This document discusses simulation models for long-term scenario analysis. It describes how IFPRI uses a suite of linked partial equilibrium and general equilibrium models to address issues like population growth, climate change, and natural resource limits. The IMPACT model is highlighted as IFPRI's main agricultural partial equilibrium model. It is composed of specialized modules that can be linked to address issues at different levels while maintaining modularity. Global CGE models are also discussed and compared to partial equilibrium models.

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Simulation Models for Long-Term
Scenario Analysis
Sherman Robinson
International Food Policy Research Institute (IFPRI)
FAO Workshop, Rome, February 2016

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FAO: Long-Term Issues
 Population growth, migration, and limits to natural
resources
 Income distribution
 Investment and finance
 Structural change and global value chains
 Climate change and the energy-agriculture-climate
change nexus

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FAO Agenda: “A global overall model”
 A work program to develop a single, overarching model
for long-run scenario analysis is not a good idea
 Instead, the goal is to start with issues, as the FAO has
done, and then design a “suite” of models to address the
issues at different levels of economy coverage (local,
country, globe) and commodity detail; different
economic/technology specifications; and different
disciplinary roots (inter-disciplinary modelling)
 The challenge is to “link” and/or “integrate” multi-
disciplinary models to address long-run issues

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Issues, Models, and Data
 Long-run simulation models should be “issue driven”
• Institutionally, model development and use should be with, or
“close” to, units that use the models in policy analysis
 Simulation models are “data driven”—models require up-
to-date estimated parameters and data
• Model code should be data driven—designed to allow change
of data aggregation and new data with minimal effect on model
specification and code
 Data estimation and management “system” should be
institutionally “close” to model development and use

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FAO: Linked Issues
 Two sets of FAO issues are strongly linked:
• Climate change and the energy-agriculture-climate change
nexus
• Population growth, migration, and limits to natural resources
 Difficult to think of them separately
• “Natural resources”: land and water are a major focus
• Population growth is not generally modeled endogenously, but
treated in scenarios (e.g., IPCC SSP scenarios)
• Migration is very difficult (e.g., World Bank work did scenarios
with a global CGE model—essentially LINKAGE)

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The IFPRI IMPACT 3 Model
 International Model for Policy Analysis of
Agricultural Commodities and Trade
• Close cousin to FAO GAPS model
• Related to GLOBIOM and MAgPIE
 Need for a multi-disciplinary approach:
• Core economic model linked to other
disciplinary models
• CGIAR and other institutional collaborators

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IMPACT version 3
• 58 Agricultural
commodities
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IMPACT 3: A Suite of Models
 Multimarket model
• Core global PE model
 SPAM:
• Spatial Production
Allocation Model
 Land-Use
• Land types, crop allocation
 DSSAT Crop Models
 Linked to global CGE
model
 Water models
• Hydrology
• Water Basin Management
• Water Stress on yields
 Value chains
• Sugar, oil seeds
• Livestock/meat/dairy
 Nutrition/health/welfare
• Post solution
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Natural Resources: Water Models
 Global hydrological module (GHM) assesses water
availability
 IMPACT Water Simulation Module (IWSM) optimizes
water supply according to demands
• Monthly time step
• Domestic, industrial (linked to GDP/population)
• Livestock, environmental, and irrigation demands
• Optimizing model for irrigation demand/supply
 Water stress module
• Optimizing model: allocation of water to crops
• Deliver crop yields to the IMPACT multimarket model

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Natural Resources: Land Use
 Land: forest, pasture, irrigated and rainfed crop land
 Demand for land by crop is a function of commodity price
and shadow price of land
 Total supplies of irrigated and rainfed land are fixed in
each region (FPU) within periods, updated with a land
use model
 Shadow price of land varies to equate supply and
demand for land by type and region
• Solution determines allocation of land to crops and equilibrium
shadow price
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Value Chains: Activity-Commodity
 Commodities are:
• Produced (activities)
• Traded (commodities)
• Consumed
• Can be endogenous
or exogenous
– Maize has endogenous production and demand
– Oilseeds have endogenous production and both endogenous
and exogenous demand (biofuels)
– Fertilizers is an exogenous commodity with fixed price
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Example: Oilseed Activity-
Commodity Value Chain
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Activity
• Soybean
Farm
(jsoyb)
• Demands
land,
fertilizer,
labor
Activity Output
• Soybean
Commodity
(csoyb)
Activity
• Soybean
Processing
(jsbol)
• Demands
soybeans
(csoyb) at
market price
Processed
Commodities
• Soybean Oil
(csbol)
• Soybean
Meal
(csbml)

