Why should there still be a need for elaborate official statistics in the future?

Official Statistics on a laptop

The second discussion will center around statements taken from an article by Walter Radermacher Governing-by-the-numbers / Statistical Governance Reflections on the future of official statistics in a digital and globalised society, published in the December 2019 issue (Vol 35, number 4). You are invited to discuss the main or detailed statement(s).

Data are given – Facts are produced

'Governing-by-the-numbers / Statistical Governance Reflections on the future of official statistics in a digital and globalised society by Walter Radermacher can be read here: https://content.iospress.com/articles/statistical-journal-of-the-iaos/sji190562

Main statement for discussion:

Data are given – Facts are produced

In the long run, trust in official statistics can only be maintained based on a continual striving for the best quality, with leadership based on profound knowledge of the business and with customer orientation as the supreme orientation. This implies that statistical products must meet the expectations of users in their design, production and communication.

Other subsidiary statements to be discussed are:

Between a data gold-rush and the death of truth

Official statistics will be under attack either by discussions on trust or by competition from statistics produced with lower quality. For official statisticians to be needed in the future, they have to be more than just data engineers. They must know the DNA of their business and use their capital (especially their know-how and internationally agreed methodological standards) to develop a market-oriented strategy. Official statistics has to be policy-relevant without being driven by politics.

Civil society’s role

Civil society should be more closely involved in official statistics, be it through participation in indicator design processes, through crowd-sourcing of data or as a partner in communication.

The power of numbers will increase dynamically with new data sources and technologies, which calls for an informational governance at both national and international level. Official statistics can and must claim a decisive role in this governance. A global organisation of professional statisticians anchored in civil society should develop a suitable indicator to measure and monitor the independence and integrity of statistics in individual countries.

Closing the scientific gap

There is a lack of scientific research, suitable textbooks and qualified training courses for official statistics. A scientifically founded, conceptual operationalisation of statistical processes, be it in data collection, national accounts or the generation of indicators, requires more than the knowledge of specific statistical methods or data sciences. Rather, aspects from other fields, such as sociology, historical, or legal disciplines have to be taken on board. There are many different strands of science contributing to research on processes of quantification and the impact of quantification within social contexts.


Comment on:
20/12/2019 11h22

A very wide ranging paper. There is so much to react to, it's hard to know where to start.

I found the remark that EBPM is a tautology in enlightened democratic societies fascinating. I had to pause and think about that. In the end, I guess it is probably is, but it wasn't always so. So, I guess that change in and of itself is a mini data revolution. Unfortunately, the enlightenment may be shorter lived than we had hoped.

But there are really 2 points I want to react to:

The first is regarding statistical literacy and closing the scientific gap. In the paper Walter notes that 'statistical competence and literacy must not be reduced to mathematical-technical skills. Rather, it also requires an understanding of the fundamentals of the humanities' (p. 523). I was so happy to read this. I could not agree more. I presented a paper at the ISI this year, effectively, but less eloquently and succinctly, making the same point. This is of profound importance to any debate on the topic.

The second issue is the role of civil society. This links directly to our paper posted on the first discussion platform. How do we co-design and co-produce? In general I agree with the thesis being proposed by Walter. I think in an era of rapidly globalizing data, the question posed 'whether the statistical governance structures dating back to the discussions of the 1990s, which focused on nationally organized public administrations of statistics...still meet today's challenges' (p.533) is a huge issue. In some recent papers, I have asked the same question. This is obviously a very sensitive issue, but it is one that surely needs to be discussed. Where I hesitate slightly, is the idea that the 'separation between the producers and the consumers of statistics needs to be removed' to create 'prosumers' (p.513). While I understand the sentiment and without question greater participation in design is the way forward, But I'm still inclined to think that some separation between production and consumption is safer for everyone.

These are my initial reactions. Congratulations on a very thought provoking paper.




