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About SIMPLE

What is SIMPLE?

SIMPLE is an acronym for a global economic model of food and the environment. It stands for the Simplified International Model of agricultural Prices, Land use, and the Environment. Its gridded version, SIMPLE-G, takes things a step further, offering a detailed, spatially resolved view of land, water, labor, and agricultural production. SIMPLE models comprise a family of quantitative economic models based on partial equilibrium and international trade theories that simulate the production, consumption, trade, land use, and prices of major agricultural commodities. They account for the effects of agricultural policies, global population and income changes, climate change, and land use change on environmental sustainability and food security metrics. These models are comparative static and are used for future (one-shot) projections as well as in ‘what-if’ economic impact analysis. This framework is focused on describing, predicting, and understanding interdisciplinary challenges in sustainability and food security employing economics as a unifying framework and a bridge between disciplines. A set of open-access, open-source tools have been developed based on this framework.

History

The SIMPLE framework was developed in the 2010s in response to the need for a more transparent, comprehensive and user-friendly framework for analyzing environmental sustainability and food security in a multidisciplinary setting. Changes in agricultural land use have important implications for environmental services. In complex models, multiple systems interact and many details are covered. Thus, the impacts of policies and the effects of changes are not easy to trace. In contrast, SIMPLE provided a flexible, simplified framework to quantify the primary economic and environmental impacts of changes and policies. The interdisciplinarity of SIMPLE has developed concurrently with its use in multidisciplinary courses and research projects. This has been facilitated by the growth in computational power, open science, and the geospatial data revolution.

SIMPLE Model

Overview of SIMPLE framework

The standard version of any SIMPLE model has three major components: consumption, production, and trade. The SIMPLE framework consists of a partial equilibrium model that characterizes demand and supply for various food commodities and associated production factors. The market clearing conditions ensure price adjustments until each market reaches an equilibrium price and quantity. The major elements of this framework are the regional food consumption module, the regional production module, the global trade module, and the nutrition module.

Graphical representation of SIMPLE-G model

graphical representation of SIMPLE-G model

SIMPLE-G Figure. This diagram shows the critical components of the SIMPLE-G model. Here, changes in income and population will cause changes in demand for food and dietary shifts, while changes in hydroclimatic conditions or investment patterns affect the production and supply of food.

SIMPLE representation of extensive and intensive margins in land use

The SIMPLE framework links the change in prices to three exogenous factors and three partial price elasticities. The long-run shocks (in the numerator) include aggregate demand, δΔ LS (population, income, biofuels, other), an exogenous land supply shift, ΔL (urbanization, conservation, etc.), and exogenous yield change ΔY. The key elasticities are the price elasticity of demand, ηD, the land supply (the area or extensification response) elasticity with respect to the agricultural price, ηE (essentially the land price elasticity adjusted for land's cost share), and the share adjusted substitution (yield or intensification response) elasticity of land with respect to the other inputs, ηI. These economic responses operate as buffers to moderate the translation of demand growth into land use change

elasticities equation, q_L^*=[(Δ_A^D+Δ_L^S-Δ_L^D)/(1+η_A^(S,I)/η_A^(S,E)+η_A^D/η_A^(S,E))]-Δ_L^S

When these elasticities are zero, agricultural land expansion must move in lockstep with the growth in demand, net of any yield-increasing technological improvements. However, when the intensive margin of supply response, and the demand response, are non-zero, land use need not expand at the same rate as demand, net of yield improvements.

Theoretical paper:

Hertel, T. W. (2011). The Global Supply and Demand for Agricultural Land in 2050: A Perfect Storm in the Making? American Journal of Agricultural Economics, 93(2), 259–275.

Versions

In addressing specific challenges in sustainability and food security and other aspects of sustainable development goals, more components are added to the basic model as necessary. Instead of one all-encompassing model, there are many different SIMPLE models, each customized to address specific questions. The SIMPLE models employ computational tools to decompose the contribution of each change to the final outcomes when multiple global change drivers are in action.

