Abstract:
This seminar begins with an overview of the Global Trade Analysis Project (GTAP). GTAP data and models underpin a large array of analyses including trade and industrial policy, energy transitions, climate change impacts and adaptation, and other environmental change such as biodiversity loss. Three example applications are then presented examining (i) regional approaches to confronting climate change focused on the Tigris-Euphrates river basin; (ii) agricultural technology and biodiversity loss, as well as terrestrial carbon emissions, in the tropics; and (iii) implications of tariffs by China on US soybeans for the spatial distribution of agricultural production in Brazil. These applications generate actionable evidence and illustrate a range of methodological approaches.
Bio:
Channing Arndt directs the Global Trade Analysis Project, which is housed at Purdue University. GTAP supports a network of more than 30,000 individuals engaged in quantitative analysis of 21st century challenges. A consortium of 31 leading national, international, and private institutions provides baseline financial support and strategic advice. GTAP aims to advance high-quality quantitative analysis of global issues and facilitate deliberate decision-making. To this end, GTAP (i) lowers analytical barriers through the provision of data, models/tools, and training; (ii) conducts research on pressing issues with global ramifications; and (iii) serves as a platform for discussion and dissemination of novel approaches and ideas.
Prior to directing GTAP, he directed the Transformation Strategies Department at the International Food Policy Research Institute overseeing a research budget of about $65 million and about 350 staff. Arndt has more than 30 years of experience in analytics for economic policy, with emphasis on large-scale global trends and their implications for country level-strategy and policy. He frequently works directly with central decision-making organs within governments, including seven years of resident experience in Africa. He has published more than 95 articles in leading academic journals. His books include Growth and Poverty in Sub-Saharan Africa, Measuring Poverty and Wellbeing in Developing Countries, and The Political Economy of Clean Energy Transitions, all published by Oxford University Press. His program of research has focused on growth, trade, economic development, poverty alleviation, market integration, nutrition, gender and discrimination, health-related shocks such as Covid-19 and HIV/AIDS, technological change, aid effectiveness, energy, bioenergy, climate variability, and climate change.
Summary:
GTAP: Global Trade Analysis Project
Goal: improve quality of quantitative analysis for global trade issues
Collaborative community
Common language for economic analysis of global policy issues
Capabilities
Data: www.gtap.org/databases
Models: www.gtap.org/models
Training: www.gtap.org/gtap-u
Database
Assembly of data from many international sources
65 sectors
Time series: 2004, 2007, 2011, 2014, 2017, 2019
Satellite data
Core: energy, electricity, emissions, agro-ecology, decomposition by end-users
New: SPP projections, tariffs, biofuels, circular economy, critical minerals, pollution, etc.
Example Applications:
OECD environmental outlook report, including integrated macroeconomic modeling
Trump Tariffs
Carbon mitigation and trade (fuels, low carbon technologies)
Regional approaches to climate change
Cooperation in Tigris-Euphrates basin
Goal: quantify changes in water scarcity by 2050 and identify economic outcomes
Model:
General Circulation Models (GCM) of the global climate
Hydrological models of water balance
Drive computable macroeconomic general equilibrium model GTAP-BIO-W
Scenarios: cross product of
SSP: RCP4.5, RCP8.5
Climate model variables
Two levels of water elasticity on capital stock
Predicted:
Significant increase in water scarcity
Major impact on national GDP
Regional collaboration significantly improves regional GDP in all scenarios
Major negative impacts of climate change are avoided via cooperation
Many other examples: EU, ASEAN cooperation
Using structural models to understand the past
Productivity growth is a key driver of agriculture
Much driven by new tech developments
Has driven increase in food production
Increased crop yield has also put stress on the environment
Analyzed land use and impact on emissions and biodiversity (some regions account for majority of global bio-diversity)
SIMPLE-G: gridded model of ag economics + environment
Uses gridded ag productivity data: 1961-2015
Runs model over historical time period back to 1961 to calibrate model
Re-run on same time period with lower ag productivity to compare impact on land use and environment
Impact: Increased crop productivity
Reduces land use of agriculture
Emissions from ag
Reduced impact on biodiversity
Back-casting useful in general: Covid-19 impacts, historical trade wars, etc.
Global to local to global
US and Brazil are major exporters of soy to China
How do Brazilian policies affecting structure of trade
GTAP V7
SIMPLE-G
Gridded crop production (SPAM2010)
Merged to combine global trade/production and local Brazilian gridded agricultural output
Simulate China’s 25% tariff of US soybeans
Predicted
Expansion of land use from pasture to cropland
Expansion of soy and oilseed expansion
Reduction in sugar (pushed out by soybeans)
Global policy has local implications, drives local responses, which affect global patterns
Can significantly affect the environment
Institutions are key for ensuring maximal gain for people
Future directions:
Global: GTAO
Gridded: SIMPLE-G
Ground-level: Machine Learning