real income

• Year-to-year change in the natural logarithm of the unemployment rate

• The function of instrumental variables calculated in the first stage

1.2.3.3. Projecting Investment

Three aspects of gross fixed investment are identified in the model: private business, private housing, 

and government, which are input into the model.

The model projects private business investment based on standard theories of investment, which 

includes real oil price. Oxford assumed that the capital stock reaches equilibrium in the long run and

fluctuates in the short run. These fluctuations occur because capital installation is costly and time

consuming, which means the benefit of an installed unit of capital differs from its cost. Firms invest 

when this benefit exceeds the cost, but they reduce or scrap capital in the reverse case.

This business behavior can also amplify changes in the economy because firms may reduce or increase 

investment in response to changes in the value of the relative rate of return on investment. The rate of 

return is defined as the ratio of the market value of a company's assets to the replacement cost of the 

company's assets.

For each region and projection year, a regression model estimates year-to-year change in private sector 

business fixed investment (in local currency) as a function of the following independent variables:

• Relative rate of return on investment during the current year (percentage)
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• The difference between the previous year’s private sector business fixed investment and the 

previous year’s value of capital stock

• Year-to-year change in real GDP (current year’s GDP minus previous year’s GDP)

The model estimates personal sector housing investment analogously to consumption, using real 

income, wealth, and interest rates because they are part of a portfolio of spending decisions households

make.

1.2.3.4. Projecting international trade

The model disaggregates trade flows into fuel, non-fuel goods, and services. The non-fuel goods 

components make up most exports and imports for most countries. The model uses two-stage least 

squares time series regression models to project year-to-year change in non-fuel exports and imports by 

region.

For the year-to-year change in the exports model:

• The first-stage independent variables are:

– Exports of non-fuel goods during the previous year

– World trade during the previous year

– A time trend

• The second-stage independent variables are:

– Year-to-year change in world trade during the current year

– Capacity utilization rate for the current year

– Year-to-year change in labor costs in the country or region under consideration, relative to 

those in its trading partners, during the current year

– The function estimated in the first stage

For the year-to-year change in the imports model:

• The first-stage independent variables are:

– Imports of non-fuel goods during the previous year

– Total final expenditures during the previous year

– Labor costs in the country or region under consideration, relative to those in its trading 

partners, during the previous year

– Capacity utilization rate during the previous year

• The second-stage independent variables are:

– Year-to-year change in total final expenditures
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– Year-to-year change in labor costs in the country or region under consideration, relative to 

those in its trading partners

– Year-to-year change in total final expenditure

– The function estimated in the first stage

The data sources for each of the variables above vary by country and region. The model coefficients

capture the effects of non-price factors on a country’s world trade share, as well as the effects that a 

sustained increase in production specialization has on imports. In general, a sustained decline in relative 

labor costs—an improvement in competitiveness—leads to an improvement in the trade balance in the 

long run.

The regression models for trade in services and total trade are analogous to those for non-fuel goods. 

Fuel trade is calculated as the residual—total trade minus the sum of trade in services and non-fuel 

goods.

1.2.3.5. Links between economies 

Through the core regression models described above and other financial calculations, GLAM links the 

individual countries and regions in a number of ways:

• Trade

• Labor and energy costs in a country relative to trading partners—competitiveness 

• Interest and exchange rates 

• Oil and other commodity prices

• Prices of manufactured goods

1.3. Oxford Economics Global Industrial Model (GIM)

Key inputs: Final demand, prices, and productivity measures from Oxford Economics model of the global 

economy

Key outputs: Real gross output for industrial and service sectors

GIM has a top-down structure, and sector forecasts are driven by national trends and aggregate demand 

from three regional blocs: the Americas, Asia Pacific and Europe, and Middle East and Africa. Sector 

demands from the three blocs are allocated to individual industries using weights based on regional 

input-output relationships. These relationships—derived from national input-output tables—show the 

percentage of each industry’s output driven by consumer expenditure, investment, exports, government 

spending, and intermediate demand.

GIM also considers the impacts of changes in competitiveness on an industry’s market share, both 

regionally and nationally. Industry classification follows the European standard classification structure

called NACE, specifically NACE 2. This structure has eight major manufacturing sectors that are further 

broken down into subsectors: 
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• Basic metals

• Iron and steel, non-ferrous metals, casting

• Basic chemicals

• Other chemicals

• Coke, petroleum, and nuclear fuel products

• Glass, ceramics, bricks, cement, and plaster

• Food, beverages, and tobacco

• Pulp and paper

• Engineering and metal goods, motors, electrical equipment, machinery, electronics and 

computers, and appliances

• Motor vehicles, transportation equipment, and parts

• Wood and wood products, furniture, textiles, garments, leather goods, printing and publishing, 

rubber and plastics, and all other manufacturing

Other production sectors outside manufacturing include agriculture, extraction, utilities, and 

construction. We do not include utilities in aggregates of the industrial sector, but instead we group

utilities with the service sector.

The service sector includes the following subsectors:

• Retail and wholesale distribution

• Accommodation and catering

• Transport and storage

• Information and communications

• Financial services

• Business services

• Public administration services

• Education services

• Health care and social work

• Other services

GIM provides projections of other variables, such as:

• Value-added output and gross output across all industries and territories

• Producer prices across all industries for the United Kingdom, Germany, France, Italy, Japan, the 

United States, and China
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• Employment and real and nominal investment across all industries for the United Kingdom

• Car and truck registrations and number of vehicles on the road for more than 44 countries

• Steel production for Belgium, China, France, Germany, Italy, Japan, Netherlands, Spain, Sweden, 

the United Kingdom, and the United States

• Investment across all industries for all territories 

2. The GLAM Interface with WEPS 

2.1. Relationship to WEPS

The Global Activity Module (GLAM) provides economic projections for the other WEPS modules to use, 

based on energy prices and quantities provided by other WEPS modules. Because the time aggregation, 

country and region mapping, and variable definitions are different in GLAM than in other WEPS

modules, we use a transfer system to make them consistent.

Figure 1. Schematic of Global Activity Module transfer system

Source: U.S. Energy Information Administration

Note: GEM=Oxford Economics Global Economic Model. GIM=Oxford Economics Global Industrial Model. 

GLAM takes energy inputs from the WEPS common database and transfers them into GEM, aggregating 

and modifying as necessary. GEM converges to an equilibrium and then passes relevant information to 

GIM, which then also converges to an equilibrium. Each model stores relevant outputs in the common 

database. In the final step, economic and population variables are passed from GIM back to WEPS via a 

database. 

2.2. Relationship to other WEPS modules 

Figure 2 shows the basic output structure of GLAM to the different end-use demand modules in WEPS. 

GLAM also takes in energy prices and quantities from other WEPS modules. 
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Figure 2. The Global Activity Module (GLAM) relationship to other WEPS modules

Source: U.S. Energy Information Administration

GLAM projects many series and provides four main projection series to WEPS:

• GDP by region, expressed in purchasing power parity (PPP)

• Population by region

• Personal income by region

• Employment by region

• Gross output by region and economic sector

Before running GLAM, we modify it to make it consistent with our energy prices. We export the GLAM

results to the WEPS common database for use by the other WEPS modules.