1 Introducing IMPACT 3: Modeling Philosophy and Environment Sherman Robinson Daniel Mason-D’Croz Shahnila Islam

Global Futures and IMPACT Objective: Use IMPACT for ex-ante analysis of potential agricultural technologies to help policy makers prioritize agricultural investments Phase 1: IMPACT Developments: – Welfare Module – Benefit-Cost Analysis – Technology Adoption Module – Tracking progress against MDGs Challenges identified in Phase 1: – Insufficient geographic disaggregation – Need to model more CG-mandate crops – 2000 base year outdated – Model needed to be recoded to allow for better integration with new modules under development (water, livestock, fish, biofuels) 2

What is IMPACT 3? More than a new FAO download and cleaner code A modeling-data platform built on modularity and interoperability – Harmonized Data – Data driven model specifi- cation – More flexible to meet user needs 3

IMPACT integrates various models, which often use similar input data Better data sharing, common definitions, and clear responsibility of data processing removes redundancy and improves quality control 4 Why Data Harmonization? IMPACT 3 FAO Database Data Processing Spatial disaggregation Balance Demand, and Trade with Production Data Cleaning Crop Production Livestock Production Commodity Demand and Trade FAO Data Collection Bulk Download

IMPACT integrates various models, which often use similar input data Better data sharing, common definitions, and clear responsibility of data processing removes redundancy and improves quality control 5 Why Data Harmonization? IMPACT 3 FAO Database Data Processing Spatial disaggregation Balance Demand, and Trade with Production Data Cleaning Crop Production Livestock Production Commodity Demand and Trade FAO Data Collection Bulk Download SPAM

IMPACT integrates various models, which often use similar input data Better data sharing, common definitions, and clear responsibility of data processing removes redundancy and improves quality control 6 Why Data Harmonization? IMPACT 3 FAO Database Data Processing Spatial disaggregation Balance Demand, and Trade with Production Data Cleaning Crop Production Livestock Production Commodity Demand and Trade FAO Data Collection Bulk Download SPAM IMPACT

Shared DataData ProcessingData Users FAO Climate Data Exogenous IMPACT Parameters Geospatial and Subnational Data SPAM IMPACT Models Hydrology Crop Models Land-Use Model 7 IMPACT Data-Model Environment

FAO – Crop Production – Livestock Production – Supply-Utilization – Food Balance Sheets – Water Stress Climate Data – GCMS – Generated Weather Geospatial and Subnational Data – Irrigation – Subnational Statistics – Crop suitability maps – Population Density Exogenous IMPACT Parameters – Yield, Area Growth – Elasticities – Prices (AMAD) – Population – GDP 8 Share Data

SPAM - Spatial Production Allocation Model Land-Use Model DSSAT Crop Models Biofuel Model Hydrology Model Water Basin Management Model Water Stress Model Food Model – Crops – Livestock – Sugar – Oilseeds 9 Models

Direct Users of FAOUsing Processed FAO SPAM FAO: Estimation FAO Climate Data Exogenous IMPACT Parameters Geospatial and Subnational Data IMPACT Food Water Stress Water Demand Shared Data 10 FAO Data

FAO Bulk Download for 3-year average around 2005 (04-06) Harmonized SPAM/IMPACT commodity, and geographic definitions Bayesian Work Plan – Iterate with new information 11 Processing FAO Data

Data Harmonization and Quality Too many cooks – Climate change is modeled in Water and Crop models for IMPACT – Need to use same initial and processed climate data – Ensure crop shocks and water shocks are compatible 12

Users of Climate Data Use Aggregated Processed Climate Data Crop Models Hydrology FAO Climate Data Exogenous IMPACT Parameters Geospatial and Subnational Data IMPACT Food Water Demand Water Stress Shared Data 13 Climate Change Consistency

Data Harmonization and Quality Building common geographical definitions Standardize mapping of data Share data (initial and processed) 14

Users of Geospatial and Subnational Data Use Aggregated Outputs from direct users SPAM Hydrology Crop Models Land-Use Model FAO Climate Data Exogenous IMPACT Parameters Geospatial and Subnational Data IMPACT Food Water Demand Water Stress Shared Data 15 Geospatial Data Users

Modularity – Data Partitioning IMPACT model is now data driven – General code built on specific data structures Each dataset has unique problems – Detox drivers vs. self-driving car – Data Processing is source-specific – Model Inputs are model-specific 16

Modularity – IMPACT Partitioning IMPACT model is now data driven – General code built on specific data structures Each dataset has unique problems – Detox drivers vs. self-driving car – Data Processing is source-specific – Model Inputs are model-specific 17

Benefits of Data Independence Cleaner Model Code – Facilitate model transfer and training Data Processing and Model design are independent tasks Model can run different data sources and aggregations without modification 18