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Sharing data on the activities of multinational enterprise groups: Innovations to redesign statistical practices and processes
Author(s) -
Timo Koskimäki,
Rami Peltola
Publication year - 2020
Publication title -
statistical journal of the iaos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.286
H-Index - 16
eISSN - 1875-9254
pISSN - 1874-7655
DOI - 10.3233/sji-200646
Subject(s) - multinational corporation , economic statistics , exploit , dimension (graph theory) , quality (philosophy) , work (physics) , computer science , business , marketing , statistics , engineering , finance , mathematics , computer security , mechanical engineering , philosophy , epistemology , pure mathematics
The professional discussion on “The future of economic statistics” has a practical driver: Economic statistics, produced by national statistical offices, face severe difficulties in describing the national and global economic development in a relevant and coherent manner. This is not only our perception as statisticians – there is a growing criticism towards traditional economic statistics among researchers, policymakers and other users. In this article, we reflect on the factors that have caused the current situation and propose solutions to improving the situation by data sharing. One aspect of the solution relates to the role of national statistical offices. Instead of being solely national institutions, dealing with national data only, they should exploit the possibilities of using statistical data, collected by statistical authorities of other countries, to produce better quality economic statistics. The other aspect of the solution is the sharing of innovative practices to understand and correctly record the activities of multinational enterprise groups (MNEs). The proposals we make in this article are not restricted to MNEs but are applicable to any type of economic activity with a cross-border dimension. The observations we make here are based on the work done when preparing the UNECE Guide to Sharing Economic Data.

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