The trade-off between COVID deaths and the economy doesn’t seem to have materialised
The pandemic and its aftermath, like any challenging situation, has been full of trade-offs, for individuals as well as policy makers. Making the right calls has been particularly challenging, given the complexity of the data available, and the cognitive biases that leave humans somewhat lacking when it comes to propabilistic inference.
Early on, some of the policy debate internationally centered around the expected trade-off between the economy and the number of deaths from COVID-19. Surely, the logic went, if the only way to avoid a large number of excess deaths was to implement drastic social distancing measures, this would have a commensurate impact on economic growth? Different countries were seen to be striking this apparent balance in different ways.
There are whole books to be written about this one day, but what was clear from day one was that it was not sufficient to just consider economic and mortality outcomes (see e.g., here and here) but that broader wellbeing metrics were critical; and that there were other instruments in policy makers’ tool box, such as track and trace, vaccinations and other safety measures, that would drastically change the nature of any trade-offs.
It is therefore not surprising that, at the macro level, such a trade-off is also not visible in the statistics. The chart here shows, on the X-axis, the cumulative number of deaths per a million people in the population for each OECD country (for with quarterly GDP data was available for Q3 2021 at the time of writing). The Y-axis shows the cumulative loss in GDP by the end of the third quarter in 2021, relative to a counterfactual where GDP stayed flat from Q4 2019 onwards.
If there were a clear trade-off between GDP and deaths, then we would expect there to be an upward sloping pattern to how the countries stack up. In other words, the lower the losses in GDP (the higher the country on the Y-axis), the higher their death toll (further right on the X-axis ). In reality, we find gently downward sloping pattern, but more importantly, countries in all quadrants.
Yes, there are a few countries some with fairly high death numbers and low GDP losses (top right corner, e.g., the US and Poland), but there are also many countries with fairly low deaths and low GDP losses (top left corner, e.g., South Korea, Finland and Denmark). [Note that the industrial make-up, population density, and many other factors played a role in the degree to which countries’ output fell.] In fact, at least as many countries have exhibited both large losses in GDP and large numbers of deaths, with Spain, the Czech Republic and Hungary faring particluarly poorly.
Sweden, which is often discussed as a country to have taken a different path, with its lack of strict social distancing measures early in the pandemic, is in fact pretty average in terms of its death toll and with a slightly lower loss in GDP. However, these aggregate figures hide a few things that are important to understand in the Swedish context.
While famous for lack of nation-wide lockdowns, Sweden’s other COVID-related restrictions actually put it middle-of-the-pack for most of the pandemic period. Sweden’s overall “stringency index”, based on the Blavantnik School of Government methodology, was somewhat lower in April to June 2020, and again from July 2021 onwards, but otherwise very similar to the median among OECD countries. Even in the April to June 2020 period, Sweden’s international travel restrictions and measures to protect the elderly were more prominent than other OECD countries on average.
There will no doubt be further chapters to this story, given that infections — and overall death rates — are on the rise again in many OECD countries, prompting changes to COVID-19 related regulations and restrictions. For now, it seems that policy makers will need to continue to consider the full toolbox of measures available, and that economic output will continue fluctuate rollercoaster-like.