Official Statistics 4.0: The Era of Digitisation and Globalisation
4.3 Globalisation—Reviewing the National Statistics Paradigm
Globalisation is the second driver behind rapidly changing requirements for, and working conditions of, official statistics. The manual of the European System of Accounts—ESA 2010 introduces globalisation in the following way: “The increas- ingly global nature of economic activity has increased international trade in all
its forms, and increased the challenges to countries of recording their domes- tic economies in the national accounts. Globalisation is the dynamic and mul- tidimensional process whereby national resources become more internationally mobile, while national economies become increasingly interdependent. … All of these increasingly common aspects of globalisation make the capture and accurate measurement of cross-border flows a growing challenge for national statisticians.
Even with a comprehensive and robust collection and measurement system for the entries in the rest of the world sector (and thus also in the international accounts found in the balance of payments), globalisation will increase the need for extra efforts to maintain the quality of national accounts for all economies and groupings of economies” (Eurostat2013b, p. 3).
The Review of UK Economic Statistics by Charles Bean highlights the intersec- tion of digitisation and globalisation as a driving force of change: “Measuring the economy has become even more challenging in recent times, in part as a conse- quence of the digital revolution. Quality improvements and product innovation have been especially rapid in the field of information technology. Not only are such quality improvements themselves difficult to measure, but they have also made possible com- pletely new ways of exchanging and providing services. …Moreover, while measuring physical capital–machinery and structures–is hard enough, in the modern econ- omy, intangible and unobservable knowledge-based assets have become increasingly important. Finally, businesses such as Google operate across national boundaries in ways that can render it difficult to allocate value added to particular countries in a meaningful fashion. Measuring the economy has never been harder” (Bean2016, p. 3).
These two statements only prove the importance of globalisation and digiti- sation for the economy and for economic statistics. However, there are also far- reaching changes in societies (migration, integration) and in the environment (cli- mate, biosphere, global boundaries), which correspond to new requests for social and environmental indicators.
Charles Bean’s report highlights the key challenges arising from these changed conditions and makes specific recommendations concerning the statistical pro- gramme (e.g. better coverage of the service industry, regional statistics). It also requests greater agility in statistics and adaptability to meet user needs, better use of existing data and technologies, and finally stresses the importance of statistical governance.
While many of the thoughts below have a lot of overlap with the Bean Report, they are generated with a different perspective in mind, and so are complementary.
The question here is where the paradigm that is fundamental for official statistics atnationallevel reaches its limits, and needs to be reflected and complemented by European or international statistics.
The National Statistics paradigm, described in Sect.2.4, is recalled. The three dimensions of national official statistics are:
• Temporal dimension: a fixed time period (often a year, but sometimes also a quarter or a month) or a fixed date (for example, for the population census).
• Spatial dimension: a country (political delimitation), or a region (province, local unit according to administrative delimitation according to the Nomenclature of Territorial Units for Statistics).
• Measurement object: resident population and their activities; methodologies (vari- ables, classifications, sampling schemes, etc.) designed to address national needs and priorities.
The gross domestic product—as the name implies—represents a section of the world economy capturing the activities (i.e. flows) in one country, in one period as accurately as possible. The underlying logic of economic statistics assumes that the essential production of goods physically takes place in the respective country. Cross- border activities (e.g. international trade and foreign investments), and cross-period activities (e.g. depreciation of assets), are amalgamated into the GDP of one specific country, in one year with the best possible accuracy. Quantifying the international aspect of economic cooperation (in particular for services) has itself traditionally been a low priority task. Similarly, the balancing of stocks (caused by depreciation and investments) has traditionally played a subordinate role in the concept of GDP, which focuses on the quantification of flows. Both features are now critically questioned: it is demanded that stocks are better quantified, and better statistics of global economic cooperation are required.
The report on global value chains by Timothy Sturgeon highlights: “International trade and foreign direct investment (FDI) have long been important features of the world economy, and both have grown steadily since the end of World War Two.
…Today the picture has grown more complex, with multilayered international sourc- ing networks and new technology-enabled business models that better integrate and accelerate cross-border economic activity” (Sturgeon2013, p. 1). With a sense of urgency, Sturgeon requests a far reaching programme for the statistical treatment of globalisation: “The greater scale, complexity, and transformational potential of economic globalization demand that we ask more from our economic statistics: ways to systematically differentiate arms-length trade from intra-group trade and external international sourcing, ways to track services trade in more detail, ways to determine the real location of value added, and ways to differentiate globally-engaged from non- globally-engaged enterprises so the performance of these very different segments of national economies can be tracked in terms of profits, innovation, employment, and wages paid” (Sturgeon2013, p. 6).
In particular, the so-called Irish case—when the Central Statistical Office (CSO) of Ireland published a level shift for its GDP (caused by relocation of the seat of a multinational company), significantly revising the growth rates for 2015 upwards to 26.3 ppt10—has clarified the urgency and brought the size of the challenge into sharp relief.