Here is the list of SIMPLE-G models and applications introduced in the textbooks below. The proper citation for each is listed on the documentation page for each version.

Model/download Video Baseline Year Gridded Inputs Learn more
SIMPLE N/A 2010 No. Land, non-land N/A
SIMPLE-G1 N/A 2010 US (5 arcmin) Land, non-land N/A
SIMPLE-G-US-Allcrops N/A 2010 US (5 arcmin) Land, fertilizer, groundwater, surface water, irrigation N/A
SIMPLE-G-US-Commuting Zone (CZ) N/A 2010 US (5 arcmin) Labor, land, fertilizer, groundwater, surface water, irrigation N/A
SIMPLE-G-US-CornSoy N/A 2010 US (5 arcmin) Land, Water, Fertilizer N/A
SIMPLE-G-Global-Water N/A 2017 Global (5 arcmin) Land, fertilizer, groundwater, surface water, irrigation N/A
SIMPLE-G-Brazil N/A Brazil (5 arcmin) N/A
SIMPLE-G-Global-Climate N/A 2017 Global (5 arcmin) Land, fertilizer, groundwater, surface water, irrigation N/A

SIMPLE Book: Global change and the challenges of sustainably feeding a growing planet

This book introduces the regional version of SIMPLE. It offers a comprehensive analysis of the fundamental drivers of long-term agricultural land use change at the global scale, with particular emphasis on their implications for environmental sustainability and food security. Each chapter focuses on a distinct driver, including established factors like population growth and income, as well as emerging trends like biofuel production, climate change, and demand for environmental services. The book further explores specialized topics such as food security outcomes, future agricultural price projections, greenhouse gas emissions, and the role of globalization and market integration. Drawing on the latest research, the book meticulously summarizes key findings and presents them within a unifying economic framework, providing valuable insights for policymakers, researchers, and anyone interested in the future of agriculture.

Table of contents
  1. Overview of Global Land Use, Food Security and the Environment
  2. Population and Income as Drivers of Global Change
  3. Productivity Growth and Yields in the Global Crops Sector
  4. Economic Responses to Scarcity
  5. Water, Food and Environmental Security
  6. Climate Change Impacts in Agriculture
  7. Land-Based Environmental Services
  8. Biofuels as a Driver of Long Run Land Use Change
  9. Livestock and Processed Foods
  10. Food Security and Nutrition
  11. Global Change and the Food System in 2050
How to cite:

Hertel, Thomas W. and Uris Lantz C. Baldos. Global change and the challenges of sustainably feeding a growing planet. Springer International Publishing Switzerland, 2016. DOI: 10.1007/978-3-319-22662-0
Detailed Bibliographic Information

SIMPLE-G Book: SIMPLE-G: A Gridded Economic Approach to Analysis of Sustainability of the Earth’s Land and Water Resources

The anticipated publication date for this book is August 2024.

This book introduces gridded version of SIMPLE with a transparent, grid-level perspective, dissecting the interconnected systems of land use, production, and trade across the globe. Through compelling applications, SIMPLE-G book illustrates how to analyze policy options, assess future scenarios, and chart a path towards a resilient and sustainable agricultural future. This book provides a framework for evaluating the intricate links between human needs, environmental demands, and sustainable environment for all living beings.

* The links to the model codes and instructions will be provided upon publication of the SIMPLE-G book, in August 2024 *

Table of contents Preface PART I: INTRODUCTION
  1. Introduction
PART II: THEORY
  1. Economic theory
  2. Gridded Analysis
PART III: MODEL
  1. Model Specification: Regional
  2. Model Specification: Gridded
  3. Data
  4. Behavioral Parameters
  5. Baseline and Computation
  6. Model Validation
PART IV: APPLICATIONS
  1. R&D cost of Climate Mitigation in Agriculture
  2. Gridded US implications of Productivity Growth
  3. Local groundwater sustainability policies and global spillovers
  4. The role of labor markets in distribution impact of sustainability policies
  5. The "Wicked" Challenge of Nutrient Pollution from Corn Production in the U.S
  6. The Role of Transportation Infrastructure Expansion Brazilian Economy
  7. Global Groundwater Sustainability and Virtual Water Trade
  8. Interplay between the Pandemic and Environmental Stressors
PART V: FUTURE DIRECTIONS
  1. Future directions
How to cite:

Haqiq, Iman and Thomas W. Hertel (eds.) SIMPLE-G: A Gridded Economic Approach to Analysis of Sustainability of the Earth’s Land and Water Resources, Springer International Publishing Switzerland, 2024.

