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Official Statistics 4.0: The Era of Digitisation and Globalisation

  • Walter J. RadermacherEmail author
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Abstract

What the future has in store for us is, not easily predictable. Certainly, foresight does not lie in the very nature of statisticians, who usually look in the rear-view mirror. Nevertheless, there are some trends or megatrends, the effects of which are not yet known in detail, to which one will undoubtedly have to adapt. Above all, because official statistics have the characteristics of an ocean liner whose course and speed can only be manoeuvred slowly, all trends must be interpreted in a forward-looking manner. If official statistics are to be sustained in their current position in five years’ time, then the necessary strategy must be established now. A simple continuation of the previous way of doing things, but including some ‘softer’ changes, is therefore not an option, even if this smooth manner of adaptation has been successful in the past. This chapter addresses the two megatrends of digitisation and globalisation. Obviously, it is not the purpose of this work to deal with their methodological, conceptual or technical aspects in this regard. Rather, it is about the consequences in terms of the statistical policy due to the changed statistical environment and conditions.

References

  1. Arnade, Chris. 2016. Why Trump Voters are not “Complete Idiots”. Accessed May 31, 2016. https://medium.com/@Chris_arnade/trump-politics-and-option-pricing-or-why-trump-voters-are-not-idiots-1e364a4ed940#.faldoe9vg.
  2. Bartl, Walter, Christian Papilloud, and Audrey Terracher-Lipinsky. 2019. Governing by Numbers—Key Indicators and the Politics of Expectations. Historical Social Reasearch 44: 1–339.Google Scholar
  3. Bean, Charles. 2016. Independent Review of UK Economic Statistics, London, UK Government.Google Scholar
  4. Beck, Ulrich. 1998. Risk Society Towards a New Modernity. London: Sage.Google Scholar
  5. Benessia, A., S. Funtowicz, M. Giampietro, A. Guimaraes Pereira, J. Ravetz, A. Saltelli, R. Strand, and J.P. van der Sluijs. 2016. The Rightful Place of Science: Science on the Verge. Tempe, AZ: Consortium for Science, Policy and Outcomes.Google Scholar
  6. Brachinger, H.W. 2005. Der Euro als Teuro? Die wahrgenommene Inflation in Deutschland. Wirtschaft und Statistik.Google Scholar
  7. Braungardt, Jürgen. 2018. Immanuel Kant: What is Enlightenment? (1784). Braungardt, Jürgen. Accessed April 20, 2018. http://braungardt.trialectics.com/philosophy/early-modern-philosophy-16th-18th-century-europe/kant/enlightenment/.
  8. Brown, W. 2015. Undoing the Demos: Neoliberalism’s Stealth Revolution. Cambridge, MA: MIT Press.Google Scholar
  9. Cao, Longbing. 2017a. Data Science: A Comprehensive Overview. ACM Computing Surveys 50: 1–42.CrossRefGoogle Scholar
  10. Cao, Longbing. 2017b. Data Science: Challenges and Directions. Communications of the ACM 80: 59–68.CrossRefGoogle Scholar
  11. Dasgupta, Rana. 2018. The Demise of the Nation State. The Guardian, April 5, 2018.Google Scholar
  12. Davies, William. 2016. The Limits of Neoliberalism—Authority, Sovereignty and the Logic of Competition. London: SAGE Publications.Google Scholar
  13. Davies, William. 2017. How Statistics Lost Their Power—and Why We Should Fear What Comes Next. The Guardian.Google Scholar
  14. De Clerck, J-P 2017. What is the Internet of Things? Internet of Things Definitions and Segments. In i-SCOOP.Google Scholar
  15. Desrosières, Alain. 1998. The Politics of Large Numbers—A History of Statistical Reasoning. Cambridge, MA: Harvard University Press.zbMATHGoogle Scholar
  16. Diakopoulos, Nicholas. 2015. Accountability in Algorithmic Decision-making. Communications of the ACM 59: 56–62.CrossRefGoogle Scholar
  17. Diaz-Bone, Rainer, and Emmanuel Didier (ed.). 2016. Conventions and Quantification—Transdisciplinary Perspectives on Statistics and Classifications.Google Scholar
  18. ECOSOC. 2017. ECOSOC Adopts SDG Indicator Framework. Accessed June 7, 2017. http://sdg.iisd.org/news/ecosoc-adopts-sdg-indicator-framework/.
