Economic Theory

Scientism and the Coronavirus Pandemic:  A Hayekian View

The reactions of much of the commentariat in the UK and elsewhere to the policy challenge represented by the coronavirus seem to reflect the polarised state of contemporary political discourse. Some maintain that governments were too slow in responding to the pandemic and that lockdowns when they came should have been more rigorously enforced. Then there are the ‘lock-down sceptics’ who proclaim that lock-down policies have been a waste of time or worse a disaster in health and economic terms. Elsewhere, those who position themselves as more ‘moderate’ voices advocate contact tracing and the wearing of face coverings as central to any policy solution. What seems to unite all these positions, however, is the belief that there are in fact clear and objectively identifiable ‘solutions’ to the problem – if only policymakers would see them and act accordingly.

In my new IEA briefing paper “The response to the pandemic: A Hayekian view”, I offer a different perspective on the pandemic. What if the nature of the problem is such that neither commentators nor policymakers can know enough to discern what an effective response might entail? This view draws on Hayek’s distinction between simple and complex phenomena and its significance for understanding the role and the limits of public policy. In a Hayekian view, the belief that there are clearly identifiable solutions to problems such as the coronavirus may stem from a misplaced ‘scientism’. This does not imply criticising the scientific method or ‘expert knowledge’ per se. Rather, it follows from the use of scientific reasoning to understand the limits of what scientific expertise – whether natural or social scientific – can achieve. Too much commentary on the pandemic proceeds as if we are dealing with a ‘simple’ rather than a ‘complex’ phenomenon and it is this ‘scientistic’ attitude which may be inappropriate to the challenge at hand.

Simple phenomena are those where it may be possible to predict the outcomes that will be generated by the application of a stimulus into a system. Complex phenomena however refer to systems where the elements that make up a greater whole do not interact in a linear fashion and where the number of interacting elements is too vast for them to be comprehended. The most that natural scientists, social scientists – and by extension policy-makers – can do when faced with such phenomena is to try to understand the general principles that allow an order to form between the various elements – such as how snowflakes form, or how prices are generated in a market – not to predict successfully the precise form the order will take.

In the case of the coronavirus we may be dealing with the interaction of two complex phenomena which makes the task of predicting the effect of policy interventions even more pronounced. The virus itself may be a complex phenomenon with unpredictable responses to differences in geography, weather and to public policy interventions. Equally, the socio-economic systems in which policymakers and the virus are ‘intervening’ are themselves complex phenomena with differences in economic, cultural and institutional circumstances generating a high level of unpredictability about the effectiveness of particular policy measures.

The lesson that a Hayekian perspective takes from the science of complexity is that in order to cope with such phenomena one should focus on developing institutions that enable flexibility in responding to an uncertain environment and that generate clear feedback signals at the most decentralised level to indicate the necessary direction of change. If the knowledge needed to coordinate effectively is too vast and uncertain to be surveyed and acted upon by any one centre of control we are better off relying on competitive processes such as markets, or decentralised governance regimes such as federal political systems to allow successful experiments to emerge through a bottom-up process. The problem, however, is that the ‘emergency’ nature of the pandemic and the public goods problems associated with infectious diseases may prevent such decentralised solutions from arising. The most we may be able to do in these circumstances, therefore, is to compare and contrast the effectiveness of the different policy responses adopted by different nation states. Yet here too because of the complexity of the issue there may be a massive ‘signal extraction problem’ involved. To recognise that Switzerland or Germany have managed an effective response does not necessarily make it easy to judge which ‘bits’ of their political institutional environment are responsible for the success and whether these might be transferred effectively to the cultural and institutional contexts of France, Italy or the UK. Moreover, even if it is possible to discern from such comparisons ‘what works’, given the emergency nature of the pandemic, it may not be possible to implement any changes with sufficient speed or to discern whether these lessons have relevance to a future pandemic which might be characterised by very different parameters.

The upshot of all this is that we should perhaps recognise that policymakers are working in a fog of ignorance and that successful responses to the pandemic may owe as much to accident as to design.   If commentators were to show more appreciation of Hayek’s distinction between simple and complex systems and cut each other and policymakers some slack that might perhaps create a more informed and tolerant platform for public debate – not only with respect to the coronavirus pandemic but to a host of other socio-economic challenges as well.


Suggestions for further reading:

Mark Pennington is Professor of Political Economy and Public Policy at the Department of Political Economy, King’s College, University of London. Among many other publications he is the author of Robust Political Economy: Classical Liberalism and the Future of Public Policy (Edward Elgar, 2011), and for the IEA, Liberating the Land: the case for private land use planning (2002).

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