Snapshot of - EPPA

Archive of EPPA, version: 6

Reference card - EPPA

The reference card is a clearly defined description of model features. The numerous options have been organized into a limited amount of default and model specific (non default) options. In addition some features are described by a short clarifying text.

Legend:

• not implemented
• implemented
• implemented (not default option)

About

Name and version

EPPA 6

Model link

https://globalchange.mit.edu/research/research-tools/eppa

Institution

Massachusetts Institute of Technology (MIT), USA, https://globalchange.mit.edu/.

Documentation

EPPA documentation consists of a referencecard and detailed model documentation

Process state

in preparation

Model scope and methods

Model documentation: Model scope and methods - EPPA

Model type

• Integrated assessment model
• Energy system model
• CGE
• CBA-integrated assessment model

Geographical scope

• Global
• Regional

Objective

Projecting Economy, Energy, and Climate Impacts

Solution concept

• Partial equilibrium (price elastic demand)
• Partial equilibrium (fixed demand)
• General equilibrium (closed economy)

Solution horizon

• Recursive dynamic (myopic)
• Intertemporal optimization (foresight)

Solution method

• Simulation
• Optimization

Temporal dimension

Base year:2007, time steps:5 years from 2015, horizon: 2100

Spatial dimension

Number of regions:18

1. USA
2. EU
3. China
4. India
5. Japan
6. Brazil
7. Canada
8. Mexico
9. Russia
10. South Korea
11. Indonesia
12. Africa
13. Middle East
14. Australia and New Zealand
15. Dynamic Asia
16. Rest of East Asia
17. Rest of Eurasia
18. Rest of Latin America

Time discounting type

• Discount rate exogenous
• Discount rate endogenous

Policies

• Emission tax
• Emission pricing
• Cap and trade
• Fuel taxes
• Fuel subsidies
• Feed-in-tariff
• Portfolio standard
• Capacity targets
• Emission standards
• Energy efficiency standards
• Agricultural producer subsidies
• Agricultural consumer subsidies
• Land protection
• Pricing carbon stocks

Socio-economic drivers

Model documentation: Socio-economic drivers - EPPA

Population

• Yes (exogenous)
• Yes (endogenous)

Population age structure

• Yes (exogenous)
• Yes (endogenous)

Education level

• Yes (exogenous)
• Yes (endogenous)

Urbanization rate

• Yes (exogenous)
• Yes (endogenous)

GDP

• Yes (exogenous)
• Yes (endogenous)

Income distribution

• Yes (exogenous)
• Yes (endogenous)

Employment rate

• Yes (exogenous)
• Yes (endogenous)

Labor productivity

• Yes (exogenous)
• Yes (endogenous)

Total factor productivity

• Yes (exogenous)
• Yes (endogenous)

Autonomous energy efficiency improvements

• Yes (exogenous)
• Yes (endogenous)

Macro-economy

Model documentation: Macro-economy - EPPA

Economic sector

Industry

• Yes (physical)
• Yes (economic)
• Yes (physical & economic)

Energy

• Yes (physical)
• Yes (economic)
• Yes (physical & economic)

Transportation

• Yes (physical)
• Yes (economic)
• Yes (physical & economic)

Residential and commercial

• Yes (physical)
• Yes (economic)
• Yes (physical & economic)

Agriculture

• Yes (physical)
• Yes (economic)
• Yes (physical & economic)

Forestry

• Yes (physical)
• Yes (economic)
• Yes (physical & economic)

Macro-economy

Trade

• Coal
• Oil
• Gas
• Uranium
• Electricity
• Bioenergy crops
• Food crops
• Capital
• Emissions permits
• Non-energy goods

Cost measures

• GDP loss
• Welfare loss
• Consumption loss
• Area under MAC
• Energy system cost mark-up

Categorization by group

• Income
• Urban - rural
• Technology adoption
• Age
• Gender
• Education level
• Household size

Institutional and political factors

• Early retirement of capital allowed
• Interest rates differentiated by country/region
• Regional risk factors included
• Technology costs differentiated by country/region
• Technological change differentiated by country/region
• Behavioural change differentiated by country/region
• Constraints on cross country financial transfers

Resource use

Coal

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Conventional Oil

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Unconventional Oil

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Conventional Gas

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Unconventional Gas

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Uranium

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Bioenergy

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Water

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Raw Materials

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Land

• Yes (fixed)
• Yes (supply curve)
• Yes (process model)

