Author: Thomas König
The Corona Pandemic has highlighted the importance of scientific research in the social sciences and economics. Our lives radically changed due to the political measures introduced to curb the epidemic, and to know which measures worked (and which did not), scientific advice was instrumental. This was the background for the conference on evidence-based policy making held on last Thursday, on 27 May 2021, jointly organized by IHS, WIFO and CEU.
Even though it was not the inaugural networking event between the three institutions due to continued COVID-19 restrictions, the conference raised to the occasion, as it hosted several presentations highly relevant for policy making. Topics were clustered in areas such as “Global Crises and Policy Response”, “Data Driven Policy Making”, and “Labor Markets and Institutions”.
What is required to adequately advise, and inform, policymakers about scientific evidence in questions that are often also time-critical and sometimes publicly contested? What are the prerequisites to provide scientific evidence in a manner that is useful for policymakers yet at the same time in line with standards/best practices of scientific conduct? In the conference’s concluding panel, those and related questions were discussed by four eminent experts, whose statements are summarized in this blog entry. As such, this text also serves the purpose of documentation as well as a starting point for continued discussion.
Martin Kocher, Federal Minister, Austrian Ministry for Labor and formerly director at IHS, kicked off with the observation that evidence-based policymaking is often more than “just” scientists and policymakers, but involves also civil servants and the media. Given this complex incentive landscape, it should become clear that the objectives of those involved are different; that the timeframe in which these groups act are completely different (politicians usually thinking in weeks, if not days, while scientists thinking in months, if not years); and also that both group have very different responsibilities. Barbara Prainsack, professor of political science at University of Vienna, reminded the audience that data itself is not neutral but political in three ways: in the way it is collected (someone has to decide that it is worth investing resources in “datafying” a given social phenomenon), the way it is collected and standardized, and in the way it is interpreted (the part of the sciences, usually). While research based on more (empirical) data is certainly a good thing, we tend to forget the causes and reasons for why this data exists in the first place.
In his statement, Tobias Thomas, Director General of Statistics Austria and professor of economics at University of Düsseldorf, relayed back to CEU President’s opening statement on the “data revolution” and stressed the importance of independent national statistical institutes. He also pointed out the limits of politically meddling with data, vividly describing the situation in late Realsozialismus in the GDR where statistical data regularly showed strong economic growth while people had to queue in front of shops for almost every household good. In the end, as we all know, the daily collective experience of citizens undermined even the legitimacy of the seemingly objective data points. Last but not least, Thomas Starlinger, Security Advisor to the Federal President and high-ranking officer in the Austrian Armed Forces, reported from his efforts to create an independent forum of scientists and policymakers. The Future Operations Clearing Board consists of around 100 associated scientists and dozens of policymakers as well as civil servants. The latter group, Starlinger emphasized, is an often-underestimated player when it comes to efficiently and reliably taking up scientific evidence for decision-making.
Discussing publicly and openly current issues concerning the science-policy-interface with an actual minister (and former researcher), a retired minister and organizer, a director of the country’s central data producing hosting facility, and an eminent researcher working comparatively in health policies, is a seldom occasion in Austria. So, what were the conclusions from the ensuing and lively discussion between the panel members and the audience?
The first topic concerned learning – both on the side of policymakers (and civil servants) when it comes to accepting scientific evidence for their decision-making, but also on the side of scientists when it comes to understanding the logic of administrative and political processes rooted in democratic (and procedural) legitimization. An important consequence of this learning concerns the division of labor between scientists, policymakers, and civil servants. While the line may not always be easily drawn, it is important to understand that the role of the scientist is to advise, and not to decide. Another consequence of similar importance concerns the fact that scientific evidence is usually only one factor in the political decision making. A good example presented in the discussion concerned the regulation on the validity of different COVID-19 tests – scientific evidence indicates that a negative PCR test would allow for a longer period of being free to meet other people (“free testing”) than any other available test should do. But since testing facilities have developed differently across the nine Austrian provinces, it would have been politically unwise to impose starkly different periods of being free tested, and the political compromise settled somewhere in the middle.
Another topic, and hardly surprising, concerned data. The pandemic has revealed weaknesses not only in the data infrastructure of public health services in Austria, but also gaps when it comes to providing data for scientific inquiry. This has become particularly painful on the side of researchers who are, at the same time, working increasingly under a regime of immediacy (“rapid science”). The discussants all referred, in one way or another, to the urgent need to establish the long-promised Austrian Micro Data Center (AMDC), located at the premises of Statistics Austria, which will ensure robust and reliable data sets for accredited scientific organizations. Yet the scientific community would be well-advised not to perceive the AMDC – hopefully up and running by 2022 – as the solution to all its current data ailments, but rather as the starting point for carefully operationalizing the needs and opportunities of scientific research within the given legal framework and the institutional landscape in Austria.
One thing that became clear during the panel is that the debate along, and about, the science-policy-interface is only to begin. Data, while for Austria currently a particularly critical issue, is one of the topics around which this debate will (or should, ideally) revolve – but not the only one. As the conference on a whole successfully manifested, evidence-based policy making is a relevant concept for democracies in the 21st century, and the COVID-19 pandemic has, among many other things, only accelerated this insight also among policymakers. Yet it remains tremendously difficult to realize.