  19. ECSA. 2016. ECSA Policy Paper #3 Citizen Science as part of EU Policy Delivery—EU Directives, 4. Berlin: ECSA.Google Scholar
  20. ESGAB. 2010. Second Annual Report to the European Parliament and the Council on the Implementation of the European Statistics Code of Practice by Eurostat and the European Statistical System as a Whole. European Statistical Governance Advisory Board.Google Scholar
  21. ESGAB. 2016. ESGAB Annual Report 2016. Luxembourg: European System Governance Advisory Board.Google Scholar
  22. ESRG. 2016. Report of the Economic Statistics Review Group (ESRG). Dublin: CSO Ireland.Google Scholar
  23. European Commission. 2012. Reinforcing Eurostat, Reinforcing High Quality Statistics, ed. European Commission. Brussels: European Commission.Google Scholar
  24. European Statistical System Committee. 2018. Bucharest Memorandum on Official Statistics in a Datafied Society (Trusted Smart Statistics). In DGINS 2018, ed. Eurostat. Bucharest: Statistics Romania.Google Scholar
  25. European Strategy and Policy Analysis System. 2019. Global Trends to 20130—Challenges and Choices for Europe, 42. Brussels: European Strategy and Policy Analysis System ESPAS.Google Scholar
  26. European Union. 2011. European Statistical Programme 2013–2017. In COM(2011) 928 Final, ed. The European Parliament and the Council. Brussels: European Commission.Google Scholar
  27. European Union. 2012. The Treaty on the Functioning of the European Union (TFEU), ed. European Commission. Brussels: Official Journal of the European Union C326/193.Google Scholar
  28. European Union. 2015. Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics and repealing Regulation (EC, Euratom) No 1101/2008 of the European Parliament and of the Council on the transmission of data subject to statistical confidentiality to the Statistical Office of the European Communities, Council Regulation (EC) No 322/97 on Community Statistics, and Council Decision 89/382/EEC, Euratom establishing a Committee on the Statistical Programmes of the European Communities. In 2009R0223—EN—08.06.2015—001.001—1, ed. European Union. Luxembourg: © European Union, https://eur-lex.europa.eu, 1998–2019.
  29. Eurostat. 2011. European Statistics Code of Practice for the National and Community Statistical Authorities—Adopted by the European Statistical System Committee 28th September 2011, ed. Eurostat. Luxembourg: Eurostat.Google Scholar
  30. Eurostat. 2013b. European System of Accounts ESA 2010. Luxembourg: Publications Office of the European Union.Google Scholar
  31. Eurostat. 2015a. Practical Arrangements Governing Working Relations Between Commissioner Thyssen, Her Cabinet and Eurostat. Luxembourg: Eurostat.Google Scholar
  32. Eurostat. 2015b. Implementation of the Framework Regulation Integrating Business Statistics (FRIBS). Eurostat. http://ec.europa.eu/eurostat/about/opportunities/consultations/fribs.