Technological change

Energy conversion technologies

• No technological change
• Exogenous technological change
• Endogenous technological change

Energy End-use

• No technological change
• Exogenous technological change
• Endogenous technological change

Material Use

• No technological change
• Exogenous technological change
• Endogenous technological change

Agriculture (tc)

• No technological change
• Exogenous technological change
• Endogenous technological change

Energy

Model documentation: Energy - EPPA

Energy technology substitution

Energy technology choice

• No discrete technology choices
• Logit choice model
• Production function
• Linear choice (lowest cost)
• Lowest cost with adjustment penalties

Energy technology substitutability

• Mostly high substitutability
• Mostly low substitutability
• Mixed high and low substitutability

Energy technology deployment

• Expansion and decline constraints
• System integration constraints

Energy

Electricity technologies

• Coal w/o CCS
• Coal w/ CCS
• Gas w/o CCS
• Gas w/ CCS
• Oil w/o CCS
• Oil w/ CCS
• Bioenergy w/o CCS
• Bioenergy w/ CCS
• Geothermal power
• Nuclear power
• Solar power
• Solar power-central PV
• Solar power-distributed PV
• Solar power-CSP
• Wind power
• Wind power-onshore
• Wind power-offshore
• Hydroelectric power
• Ocean power

Hydrogen production

• Coal to hydrogen w/o CCS
• Coal to hydrogen w/ CCS
• Natural gas to hydrogen w/o CCS
• Natural gas to hydrogen w/ CCS
• Oil to hydrogen w/o CCS
• Oil to hydrogen w/ CCS
• Biomass to hydrogen w/o CCS
• Biomass to hydrogen w/ CCS
• Nuclear thermochemical hydrogen
• Solar thermochemical hydrogen
• Electrolysis

Refined liquids

• Coal to liquids w/o CCS
• Coal to liquids w/ CCS
• Gas to liquids w/o CCS
• Gas to liquids w/ CCS
• Bioliquids w/o CCS
• Bioliquids w/ CCS
• Oil refining

Refined gases

• Coal to gas w/o CCS
• Coal to gas w/ CCS
• Oil to gas w/o CCS
• Oil to gas w/ CCS
• Biomass to gas w/o CCS
• Biomass to gas w/ CCS

Heat generation

• Coal heat
• Natural gas heat
• Oil heat
• Biomass heat
• Geothermal heat
• Solarthermal heat
• CHP (coupled heat and power)

Grid Infra Structure

Electricity

• Yes (aggregate)
• Yes (spatially explicit)

Gas

• Yes (aggregate)
• Yes (spatially explicit)

Heat

• Yes (aggregate)
• Yes (spatially explicit)

CO2

• Yes (aggregate)
• Yes (spatially explicit)

Hydrogen

• Yes (aggregate)
• Yes (spatially explicit)

Energy end-use technologies

Passenger transportation

• Passenger trains
• Buses
• Light Duty Vehicles (LDVs)
• Electric LDVs
• Hydrogen LDVs
• Hybrid LDVs
• Gasoline LDVs
• Diesel LDVs
• Passenger aircrafts

Freight transportation

• Freight trains
• Heavy duty vehicles
• Freight aircrafts
• Freight ships

Industry

• Steel production
• Aluminium production
• Cement production
• Petrochemical production
• Paper production
• Plastics production
• Pulp production

Residential and commercial

• Space heating
• Space cooling
• Cooking
• Refrigeration
• Washing
• Lighting

Land-use

Model documentation: Land-use - EPPA

Land cover

• Cropland
• Cropland irrigated
• Cropland food crops
• Cropland feed crops
• Cropland energy crops
• Forest
• Managed forest
• Natural forest
• Pasture
• Shrubland
• Built-up area

Agriculture and forestry demands

• Agriculture food
• Agriculture food crops
• Agriculture food livestock
• Agriculture feed
• Agriculture feed crops
• Agriculture feed livestock
• Agriculture non-food
• Agriculture non-food crops
• Agriculture non-food livestock
• Agriculture bioenergy
• Agriculture residues
• Forest industrial roundwood
• Forest fuelwood
• Forest residues

Agricultural commodities

• Wheat
• Rice
• Other coarse grains
• Oilseeds
• Sugar crops
• Ruminant meat
• Non-ruminant meat and eggs
• Dairy products

Emission, climate and impacts

Model documentation: Emissions - EPPA, Climate - EPPA, Non-climate sustainability dimension - EPPA

