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Simulation Models for Long-Term Scenario Analysis


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Simulation Models for Long-Term Scenario Analysis.

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Simulation Models for Long-Term Scenario Analysis

  1. 1. Simulation Models for Long-Term Scenario Analysis Sherman Robinson International Food Policy Research Institute (IFPRI) FAO Workshop, Rome, February 2016
  2. 2. 2 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
  3. 3. 3 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
  4. 4. 4 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
  5. 5. 5 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)
  6. 6. 6 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
  7. 7. IMPACT version 3 • 58 Agricultural commodities 7
  8. 8. 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 8
  9. 9. 9 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
  10. 10. 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 10
  11. 11. 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 11
  12. 12. Example: Oilseed Activity- Commodity Value Chain 12 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)
  13. 13. 13 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
  14. 14. 14 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
  15. 15. 15 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
  16. 16. 16 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
  17. 17. 17 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
  18. 18. 18 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
  19. 19. 19 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
  20. 20. 20 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
  21. 21. 21 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
  22. 22. 22 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
  23. 23. Global Computable General Equilibrium and Partial Equilibrium Models: CGE/PE Sherman Robinson International Food Policy Research Institute (IFPRI) FAO Workshop February 2016
  24. 24. 33 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) 33
  25. 25. 34 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 34
  26. 26. 35  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 35
  27. 27. 36 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 36
  28. 28. 37 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
  29. 29. 38 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 38
  30. 30. 39 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 39
  31. 31. 40 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 40
  32. 32. 41 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 41