Historical High-Quality Company-Level Data for Europe (EURHISFIRM)

EURHISFIRM aims at designing a world-class research infrastructure to collect, merge, extract, collate, align and share detailed historical high-quality firm level data for Europe. To achieve this goal, it develops innovative tools and sparks the “Big data” revolution in historical social sciences.

The EURHISFIRM project meets the need for such a benchmark research infrastructure in Europe. It will operate the most comprehensive long-run economic and financial database in the world. It will handle data on European companies such as accounting, funding and investment, stock exchange data, governance rules, directors, patents, location of headquarters. The creation of a vibrant European community will support the development of revolutionary RI technology, which in turn will enable a scientifically reproducible, technically sound and socio-legally robust evidence-base for the stakeholders. Not only policy makers and scholars will benefit from, but notably private companies: on the one hand, companies are major data users, the global spend for market data, an industry where US holds a quasi-monopoly, amounting to nearly 30 billion of dollars in 2015 (Burton and Taylor, 2016); on the other hand, the disruptive technologies developed within the RI will push further the technological frontier and bring major spin-offs to the European IT industry.

This project stems from the experience of the research group Eurhistock that brings together specialists in economic and financial history on a yearly basis since 2009. This group acknowledged both the incompleteness of the existing datasets, the fragmentation of the initiatives, and the heterogeneity of the data collection practices in Europe. This observation led some countries like France and Belgium to put in place coordinated initiatives to build long-run structured data with digital techniques at the technological frontier. Other countries in the consortium have started to collect data or are reflecting on the comparative issues of their datasets.

Project website

Zugehörige Working Papers

Nr.Forscher/innenTitelJahrBereichKeywords
300Dennis Gram, Pantelis Karapanagiotis, Jan Krzyzanowski, Marius Liebald, Uwe WalzAn Extensible Model for Historical Financial Data with an Application to German Company and Stock Market Data2021 Data Center
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