Greenhouse gases

• CO2 fossil fuels
• CO2 cement
• CO2 land use
• CH4 energy
• CH4 land use
• CH4 other
• N2O energy
• N2O land use
• N2O other
• CFCs
• HFCs
• SF6
• PFCs

Pollutants

• CO energy
• CO land use
• CO other
• NOx energy
• NOx land use
• NOx other
• VOC energy
• VOC land use
• VOC other
• SO2 energy
• SO2 land use
• SO2 other
• BC energy
• BC land use
• BC other
• OC energy
• OC land use
• OC other
• NH3 energy
• NH3 land use
• NH3 other

Climate indicators

• Concentration: CO2
• Concentration: CH4
• Concentration: N2O
• Concentration: Kyoto gases
• Radiative forcing: CO2
• Radiative forcing: CH4
• Radiative forcing: N2O
• Radiative forcing: F-gases
• Radiative forcing: Kyoto gases
• Radiative forcing: aerosols
• Radiative forcing: land albedo
• Radiative forcing: AN3A
• Radiative forcing: total
• Temperature change
• Sea level rise
• Ocean acidification

Carbon dioxide removal

• Bioenergy with CCS
• Reforestation
• Afforestation
• Soil carbon enhancement
• Direct air capture
• Enhanced weathering

Climate change impacts

• Agriculture
• Energy supply
• Energy demand
• Economic output
• Built capital
• Inequality

Co-Linkages

• Energy security: Fossil fuel imports & exports (region)
• Energy access: Household energy consumption
• Air pollution & health: Source-based aerosol emissions
• Air pollution & health: Health impacts of air Pollution
• Food access
• Water availability
• Biodiversity

Model Documentation - EPPA

This document describes the Integrated Assessment Model EPPA, which stands for “Economic Projection and Policy Analysis,” in this version 6. More information—including a documentation of the system of equations—is available on the EPPA website.

The EPPA model provides projections of world economic development at a regional and sectoral level, including the economic implications of greenhouse gas (GHG) emissions, conventional air pollution, land-use change, food demand, and natural resource use.

EPPA simulates the evolution of economic, demographic, trade and technological processes involved in activities that affect the environment. We use it to investigate the economic implications of a wide range of phenomena, including:

• Climate and environmental impacts (e.g. changes in crop yields and human health)
• Resource depletion and new technologies
• Policies aimed at reducing emissions of GHGs and other pollutants
• Policies aimed at limiting trade or land-use change
• Deployment of specific technologies (e.g. wind power, solar power, carbon capture and storage, crop yield-enhancing technology)
• Simulations of future emissions of GHGs and other pollutants as input for the MIT Earth System Model (MESM).
• Land-use change and cover as input for the MIT Earth System Model (MESM).

The core model includes 18 global regions, but its framework has been applied with greater spatial, economic sector and household resolution for detailed studies.

1) Model scope and methods - EPPA

The MIT Economic Projection and Policy Analysis (EPPA) model is a computable general equilibrium (CGE) model of the global economy. It has been applied to the study of policy impacts on the economy and emissions, prospects for new technologies, agriculture and land use, and—in some versions—environmental feedbacks on the economy through human health and agricultural productivity. The model can be run in a standalone mode to, for example, investigate the implications of climate and energy policy, or it can be coupled with the MIT Earth System Model (MESM) to form the MIT Integrated Global System Modeling (IGSM) framework. The EPPA model is regularly updated as new global economic data become available. Previous EPPA versions are described in Babiker et al. (2001), Paltsev et al. (2005), and Chen et al. (2015).

The EPPA is a multi-region and multi-sector recursive dynamic model of the world economy solved at 5-year intervals from 2015 through 2100. The model includes explicit advanced energy conversion technologies and accounting of both greenhouse gas and conventional pollutant emissions. The current version of the model includes 18 regions and 32 sectors (including detailed representation of advanced energy technologies), with labor, capital and multiple energy resources as primary factors. The model represents economic activities of three types of agents in each region: producers, consumers, and the government.

The GTAP data set provides the base information on Social Accounting Matrices and the input-output structure for regional economies, including bilateral trade flows, and a representation of energy markets in physical units. EPPA also incorporates data on greenhouse gas (CO₂, CH₄, N₂O, HFCs, PFCs, and SF₆) and air pollutant emissions (SO₂, NO_x, black carbon, organic carbon, NH₃, CO, VOC).