  33. Eurostat. 2016. Manual on Government Deficit and Debt—Implementation of ESA 2010. Luxembourg: Publications Office of the European Union.Google Scholar
  34. Eyraud, Corine. 2018. Stakeholder Involvement in the Statistical Value Chain: Bridging the Gap Between Citizens and Official Statistics. In Power from Statistics: Data, Information and Knowledge—Outlook Report—2018 Edition, ed. Eurostat. Luxembourg: Publication Office of the European Union.Google Scholar
  35. Foucault, Michel. 1991. ‘Governmentality.’ in Graham Burchell, Colin Gordon and Peter Miller (eds.), The Foucault Effect (Chicago University Press: Chicago).Google Scholar
  36. Fritz, Steffen, Linda See, Tyler Carlson, Mordechai Muki Haklay, et al. 2019. Citizen science and the United Nations Sustainable Development Goals. Nature Sustainability 2: 922–930.CrossRefGoogle Scholar
  37. Georgiou, Andreas V. 2018. A New Statistical System for the European Union. Brussels: Bruegel.Google Scholar
  38. Gericke, Kilian, Boris Eisenbart, and Gregor Waltersdorfer. 2018. Staging Design Thinking for Sustainability in Practice: Guidance and Watch-Outs. In Sustainability Science, ed. Ariane König. New York: Routledge.Google Scholar
  39. GfdS. 2016. GfdS wählt » postfaktisch « zum Wort des Jahres 2016, ed. Gesellschaft für Deutsche Sprache. Wiesbaden.Google Scholar
  40. Global Commission on the Future of Work. 2019. Work for a Brighter Future, ed. International Labour Organization ILO, 71. Geneva: International Labour Organization ILO.Google Scholar
  41. Gray, Jonathan. 2017. Quand les mondes de données sont redistribués: Open Data, infrastructures de données et démocratie. Statistique et Société 5: 29–34.Google Scholar
  42. Haklay, Muki. 2015. Citizen Science and Policy: A European Perspective. In Case Study Series, 61. Washington, DC: Wilson Center COMMONS LAB.Google Scholar
  43. Hale, Thomas, David Held, and Kevin Young. 2013. Gridlock: Why Global Cooperation is Failing When We Need It Mos. Cambridge: Polity Press.Google Scholar
  44. Hand, D.J. 2004. Measurement Theory and Practice: The World Through Quantification. London: Arnold.zbMATHGoogle Scholar
  45. Hendricks, Vincent F., and Mads Vestergaard. 2018. Postfaktisch—Die neue Wirklichkeit in Zeiten von Bullshit, Fake News und Verschwöruungstherien. München: Karl Blessing Verlag.Google Scholar
  46. Heubl, Ben. 2018. Night Light Images Paint Accurate Picture of China GDP. NIKKEI ASIAN REVIEW, 24 March 2018.Google Scholar
  47. Hisschemöller, Matthijs, and Eefje Cuppen. 2015. Participatory Assessment: Tools for Empowering, Learning and Legitimating? In The Tools of Policy Formulation, ed. Andrew J. Jordan and John R. Turnpenny. Cheltenham: Edward Elgar Publishing Limited.Google Scholar
  48. HLEG. 2018. “A multi-dimensional approach to disinformation - Final report of the High Level Expert Group on Fake News and Online Disinformation.” In, 39. Luxembourg: European Commission.Google Scholar
  49. HMTreasury. 1998. Statistics: A Matter of Trust. London: HM Treasury.Google Scholar
  50. Independent Commission for Sustainable Equality. 2018. Sustainable Equality—Well-Being for Everyone in a Sustainable Europe, ed. Marcel Mersch, 193. Brussels: Group of the Progressive Alliance of Socialists & Democrats in the European Parliament.Google Scholar
  51. Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. 2019. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services, 39. Bonn, Germany: Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES).Google Scholar
  52. ISI. 2010. ISI Declaration on Professional Ethics. Hague: International Statistical Institute.Google Scholar
  53. Jasanoff, Sheila. 2003. Technologies of Humility: Citizen Participation in Governing Science. Minerva 41: 223–244.CrossRefGoogle Scholar
  54. Jasanoff, Sheila. 2004. States of Knowledge: The Co-production of Science and the Social Order. London: Routledge.CrossRefGoogle Scholar