After this case, the international statistical community has intensified the search for new solutions to this problem, which could include new indicators for improving insight to national economies. Further, it might become necessary to modify or extend
10See ESRG (2016), Stapel-Weber and Verrinder (2016).
statistical standards11to avoid the distortions caused by multinational enterprises that arrange cross-border business practices for the purposes of tax avoidance.12Finally, one might have to arrange new international statistical components, particularly in Europe. A deeper and more holistic review of methodologies (National Accounts and business statistics), seems to be necessary,13 in which new statistical infrastructural elements and new international cooperation models are agreed between statistical compilers.
In recent years, international cooperation has successfully led to new indicators that can quantify key aspects of globalisation. Above all, these include the interlinked input–output tables14of individual countries, and the calculation of trade-in-value- added (TIVA).15These input–output tables prepare the ground at a global level for an economic analysis of globalisation, and for environmental indicators that measure pollutants or other environmental pressures. Among these measures are the ‘Car- bon Footprint’16 or the ‘Total Material Consumption (TMC)’, which differs from the ‘Domestic Material Consumption (DMC)’ which excludes the environmental impacts of imports or exports.17
Registers of business statistics allow the development of recent years to be traced and an outlook for the near future to be derived. After the establishment of indi- vidual national business registers in the 1980s, a European standard format was agreed,18then a EuroGroups Register (EGR)19was created, which is currently being further developed into the European System of interoperable Business Registers (ESBRs).20 Future tasks of this working area in official statistics will contain the so-called profiling of large cases and multinational companies.21
It makes little sense that each country’s statistical office builds a new team for pro- filing in isolation, only the national segments of multinational companies. Profiling requires that the statistical data correctly monitors the overarching multinational in its entirety, as well as each of its national sub-elements according to the usual statistical
11See, for example, the Guide to Measuring Global Production (https://www.unece.org/index.php?
id=42106).
12See Moulton and Ven (2018).
13See Stapel-Weber et al. (2018).
14Seehttps://www.oecd.org/sti/ind/inter-country-input-output-tables.htmorhttp://www.wiod.org/
home.
15See https://unstats.un.org/unsd/trade/globalforum/trade-value-added.asp or https://www.oecd.
org/sti/ind/measuring-trade-in-value-added.htm.
16See http://ec.europa.eu/eurostat/statistics-explained/index.php/Greenhouse_gas_emission_
statistics_-_carbon_footprints.
17For both indicators see the definition herehttps://www.un.org/esa/sustdev/natlinfo/indicators/
methodology_sheets/consumption_production/domestic_material_consumption.pdf.
18Seehttp://ec.europa.eu/eurostat/statistics-explained/index.php/Business_registers.
19See http://ec.europa.eu/eurostat/web/structural-business-statistics/structural-business-statistics/
eurogroups-register.
20Seehttp://ec.europa.eu/eurostat/web/ess/esbr.
21Seehttps://ec.europa.eu/eurostat/cros/content/profiling-esbrs_en.
methods. Double counting is just as inadmissible as statistical gaps. Such a consis- tent statistical profile of a multinational company can only be achieved through close cooperation and data exchange, preferably combined with a strong work-sharing ethic.
However, this division of labour affects the affiliation of the statistical offices to the public administrations of each individual country. In turn, this leads to consider- able problems sharing and transferring responsibilities and in exchanging data. This difficulty is demonstrated by the example of trade statistics between the European Member States. Following the introduction of the European Single Market, statistical evaluations of border controls (and thus customs declarations for the movement of goods) were stopped. The collection procedure Intrastat was introduced instead, the complete opposite of the trend, common today, of replacing surveys with adminis- trative data. To fully satisfy all the data needs of the past, all exports, as well as all imports, were collected. Theoretically, the sum of all European exports would have to be identical to all imports, so the imports of one country could, in principle, be calculated by summing up the exports of all its neighbours. Nonetheless, a two-flow concept was established that has been in place for more than two decades, despite involving extremely high costs and burdens. One of the main reasons for keeping this procedure from a national point of view is that the so-called mirror differences (i.e. the discrepancy between collected and calculated imports) are solved by sys- tematically favouring data collected nationally. As a consequence, while the Intrastat process produces 28 results (each being of the best quality from a national point of view), they are all contradictory and do not result in a plausible, consolidated figure at European level.
After years of difficult negotiation, a compromise has been found based on the exchange of confidential export data between the statistical offices of all Member States. For this exchange to work, strict principles have been agreed to ensure the protection of this sensitive data. It remains to be seen how this new and creative process will work in practice.
After all, this completely new form of cooperation between national statistical offices can be regarded as a successful first step into the future. A next important step could be taken with a work-sharing procedure for profiling.
Unfortunately, there are currently also signs that the national statistics paradigm is likely to be reinforced. For example, the overall architecture and governance of the Sustainable Development Goals and Indicators programme follows a political doctrine, according to which the UN Member States each take the lead in imple- menting both the political strategy and the corresponding indicators. One might ask whether this will result in a fragmented landscape of national indicator sets, rather than capturing global aspects of sustainability.
A very special field of work is that of public finance statistics in Europe. This is about indicators (debt and deficit) with extraordinary political significance, which does not allow any scope for national variants in the production of statistics. With such close integration and interdependence, it would be worth considering a different statistical system with a more centralised structure and governance to replace the current decentralised system of national and European institutions (Georgiou2018).
However, such considerations have so far had little chance of being realised, although they could offer major advantages in terms of effectiveness and efficiency.