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IMPACT 3: Potential Improvements
 New livestock module: under development with ILRI
 Fish module: joint work with World Fish
• Two stage work program underway
 Linked global CGE model: joint work with IDS
• Welfare analysis, economywide direct/indirect links
 Links to environmental models
• Biodiversity: IFPRI and Bioversity
• GHG emissions, nitrogen use efficiency: IFPRI
 Water model improvements:
• Ground water, water quality, hydropower

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IMPACT 3: Potential Improvements
 New crop modules: fruits/vegetables, other crops
 Nutrition module: IFPRI, PHND, A4NH, CIMSANS, Oxford,
and others
 Health module: with Oxford (Martin Centre)
 Improved land-use module: land supply/demand by type
 Variability and extreme events
• Work with UK/US collaborators
• Covariate climate shocks
• Pest/disease scenarios

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Linked Global CGE Model
 Link IMPACT 3 with the GLOBE CGE model
• GLOBE is based on GTAP data and written in GAMS
• Includes activity/commodity distinction, as in IMPACT 3
 One-way links: IMPACT to GLOBE
• Crop/livestock production from IMPACT 3 passed to GLOBE,
which then is run assuming those outputs are fixed
• GLOBE solves for economywide impacts (direct and indirect
links): production, employment, and prices
• All welfare analysis is done in GLOBE (EV/CV, total absorption)
• Links to labor markets, wages, and poverty done in GLOBE

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Linked Global CGE Model
 Two-way links: IMPACT to/from GLOBE
• Agricultural output from IMPACT: GLOBE generates GDP
originating in agriculture, and changes in total GDP
• GDP from GLOBE sent back to IMPACT, so GDP in IMPACT
reflects changes in agricultural productivity
– Currently, GDP is exogenous in IMPACT
• Energy interactions: biofuels and other energy sources
 GLOBE and IMPACT need not run on the same time step
• Both can be annual, but can run on different multiyear time
steps (e.g., annual for IMPACT, every 5 years for GLOBE)
 GLOBE linked via a standalone module that takes input
from IMPACT and runs GLOBE

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Modularity: Linking Modules
 Modularity; “a la carte” model system
• Use the models you need, turn off those you do not need
• Separate models can be run independently
• Modules can run with different time steps
 Standardize data transfer
• Information flows
• Dynamic or iterative interaction
 “Data driven” model specification
• IMPACT 3 multimarket model can be run at any level of
aggregation without changing the model code
• Change input data and sets only: user need not even see the
GAMS code

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Advantages of Modularity
 “Standalone” modules can be run independently of
IMPACT, but use inputs from IMPACT scenarios
• Can be developed, calibrated, and tested by specialists (e.g,
from various CGIAR centers).
• Designed to be used in Center research programs
 Design: separate modules can reflect their disciplines
• No need to compromise to “fit” one model into another
• E.g. water in economic models or economics in water models—
always unsatisfactory
 Model development, testing, and debugging is greatly
facilitated if the modules can be run separately

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Desiderata for Modular Model Systems
“Modules” should be designed to:
 Operate in “standalone” mode
 Read its own parameters
 Initialize its own variables
 Accept variables/parameters passed to it from
other modules and the environment;
 Pass variables that are computed within the
module to other modules or the main model
 Own its set of state variables

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Modularity: Linking Modules
 Three ways to link modules:
• Exogenous: Information flows in one direction
– To IMPACT: hydrology, DSSAT, GCMs, SPAM
– From IMPACT: welfare, nutrition/health, GLOBE/CGE
• Linked dynamically: Two-way information flow between years
– Water basin management, water stress on crops
– Land use by type
– GDP/economywide links: GLOBE
• Endogenous: Module equations are solved simultaneously
– Livestock, sugar processing, oilseeds/oils
– Land allocation to crops

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IMPACT 3 Modules
 Standalone modules, one-way links:
• Welfare, nutrition, GLOBE (e.g., welfare, economywide
impacts), hydrology, DSSAT, GCMs
 Standalone modules, inter-period links:
• Water models (IWSM, water stress), land use (by land type),
livestock (herds), GLOBE (e.g., GDP, non-ag prices)
 Standalone modules, intra-period links:
• Land use (cropping, irrigated/rainfed), Livestock
 Value chains, within IMPACT: sugar, oilseeds,
livestock

