# Presentation: 589343

## 	 The Second Generation Model

***US Environmental Protection Agency***
**Science Advisory Board**
**SAB-SGM Advisory Panel**
**Jae Edmonds, Ron Sands, Hugh Pitcher, Antoinette Brenkert**
- 04 February 2005
- US Environmental Protection Agency
- Washington, DC

## Overview

- Model Structure and Purpose
- Hybrid Input-Output Table
- International Trade
- Production, Expectations and Market Clearing in the SGM
- Access to the Model

## SGM Origins

- The SGM is a computable general equilibrium model of an economy
- Original design began in 1988—at a time when there were no CGE models in use to address climate change
- Designed as a complement to the Edmonds-Reilly model—a long-term partial equilibrium model
***Designed from the problem back to the model.***
- Primary focus was on emissions of greenhouse gases including CO2 from energy and land-use emissions and non-CO2 greenhouse gases
- Time frame:  5-50 years into the future

## MiniCAM-SGM Relationship

- MiniCAM
- Simpler, long-term, partial equilibrium model
- Test bed for new ideas
- SGM
- Computable general equilibrium
- Energy-economy and other interactions matter
- More detailed framework than MiniCAM
- Medium term (5-year time steps, 50-year time horizon)
- Tracks capital stocks by vintage

## The SGM

- The SGM is a simple model at its base
- Implements an Economics 101 circular flow diagram
- Sectors chosen for emphasis reflect a concern for the climate issue in general and the emissions of GHG’s in particular

## Global Fossil Fuel Carbon Emissions 1999

- Source:  Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory.

- Fossil fuel use (6.5 PgC/y in 1999)
- Natural gas 13.7 TgC/EJ
- Oil 20.2 TgC/EJ
- Coal 25.5 TgC/EJ
- Industrial process emissions (e.g. cement)
- 0.2 Pgc/y
- Land-use change emissions (1.7; 0.6-2.6 PgC/y)
- Deforestation
- Soil cultivation

## SGM Production Activities

## Fossil Fuel Carbon Emissions1999

- SGM Regions
- USA,
- Western Europe,
- China,
- former Soviet Union,
- Japan,
- India,
- Canada,
- South Korea,
- Mexico,
- Eastern Europe,
- Australia/New Zealand,
- Brazil,
- Middle East,
- Rest of World

- Source:  Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory.

## Key Ideas

- Emissions—energy, ag-land-use, other
- Production functions—why CES?
- Energy production
- Resources-reserves
- Energy consumption
- Model sectors—chosen because they have emissions that matter
- Households—energy services & transport
- Sector-subsector
- Fuels matter
- Energy-emissions coefficients
- Region choice—emissions today and tomorrow
- Time scale—5-50 years
- Complementarity with MiniCAM
- Need for vintaged capital stocks

## Key Features

**14** regions of the world
- USA, Canada, Mexico, Western Europe, Eastern Europe, former Soviet Union, China, India, Brazil, Japan, South Korea, Australia/New Zealand, Middle East, Rest of World
- Can be operated in single region mode
- Many regional models are developed in collaboration with in-country researchers
**5-**year time steps from 1990 to 2050
**7** Greenhouse Gases
- CO2, CH4, N2O, HFCs, HFC-23, PFCs, SF6

## Regional Partnerships

- SGM regions are developed with regional partners
- Regional researchers have the best understanding of their regional data, institutions, market structure, and trends
- Regional partnerships have helped shape the development of most SGM regions

## Energy Supply in the SGM

- Finite resources use a resource-reserve-production model
- Production occurs out of reserves
- Each period producers bring new reserves on line from the resource base based on expected profitability
- The resource base is graded
- Production can occur from more than one grade of the resource simultaneously

## Anthropogenic GHGs

## Mapping Emissions from Production Sectors

## Technology Matters to the Answer

- MiniCAM Output:  Limitation of GMST to 2oC

## Technology Vintages in the SGM (1)

- Technology is embodied in the SGM’s production functions
- Technology is tracked by vintage
- Existing technology vintages produce as long as they can cover their operating costs
- Each existing technology is associated with a level of capital investment that constrains total production