  55. Jasanoff, S., and Society for Social Studies of Science. 1995. Handbook of science and Technology Studies. Thousand Oaks: Sage Publications.Google Scholar
  56. Joost, Gesche, and Andreas Unteidig. 2015. Design and Social Change: The Changing Environment of a Discipline in Flux. In Transformation Design, ed. Wolfgang Jonas, Sarah Zerwas, and Kristof von Anshelm. Birkhäuser: Basel.Google Scholar
  57. König, Ariane (ed.). 2018. Sustainability Science. New York: Routledge.Google Scholar
  58. Latour, B., S. Woolgar, and J. Salk. 1986. Laboratory Life: The Construction of Scientific Facts. Princeton: Princeton University Press.Google Scholar
  59. Lehtonen, Markku. 2015. Indicators: Tools for Informing, Monitoring or Controlling? In The Tools of Policy Formulation—Actors, Capacities, Venues and Effects, ed. Andrew J. Jordan and John R. Turnpenny. Cheltenham: Edward Elgar Publishing.Google Scholar
  60. Lehtonen, Markku, Léa Sébastien, and Tom Bauler. 2016. The Multiple Roles of Sustainability Indicators in Informational Governance: Between Intended Use and Unanticipated Influence. Current Opinion in Environmental Sustainability 2016: 1–9.CrossRefGoogle Scholar
  61. Lohr, Steve. 2016. Civility in the Age of Artificial Intelligence. In ODBMS.org. Zicari, Roberto.Google Scholar
  62. Mance, Henry. 2016. Britain has had Enough of Experts, Says Gove. Financial Times.Google Scholar
  63. Martín-Guzman, Pilar. 2018. Old and New Risks for the Credibility of Official Statistics: Comments from a User. In Conference of European Statistical Stakeholders, ed. University Bamberg. Bamberg, Germany: University Bamberg.Google Scholar
  64. Moulton, Brent R., and Peter van de Ven. 2018. Addressing the Challenges of Globalization in National Accounts. In Conference on Research in Income and Wealth “The Challenges of Globalization in the Measurement of National Accounts”. Washington.Google Scholar
  65. Office for Statistics Regulation. 2018. Joining Up Data for Better Statistics. In Systemic Review Programme, ed. UK Statistics Authority, 39. London: UK Statistics Authority.Google Scholar
  66. Oxford Dictionairies. 2016. Oxford Dictionairies Word of the Year 2016. Accessed June 26, 2018. https://www.oxforddictionaries.com/press/news/2016/12/11/WOTY-16.
  67. Peruzzi, Alberto. 2017. Complexity: Between Rhetoric and Science. In Complexity in Society: From Indicators Construction to their Synthesis, ed. F. Maggino. Cham: Springer International Publishing.Google Scholar
  68. Pope Francis. 2014. Address to European Parliament, Strasbourg, France, November 25, 2014.Google Scholar
  69. Radermacher, Walter. 2016. Quality Declaration of the European Statistical System—Inauguration. In CESS 2016. Budapest.Google Scholar
  70. Radermacher, Walter J., and Emanuele Baldacci. 2016. Official Statistics for Democratic Societies—Dinner Speech at the CESS 2016, Budapest. In Conference of European Statistical Stakeholders. Budapest.Google Scholar
  71. Randers, Jorgen, Johan Rockström, Per Espen Stoknes, Ulrich Golücke, David Collste, and Sarah Cornell. 2018. Transformation is Feasible—How to Achieve the Sustainable Development Goals Within Planetary Boundaries—A Report to the Club of Rome, for its 50 years Anniversary 17 October 2018. Stockholm: Stockholm Resilience Centre, Stockholm University, Norwegian Business School, Global Challenges Foundation.Google Scholar
  72. Ricciato, Fabio, Michail Skaliotis, Albrecht Wirthmann, Kostas Giannakouris, and Fernando Reis. 2018. Towards a Reference Architecture for Trusted Smart Statistics. In DGINS 2018. Bucharest: Statistics Romania.Google Scholar
  73. Roser, Max. 2018. Most of Us are Wrong About How the World has Changed (Especially Those Who are Pessimistic About the Future). In Our World In Data.Google Scholar
  74. Ryan, Liz. 2014. ‘If You Can’t Measure It, You Can’t Manage It’: Not True. In Forbes/Leadership. Forbes.Google Scholar
