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Exploring the World of Data in Merchandise Trade: Insights from RUG researchers

Workshop of the Circular Economy research group|Rudolf Agricola School for sustainable development
05 October 2023
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dr. Lukas Linsi presenting on merchandise trade data

In a recent meeting of the Circular Economy research group of the Rudolf Agricola School, Franco Ruzzenenti (FSE), Lukas Linsi (Arts) and Danyang Zang (FSE) shed light on the fascinating world of data banks, specifically in the context of merchandise trade and supply chains. The workshop started with the critical role of trade data, one of the oldest economic statistics, in our globalized world. 

Dr. Linsi introduced three fundamental categories of trade data:

Monadic Data: This category encompasses total imports and exports of a given entity, for instance the Netherlands’ total imports or exports in a year.

Dyadic Data: These are bilateral trade data, tracking the flow of goods between two specific parties or countries, for instance the annual trade between the Netherlands and Germany.

Product-level data: More fine-grained data that breaks down trade flows (at monadic or dyadic level) by industrial sector. For instance, the volume of Dutch imports of soybeans, shoes, or semiconductors.

Prominent sources of Merchandise Trade data

One of the prominent sources for product-level trade data discussed is UN Comtrade , a comprehensive database offering a wealth of information on global trade dynamics. Additionally, the presentation highlighted the significance of World Input-Output Database, a project by the Groningen Growth and Development Centre (FEB), which provides detailed data on global value chains at the country level. This resource, characterized by its transparency and reliability, is publicly available and free of charge.

However, the discussion took an interesting turn when considering the realities of global trade. It was emphasized that in practice, it's not countries that trade with each other, but companies. More recently, new data has become available that allows researchers to study trade at the level of firms. One example is the   Open Supply Hub, an intriguing platform, offering publicly accessible data, albeit with the caveat that not all companies contribute to it (based on voluntary disclosures). Despite this limitation, it provides a valuable overview, especially in garments and apparel industries. Open Supply Hub (OS Hub) is an accessible, collaborative, supply chain mapping platform, used and populated by stakeholders across sectors and supply chains.)

Dr. Linsi also introduced several other commercial data sources, including:

Factset Revere: An established database that provides detailed information on supplier linkages for more than twenty thousand multinational corporations from the USA, Europe and Asia. It also contains information on domestic suppliers. But, in contrast to customs-based trade data, it only indicates whether or not there is a supplier/client relationship between two entities. It does not specify what volume or type of good two parties exchange.

Wirescreen (Global Intelligence Platform): Relatively new and database predominantly focused on supply chain linkages of Chinese firms. Promising addition to existing database, but the data’s its reliability is yet to be fully tested.

Panjiva: Distinguished by its data derived from customs agencies, it provides detailed, administrative transaction information based on bill of lading data. It is a reliable data source that covers all transactions based on shipping data, both maritime and airborne, based on customs agencies data.

However, it was noted that Panjiva has some  limitations, including its coverage of only 17 countries, excluding the EU due to data protection concerns. It is also characterized by its high cost and the complexity of working with the extensive dataset that contains over 2 billion records.

Subsequently, representatives from Standard and Poor’s Panjiva team joined the workshop virtually to demonstrate the features of the online database. Thereafter, Danyang Zhang showed the participants how to access the Panjiva data feed and also illustrated some of the challenges in working with the data. To conclude, Franco Ruzzenenti presented different streams of research on trade and sustainability, pointing out avenues for future research that could leverage newly available data on firm-level trade.

Dr. Lukas Linsi is assistant professor in International Political Economy.

Dr. Franco Ruzzenenti is assistant professor in Energy and Complexity Nexus. Ms Danyang Zhang is a visiting PhD student at IREES.

Their insightful presentations left the research group with a deeper understanding of the complexities and opportunities within the world of merchandise trade and supply chain data, highlighting both the potential and challenges in leveraging these invaluable resources for their research endeavors.

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The Panjiva website
Last modified:05 October 2023 5.12 p.m.

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