In the event of a trade shock, how can data requirements for taking rapid decisions be met using real time indicators (RTIs) and non-traditional sources of data? How can data science evaluate and improve the quality and reliability of RTIs?
Background
COVID-19 has posed a major economic shock, disrupting trade flows, stretching supply chains, and challenging international organisations that uphold systems of global governance as well as broader perceptions of international openness. Beyond immediate policy responses, evidence should support long-term recovery and economic security within the global rules-based system.
Next steps
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Source
This question was published as part of the set of ARIs in this document:
Topics
Related UKRI funded projects
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MultiLateral Thinking - Coriolis Technologies
**Vision** - COVID-19 will change the nature of trade and impact the UK's economic performance, trade strategy/policy and global position. WTO forecasts global trade will fall 30% due to COVID-19\. COVID-19 places unique...
Funded by: Innovate UK
Why might this be relevant?
The project specifically addresses the use of real-time indicators and non-traditional data sources to support rapid decision-making in the event of a trade shock.
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Data and Analytics for Real-time Trade modelling (DART)
"**Need** - UK government wishes to support SMEs to increase trade. To assess trade and supply chain impacts of policy changes and political/economic events like Brexit, politicians, trade negotiators and businesses...
Funded by: Innovate UK
Why might this be relevant?
The project focuses on providing accurate, near real-time, granular trade data for goods/services to support decision-making in the event of a trade shock.
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Machine Learning in International Trade Research - Evaluating the Impact of Trade Agreements
International trade is of vital importance for modern economies, and governments around the world try to shape their countries' exports and imports through numerous interventions. Given the problems facing trade negotiat...
Funded by: ESRC
Why might this be relevant?
The project proposes to use machine learning to evaluate the effects of preferential trade agreements (PTAs) on trade flows, which partially addresses the question of evaluating and improving the quality and reliability of real-time indicators (RTIs).