Eurostat activities. Global Value Chain Measurement for Sustainable Development. New York 7 March Walter J. Radermacher 1.

Transcription

1 Eurostat Eurostat activities Global Value Chain Measurement for Sustainable Development New York 7 March 2016 Walter J. Radermacher 1

2 Background Globalisation in statistics remains a challenge Eurostat offers a platform bridging macro and micro dimensions of globalisation Different streams of work at international level where Eurostat and the European National Statistical Institutes are involved A representative sample of these activities will be the topic of this presentation Walter J. Radermacher 2

3 Focus Input-Output analysis / Integrated global accounts Environmental footprints Business statistics Eurogroups register e-intermediaries Walter J. Radermacher 3

4 Figaro and IGA Walter J. Radermacher 4

5 OECD Rest of the world OECD Rest of the world OECD Rest of the world Input-output analysis Car Clothing Pharma Export Car Clothing Pharma Export Car Clothing Pharma Export Car Car Car Clothing Clothing Clothing Car Clothing Pharma Export Pharma Pharma Pharma Import Import Import OECD Car OECD OECD Car Clothing Pharma Export Car Clothing Pharma Export Car Clothing Pharma Export Car Car Car Clothing Clothing Clothing Clothing Pharma Pharma Pharma Import Import Import Rest of the world Rest of the world Rest of the world Pharma Car Clothing Pharma Export Car Clothing Pharma Export Car Clothing Pharma Export Car Car Car Clothing Clothing Clothing Import Pharma Pharma Pharma Import Import Import Walter J. Radermacher 5

6 Environmental footprints How much water goes into one steak? Walter J. Radermacher 6

7 Your country Eurostat environmental footprints Input Ouput table Cars Clothes Pharma TOTAL Cars Clothes Pharma TOTAL Water Water Land Land Material Energy CO2 Material Energy CO2 Walter J. Radermacher 7

8 Country x Build on existing business statistics Input Ouput table Cars UCI Country x Cars Clothing Pharma Export FATS Clothes : : FDI Pharma Import Walter J. Radermacher 8

9 Build on existing business statistics Use micro-data linking to combine all possible datasets for obtaining new and more information e.g. on R&D performers or ICT providers Complete statistics with information on control independent/domestic/foreign) and trade (yes/no) Take a new look at the multinationals already under statistics' loop Advance from preparing manuals and classifications internationally to also producing statistics internationally Walter J. Radermacher 9

10 Eurogroups register The EuroGroups Register (EGR) contains microdata for multinational enterprise groups. It is part of the network of European business registers A multinational enterprise group (MNE) is defined as an enterprise group composed of at least two enterprises or legal units located in different countries The EGR data is provided by national statistical business registers in the ESS and from commercial data sources Walter J. Radermacher 10

11 Eurogroups register National staff of NSIs/NCBs have access to all units of the multinational enterprise groups, if at least one unit of the group is located in their national territory The EGR output should be used as survey frames at national level (at the moment increasingly for FATS) Annual production cycle with an increasing coverage of multi-national enterprise groups; Profiling results will be successively integrated into the EGR Walter J. Radermacher 11

12 e-intermediaries e-intermediaries / e-platforms Internet based; Functions as: travel agency, supermarket, manufacturing, etc. E-Intermediaries are potentially borderless have global reach Examples B2C (Amazon.com), B2B (Alibaba partly), C2C (Airbnb, UBER), C2B (Amazon Mechanical Turk) Intermediate (commercial) transactions between two or more parties NB: Google, Facebook, etc. have different business model do not intermediate transactions Walter J. Radermacher 12

13 e-intermediaries Statistical measurement issues What is size of e-intermediaries Value added, employment, etc. What is size of transactions mediated by e-intermediaries Value added, employment, etc. For example C2C transactions that are not captured in normal surveys Statisticians need information e-intermediaries has wealth of information relevant for the production of statistics Need mutual trust to exchange data for statistical purposes Such data should be treated as public good (no or low cost) Walter J. Radermacher 13

14 THANK YOU Walter J. Radermacher 14