Uncertainty is an integral part of living. Human beings have always grappled with this complexity. People try to understand the consequences of their decisions, or what the future might throw up. Sometimes what is uncertain may reflect incomplete information or knowledge about the future; sometimes the future itself could be unknowable. For instance, ordinary citizens do not know what exactly is going on in the Indo-China border because they do not have the kind of information the Indian military has. Covid-19 and the course the disease will run remain unknowable.
However, statisticians will use available data and make probabilistic forecasts on such issues. A critique of the quality of these forecasts and the methodology used by statisticians, business analysts, financial managers and, above all, the tribe of mainstream economists comprise the subject of this absorbing book. John Kay and Mervyn King are professional economists with experience in academics, public policy-making and private sector consulting. Their contention is that the overwhelming majority of statistical exercises are based on the presumption of a stationary world where things do not change. However, the future is unknowable because things change in a fashion which one has no idea of. This is what the authors describe as radical uncertainty.
The book is filled with wonderful examples of the limitations of forecasts. To give one example, consider a horse race with a particular horse likely to win with a chance of 90 per cent. The authors ask the question: how is this number arrived at? There is no data that can predict a trend on the particular race being run a number of times, with the same jockey and the same contestants in the same course with the same weather. What do gamblers do? They, the authors argue convincingly, put together a story about the horse, its health, the jockey’s past performances in different circumstances and the other horses comprising the field and so on. No one decides on the basis of a number alone. They need compelling stories to justify their decision. Different gamblers will construct different stories.
Radical Uncertainty by John Kay and Mervyn King, The Bridge Street, Rs 799 Amazon
A running theme in the book is based on what a professor at a business school asks his class when presenting a case-study based on real-life data: what is going on here? That appears to be the most searching question in comprehending a situation and drawing predictions. Economists use statistics on the assumption that the world is stationary and linear so that small changes can be scaled up to make predictions. In the social sciences and the world of business, there is frequent use of the words, ‘risk’, ‘uncertainty’ and ‘rational decision-making’. These words are given a technical meaning and a quantifiable measure that are different from the everyday use of these words as understood by ordinary people. In most cases, we simply do not know what the risk or future outcomes are, reflecting the presence of radical uncertainty.
There is an interesting example from cricket. Usually, team-mates wish a batsman good luck when he goes in to bat. They would say ‘bad luck’ if the batsman failed. One captain stopped the wishing, claiming that luck had no role and it is purely a batsman’s skills that make him succeed or fail. However, it is quite true that despite the best of skills there are a million reasons why a batsman may fail, most of which may be beyond his control. It is radical uncertainty that is the culprit.
This book can be read as a wide-ranging history of probability theory, statistical reasoning, basic mainstream economics and finance. It is interspersed with innumerable examples from almost all branches of knowledge and everyday life. It is a fascinating book but, unfortunately, not for the uninitiated in basic statistics and economics.
