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Towards a comprehensive global policy agenda: what does it mean for statistics? Enrico Giovannini University of Rome “Tor Vergata”

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Presentation on theme: "Towards a comprehensive global policy agenda: what does it mean for statistics? Enrico Giovannini University of Rome “Tor Vergata”"— Presentation transcript:

1 Towards a comprehensive global policy agenda: what does it mean for statistics? Enrico Giovannini University of Rome “Tor Vergata” (enrico.giovannini@uniroma2.it)

2 The Sustainable Development Agenda In September 2015 the UN Member States agreed, for the first time ever, on a comprehensive and long- term policy agenda for all countries of the world. Given the wide range of topics covered by SDGs, it is not yet clear how the new agenda will encompass sectoral agendas developed over the years by the UN and other international, regional and supranational organisation.

3 The Sustainable Development Agenda As already happened with the Millennium Development Goals (MDGs), the adoption of SDGs should also stimulate a massive investment to improve the availability and the quality of statistical indicators. The demand for SDGs indicators should absorb existing sectoral programs. If it does not happen the global statistical system could face an unsustainable situation, given the limited resources available.

4 The Medium-Term Strategy for Europe It is not yet clear how the Global Agenda will be translated into the European Agenda. Two options: – Confirm the Europe 2020 Strategy; – Progressive shift from Europe 2020 to SDGs. It is likely that the ESS will be asked to speed up the production of several indicators (especially social and environmental). Possible new focus on measuring vulnerability and resilience of economic, social and environmental systems.

5 Preliminary assessment of the data availability for SDGs A lot of data do not exist or are produced too late Big differences between developed and developing countries None looks able to produce all data with the necessary timeliness

6 The Data Revolution The report A World that Counts published by IEAG one year ago (www.datarevolution.org) called for a better coordination of statistical programmes developed by international organisations.www.datarevolution.org Notwithstanding the improvements made over the last few years, such a coordination is still unsatisfactory, especially in terms of data collection and the development of common infrastructures, also to exploit economies of scale. In the meantime, the private sector is moving very fast.

7 Article “Who will lead development’s big data revolution?” “In New York, as United Nations delegates adopted the Sustainable Development Goals this week, celebration met a stern reminder: the goals cannot be achieved without a way to monitor and measure progress toward them. And with that call to action, big data companies are racing to position themselves as ideal partners for development organizations seeking better analysis in real time”.

8 Valor Equity Partners: – is a lower middle market private equity firm whose unique investment approach combines the disciplines of value investing with operational activism; – begins by identifying market segments and industries which it believes exhibit positive long-term demand dynamics; – invests in lower middle market companies which have sustainable revenues derived from a strategic or niche market position. Article “Who will lead development’s big data revolution?”

9 Article “Who will lead development’s big data revolution?” Valor Equity Partners: – Invested 50M$ in Premise, a company that “maps truth from the ground up”, a technology company building a global network to track macroeconomic and human development trends in real time. – Premise software and mobile infrastructure collects millions of discrete data points every day from thousands of local sources, enabling their clients, who are among the world's largest institutions, to understand and navigate unprecedented volatility in global inflation, industry competitive dynamics, and food security. – Based in San Francisco with a presence in 30 countries, and are backed by some of the most forward-looking investors including Google Ventures, Harrison Metal, and Andreessen Horowitz.

10 International Open Data Charter The Open Data Charter was set up as a Global Multi- Stakeholder Action Network with two types of leading members: Stewards and Lead Stewards. Members of these two groups form different working groups according to their interests. The Charter’s Lead Stewards are: – The Government of Canada The Government of Canada – The Government of Mexico The Government of Mexico – The International Development Research Centre / Open Data for Development The International Development Research CentreOpen Data for Development – The World Wide Web Foundation The World Wide Web Foundation – Omidyar Network Omidyar Network

11 International Open Data Charter The world is witnessing a significant global transformation, facilitated by technology and digital media, and fueled by data and information. This transformation has enormous potential to foster more transparent, accountable, efficient, responsive, and effective governments and civil society and private sector organizations, and to support the design, delivery, and assessment of sustainable development goals at a global scale. Open data is at the center of this global shift. Building a more prosperous, equitable, and just society requires that governments are transparent and accountable, and that they engage regularly and meaningfully with citizens. Accordingly, there is an ongoing global data revolution that seeks to advance collaboration around key social challenges, provide effective public oversight of government activities, and support innovation, sustainable economic development, and the creation and expansion of effective, efficient public policies and programs. Open data is crucial to meeting these objectives.