Education

Emergence in academic curriculum

Emergence in academic curriculum Thomas Hertel and Uris Baldos are credited with developing the first version of SIMPLE for use in the classroom. Through a series of lab assignments, students develop the skills to perform economic analysis and to interpret results and provide analysis of a variety of challenges facing the global food and environment systems. Major topics of particular relevance covered are the tradeoffs between food security and environmental sustainability, and the role of international trade in mediating the impact of particular sustainability solutions.

For instructors

How to connect the fundamental theoretical models with the more complex real-world research questions has been identified as a major obstacle in the education of economics. The structural models taught from junior or senior undergraduate to the first or second year PhD courses are often highly simplified for educational purposes. When students begin to apply those fundamental models to analyze real-world problems, it does not take long for them to find there remains a frustrating gap between what they have learnt from classes and what is needed in research.

To help students to overcome this gap, we have developed a series of materials with SIMPLE that address how to connect analytical solutions from structural models they have already learnt to the more complex computable models that can be solved with programs. With simple tailoring, those materials can be used to offer courses to students in the economic major or majors relevant with sustainability studies, for undergraduate, Master or PhD level. We believe including SIMPLE as a complement of existing economic courses would strengthen the connection between the theoretical and applied aspects of training, and help students to be better prepared for conducting studies for advanced education or future jobs.

For students

As a student, have you ever considered how your knowledge and skills can contribute to a better understanding of the world around you? Have you ever wondered how global events impact the human-nature system? Have you ever considered how human responses to environmental changes can either worsen or mitigate their impact? If you have, then we have some exciting news for you! We recommend using SIMPLE, a simplified economic model that helps you analyze complex challenges related to agriculture and the environment. With no more than an undergraduate-level economic education, you can master the fundamental theory of SIMPLE. Additionally, we have created two textbooks that provide comprehensive guidance, downloadable models, and replicable projects. These textbooks are a self-study guide that will help you add an easy-to-use yet information-rich economic model to your skillset. By using SIMPLE, you can better understand the world and gain the knowledge and tools to make a difference in the future.

SIMPLE Course

The SIMPLE course is specifically designed for providing interdisciplinary analysis of the issues related to food security and environmental sustainability. In this course, the participants will learn about the core economic and environmental dynamics that power the global food system, using the SIMPLE model. Through engaging modules, the participants will explore the intricate connections between agricultural production, environmental resources, and global markets. They will also learn to identify the tradeoffs that are inherent in pursuing ambitious sustainability goals, and master the necessary tools to craft solutions that prioritize both food security and planetary health. The SIMPLE course will equip the participants with the knowledge and skills to navigate the intricate link between feeding the world and protecting our planet.

SIMPLE-G short Course

The SIMPLE-G short course is designed for graduate students and advanced researchers with an interest in sustainability and food security. The short course provides a comprehensive and two-part learning experience. Participants will start by exploring the theoretical foundations of the model and sharpening analytical abilities through assignments. Then, it offers an immersive on-site program, which includes interactive lectures, hands-on workshops, and the chance to develop research projects using various versions of SIMPLE-G. Participants with different backgrounds interact and generate insightful discussions to bring new dimension to the spatial economic analysis of sustainability. After completing the course, participants will be well-equipped to tackle critical food security and sustainability challenges with more confidence.

