John Longworth is a businessman and entrepreneur, Chairman of the Foundation for Independence and of the Independent Business Network, and a former MEP for the Brexit Party and the Conservatives.
I must confess that I have always had a preference for evidence-based decision making – perhaps that is the scientist in me, for I started out as a scientist. Having said that, as an entrepreneur, businessman and (I hesitate to say) politician, I soon came to realise that evidence can be a scarce commodity, in which case judgement and the acceptance of risk comes to the fore.
“Fortune favours the brave” – andit is the brave who have been responsible for most human progress and prosperity. Creative destruction is the primordial soup of growth and development. Only by innovation, through ideas, can humanity prosper and sustain itself.
We live in a strange era – one in which there is an almost religious reliance on the mathematical model, a belief in “science” and the model-backed “expert” . At the same time, there is an aversion to risk. It is as if, in the western world at least, humankind has retreated to a garden of Eden in which everything is predictable. This state of affairs has been made more meaningful by the fact that so few among our elites have any knowledge of science.
At its basic level, science is a discipline based on hypothesis and experiment – or at least the stress-testing of propositions. Unfortunately, the world of the “model” has created a fiction whereby those especially in such pseudo-sciences such as economics and sociology predict the future via apparently immutable mathematics: man-made models of the world, as if man were God.
These models are based on a series of assumptions which can easily fall victim to bias based on the thinking framework of the modeller – so the assumptions effectively drive the outcomes.
Simplistically, for example: that we will die if CO2 emissions do not cease; that the economy will crash without austerity or that there will be a massive death toll without lockdowns. These assumptions may not be based on reality, and experience may contradict them. These models also depend upon data. So the quality of the data input is crucial. The modelling adage of “garbage in, garbage out” holds true even for the most sophisticated of constructs. Politicians and the media worship unquestioningly at the altar of the model as if it had religious certainty.
This state of affairs has brought misery, poverty and destabilisation to the world, and it must stop. Much more reliable than the model is practical experience or testing hypotheses. Models should only guide policy-making, and it is the examination of practical application that informs.
There are three particular areas of recent activity in which the reliance on models has served us badly.
First, the pandemic produced a textbook example of the flaws of models. There is an avalanche of evidence suggesting that the use of models produced lockdown policy decisions which then led to excess deaths from other causes – far outstripping the risk from Covid itself, and producing major economic disruption which then to huge costs, not least through austerity policies, including tax increases and spending cuts which will damage economic growth and healthcare provision for years to come.
An alternative, practical experiment was available right at the commencement of the Covid episode which would have shown the true risk of morbidity and death across age groups of unvaccinated people – that of
the cruise liner locked down at the start of the pandemic. This was a petri dish far more reliable than any model, and showed a very different picture to that portrayed by the Imperial College model relied upon by SAGE and our political leaders.
A second example of the stupidity of models as a basis of policy making is that of climate change. The cost of reacting to these is enormous, both financially and politically, and is creating a cost of living and security crisis in the U.K. as we adopt misguided and expensive compliance policies. Furthermore, there is ample evidence from history of the existence of climate change and its causes. Practical, empirical evidence which is much more reliable than relying on forecasting “models” alone.
A third area in which “models” have come to prevail in respect of forecasting and therefore policy making is in economics. I remember in a previous post when head of the British Chambers of Commerce that we would await with anticipation for the published new year results ranking the performance of a range of organisations in their forecasting of the previous year’s economic performance of the U.K.
The chambers often did relatively well, since our own were based not only on a model but on data from businesses around the country. Many organisations, including the International Monetary Fund, OECD, Office for Budget Responsibility, Bank of England and Treasury often did badly in practice – sometimes appallingly. Yet Government policy is based on these models. So we now have a doom loop policy of austerity rather than growth.
A better approach would be to look at what has worked in the past in similar circumstances, or which can be modified to fit the present. Growthenomics, for example, worked well following the First World War and flu pandemic. However, following the Hong Kong flu pandemic of 1969 and the energy price shock, the austerity of the 1970’s was a disaster. Only later under Nigel Lawson did growthenomics provide a boost. Similarly, Ronald Reagan successfully boosted the economy via a growth package following on from an energy cost squeeze.
(Of course Margaret Thatcher teed up the Lawson boom with an initial dose of austerity in order to control inflation and wrest control of the nation from the trade unions. She soon realised that growth was the answer.)
However, the situation now is very different with inflation largely caused by a one-off, global event akin to a war: Covid – exacerbated by the real war in the Ukraine. Britain could have side-stepped the worst effects of it by utilising our energy resources rather than virtue signalling in favour of Net Zero. The lessons from history are powerful and real.
The moral of this story is that models provide interesting context – a little like horoscopes. But when it comes to decision-making, give me an economic historian in preference to a model any day.
Models are in danger of becoming a new religion. Science is a generator of hypotheses to be tested in practice and against previous practice – and no more. Decision-makers need to be prepared to question the cult of models. The media also require much more understanding. Practical knowledge, and an appreciation of what has previously taken place, or is happening in practice, is vitally important. Good Judgement is key. The cost of abrogating responsibility to models is huge.
John Longworth is a businessman and entrepreneur, Chairman of the Foundation for Independence and of the Independent Business Network, and a former MEP for the Brexit Party and the Conservatives.
I must confess that I have always had a preference for evidence-based decision making – perhaps that is the scientist in me, for I started out as a scientist. Having said that, as an entrepreneur, businessman and (I hesitate to say) politician, I soon came to realise that evidence can be a scarce commodity, in which case judgement and the acceptance of risk comes to the fore.
“Fortune favours the brave” – andit is the brave who have been responsible for most human progress and prosperity. Creative destruction is the primordial soup of growth and development. Only by innovation, through ideas, can humanity prosper and sustain itself.
We live in a strange era – one in which there is an almost religious reliance on the mathematical model, a belief in “science” and the model-backed “expert” . At the same time, there is an aversion to risk. It is as if, in the western world at least, humankind has retreated to a garden of Eden in which everything is predictable. This state of affairs has been made more meaningful by the fact that so few among our elites have any knowledge of science.
At its basic level, science is a discipline based on hypothesis and experiment – or at least the stress-testing of propositions. Unfortunately, the world of the “model” has created a fiction whereby those especially in such pseudo-sciences such as economics and sociology predict the future via apparently immutable mathematics: man-made models of the world, as if man were God.
These models are based on a series of assumptions which can easily fall victim to bias based on the thinking framework of the modeller – so the assumptions effectively drive the outcomes.
Simplistically, for example: that we will die if CO2 emissions do not cease; that the economy will crash without austerity or that there will be a massive death toll without lockdowns. These assumptions may not be based on reality, and experience may contradict them. These models also depend upon data. So the quality of the data input is crucial. The modelling adage of “garbage in, garbage out” holds true even for the most sophisticated of constructs. Politicians and the media worship unquestioningly at the altar of the model as if it had religious certainty.