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Day 3.1 robinson impact3-gfsf-rome-may-2015-sr2

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Day 3.1 robinson impact3-gfsf-rome-may-2015-sr2

  1. 1. IFPRI IMPACT 3 Model System: Modularity Sherman Robinson IMPACT Model Team International Food Policy Research Institute (IFPRI) Rome, GFSF Team Meeting, May 2015
  2. 2. 5 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)
  3. 3. IMPACT version 3 • 58 Agricultural commodities 6
  4. 4. IMPACT 3 Model System 7
  5. 5. 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 8
  6. 6. 9 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
  7. 7. 10 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
  8. 8. 11 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)
  9. 9. 12 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 12
  10. 10. 13 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) 13
  11. 11. 14 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”
  12. 12. 15 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) 15
  13. 13. 16 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? 16
  14. 14. 17 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. 17
  15. 15. 18 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 18
  16. 16. 19 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
  17. 17. 20 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
  18. 18. 21 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
  19. 19. 22 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
  20. 20. 23 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
  21. 21. 24 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
  22. 22. 25 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;
  23. 23. 26 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
  24. 24. 27 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
  25. 25. 28 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
  26. 26. 29 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
  27. 27. 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 32 In each year, solve in two steps:
  28. 28. 33 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