12 The lost opportunities The revision of UN Fundamental Principles of Official Statistics The cultural leadership of the Data Revolution The merger of statistics and geographical information systems UN Commissions … What’s next? Time is running and the international statistical system is not fast enough

13 Data, open data, statistics and official statistics Official statistics Government data Non-government data

14 Proposals to better structure the UNSC work The list of indicators needed to monitor progress towards SDGs is been discussed now, but in the meantime the following actions could have been undertaken: The Goals and Targets had to be mapped with the activities carried out by the UNSC, to check whether the “domains” used to frame the work of the UNSC need adjustments to better incorporate the subject matters included in the SDGs list. A detailed analysis had to be carried out to develop, by the end of 2015, a comprehensive proposal to be presented for decisions at the 2016 meeting of the UNSC.

15 Towards global statistical infrastructures for SDGs Develop a coordinated global statistical programme Strengthen the role of CCSA Establish new rules to engage key non-governmental data providers in the international statistical system Develop a global data and metadata collection portal Establish a global “statistical cloud” Speed up the development and the adoption of standards for data and metadata exchange

16 Towards global statistical infrastructures for SDGs Quickly identify a research agenda to fill the existing gaps in statistical standards Develop a proposal to speed up the process of standard setting at global level and to fully benefit from the work done outside the UNSC mandate Foster the linkage between statistical and geospatial information and standards Establish a “global data users network”

17 Challenges and opportunities for national statistical systems Institutional setting – The data revolution and the SDGs may be a great opportunity to strengthen the institutional setting of national statistical offices and systems. – Statistical authorities will be more oriented to re-use data collected by other organisations. Therefore, administrative data and other Big Data must be fully accessible to national statistical offices, who will also be mandated, much more than in the past, to check the quality of data produced by others.

18 Challenges and opportunities for national statistical systems Institutional setting – Appropriate revisions of legal and institutional settings under which statistical agencies operate supported by: the adoption of global principles on legal and technical issues; the review of principles for confidentiality protection, while allowing the maximum circulation of properly anonymised data for research and business purposes.

19 Challenges and opportunities for national statistical systems Institutional setting – A higher responsibility of NSOs needs to be accompanied by a stronger national and international system for verification and monitoring of possible misbehaves. Therefore: proposals to strengthen the architecture of the international statistical system have to be developed, including the establishment of an independent body such as “Worldstat”, who would have a watchdog function vis- à-vis national and international bodies active in statistics (like it already happens in Europe).

20 Challenges and opportunities for national statistical systems Experiment new approaches – The very high pace of technological and methodological developments, as well as the availability of new sources, require a growing capacity by NSOs to benefit from them. – Given the limited resources available, it is vital to join forces to experiment new approaches and exploit economies of scale. For example: the use of satellite images by a properly resourced central unit; the development of “experimental” statistics and indicators on some new SDGs domains, or of “early estimates” could be carried out at global or regional levels.

21 Challenges and opportunities for national statistical systems Experiment new approaches – It is vital that statistical offices and national statistical systems invest in continuous innovation to minimise costs and improve efficiency and the quality of services provided to users. – Modernization of national statistical systems should be broadly formulated in terms of mainstreaming principles and standards, strengthening institutional arrangements (including access and use of public and privately generated administrative data sources) and harmonizing and centralizing statistical production processes using a standard- based architecture.

22 Challenges and opportunities for national statistical systems Experiment new approaches – This approach would have important organisational and human resources implications: The IEAG Report recommended the establishment of a “SDGs lab” to carry out this kind of activities and exploit global data sources; Integrate statisticians and data scientists; Look at what Universities are doing in the development of courses in data science and modify, as needed, the EMOS syllabus.

23 The Global Partnership on Sustainable Development Data Support multi-stakeholder data initiatives that harness the data revolution to achieve the SDGs, focusing on building capacity to generate, share and use data at the country and local levels; Contribute to filling data gaps, including the production of novel data and dynamic visualizations of the best available existing data, to achieve the Global Goals; Help to develop and build support for international principles to harness the data revolution to achieve the Global Goals, including sharing and leveraging privately held data; Organise thematic, local, regional, and global data events to foster increased connectivity, collaboration and innovation towards achieving and measuring the SDGs. See more at: http://www.data4sdgs.org/#introhttp://www.data4sdgs.org/#intro

24 Important decisions to be taken Relationships between official statisticians and the Global Partnership The organization of the World Data Forum The establishment of a single website for SDGs indicators and data The establishment of a SDGs Data Lab … Europe should lead by example and be the frontrunner not only on SDGs, but also on data for SDGs


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