Shared problem is halved: UNECE publishes Guide to improving cross-border economic data sharing
As globalization increases the diversity of innovative business practices around the world, economies are becoming more and more interdependent. Multinational corporations, or multinational enterprises (MNEs) have operations in several countries, so calculating their economic impacts requires looking across borders to collect revenue. gather information from all the places they operate. To accurately measure global production and trade, it is increasingly necessary for statistical agencies to collect data on these MNEs from a variety of entities, both within and outside their own countries; and doing this effectively requires a framework about what data should be shared, how, and by whom.
New UNECE guidelines on sharing economic data for official statistics, published. Its purpose is to help national statistical offices ensure the quality of GDP and other key economic statistics, support sound economic policymaking, and help businesses make important decisions. and offer ways to reduce their reporting burden.
Faced with the daunting and new challenges posed by business globalization, statisticians across the UNECE region quickly joined forces to figure out how to compile relevant statistics. Back in 2012, UNECE published its first Guidelines on the Impact of Globalization on Country Accounts, followed in 2015 by the Guidelines for Measuring Global Production. Discussions among the international statistical community as they developed these guidelines suggest that data sharing is the missing part of the problem that needs to be addressed. Successful international cooperation on the standards and methods needed to extend the scope of cooperation to the actual data level. In this way, the global statistical system can get a more complete and accurate picture of international economic activity.
So far, countries have worked mostly in isolation when it comes to economic statistics. But a few exceptions demonstrate that cross-border sharing is possible and effective. For example, data sharing within and between the European Statistical System and the European Central Bank System has paid off. A number of national statistical offices have been involved in data sharing with key trading partner countries, and have recognized the core importance of data sharing to generate numbers. relevant and reliable economic statistics.
For example, prior to data sharing, trade statistics show that Canada's imports from China exceeded China's exports to Canada by $21.3 billion in 2016. Just share the total data. and information on the aggregation methods they used – i.e. without sharing any enterprise-level information – the two countries were able to compare their figures and explain much of the variance. this difference ($20.3 billion). Romania has taken a similar approach with a number of European Union countries and significantly reduced the asymmetry in trade flows.
New UNECE guidelines, adopted by the Conference of European Statisticians, provide tools to improve the quality of economic statistics by promoting this form of sharing while adhering to rigorous standards. on statistical security. The guidance focuses on establishing safeguards, safe environments and clear laws for the data to be exchanged. Comprehensive toolkit for national statistical offices, providing a wide range of resources including: analysis of the drivers and obstacles of data exchange links with resources to overcome barriers; sample documentation for communicating with the MNE; legal and procedural recommendations and a Model Memorandum of Understanding for data sharing between statistical offices; information on useful information technology tools and solutions;
The guide highlights that international organizations like UNECE will be key players in driving the cultural change needed to move data sharing from vision to reality.