Among factor inputs are both depletable (oil, natural gas, coal) and renewable natural inputs (solar, wind, hydro), as well as produced capital and labor. EPPA also disaggregates the GTAP data for transportation to include household transport (i.e. personal automobile), and further detail on technologies that produce electricity from fuels and natural resources and fuels from unconventional sources such as liquid fuels from biomass and shale oil resources; and gas from coal or unconventional gas resources. To represent such technologies, detailed bottom-up engineering studies are used to parameterize production functions for each. The parameterization of these sectors is described in detail in Chen et al. (2016) and Morris et al. (2019).

1.1) Model concept, solver and details - EPPA

The model represents economic activities of three types of agents in each region: producers, consumers, and the government. Solving the model recursively means that production, consumption, savings and investment are determined by current period prices. Savings supply funds for investment, and investment plus capital remaining from previous periods forms the capital for the next period's production. The model is formulated in a series of mixed complementary problems (MCP), which may include both equations and inequalities. It is written and solved using the modeling languages of GAMS and MPSGE, and the latter is now a subsystem of the former (Rutherford, 1999).

In the recursive formulation, the model finds prices, quantities and incomes that represent an equilibrium in each period by solving an optimization problem for three types of agents in each region: the household, producers, and the government. The household owns primary factors including labor, capital, and natural resources, provides them to producers, receives income from the services it provides (wages, capital earnings and resource rents), pays taxes to the government and receives net transfers from it. In addition, representative regional household allocates income to consumption and savings.

Producers (production sectors) transform primary factors and intermediate inputs (outputs of other producers) into goods and services, sell them to other domestic or foreign producers, households, or governments, and receive payments in return. To maximize profit, each producer chooses its output level, and—under the given technology and market prices—hires a cost-minimizing input bundle. Production functions for each sector describe technical substitution possibilities and requirements. The government is treated as a passive entity, which collects taxes from household and producers to finance government consumption and transfers.

The activities of different agents and their interactions can be described by three types of conditions: 1) zero profit conditions; 2) market-clearing conditions; and 3) income balance conditions. Zero-profit conditions represent cost-benefit analyses for economic activities. For the household, the economic activity is consumption that produces utility and for each producer, the activity is production, which results in output.

1.3) Temporal dimension - EPPA

The model is solved in 5-year intervals from 2015 to 2100. The base year for the version 6 of EPPA is 2007, which is the base year of the GTAP 8 database the model adopted. From 2007 to 2015, the model is calibrated to the data from International Monetary Fund and International Energy Agency.

1.4) Spatial dimension - EPPA

The GTAP data set provides the base information on Social Accounting Matrices and the input-output structure for regional economies, including bilateral trade flows, and a representation of energy markets in physical units. We aggregate the GTAP data into 18 regions.

1. USA
2. EU
3. China
4. India
5. Japan
6. Brazil
7. Canada
8. Mexico
9. Russia
10. South Korea
11. Indonesia
12. Africa
13. Middle East
14. Australia and New Zealand
15. Dynamic Asia
16. Rest of East Asia
17. Rest of Eurasia
18. Rest of Latin America

1.5) Policy - EPPA

The EPPA model can represent the following policies

• Emission tax
• Emission pricing
• Cap and trade
• Fuel taxes
• Fuel subsidies
• Feed-in-tariff
• Portfolio standard
• Capacity targets
• Emission standards
• Energy efficiency standards
• Agricultural producer subsidies
• Agricultural consumer subsidies
• Land protection
• Pricing carbon stocks

  2) Socio-economic drivers - EPPA

  The key socio-economic driver of EPPA is the Hick’s neutral productivity growth, which is calibrated to match a baseline GDP growth trajectory under 1) a set of exogenously given factors, including labor endowment growth, which is assumed to increase proportionally to the population growth and autonomous energy efficiency improvement (AEEI), and 2) a set of factors determined by the model dynamics, which encompass savings, investment, fossil fuel resource depletion, and the evolution of technology specific factor for each backstop technology. While the Hick’s neutral productivity levels are held constant across scenarios, changes in prices and model dynamics will determine levels of variables such as resource allocations, sectoral outputs and GDP .