Research

Adoption in research in sustainability

Over time, SIMPLE has evolved from a model for use in the classroom into a vehicle for undertaking research into a wide range of sustainability challenges facing the world. These SIMPLE models have been adopted by both economists and non-economists for interdisciplinary research. By keeping the core economic model simple, the researchers have focused on the most important elements of the economic, environmental, and agricultural systems. This framework is also the foundation of new emerging models developed for understanding of sustainability and food security in a changing world. SIMPLE applications have contributed to the sustainability literature through studying the forces that affect the decisions about water use, land use, food production, food trade, food consumption, and diets. Recently, SIMPLE has been extended to allow for economic analysis at the level of individual grid cells. The ensuing versions of the SIMPLE family of models is dubbed "SIMPLE-G".

For researchers

Researching the challenges of sustainability requires the convergence of multi-discipline studies. However, to provide a platform for researchers from different fields to exchange ideas, data and findings itself is one of the major challenges we face today, in particular for researchers from both natural science and social science aspects.

The SIMPLE framework has shown the potential to contribute to the convergence of research from natural and social sciences. Researchers from environment, geography, ecology, and climate science fields would find their data and results can be easily connected with the database and applications of SIMPLE, in order to evaluate the socio-economic impacts from natural shocks and further adds to their findings and implications. And the simplified structure of SIMPLE makes it very easy to understand and use for researchers without advanced training in economics. On the other hand, researchers from social science (in particular economists) would find SIMPLE as a natural extension of equilibrium-based structural models, but already equipped with the rich-information database and grid-resolving feature that allow them to easily conduct simulations to test economic theories, track impacts at local level, and communicate with colleagues from multi-discipline fields or more general stakeholders.

List of related publications

Zuidema, S., Liu, J., Chepeliev, M. G., Johnson, D. R., Baldos, U. L. C., Frolking, S., Kucharik, C. J., Wollheim, W. M., & Hertel, T. W. (2023). US climate policy yields water quality cobenefits in the Mississippi Basin and Gulf of Mexico. Proceedings of the National Academy of Sciences, 120(43), e2302087120. https://doi.org/10.1073/pnas.2302087120

Kabir, K., Baldos, U. L. C., & Hertel, T. W. (2023). The new Malthusian challenge in the Sahel: Prospects for improving food security in Niger. Food Security, 15(2), 455–476. https://doi.org/10.1007/s12571-022-01319-3

Liu, J., Bowling, L., Kucharik, C., Jame, S., Baldos, U., Jarvis, L., Ramankutty, N., & Hertel, T. (2023). Tackling policy leakage and targeting hotspots could be key to addressing the ‘Wicked’challenge of nutrient pollution from corn production in the US. Environmental Research Letters, 18(10), https://doi.org/10.1088/1748-9326/acf727.

Johnson, D. R., Geldner, N. B., Liu, J., Baldos, U. L., & Hertel, T. (2023). Reducing US biofuels requirements mitigates short-term impacts of global population and income growth on agricultural environmental outcomes. Energy Policy, 175, https://doi.org/10.1016/j.enpol.2023.113497.

Haqiqi, I., Grogan, D. S., Bahalou Horeh, M., Liu, J., Baldos, U. L., Lammers, R., & Hertel, T. W. (2023). Local, regional, and global adaptations to a compound pandemic-weather stress event. Environmental Research Letters, 18(3), https://doi.org/10.1088/1748-9326/acbbe3.

Ray, S., Haqiqi, I., Hill, A. E., Taylor, J. E., & Hertel, T. W. (2023). Labor markets: A critical link between global-local shocks and their impact on agriculture. Environmental Research Letters, 18(3), https://doi.org/10.1088/1748-9326/acb1c9.

Baldos, U. L. C. (2023). Impacts of US Public R&D Investments on Agricultural Productivity and GHG Emissions. Journal of Agricultural and Applied Economics, 55(3), 536–550. https://doi.org/10.1017/aae.2023.29

Haqiqi, I., Bowling, L., Jame, S., Baldos, U., Liu, J., & Hertel, T. (2023). Global drivers of local water stresses and global responses to local water policies in the United States. Environmental Research Letters, 18(6), https://doi.org/10.1088/1748-9326/acd269.