## Technology Vintages in the SGM (2)

- New technologies are chosen from the ex ante technology possibility frontier
- Technologies are chosen based on expected profitability
- Expectations are treated explicitly in the model  (The default is myopic foresight, but others have been tried)
- The level of investment in the technology depends on expected profitability
- Aggregate investment in the sector depends on expected demands for the sector

## Technology Vintages in the SGM (3)

- The capital market balances the demands and supplies for loanable funds
- Existing capital stocks are associated with a specific production function (technology) and cannot move from sector to sector
- Only new investments are perfectly malleable
- The interest rate clears the market

## Production Functions

- All goods are produced with either a non-nested Constant-Elasticity-of-Substitution (CES) production function
- New investment within the electricity sector (e.g., new coal, gas, oil, etc.) is allocated based on a logit sharing mechanism
- or
- Leontief production function
- For production functions with elasticities of substitution < 0.05
- Oil refining
- Electricity generation from its various energy sources

## Technological Change

- Set of parameters that can be used to simulate technical change over time for production sectors
- Separate parameters are available for each input to each production process (and each vintage)
- Parameters that determine energy, land, labor, and capital productivity, i.e., non-neutral technical change
- Labor productivity parameters are the primary determinant of economic growth
- Both energy efficiency and labor productivity parameters can be altered to construct reference scenarios

## The Details

- Ron Sands
- Hybrid data structure
- Trade in SGM
- Hugh Pitcher
- Production
- New technologies, vintage structure & expectations
- Solution mechanism
- Lots of discussion

## Hybrid Input-Output Table

## Terminology

- The term “hybrid” refers to model input data and not model structure
- No code changes needed
- Does not limit form of production function
- The input-output table used to calibrate SGM base year uses hybrid units
- Joules for energy flows
- Base-year currency (e.g., 1990 US$) for all other goods
- Reference: Miller, R. and P. Blair, *Input-Output Analysis*, Prentice-Hall, 1985, pp. 200-235. (Chapter 6, “Energy Input-Output Analysis”)

## Motivation

- Carbon dioxide emissions are tied closely to energy flows
- Energy balance tables are the best source of data on energy flows
- Energy balance tables are actually energy input-output tables
- Can construct energy “use” and “make” tables
- One price for each energy commodity ensures quantity balance during model operation
- Energy commodities are relatively homogeneous
- Strict energy accounting

## Typical Energy Balance Table

## Data Sources

- Base-year input-output table
- Locally produced and in local currency, if available
- Otherwise a composite in US dollars
- Base-year energy balances
- Locally produced, if available
- International Energy Agency
- Engineering parameters and costs for electric generating technologies

## Composition of Hybrid Use Table (United States)

## International Trade

## Overview

- Current Configuration
- Single Region
- Global Operation
- Design Considerations
- Status of Model Development
- Comprehensive revision of input data
- Theoretical considerations

## Single-Region Configuration

- Types of commodities
- Numeraire good (large services sector) is tradable
- Other tradables (crude oil, natural gas, emissions permits)
- Trade in remaining goods is fixed at base-year quantity
- Prices
- Numeraire price set equal to 1.0 in each period
- Crude oil and gas price set exogenously (can vary by time period)
- Other prices solved endogenously each time period
- Emissions Permits
- Can be traded in a regional market (endogenous price)
- Can be a traded in a global market (exogenous price)
- Balance of payments constraint
- Specified as an exogenous capital flow (can vary by time period)
- Any increase in imports must be paid for with exports of another tradable

## Global Configuration

- Configuration for recent Energy Modeling Forum studies
- Emissions permits trade globally or in regional blocks, depending on policy scenario
- Otherwise, each region operates in same way as its regional configuration
- Numeraire, crude oil, natural gas are tradable
- Trade in other goods is fixed at base-year quantity
- Regional balance of payments constraint
- Crude oil and natural gas prices set exogenously on a scenario basis
- Many SGM regions modeled in local currency (USA, India, China, Canada, Mexico, Japan, S. Korea)
- Trade takes place between each region and a global market
- Exogenous exchange rate converts world price of traded good to local price (set to base-year market exchange rate)
- No attempt to track bilateral trade