Comment on:
05/01/2020 21h22

Congratulations to the author! Indeed a thought-provoking paper with a lot of issues of relevance for statistics in a very unstable, fragmented, digitised and globalising world with in some quarters an anti-science, and anti- (expert) knowledge attitude. I will give some general comments or better ideas, that were induced by reading the paper and then give some concrete reactions to the topics raised.
Of course, statistics and science in general cannot solve all the ills of society but at least we can try to keep our house (statistics) in order and keep it tidy. One of the main issues that emerge in the paper and also in the issues for discussion is the right focus. It is fashionable to see statistic as an a business enterprise with products that the customers (clients) need or want. The objective of business is to make a profit; statistics are common goods and should be freely available to all sectors of society. There is therefore an inherent conflict between these two views! I personally see the production of official statistics as part of public administration, which requires a special status (see Fundamental principles) to perform optimally!
On several occasions Walter mentions the need for epistemology bring some order in the chaos. I fully agree and will go further and state that what is needed is that all statisticians, or all academics for that matter, have a clear understanding on the nature and principles of science in general and of the main institutions and sectors of their society. What is required is a solid education in the principles of sciences (logic, ontology, epistemology and methodology) so that statisticians will be able to develop proper definitions, systems of reasoning, avoid tautologies and fallacies.
Whether we like it or not statistics has a fundamental mathematical underpinning and we can basically make a distinction between theoretical (mathematical) statistics and applied statistics, statistics used in a wide variety of disciplines. Official statistics are just statistics provided by governments, which are needed for society to function properly. The statistics required have to reflect the needs of the society as a whole and not just what the government of the day would like, and yes, it needs the input of all relevant sectors, or to use a fashionable term, stakeholders. There are several mechanisms in place to receive the input of society (or stakeholders) in the national statistical needs or national programmes. Now, there are criteria, which hopefully are explicit and known to stakeholders, what could and could not be part of a national statistical programme that will be carried out by the national statistical system. Some topics of interest to specific sectors or sub-groups in society may not qualify, and for which ad hic research projects could be developed by other professional organisations. Also, often vocal sectors of societies against the results of statistical exercises are often those that do not participate in the definition and shaping of the national statistical needs programmes.
There are two main issues we have to deal with, 1. Who is a statistician, and 2. What is the subject matter of statistics?
Until recently statisticians were persons with a specific training (academic or professional) in statistics, either as the general science of statistics or a specific type of application (remember actuarial science and actuaries) or in a specific discipline (astronomy, agriculture, health sociology, economics, etc.). Now, basically everybody who uses statistical techniques or data is considered a statistician, irrespective of their background or training. Remember some statistical packages claim that to apply some rather sophisticated statistical technique one does not need to have studied statistics!
There are myriads of definitions of what statistics as a profession or science is and also what statistics are. Not everybody may agree but statistics as a science (free to Fisher) may be considered as the application of mathematical principles to observational data, of populations (any collections of objects) with the aim to study (describer and explain) their variations, interrelations and causes and the reduction of the masses of data. Statistics are series of numerical values of objects (parts of populations, hence calculated values (facts) of characteristics of society or the universe affected by multiple causes (free to Yule)).
Based on the above, not every number is a statistic! Statistics are constructed or calculated numerical values of characteristics of a unit of observation that derive their meaning from a conceptual framework, that have probability distributions, and are time and location specific. Statistics that are confirmed over time and different location may become (scientific) facts.
Now some remarks on the items for discussion:
Although I like the article very much for the issues to present, I do not share the sales pitch of “'Governing-by-the-numbers”. Numbers have no intrinsic meaning; they acquire meaning only when they are linked with an object. The statement “You ow me 100” means nothing. It becomes interesting when we know that 100 could means dollars, euros or ounces of gold! It is better to state “Governing by statistics”.
Main item:
Indeed data are given facts are produced. Data are the raw material for statistics,. However it takes a long time for facts, scientific facts, to be established hence it is more prudent to start governing using good statistics!.
There is a need for authoritative statistics, and society needs “official statistics” and a system that produces them free from interference by governments and societal groups. What is needed is an autonomous national statistical system headed by an independent National Statistical Authority, and bringing together national statistical data producers, Government agencies, but also, (why not?), academic research institutions that produce the required data of an flexible but comprehensive programme established through dialogue and consultation of all sectors of society. One key issue for such a system is the necessary financial resources to ensure that it is truly autonomous.
Secondary items
Trust in official statistics.
The level of professionalism or adherence scientific principles of the data producers and transparent and comprehensive communication of the data and their limitation are key elements to create trust in the national statistical system.