Haqiqi, I., Perry, C. J., & Hertel, T. W. (2022). When the virtual water runs out: Local and global responses to addressing unsustainable groundwater consumption. Water International, 47(7), 1060–1084. https://doi.org/10.1080/02508060.2023.2131272

Fuglie, K., Ray, S., Baldos, U. L. C., & Hertel, T. W. (2022). The R&D cost of climate mitigation in agriculture. Applied Economic Perspectives and Policy, 44(4), 1955–1974. https://doi.org/10.1002/aepp.13245

Liu, J., Bowling, L., Kucharik, C., Jame, S., Baldos, U., Jarvis, L., Ramankutty, N., & Hertel, T. (2022). Multi-scale Analysis of Nitrogen Loss Mitigation in the US Corn Belt (arXiv:2206.07596). arXiv. http://arxiv.org/abs/2206.07596

Woo, J., Zhao, L., Grogan, D. S., Haqiqi, I., Lammers, R., & Song, C. X. (2022). C3F: Collaborative Container-based Model Coupling Framework. Practice and Experience in Advanced Research Computing, 1–8. https://doi.org/10.1145/3491418.3530298

Hertel, T. W., Baldos, U. L., & Fuglie, K. O. (2020). Trade in technology: A potential solution to the food security challenges of the 21st century. European Economic Review, 127, 103479. https://doi.org/10.1016/j.euroecorev.2020.103479

Baldos, U. L. C., Fuglie, K. O., & Hertel, T. W. (2020). The research cost of adapting agriculture to climate change: A global analysis to 2050. Agricultural Economics, 51(2), 207–220. https://doi.org/10.1111/agec.12550

Baldos, U. L. C., Haqiqi, I., Hertel, T. W., Horridge, M., & Liu, J. (2020). SIMPLE-G: A multiscale framework for integration of economic and biophysical determinants of sustainability. Environmental Modelling & Software, 133, 104805. https://doi.org/10.1016/j.envsoft.2020.104805

Zhao, L., Song, C. X., Biehl, L., Merwade, V., Huber, M., Liu, J., Baldos, U., & Shunko, I. (2020). Building a Gateway Infrastructure for Interactive Cyber Training and Workforce Development *. Practice and Experience in Advanced Research Computing, 436–443. https://doi.org/10.1145/3311790.3396639

Hertel, T. W., Baldos, U. L. C., & Van Der Mensbrugghe, D. (2016). Predicting Long-Term Food Demand, Cropland Use, and Prices. Annual Review of Resource Economics, 8(1), 417–441. https://doi.org/10.1146/annurev-resource-100815-095333

Baldos, U. L. C., & Hertel, T. W. (2016). Debunking the ‘new normal’: Why world food prices are expected to resume their long run downward trend. Global Food Security, 8, 27–38. https://doi.org/10.1016/j.gfs.2016.03.002

Hertel, T. W., & Baldos, U. L. C. (2016). Attaining food and environmental security in an era of globalization. Global Environmental Change, 41, 195–205. https://doi.org/10.1016/j.gloenvcha.2016.10.006

Baldos, U. L. C., & Hertel, T. W. (2015). The role of international trade in managing food security risks from climate change. Food Security, 7(2), 275–290. https://doi.org/10.1007/s12571-015-0435-z

Hertel, T. W., Ramankutty, N., & Baldos, U. L. C. (2014). Global market integration increases likelihood that a future African Green Revolution could increase crop land use and CO 2 emissions. Proceedings of the National Academy of Sciences, 111(38), 13799–13804. https://doi.org/10.1073/pnas.1403543111

Baldos, U. L. C., & Hertel, T. W. (2014). Global food security in 2050: The role of agricultural productivity and climate change. Australian Journal of Agricultural and Resource Economics, 58(4), 554–570. https://doi.org/10.1111/1467-8489.12048