2.1) Population - EPPA

Population is an exogenous input for EPPA. It can enter the model in two forms: total population and working age population. While the welfare measuring is based on total population, in a special version of EPPA that focuses on the health impact of air pollutants exposure, the working age population is used for air pollution health effects calculation that affects the available labor input . For each region, the labor input is assumed to change proportional to the population, and the labor input affects the dynamics of other macroeconomic production factors (capital, energy) since the model seeks an optimal allocation of production factors. For the version 6 of EPPA, population data come from the World Population Prospects: The 2012 Revision (United Nations, 2013) .

2.2) Economic activity - EPPA

The social-economic drivers of EPPA also include a set of endogenously determined variables, which consist of savings, investment, resource depletion of fossil fuels, and the evolution of technology specific factor (a.k.a. fixed factor) supply for each backstop technology. Savings provide funds for investment, which increases the output of the following period. On the other hand, the use of fossil fuels in the current period decreases the resources available for future consumption. In addition, EPPA considers the technology specific factor to model the introduction of a backstop technology. The limited supply of the factor at the beginning captures the phenomenon that costs of operating a new technology tend to be higher when the technology is at the early stage of introduction, but the costs may go down gradually with learning-by-doing, knowledge accumulation, etc. The parameterization of technology specific factors is based on empirical evidence presented in Morris et al. (2019) .

3) Macro-economy - EPPA

Each period of EPPA forms an Arrow-Debreu type of model that is the basis of the general equilibrium theory. The recursive structure connects periods together through the evolution of endowments (see model scope and methods). Since the main application of EPPA is to provide long-term projections under some counterfactual scenarios rather than short-term business fluctuations, the model only focuses on the real variables of economies without considering the monetary markets and financial instruments.

3.1) Production system and representation of economic sectors - EPPA

The basic production setting of EPPA is based on the Constant Elasticity of Substitution (CES) function. To account for the empirical observation that income elasticities for the demand of commodities such as food tend to decrease when an economy grows, the Stone-Geary adjustment is applied by recalibrating the subsistence consumption over time to approximate the empirical income elasticity evidence.

3.2) Capital and labour markets - EPPA

Capital markets are region-specific. The demand for capital comes from each sector's production activity, while the supply of capital comes from investment and the remaining capital from the previous period. In each region, there is a capital market for the malleable capital, which moves freely across sectors to equalize the rate of return of capital. For the vintage (nonmalleable) capital it is locked into a sector (i.e., sector-specific) and will not be able to be traded in a capital market to search for a higher rate of return in other sectors. In EPPA, labor markets are also region-specific. Labor supply comes from the labor endowment, and labor demand is from each sector's production activity. In the standard EPPA setting, labor is homogenous and can move across sectors freely to equalize the wage rate.

3.3) Monetary instruments - EPPA

As briefed earlier, EPPA only considers the real variables of an economy as it focuses on long-term projections. Therefore, financial and monetary instruments are beyond the model scope and are not included in the model.

3.4) Trade - EPPA

All goods in the model are traded in world markets with the base year data coming from the GTAP database. The Armington goods specification allows an explicit representation of bilateral trade flows, such that regions are both exporters and importers of a particular good. Bilateral trade flows involve export taxes, import tariffs, and international transport margins, all of which are explicitly represented in the model. Electricity trade is represented but very little trade occurs in the base data, and it only occurs among regionally contiguous regions. The share-preserving nature of the CES function tends to limit expansion of electricity trade, and, realistically given difficulty of transmission, prevents trade from ever occurring among two regions if it is not in the base data.

One exception is for crude oil, which is treated as a homogeneous product in standard EPPA, subject to tariffs, export taxes, and international transport margins. Therefore, for each region, only net exports or imports of crude oil are represented. Given the transportation costs and different products/grades involved we treat coal, gas, and refined oil as Armington goods.

3.5) Technological change - EPPA

Changes in technologies are captured in EPPA by: 1) price-driven ones, which are induced by changes in relative prices; 2) non-price driven ones, which are considered by the inclusion of autonomous energy efficiency improvement (AEEI). Besides, EPPA also considers a set of "backstop" technologies that may not be technically or economically feasible until later years. For instance, there are backstop generation options (e.g., advanced nuclear, gas with CCS, bioenergy with CCS) that provide low-carbon or even negative emissions alternatives to existing technologies. Even if these technologies become technically feasible, they may not be economic without more aggressive climate policies that penalize the operation of generation technologies with much larger carbon footprints.