New data sources
Statisticians should be weary of being swept away by the lure of new sources of data and should carefully study what these new sources are and how they could fit the requirements of the national statistical system and how well these new sources abide by the principles of science.

Closing the gap.
Official statistics is not a special field of statistics; trey can be of any areas of science provided that they are produced by the system that provides the “official” label. Up to now it is government produced statistics, but if the national system under a national statistical authority is created and operated they will be responsible for the official statistics.
Up to now official statistics is part of the public administration. In public administration as a domain of action, research and study there are a many different monographs, guidelines and studies dealing with all aspects of public administration. There is even a Handbook of Research Methods in Public Administration as part of a Comprehensive Publication Program; some of the publications in this series answer part of the concerns presented by Walther. See the Public Administration And Public Policy programme of the CRC Press of the Taylor & Francis Group.



Comment on:
06/01/2020 13h51

There’s a lot in Walter’s paper that many of us have been thinking about and saying for years.

However I’m struggling with his point on the lack of textbooks and training material. On the one hand we all know that there is a general problem of statistical literacy on the user side, but is the same true on the producer side? Official statistics is something of a niche business and even within it there are some even more niche areas. It’s difficult to see how this could be done in an efficient manner. Who would be responsible? How much would it cost? What is the market for the proposed textbooks? Where does this fit into a very long priority list? Where do we start? And… where do we stop?

Yes, there is a skills shortage that continually needs to be addressed, but the official statistical community has worked well in this, given resources and priority constraints, through co-operation programmes, existing training initiatives, institutions like IOAS and a plethora of manuals and handbooks. In niche areas, where there are so few experts, one-on-one training though getting them together is an efficient solution and this approach has been particularly successful in national twinning schemes.



Comment on:
19/01/2020 23h16

This is a thoughtful paper that addresses many challenges that official statistics face. I liked especially the double focus on the production and use of numbers/indicators, both related through the notion of a statistical chain. With regard to the use of indicators I fully agree that there should be more "market research". Probably that could be a fruitful field of cooperation between academia official statistical institutes.

Furthermore the triangle representing Data, Facts and Politics seems to work well for going through their relationships in a systematic way. Yet, their graphical depiction (showing reciprocal and symmetrical arrows going from one corner of the triangle to the other) could be misleading, in particular with regard to the relationship between data and policy. I guess - and this is rather in agreement with the text itself - the arrow should point from policy to data only.

The author bemoans that very often raw data and the facts resulting from them are both labelled "data", the triangle suggests that there could be a fruitful and direct relationship between data and policy. I agree that such a relationship is often imagined, such as in the catchphrase Data for Policy (D4P) that relates basically to new (digital) data sources and also to political expectations towards our assumed data wealth. However, such a direct relationship seems to be rather ficticious. Raw data typically requires laborious steps of refinement - among that I would also count what the text called 'experimental statistics' - before "facts" can be derived. Although it might not be impossible to fully automatize these stages of refinement, the automatization itself requires time, methodological decisions and the explication of correspondence rules that assure the validity of aspired "facts". When these correspondence rules stand the test of professional reflection and critique, results can legimitately be regarded as "facts".

Hence, different from what the figure of the triangle suggests, I would argue that "data" that seem to intuitively speak to laypeople as "facts", indeed invisibilise the professional and institutional work of sens-making that has been invested into them. I think that there is no shortcut from data to policy or politics without serious efforts of sense-making. But that is rather a call for more "reasearch-and-development" with regard to new "raw data" sources and does not preclude that the resulting facts might drive politics or policy at some point in the future.