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Standalone IMPACT Module: Template
 GAMS IMPACT-compatible standalone module
• Include file with definition of relevant IMPACT parameters
• Include GDX file(s) of scenario output of IMPACT results
• Load IMPACT data needed by the module
 Data estimation and management
• Module has its own data base, in addition to IMPACT data
 Model specification and parameterization
• If module is to be integrated with IMPACT, must avoid name
collisions for parameters, variables, and equations
 Linking to IMPACT 3
• Communication: exogenous, intra-period, within-period

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Global Computable General
Equilibrium and Partial
Equilibrium Models: CGE/PE
Sherman Robinson
International Food Policy Research Institute (IFPRI)
FAO Workshop
February 2016

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Simulation Models & Scenario Analysis
 Given the uncertainties of climate change, researchers
have used simulation models to explore the effects of
different CC scenarios
• Integrated Assessment Models (IAM), early work
• Steady advances in the reach, size, and sophistication of CC-
scenario simulation models
– Geographic disaggregation
– Impact chains (e.g., temp, precip, extreme events)
– Economic coverage (global, national, sub-regional)
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CC Simulation Models
 Need for an interdisciplinary approach
• Climate change (GCMs)
• Civil engineering: infrastructure
• Energy (fossil fuels, renewables, hydropower)
• Hydrology, water management
• Agriculture (crop models)
• Economic models: markets matter
– Two major families of economic simulation models: CGE
(computable general equilibrium) and PE (partial equilibrium
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 Relative strengths of different global models with an
agricultural focus: CGE and PE models
• Relevance for issues of biodiversity and ecosystem services
in Foresight Models
 Exploiting comparative advantages of different model
systems
• Modularity within and between model families
• “Soft” and “hard” linking different models
 Data base estimation and management
Global CGE and PE Model Families
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Global CGE Models at IFPRI: GLOBE, MIRAGE
 Global CGE models simulate the interaction of national
economies across world markets
• Determine national and world market prices
 CGE models are “complete”: they incorporate all
economic activity in the economies simulated
• Production (supply), income to “agents” (households, govt.,
enterprises), demand (C, I, G), exports/imports, prices, wages,
land rents, exchange rates
• Markets “clear”: supply/demand equilibrium conditions
determine prices, wages, profits, land rents
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Producers
Product
Markets
Factor
Markets
Rest of the
World
Households Government Saving/INV
Factor
Costs
Wages
&
Rents
Demand for
Intermediate
Inputs
Sales
Revenues
Private
Consumption
Taxes
Domestic Private Savings
Government
Expenditure
Gov. Savings
Investment
Demand
Imports
Exports
Foreign Savings
Demand for Final Goods
Transfers
CGE: Circular Flow of Income

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CGE: Deep Structural Models
 Includes “representative” economic agents:
• Utility-maximizing consumers (households)
– Expenditure functions, given budget constraints
• Profit-maximizing producers
– Maximize profits given technology and prices
– Yields factor demands, given wages and prices
 Wages/prices are “signals” on all markets
 Market “institutions”: competitive markets with agents
who cannot manipulate prices
• Supply = demand determines prices
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CGE: Completeness
 CGE models are “closed” in the sense that they account
for all economic activity: no “leakages”
 SAM accounting framework: describes the economic
“universe” of the models
• Double-entry bookkeeping: expenditure/receipt accounts of all
economic agents must balance
 General equilibrium theory/practice: powerful discipline
for modelers
 Welfare analysis
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CGE: Direct and Indirect Effects
 PE models (GLOBIOM, MAgPIE, IMPACT, GAPS) are
“partial” and do not include links between agricultural
and non-agricultural sectors
 CGE models include all direct/indirect links across the
economy: PE models miss them
• Indirect effects (forward and backward linkages) are empirically
important
 Shocks to agriculture “leak” to the rest of the economy:
prices and factor flows
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PE Models: Agricultural Detail
 The PE models provide much more disaggregated
description of agriculture than the CGE models
• Regional, land, and crop disaggregation
• Focus on crop inputs and biology: seeds, water, light, heat,
nutrients: process technologies
 Better host for analysis of issues of biodiversity and
ecosystem services
• Links to land use and crop simulation models
 Potentially PE a better host for a modular system of
models, but also feasible with CGE models
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