Using trade data to examine the new political economy of resources by Jaakko Kooroshy and Felix Preston Energy, Environment and Resources - Chatham House. Analysing and making data on global resource trade available has been a major part of the Chatham House Resources Futures project

1. Using trade data to examine the new political
economy of resources
Jaakko Kooroshy and Felix Preston
Energy, Environment and Resources
5 May 2013
‘Follow the Data’ hack day, New Zealand House, London

2. Analysing and making data on global resource trade available has
been a major part of the Chatham House Resources Futures project
• Published in December 2012, Resources
Futures is the result of two years of
research.
• Underpinned by a resource trade database
covering 1200 different types of natural
resources and resource products and 200
countries and territories, from 1998 and
2010.
• It analyses the latest global trends in the
production, trade and consumption of key
raw materials and intermediate products –
from crops, fuels, fisheries, forest products,
metals to fertilizers.
• It also explores how moves by governments
and other stakeholders are creating new
fault lines on top of existing weaknesses
and environmental uncertainties, and
proposes a series of critical interventions.

3. Our starting point on Resources Futures
• Prospect of resource scarcity, both real and perceived, is a major
item on the global policy agenda.
• Misperceptions and poor policy could fuel geopolitical tensions,
undermine global economic and environmental cooperation, foster local
and regional insecurity and disproportionately affect the livelihoods of
the world’s poorest.
• Managing these growing global resource stresses together with a
successful transition to sustainable and equitable resource use will test
the resilience of global and regional regimes and governance
mechanisms.
• The ongoing reconfiguration of the international political economy
of resources trade and use remain poorly understood. The complex
policy implications of these momentous shifts need to be systematically
evaluated and translated into concrete policy recommendations for
governments and businesses.

4. • Extractive industries are still a ‘black box’ in many respects due
to patchy data on trade, investment, production
costs, environmental impacts, supply chains, financial flows etc.
• Where data exists it is often only accessible to a small number
of commercial actors and experts: Requires significant financial
resources, specialized software, and expert knowledge to navigate
complex data sets.
• There are significant problems with data quality e.g. due to non-
transparent methodologies and inconsistency.
• Lack of intuitive, flexible tools for exploring and analysing the
publically available data. You have to be an expert, and even then it
is labour-intensive.
These challenges apply whether the focus is on transparency; conflict;
environmental impacts; etc.
Unfortunately, the limited empirical base for resources hampers any
analysis of extractive industries

5. Bilateral resource flows are key to understanding resource
interdependencies between countries. But the available data is not
set up for this purpose.
• The data has been publically available for 50 years. Since 1962 bilateral
trade data has been part of UN International Merchandise Trade
Statistics, which are publically accessible through the COMTRADE
database.
• But using it for comprehensive trend analysis is very challenging!
o There are entries by importers and exporters – which often do not
match
o Product codes are not organised according to commodities – and
there are >5000 of them.
• And data quality is highly inconsistent (they are reported by individual
customs offices)
• The database is also quite large (>5 million data points per year), which
until recently made it difficult to handle / build upon.
• The full dataset has restrictions on use

6. Faced with this, we decided to construct a new database
1. Addressed double reporting problem (use French BACI database instead of raw
COMTRADE data).
2. Reorganised ‘Harmonized System’ from a commodity perspective (selecting trade
codes relevant to raw materials and intermediate products, grouping according to
commodities and steps along the value chain)
3. Assessed data reliability and identifying outliers (we developed a ‘distance’
measure that compares individual value-weight ratios to global weight-value ratios)
4. Dealt with outliers (mix of manually adjusting, re-estimating and excluding outliers)

7. The Chatham House Resource Trade Database – how we use it
• Database is housed in Jmp (considering migration to mySQL)
• Jmp outputs can be easily manipulated in excel to give cuts
over time; by region and country; by commodity (at different
levels of detail) etc.
• Outputs from excel also analysed in arcgis and esankey for
spatial analysis/presentation.
t EX IM Sum(Value (USD1000))Sum(Weight (1000KG))Type of steel/iron Import CountryImporting RegionImporting Region 2Importer StatusExport CountryExporting RegionExporting Region 2Exporter StatusIntraregio
1998 4 218 82.3117 1082.385 Intermediate, iron or non alloy steelEcuador South AmericaSouth AmericaSouth AfghanistanSouth AsiaSouth AsiaSouth 0
1998 8 300 16.86366 120.593 Intermediate, iron or non alloy steelGreece Europe Europe North Albania Europe Europe South 1
1998 8 381 2.907 1.812 Intermediate, iron or non alloy steelItaly Europe Europe North Albania Europe Europe South 1
1998 8 699 26.8738 25.289 Intermediate, iron or non alloy steelIndia South AsiaSouth AsiaSouth Albania Europe Europe South 0
1998 12 58 569.875 596.565 Intermediate, iron or non alloy steelBelgium (incl. Luxembourg)Europe Europe North Algeria MENA MENA South 0
1998 12 251 246.774 91.5 Intermediate, iron or non alloy steelFrance Europe Europe North Algeria MENA MENA South 0
1998 12 381 15771.43 48267.67 Intermediate, iron or non alloy steelItaly Europe Europe North Algeria MENA MENA South 0
1998 12 392 18.6438 39.636 Intermediate, iron or non alloy steelJapan East Asia ex ChinaEast Asia North Algeria MENA MENA South 0
1998 12 504 4269.904 12110 Intermediate, iron or non alloy steelMorocco MENA MENA South Algeria MENA MENA South 1
1998 12 528 6396.43 19570.15 Intermediate, iron or non alloy steelNetherlandsEurope Europe North Algeria MENA MENA South 0
1998 12 686 124.674 197.82 Intermediate, iron or non alloy steelSenegal Subsaharan AfricaSubsaharan AfricaSouth Algeria MENA MENA South 0
1998 12 724 937.408 7359.84 Intermediate, iron or non alloy steelSpain Europe Europe North Algeria MENA MENA South 0
1998 12 788 7558.282 31809.75 Intermediate, iron or non alloy steelTunisia MENA MENA South Algeria MENA MENA South 1
1998 12 792 559.88 2638.88 Intermediate, iron or non alloy steelTurkey Europe Europe South Algeria MENA MENA South 0

8. Metal exporters are increasingly dependent
on China. 45% of metals traded goes to China
South-South trade in resources overtook South-
North trade in 2010
Global resource trade expanded 5-fold between
2000 and 2010
Imports and exports by region
Examples of insights from the database, with simple visualisations

9. No surprise that visualizations are key to conveying insights from complex data –
this is borne out by responses on social media

10. A major challenge is how to communicate complex resource narratives – we
worked with a design agency to built an innovative interactive that takes you
through the story of the report – with details.
Top Coal trade flows to/from China
2000
2010
www.resourcesfutures.org and
http://chinafocus.resourcesfutures.org (for the new China content)

11. Collaboration, collaboration, collaboration
• Collaborations so far
with the Financial
Times, The Times and
WWF
• Exploring other
avenues for
collaboration and
interaction with
stakeholders.
• For example, we are
in discussions to use
the database and
other content to
construct educational
tools at high school
and MBA levels.

12. What’s next?!
• Improving the interface e.g. enabling more complex
queries on the data without intermediate steps.
• Connecting with other data and platforms – dynamically
linking the database with other data e.g. on resource
production and consumption; macro-economic; spatial.
• Making the database publicly accessible - depending on
copyright issues and resources, we would like to take it
online.
• Participating in discussions on improving data quality
and access etc.
This adds up to a significant challenge!