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A problem shared is a problem halved: UNECE publishes Guide to improve transnational sharing of economic data

Two laptop computers sharing folders

As globalization increases the diversity of innovative ways of doing business around the world, economies become ever more interdependent. Multinational enterprise groups, or MNEs, have operations in several countries, so counting up their economic impacts entails looking across borders to gather information from all the places in which they operate. To measure global production and trade accurately, statistical offices increasingly need to obtain data about these MNEs from many entities, both within and outside their own countries; and doing this efficiently requires a framework for what data should be shared, how and by whom. 

The new UNECE Guide to Sharing Economic Data for Official Statistics, published today, provides this framework. The aim is to help national statistical offices ensure the quality of GDP and other key economic statistics, supporting sound economic policymaking and helping businesses to make critical decisions while also offering ways to reduce the reporting burden on them.  

Faced with the significant and novel challenges presented by globalization of business, statisticians across the UNECE region rapidly joined forces to figure out how to compile relevant statistics: back in 2012 UNECE published the first Guide on the Impact of Globalization on National Accounts, followed in 2015 by the Guide to Measuring Global Production. The discussions among the international statistical community as they developed these guides revealed data sharing as the missing piece of the puzzle.  successful international collaboration on standards and methods needed to extend its scope to cooperation on the level of the actual data. In this way the global statistical system can achieve a more complete and accurate picture of international economic activity. 

Until now countries have mostly worked in isolation when it comes to producing economic statistics. But the few exceptions prove that cross-national sharing is possible and effective. For instance, data sharing within and between the European Statistical System and the European System of Central Banks has borne fruit. Several trailblazing national statistical offices have engaged in data sharing with countries that are important trading partners, and have come to realize the pivotal importance of data sharing to producing relevant and reliable economic statistics.  

For example, before data sharing, trade statistics showed Canada's imports from China exceeding China's exports to Canada by 21.3 billion US dollars in 2016. Simply by sharing aggregated data and information about the compilation methods they had used – that is, without needing to share any enterprise level information – these two countries were able to reconcile their figures and explain away most of this difference (20.3 billion dollars). Romania undertook a similar exercise with a number of European Union countries and significantly reduced asymmetries in trade flows. 

The new UNECE Guide, endorsed by the Conference of European Statisticians, provides tools for improving the quality of economic statistics by fostering this kind of sharing while observing strict standards of statistical confidentiality. The Guide focuses on establishing safeguards, secure environments and clear legislation for data to be exchanged. A comprehensive toolkit for national statistical offices, it offers a range of resources including: an analysis of enablers and obstacles of data exchange with links to resources to overcome barriers; sample materials for communication with MNEs; legal and procedural recommendations and a template Memorandum of Understanding for data sharing among statistical authorities; information on useful IT tools and solutions; and many examples of experience from   statistical offices as well as of a variety of types of data sharing. 

The Guide emphasizes that international organizations such as UNECE will be key players in driving the necessary culture change to move data sharing from vision to reality. 

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