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Introducing IMPACT 3: Modeling Philosophy and Environment

Sherman RobinsonDaniel Mason-D’CrozShahnila Islam

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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identified in Phase 1:– Insufficient geographic disaggregation– Need to model more CG-mandate crops– 2000 base year outdated– Model needed to be recoded to allow for better integration with new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)

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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 tomeet user needs

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• 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

Why Data Harmonization?

IMPACT 3 FAO Database

Data ProcessingSpatial disaggregation Balance Demand, and Trade

with Production

Data CleaningCrop Production Livestock

ProductionCommodity

Demand and Trade

FAO Data CollectionBulk Download

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• 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

Why Data Harmonization?

IMPACT 3 FAO Database

Data ProcessingSpatial disaggregation Balance Demand, and Trade

with Production

Data CleaningCrop Production Livestock

ProductionCommodity

Demand and Trade

FAO Data CollectionBulk Download

SPAM

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• 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

Why Data Harmonization?

IMPACT 3 FAO Database

Data ProcessingSpatial disaggregation Balance Demand, and Trade

with Production

Data CleaningCrop Production Livestock

ProductionCommodity

Demand and Trade

FAO Data CollectionBulk Download

SPAMIMPACT

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Shared Data Data Processing Data Users

FAOClimate

Data

Exogenous IMPACT

Parameters

Geospatial and

Subnational Data

SPAMIMPACT Models

HydrologyCrop

Models

Land-UseModel

IMPACT Data-Model Environment

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• 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

Share Data

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• 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

Models

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Direct Users of FAO Using Processed FAO

SPAM FAO: Estimation

FAO

Climate Data

Exogenous IMPACT

Parameters

Geospatial and

Subnational Data

IMPACT• Food• Water Stress• Water Demand

Shared Data

FAO Data

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• 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

Processing FAO DataSource Data (FAO, SPAM)

Feedback to data source

Priors on values and estimation errors of

production, demand, and trade

Estimation by Cross-Entropy Method

Check results against priors and identify

potential data problems

New information to correct identified

problems

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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

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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

Climate Change Consistency

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Data Harmonization and Quality

• Building common geographical definitions• Standardize mapping of data• Share data (initial and processed)

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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

Geospatial Data Users

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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

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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

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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