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The costs of lockdown can no longer be justified

The costs of lockdown can no longer be justified

In an otherwise depressing week, two pieces of very good news emerged from India.

In Mumbai, blood tests conducted by the city authorities on 6,936 randomly selected people found that some 40 per cent had coronavirus antibodies. Just 6,000 deaths have been reported so far in a city of 20 million.

A similar exercise in Delhi (population 29 million) found that around a quarter had had the virus. Only 3,300 deaths have been attributed to Covid-19.

Indian experts are clear about what these figures mean. Asymptomatic infections are a high proportion of the total. Further, the virus death rate is “very low”, to quote the Mumbai study.

These studies fit in with a mounting body of evidence that the virus is nowhere near as deadly as first thought. Even the cautious Centers for Disease Control and Prevention (CDC) in America has revised its estimate of the mortality rate down to 0.26 per cent — comparable to a bad influenza year.

Casting our minds back to the middle of March, the picture seemed completely different. Data from Wuhan suggested that the death rate was between three and four per cent. Our television screens were full of images of the health system in northern Italy being overwhelmed.

Given this particular set of information, it was perfectly understandable for the government to impose a lockdown. Behaviour was already changing rapidly in a spontaneous fashion as people voluntarily limited their social contact, but it would still have been very difficult at the time for the government not to take the action it did.

One of the most balanced set of commentaries throughout the whole crisis has been provided by Professor Carl Heneghan and his team at the Oxford University Centre for Evidence Based Medicine.

It was Heneghan, for example, who recently exposed the fact that Public Health England (PHE) did not let anyone recover from Covid-19 — at least not on paper. If you had recovered from the disease and were subsequently killed in a car crash, say, according to PHE data you died from the virus.

The Centre’s work shows that since the week of 14 June, total deaths in England and Wales have been running below their five-year average — despite an apparent upsurge in Covid cases.

Heneghan’s latest research even casts serious doubt on whether the true number of new cases has in fact risen.

On a technical point, the reported number of new cases follows a fairly shallow upward linear trend — not the exponential rise which would characterise a genuine second wave.

His key point, however, is that the number of tests has increased. Once this is taken into account, the rise in cases disappears completely. On the basis of personal knowledge, I can confirm that this seems to have happened in Rochdale in Greater Manchester. The Council installed walk-in test facilities in the town centre. Shortly afterwards, the number of reported new cases rose.

Covid-19 can be highly unpleasant and it retains the capacity to kill, so it is sensible to take precautions to avoid getting it. But the massive costs of lockdown — both economic and social — can no longer be justified.

As published in City AM Wednesday 5th August 2020
Image: Post Lockdown by Bastian Greshake Tzovaras  via Flickr  CC BY-SA 2.0
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Great expectations: The Darwinian wars of economic and epidemiological forecasting

Great expectations: The Darwinian wars of economic and epidemiological forecasting

A key concept in modern economics is, to use the jargon term, rational expectations.

The idea has dominated orthodox macroeconomics over the past 30 years. Not all economists have been persuaded of its merits by any means, but nevertheless, its influence has extended far beyond academia, into finance ministries and central banks around the world.

The basic idea is simple, even though the maths of the macroeconomic models which use rational expectations can rapidly become hair-raising.

When forming a view about the future, an individual chooses the model which best describes how the economy works. It is then simply a matter of running the model and using the values which it outputs as your expectations.

An obvious criticism seems to be that economic forecasts are very often wrong, but this is easily handled by the rational expectations enthusiasts. Each individual forecast in a sequence of months or years can be wrong. The key thing is that the errors over time cancel out. On average over time, the forecasts are correct.

The idea is not as absurd as it may appear to the layperson. For example, the Federal Reserve Bank of Philadelphia has published the Survey of Professional Forecasters since 1968.

This does what it describes on the label. It takes a wide range of forecasts by academic, commercial, financial and governmental bodies. Information on the average forecast for, say, GDP growth one year ahead is published, as well as details of the spread around the average.

Remarkably — and exactly in line with rational expectations — comparing the predictions with the actual growth over many years, the errors do indeed balance out. Spectacular errors have been made for individual years, but the over and under-predictions cancel out over time.

A more telling attack is that economists themselves do not seem to agree on what constitutes the correct model of the macroeconomy. Different groups have different models.

The standard defence is that the best model will eventually prove its superiority and will drive the others out of existence. But the problem here is that this has just not happened.

The concept of rational expectations can be applied directly to the predictions of the epidemiological models. These purport to describe how a virus spreads. So to form a view about the future, make a set of assumptions about the key inputs, and use the forecasts generated by the model.

It should be much easier in epidemiology for the best model to eliminate its competitors than it is in economics. Economics has a wide range of variables to predict, such as inflation, GDP, unemployment, public borrowing, interest rates. The focus of epidemic predictions is much narrower and their models are in general mathematically simpler than those of economics.

The Covid pandemic set up a competition between epidemiological modelling groups of fierce Darwinian intensity. The efforts of many years of academic debate have been concentrated into a handful of months.

But no group seems to have admitted yet that its model is not up to scratch — and huge differences in forecasts persist.

As published in City AM Wednesday 29th July 2020
Image: Opposites via Pxfuel
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