## Design Considerations

- Full global trade in crude oil and natural gas
- Revisit fossil supply methodology (especially Middle East)
- Calculation of terms-of-trade component in the cost of a climate policy
- Full global trade in agricultural products
- Draw from Battelle-PNNL experience with partial-equilibrium Agriculture and Land Use (AgLU) model
- Commodity flows calibrated to base-year food balance tables from UN Food and Agriculture Organization
- Full global trade in energy-intensive goods
- Shift in production capacity across regions in response to a climate policy
- Carbon leakage

## Development Activities

- Comprehensive revision of input data
- Selective use of GTAP data
- Greater coverage of input-output tables
- Consistent base-year trade data across regions
- Automate data preparation process
- Methodology to move input-output table to a different base year
- Develop data templates applicable to all regions
- Organize data on national income accounts into a social accounting matrix
- Evaluate alternatives
- Fossil energy supply
- Trade in energy-intensive goods

## Production, Expectations and Market Clearing in the SGM

## Production, Expectations and Market Clearing in the SGM

- Production technology representation
- Combining technologies (nesting)
- Expectations and Investment
- Solving the model

## Production

- All technologies use either a flat CES or Leontief production function (no nested CES functions)
***0*  is constrained to be one
- All technical change occurs through changes in the ***i*
- Technologies produce at original capacity until they are retired either by reaching their physical or economic lifetime (they may operate at lower capacity if rate of return is low)
- Nested energy bundles will not preserve energy balance

## Technology Characteristics

- Technologies have larger elasticities of substitution at the point of investment than in subsequent periods
- Putty-semi putty (or putty-clay) formulation
- Investment value chosen to be representative of literature—operation value chosen to meet energy conversion constraints (0.1 or lower)
- Fixed physical lifetime (typically twenty years with no life extension)
- A vintage has a fixed capacity until it is retired
- New technologies can be made available in future periods

## Technology (2)

- Technologies are represented as a series of vintages—each with its own capital stock which can be operated at full capacity, part capacity or prematurely retired depending on current period profit rate
- Profits in the SGM are defined as revenue minus variable costs

## Parameterization Process for Existing Technologies

- Exogenous value for elasticity of substitution
- Use IO data and functional specification to derive remaining technology parameters
- Non-neutral technical change values can be used to tune energy technologies to match EIA forecast
- Sector specific discount factor derived from historical sector level investments and the investment equation

## New Technologies

- Engineering cost studies are the primary source of data on new technologies
- Issues:
- Optimism about costs
- Breaking out inputs into SGM sectors
- Consistency of discount rates and prices
- Technologies have individual discount rate which reflects sub-sector specific factor plus cost of capital from capital market
- Level playing field—Existing technologies reflect additional costs, such as transmission and distribution expenses, regulatory requirements, etc.

## New Technology (2)

- Start up is an issue
- Single digit nameplate problem
- Penetration rates for new technologies
- Assigning technology specific discount factor
- Nesting or other sub-sectors that the technology competes with directly

## Key Lessons Learned (1)

- Neutral technical change in energy transformation technologies leads to violations of the conservation of energy principle
- For example, consider a petroleum refinery that presently converts 80 percent of crude to refined product
- Under a one percent per year neutral technical change assumption, after 25 years, the refinery will convert 103 percent of crude to refined product
- Solution
- Only non-neutral technical change
- This allows capital and labor efficiency to increase but maintains physical limits

## Key Lessons Learned (2)

- Elasticities of substitution in the range of the literature (say .3 to .5) in the presence of carbon prices can result in implied technologies that violate the second law of thermodynamics
- Existing coal fired electricity plant operating at 33% efficiency
- Carbon price of $300 a ton
- Elasticity of Substitution = .5 => Efficiency of 75%
- Elasticity of Substitution = .05 => Efficiency of 34.5%
- Solution:  Existing energy technologies have sharply limited elasticities of substitution or are Leontief once installed

## Key SGM Characteristics

- Technological change in the SGM under a greenhouse gas mitigation strategy is primarily a matter of shifting across technologies
- The model manages GHG emissions by introducing new technology, not by improving existing technology—essentially bottom up
- This approach requires explicit new technologies and maintains physical consistency between energy inputs and outputs

## Advantages of SGM approach

- The model can maintain a fully consistent energy balance table across time
- New technologies have to be explicitly identified and parameterized
- There is no vague implicit or explicit backstop technology
- The value of new technology can be assessed
- Explicit representations of technologies enable consideration of additional characteristics of a technology—e.g. safety or local air pollution

## Disadvantages

- Non-standard production characterization makes it difficult to use existing literature on parameter values—i.e. estimates of technical change based are two-digit industries are of limited value
- It is difficult to foresee technology characteristics beyond the current set of potential new options (What comes after IGCC with capture and disposal?)

