2024 Multi-Scale Analysis of Sustainability SIMPLE-G Short Course

The security of food, energy, and water is interwoven with human, economic, and environmental sustainability. This recognition suggests that decision-making for sustainability could benefit from a nexus approach that integrates resources across sectors and scales. This short course is designed to provide participants comprehensive training in the equilibrium modeling tools for economic as well as interdisciplinary analysis of sustainability issues across local, national, and global scales. The training modules are designed to provide an immersive experience that spans geospatial data, model code, and software structures to allow participants to examine real policy problems and synthesize quantitative results while enhancing their own intuition.  Participants have four weeks to complete a self-guided online learning of the non-gridded SIMPLE model and prepare themselves for the transition to learning the gridded SIMPLE-G model. In the fifth week, participants are invited to come to Purdue University for a week-long in-person training that is composed of lectures,  hand-on labs, and small group projects. This course includes recently developed model variants and a book about the theory, model development and applications of SIMPLE-G framework.


Course Overview

  • Phase 1: Online - Each weekly module is estimated to take 5 hours and is comprised of book chapters (theory-focused), lab exercises and discussions (implementation-focused) to highlight major learning objectives.
    • Week 1 - Introduction to the SIMPLE framework: Assessing the impacts of population and income growth on global land use
    • Week 2 - Assessing the impact of climate change on global agriculture
    • Week 3 - Technological progress and food security
    • Week 4 - Preparing for in-person course
  • Phase 2: In-Person - 5 days at Purdue University
    • Day 1 
      • Recap of theory in SIMPLE
      • Introduce segmented and integrated market of the SIMPLE model
      • Introduce gridded model: theory and gridded indexing
      • Nested production function
      • Hands-on lab: Replicate and discuss SIMPLE application (Hertel & Baldos, 2016)
    • Day 2
      • Rainfed/irrigated split
      • Water supply and demand
      • Hands-on lab: Replicate and discuss SIMPLE-G-US application (Haqiqi et al. 2018)
      • SIMPLE-G Data
      • SIMPLE-G Parameters: emulators and elasticities
      • Hands-on lab: Replicate and discuss SIMPLE-G-US application (Liu et al. 2018)
    • Day 3
      • Mapping and analysis of SIMPLE-G results
      • Parameter sensitivity analysis and model uncertainty
      • Critique of existing applications
      • Small group breakout: develop extension ideas
      • Small group breakout: Experiment with ideas/change direction as needed
    • Day 4
      • Hands-on lab: Replicate and discuss SIMPLE-G-global application (Liu et al, 2017)
      • Small group breakout: modification, experiment and analysis
    • Day 5
      • Presentations


  • There is no cost to attend, but participants are responsible for their own travel and lodging expenses.

Travel Requirements

  • Vaccination Requirements - All travelers should be up-to-date on routine vaccinations while traveling to any destination. For requirements specific to the United States, please visit the Centers for Disease Control and Prevention website.
  • Invitation Letters - Invitation letters will be emailed to those selected to enroll in the course at the time of acceptance. Physical invitation letters will not be provided.
  • Visas - Those selected to enroll who require a visa to enter the United States should review the U.S. Department of State's website for details on applying for and obtaining the appropriate visa immediately after being notified of their acceptance. Those who plan to apply for a nonimmigrant visa as a temporary visitor, can review visa appointment wait times online.

Local Transportation and Lodging

Background Publications

Contact Information

Please direct questions on this course to:

Jing Liu (

Senior Research Economist / Science Coordinator