GSFS_XTM_May2015

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IFPRI IMPACT 3 Model System:
Modularity
Sherman Robinson
IMPACT Model Team
International Food Policy Research Institute (IFPRI)
Rome, GFSF Team Meeting, May 2015

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The IMPACT 3 Model
 International Model for Policy Analysis of
Agricultural Commodities and Trade
 Need for a multi-disciplinary approach:
• CGIAR and other collaborators:
– Economics, agronomy, hydrology, livestock,
fish, crop models, nutrition/health
• Civil engineering: infrastructure
• Climate change (GCMs)
• Energy (biofuels, inputs)

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IMPACT version 3
• 58 Agricultural
commodities
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IMPACT 3 Model System
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IMPACT 3.2: A Suite of Models
 Multimarket model
• Core global PE model
 SPAM:
• Spatial Production
Allocation Model
 Land-Use
 DSSAT Crop Models
 Welfare
 Water models
• Hydrology
• Water Basin Management
• Water Stress on yields
 Sugar and oilseeds
• Processing value chains
 Livestock/meat/dairy
• Current version running
 Nutrition/health:
• Current version running
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IMPACT 3.2 to 3.3: Improvements
 Data on policies: tariffs and subsidies (GTAP data, OECD
PSE/CSE data
• Incorporated into IMPACT 3.2 data set
 Review of productivity growth trends and model
improvements by CGIAR centers
• Rome GFSF meeting, May, 2015
 Menu of possible model improvements
• Priority setting

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IMPACT 3.3: Potential Improvements
 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
 Links to environmental models
• Biodiversity: IFPRI and Bioversity
• GHG emissions, nitrogen use efficiency: IFPRI
 Water model improvements:
• Ground water
• Water quality

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IMPACT 3.3: Potential Improvements
 Micronutrient module: IFPRI, PHND, A4NH and others
• Under development
 Health module: with Oxford (Martin Centre)
• Under development
 Land module: land supply and demand by type
• Under development at IFPRI
 Variability and extreme events
• Work with UK/US collaborators (sponsored by Lloyds)

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Nutrition Module
 IMPACT model solves for supply/demand for agricultural
commodities in physical units
• Nutrition module: post solution calculation of nutrition impacts
 Nutrition content measured at the agricultural
commodity level--extensive empirical work
• FAO: Food balance sheets. Nutrition content of various
agricultural commodities, focusing on “energy” (calories)
• IFPRI (PHND, Haddad-Smith, Derek Headey), CSIRO (Mario
Herrero), CIMSANS (Jerry Nelson), Oxford (Marco Springmann),
Nestle Research
– Extending food balance sheets to include more nutrients
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Nutrition Module: Regression Model
 Reduced-form regression models
• Statistical models linking nutrient supply at the commodity level
to nutritional status at the household/ consumer level
• Haddad/Smith cross-country regression model is currently used
in IMPACT to calculate nutrition outcomes, focusing on energy
– Nutrient supply is one variable among many in the model,
but is the only variable linked to IMPACT
– They are updating the regression model to include more
nutrients and outcomes (obesity as well as under nourished)
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Nutrition Outcomes
 Since actual household demand is for processed
commodities (e.g., bread, not wheat), food balance
sheets measure supply of nutrients, not what is actually
consumed at the household level
• Haddad-Smith regression model skips value chain to processed
food commodities
• Nestle: EcodEx (Product Ecodesign Tool) considers value chains
to processed commodities and 32 nutrients
• Tilman et al.0(2011), “Global food demand and the sustainable
intensification of agriculture”
– Demand functions for “nutrients”

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Nutrition:
• Oxford Martin Programme on the Future of Food, study linking
IMPACT model results for fruit and vegetable and red-meat
consumption on body weight and health outcomes using a
Markov model and detailed information on nutritional content
of foods
– Springmann et al. paper
– Health outcomes linked more to consumption of fruits and
vegetables (micronutrients) than to energy (calories)
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Production to Nutrition
 To support more structural models of food demand and
nutritional status requires specifying the value chain in
both PE and CGE models
• Wheat to flour to bread/pasta/cake to retail sector to
households
• Production of “other” food commodities such as beverages, fish
products, etc.
 Extensive data on nutritional content of processed food
commodities.
• Feasible to use these data in models?
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Demand, Utility, and Nutrition
 How to link nutritional status and commodity demand
functions:
• Current practice. Add equations determining nutritional status
as an “add on” after commodity demands have been
determined based
– Data are available, both at the agricultural and food
commodity levels. Current treatment is to work at the
agricultural commodity level.
– Thin links with utility/demand theory. Households demand
food commodities, not agricultural products or nutrients.
Only an indirect link with nutritional status indicators.
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Demand, Utility, and Nutrition
 Add nutrition indicators to the utility function, with
implications of commodity demand
• Hedonic quantity/price indices: consumers do not demand
nutrients, but commodities with nutritional attributes
– K. Lancaster, “A New Approach to Consumer Theory”, 1966
 Add nutritional status indicators as constraints in the
utility optimization problem
• Integrate the classic LP “diet problem” with an NLP utility
maximization problem
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IMPACT 3.4: Potential New Modules
 Production: better specification of technology and supply
• Optimization given production/cost functions (CGE models)
• Activity/process specification of production/costs
– GLOBIOM (IIASA), MAgPIE (PIK, Potsdam)
• Stylized “farm” simulation models
 Value chains: more “processing” activities to move from
crops/livestock to marketed “commodities”
• From cows to hamburgers & milk (livestock module)
• From wheat and corn to Wheaties and Cornflakes
• Cassava: food vs industrial demand, tradability

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Current Value Chain Modules
 Oilseeds and sugar (integrated in IMPACT)
• Processing from crops (sugar cane/beet, various oil seeds) to
“commodities”: processed sugar, oils, meal
• Simple cost pricing: “markup” on cost of crop inputs
• Implicit assumption of competitive markets
 Livestock (standalone module and integrated)
• Value chain from herds to dressed meat, eggs, milk
• New livestock module: elaborate specification of feed inputs
and livestock production “systems”
• Simple model of commodity production: “markup” on inputs
• Implicit assumption of competitive markets

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New Value Chain Modules
 Interest in expanding range of value chain modules
• Cassava, fish, wheat/maize/rice/soy beans
• Welfare analysis using demand curves for intermediate inputs is
problematic—consumer surplus calculation is suspect
• Links to nutrition analysis: more detail on food commodities
• Simple specification of competitive markets is suspect
– E.g., sugar
 Combine value chain with industry studies
• “Structure, conduct, performance” analysis
• Schmalensee and Willig: Handbook of Industiral Organization

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Linked Global CGE Model
 New project: 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
 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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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
 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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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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Water Models in IMPACT
 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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Water: Two-Way Model Integration
Food Model
• Crop areas
• Population
• GDP
• Livestock
numbers
• Prices
Water
Models
• Water supply
• Water Stress:
shock on crop
yields
Solve multimarket
model given
trends and
variable crop
areas
Fix crop areas
and livestock; call
the water models:
solve for water
stress yields
Re-solve the
multimarket
model with fixed
crop areas and
stress yields
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In each year, solve in two steps:

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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