## Nesting of Technologies

- The specific nature of technologies requires a mechanism to shift across technologies
- We use a logit approach to share investment across technologies within a sector
- A flat logit approach violates dominance
- A logit approach based on expected profits prevents peak load technologies from entering into production—therefore we are using expected costs

## Why Logit Sharing Rather than Nested CES?

- Logit mechanism maintains mass balance if components are consistent
- It is more flexible than a CES nest
- It does not require all inputs (subsectors) to be positive
- Logistic sharing does imply equal risk adjusted marginal returns within the industry

## The Electricity Sector Nest

## Expectations

- Expectations enter into production sector decision making through the investment process
- The model computes either expected cash flow or levelized costs using current and future prices over the lifetime of the investment
- At present, future prices are projected to be the same as current prices (myopic expectations)
- Levelized costs (expected profits) are computed using a discount rate which is the sum of price of capital and a sector specific discount factor

## Expectations and Investment

- Current investment produces under the same price and output as used to make the investment decision  (Expectations are realized in the first period)
- Current investment is driven by
-  a scale factor representing either
- (1) previous investment or
- (2) expected output
-  current period expected cash flow per dollar of investment
- Investment in subsectors is allocated by a logistic process using subsector levelized costs (or expected profits) as arguments

## Dynamic Expectations

- A simple trend extrapolation experiment failed due to instability
- We plan experiments using simulated values as the basis for price expectations
- The role of current investment in equating supply and demand may limit potential options

## Solution Mechanism

- At solution, supply and demand for each market are equal to within the tolerance given to solution mechanism (typically .01%)
- Solution requires consistent model in order to solve—budget equations for all decision makers must hold
- Functions rapidly and reliably as long as the problem posed to the model can be solved using available technology options => low to medium carbon price
- Single region run time 1-2 minutes
- Global run <10 minutes

## Access to the SGM

- _[http://www.globalchange.umd.edu/?models](http://www.globalchange.umd.edu/?models)_
-  _[http://www.globalchange.umd.edu/sgmrelease.php](http://www.globalchange.umd.edu/sgmrelease.php)_
- _[http://www.globalchange.umd.edu/models/download/](http://www.globalchange.umd.edu/models/download/)_
- 	SGM Users Guide I

## \Exec

- \SGM_US_A

- \Inputs

- \Outputs

- \USInputs

- \Paths

- sgmctrl.csv

**RunSGM_US.xls**

**DataViewer_US.xls**

- SGM.exe

- CE policy files

- US-specific input files

- sgmgen2004_us.csv files

- sgm_us.mbd

- \screen.csv

- datamover.exe

- DONE.csv

- ddao36.dll: required but Microsoft owned

**Legal Notice.txt**

**SGM_output.xls files**

## RunSGM_US.xls   Scenario Examples

| USA baseline |   | US CE$100 |   | US CEstab2015 |   |
| --- | --- | --- | --- | --- | --- |
|   |   |   |   |   |   |
| ..\inputs\USinputs\usa_baseline_2004_A.csv |   | ..\inputs\USinputs\usa_baseline_2004_A.csv |   | ..\inputs\USinputs\usa_baseline_2004_A.csv |   |
| ..\inputs\screen.csv |   | ..\inputs\paths\us_CE_$100.csv |   | ..\inputs\paths\us_CEstab2015.csv |   |
|  |   | ..\inputs\USInputs\non-CO2_MACs_US.csv |   | ..\inputs\USInputs\non-CO2_MACs_US.csv |   |
|  |   | ..\inputs\screen.csv |   | ..\inputs\screen.csv |   |
|  |   |  |   |  |   |

## Dataviewer_US.xls

**Example of Single Query Output**

## Example of SGMgen2004_US output