Baldos, U. L. C., & Hertel, T. W. (2013). Looking back to move forward on model validation: Insights from a global model of agricultural land use. Environmental Research Letters, 8(3), 034024. https://doi.org/10.1088/1748-9326/8/3/034024

Lobell, D. B., Baldos, U. L. C., & Hertel, T. W. (2013). Climate adaptation as mitigation: The case of agricultural investments. Environmental Research Letters, 8(1), 015012. https://doi.org/10.1088/1748-9326/8/1/015012

Resources: Models, Data Bases, and Tools

Here are some resources for more information about SIMPLE and SIMPLE-G models:

GLASSNET
GLASSNET stands for Global to Local Analysis of Systems Sustainability. This is a network of networks to link global communities of researchers working towards achieving Sustainable Development Goals related to water and land.
https://mygeohub.org/groups/glassnet

SIMPLE-G in-cloud:
You can access SIMPLE-G on MyGeohub, a web platform that offers geospatial data, modeling, and analysis tools. It has multiple versions of SIMPLE-G, which are user-friendly and provide interactive maps, charts, and tables to visualize the model outputs.
https://mygeohub.org/tools/simplegus

SIMPLE data and model
You can find the SIMPLE regional model and data here. This includes scripts to create different regional aggregation of the SIMPLE model. Baldos, U. L. (2023). SIMPLE Database and Model for Base Year 2017. MyGeoHUB.

FAQs: Frequently Asked Questions

Q: What is SIMPLE?
A: SIMPLE stands for "Simplified International Model of Prices Land use and the Environment." It's a flexible modeling framework designed to analyze the economic and environmental impacts of changes in agricultural land use, trade, and policies.

Q: What is SIMPLE-G?
A: SIMPLE-G builds on SIMPLE by adding a geospatial dimension. It analyzes land use, production, and consumption at the grid-cell level, providing more detailed insights into the spatial distribution of impacts and drivers.

Q: What are the advantages of using SIMPLE and SIMPLE-G?
A: They are validated, easy to understand, transparent, and computationally efficient compared to complex models. They are also flexible and can be adapted to address specific questions about sustainability and food security.

Q: What are some areas where SIMPLE and SIMPLE-G can be applied?
A: They can be used to study the impacts of climate change, biofuel production, trade policies, and other factors on land use, agricultural production, food security, and greenhouse gas emissions.

Q: What are the key components of the SIMPLE model?
A: The standard version has three core components: consumption, production, and trade. Additional components can be added to address specific issues.

Q: How is SIMPLE used to analyze the impacts of policy changes?
A: Users can introduce new shocks and modify the model parameters to simulate different policy scenarios and see how they would affect land use, production, and prices. They can also link new biophysical dimensions as inputs to production or as influenced by agriculture.

Q: What are some limitations of the SIMPLE model?
A: It is a simplified partial equilibrium model and may not capture all the complexities of real-world agricultural systems.

Q: What data does SIMPLE-G use?
A: It uses a combination of gridded and regional global datasets on land use, climate, crop yields, and economic parameters.

Q: What kind of spatial analysis can be done with SIMPLE-G?
Users can analyze the spatial distribution of land use, crop production, and environmental impacts, identifying areas with high vulnerability or potential for improvement.

Q: What are the assumptions of the SIMPLE-G model?
As a partial equilibrium model, main assumptions include imperfect substitution between domestic and imported goods, zero profit for agricultural production, market clearing for food commodities and agricultural inputs, constant elasticity of substitution in production and constant elasticity of transformation in land allocation.

Q: What are some useful computational techniques, tools, and lessons learned in the parameterization of the SIMPLE-G model?
SIMPLE and SIMPLE-G models are often written in GEMPACK. Geospatial programs and packages (such as R and Python) are required to process input files and plot the results. To improve replicability and visualization, there are tools for in-cloud computation without the need to install GEMPACK or geospatial programs.

Q: What are some challenges of using the geospatial version of SIMPLE-G?
Data availability and quality can be challenges, and ensuring accurate representation of local conditions requires careful parameterization.


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