4) Energy - EPPA

In standard EPPA, it considers various types of primary energy, including 1) coal, 2) crude oil, 3) gas, 4) nuclear, 5) hydro, 6) wind, 7) solar, and 8) bio-energy. Per the crude oil, it is further converted into the refined oil, which is then consumed by intermediate and final use. On the other hand, the bio-energy considered in EPPA includes the first-generation biofuels, which are made from different types of food crops, and the second-generation cellulosic biofuels derived from non-food crops and waste biomass (EPA, 2022).

There are also project-specific versions of the model that were developed to offer more options of energy sources (e.g., hydrogen (Sandoval et al., 2009)), or higher resolution on energy types (e.g., separating crude oil into conventional crude and tar sand (Chan et al., 2012), and disaggregating refined oil into gasoline and diesel (Choumert et al., 2006), Ramberg and Chen (2015)). More details about the energy reserves and flows will be provided later.

4.1) Energy resource endowments - EPPA

The fossil energy endowments of EPPA are from the United States Geological Survey and World Energy Council, with details provided in Paltsev et al. (2005). Nuclear , hydro and renewables (wind and solar) are represented in a simpler fashion, focusing on the relevant resource and capital and labor. For each of the aforementioned energy type the resource is a technology specific factor (a.k.a. fixed factor) endowment specific to the technology and region. Changes in the resource over time are controlled exogenously. Details for these exogenous assumptions are presented in Paltsev et al. (2005). Besides, bio-energy is derived from distinct types of crop with output levels ultimately determined by the land resources.

4.1.1) Fossil energy resources - EPPA

Fossil energy resources considered in EPPA include coal, crude oil, and natural gas. For each type of fossil fuel, there is a module in EPPA that takes into account the effect of fossil fuel depletion on its price.

4.1.2) Uranium and other fissile resources - EPPA

The natural resource of nuclear power is represented by the technology specific factor, which is calibrated to match the long-term nuclear output projection of International Energy Agency under comparable scenarios.

4.1.3) Bioenergy - EPPA

Bio-energy is derived from various crops, with the output levels determined by factor productivities and ultimately, land-use patterns, and ultimately the available land endowment. The supply of bio-energy is also limited by different types of resource competition, including those coming from meeting the food demand and from capital and labor that could be used in other sectors to seek higher returns.

4.1.4) Non-biomass renewables - EPPA

Non-biomass renewables considered in EPPA include hydro, wind, and solar. For each energy type, the supply is limited by the technology specific factor that is calibrated to meet the projections of International Energy Agency under comparable scenarios.

4.2) Energy conversion - EPPA

The energy conversion channels considered in EPPA include: 1) various types of electricity generation that convert distinct forms of energy into electricity; 2) the conversion of crude oil or biomass into refined oil products that are used as intermediate inputs or final consumption.

4.2.1) Electricity - EPPA

Electricity in EPPA comes from: 1) coal; 2) gas; 3) oil; 4) nuclear; 5) hydro; 6) wind; 7) solar; and 8) biomass. The energy conversion process of each type of generation is represented by a production technology that transforms different inputs into the electricity output. Some low-carbon or negative emissions generation options (e.g., gas with CCS; biomass with CCS) are not economically feasible without stringent policies, and therefore they are calibrated based on engineering data (e.g., various years of data from EIA's Annual Energy Outlook) as they have not been commercially operated currently and are not observed in the base year input-output data. Besides the economic data, physical flows of energy are also tracked to ensure that the thermal efficiency (if applicable) of each type of conversion is valid with price-driven (endogenous) or non-price-driven (exogenous) energy efficiency improvements.

4.2.2) Heat - EPPA

While the conversions of various types of energy for heating purposes may be included in the base year input-output data, they are not considered explicitly in EPPA as the physical flows of these conversions are not included in the datasets we use.

10) References - EPPA

Chen, Y.-H.H., Paltsev, S., Reilly, J.M., Morris, J.F., Babiker, M.H., 2016. Long-term economic modeling for climate change assessment. Economic Modeling, 52, 867–883.

Ghandi, A. and Paltsev, S., 2019. Representing a Deployment of Light-Duty Internal Combustion and Electric Vehicles in Economy-Wide Models. MIT Joint Program Technical Note 17.

Paltsev, S., Reilly, J., Jacoby, H., Eckaus, R., McFarland, J., Babiker, M., Paltsev, S., Reilly, J., Jacoby, H., Eckaus, R., McFarland, J., Babiker, M., 2005. The MIT emissions prediction and policy analysis (EPPA) model: version 4. MIT Joint Program Report 125. Cambridge, MA.