  75. Sangolt, Linda. 2010a. A Century of Quantification and “Cold Calculation”. Trends in the Pursuit of Efficiency, Growth and Pre-eminence. In Between Elightenment and Disaster—Dimensions of the Political Use of Knowledge, ed. Linda Sangolt. Brussels: P.I.E. Peter Lang.CrossRefGoogle Scholar
  76. Sangolt, Linda. 2010b. Between Enlightenment and Disaster: Dimensions of the Political Use of Knowledge. Brussels: P.I.E. Peter Lang.CrossRefGoogle Scholar
  77. Seltzer, William. 1994. Politics and Statistics: Independence, Dependence, or Interaction?, ed. UN Dept. of Econ. and Soc. Information and Policy Analysis. New York: UN.Google Scholar
  78. Soma, Katrine, Marleen C. Onwezen, Irini E. Salverda, and Rosalie I. van Dam. 2016a. Roles of citizens in environmental governance in the Information Age—four theoretical perspectives. Current Opinion in Environmental Sustainability 2016: 122–130.CrossRefGoogle Scholar
  79. Soma, Katrine, Bertrum H. MacDonald, Catrien J.A.M. Termeer, and Paul Opdam. 2016b. Introduction article: informational governance and environmental sustainability. Current Opinion in Environmental Sustainability 2016: 131–139.CrossRefGoogle Scholar
  80. Stapel-Weber, Silke, and John Verrinder. 2016. Globalisation at Work in Statistics—Questions Arising from the ‘Irish Case. Eurona—Eurostat Review on National Accounts and Macroeconomic Indicators, 29–44.Google Scholar
  81. Stapel-Weber, Silke, Paul Konijn, John Verrinder, and Henk Nijmeijer. 2018. Meaningful Information for Domestic Economies in the Light of Globalization—Will Additional Macroeconomic Indicators and Different Presentations Shed Light? In Conference on Research in Income and Wealth “The Challenges of Globalization in the Measurement of National Accounts”. Washington.Google Scholar
  82. Stapleford, Thomas A. 2015. Price Indexes, Political Judgments, and the Challenge of Democratic Control. In Ottawa Group—International Working Group on Price Indices—Fourteenth Meeting. Tokyo, Japan: Statistics Japan.Google Scholar
  83. Stiglitz, Joseph E., Jean-Paul Fitoussi, and Martine Durand. 2018a. Beyond GDP—Measuring What Counts for Economic and Social Progress. Paris: OECD Publishing.CrossRefGoogle Scholar
  84. Stiglitz, Joseph E., Jean-Paul Fitoussi, and Martine Durand (eds.). 2018b. For Good Measure, Advancing Research on Well-being, Metrics Beyond GDP. Paris: OECD Publishing.Google Scholar
  85. Sturgeon, Timothy J. 2013. Global Value Chains and Economic Globalization—Towards a New Measurement Framework. Luxembourg: Eurostat.Google Scholar
  86. Thomas, Ray. 2007. Who is in Charge of Public Statistics?, radstats. http://www.radstats.org.uk/no094/Thomas94.pdf.
  87. United Nations. 2014. Fundamental Principles of Official Statistics. New York.Google Scholar
  88. United Nations. 2018. Sustainable Development Goal indicators website. United Nations. Accessed August 17, 2018. https://unstats.un.org/sdgs/.
  89. Villani, Cédric. 2018. For a Meaningful Artificial Intelligence—Towards a French and European Strategy. In Mission Assigned by the Prime Minister Édouard Philippe, 151. Paris: AI for Humanity—French Strategy for Artificial Intelligence.Google Scholar
  90. WeObserve. 2018. An Ecosystem of Citizen Observatories for Environmental Monitoring. WeObserve, Accessed August 17, 2018. https://www.weobserve.eu/.
  91. Wigglesworth, Robin. 2018. Can Big Data Revolutionise Policymaking by Governments? Financial Times, 31 January 2018.Google Scholar
  92. World Economic Forum. 2019. The Global Risks Report. In The Global Risks Report, ed. World Economic Forum WEF, 107. Geneva: World Economic Forum WEF.Google Scholar
  93. WorldBank. 2017. International Comparison Program (ICP). http://www.worldbank.org/en/programs/icp.

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Authors and Affiliations

  1. 1.Department of Statistical SciencesSapienza University of RomeRomeItaly

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