04.05.2021 - Comments
The #allesdichtmachen campaign, a series of short videos recently published by German actors, has sparked fierce controversy. Critics have accused the actors of hatred for mocking the lockdowns. From an economic perspective, however, the campaign can be interpreted as a response to Germany's inefficient pandemic policy, which has relied on extensive lockdowns and resulted in high economic costs.
Last year's lockdowns restricted civil liberties around the world to contain the coronavirus pandemic. To ultimate goal of reducing social contact was to save lives by breaking infection chains and thereby preventing the breakdown of the healthcare system. The government interventions resulted in people being impeded from economic activity and consumption, which in the aggregate is reflected in a decline of the gross domestic product (GDP). The assumption behind this argument is that there is a trade-off between protecting human lives on the one hand and protecting the economy on the other. Is this assumption correct?
Excess mortality, the ratio of deaths in one year and the average of the previous five years, shows the deadly consequences of the corona pandemic.1 It was highest in the Americas (Brazil +22.3 %, USA +19.5 %). In Norway (-0.6 %) and New Zealand (-0.5 %), however, fewer people died than in previous years. Even with an excess mortality of +4.8 %, Germany is one of the less affected countries.
The highest economic loss in terms of gross domestic product (GDP) occurred in Europe, with a decline of 10.8 % in Spain and 9.8 % in the United Kingdom. Taiwan, on the other hand, even reported economic growth of +3.1 %. The German economy declined by -5.3 % in the same period. The economic losses represent individual lives, which are physically, psychologically, and financially burdened by the lockdown and its direct and indirect consequences. The campaign #alledichtmachen shows this in one of the most severely affected professions.
According to the narrative of economic and social sacrifice to reduce excess mortality, excess mortality should decline with the magnitude of the economic costs. Figure 1 plots GDP loss (horizontal axis) against excess mortality (vertical axis). The further to the right a country is located, the higher are the economic and social costs. The higher it is situated, the greater was the excess mortality.
The trade-off, which would be reflected by an inverse relationship, is not clear in our international comparison. Contrary to the narrative, various countries are in the top-right (e.g., Italy, the United Kingdom, and Spain) or in the bottom-left (e.g., Taiwan, New Zealand, and Australia) of the chart. The countries at the top-right corner have high economic and social costs, but also high excess mortality. Here, the economic sacrifice did not prevent the loss of lives. The countries in the bottom-left were spared and enjoyed both low economic and social costs as well as low excess mortality.
A simple eyeballing of the scatter plot even suggests a positive relationship between economic costs and excess mortality.2 This would support the opposing narrative that any kind of lockdown with severe economic consequences is not an effective measure to prevent excess mortality in a country. The question arises as to why the expected negative trade-off cannot be found in our simple cross-country comparisons.
Differences in the level of development across countries could explain both the variation in excess mortality and the GDP decline in 2020. First, a country's low level of development is usually associated with poorer medical care. When an infectious disease outbreak occurs, a health system's capacity is quickly exhausted, increasing excess mortality. Second, lockdowns might have a stronger impact on the GDP of countries with a lower development stance because poorer countries tend to have more fragile economic structures (tourism vs. industry) and less widespread social systems to compensate for income losses. Thus, it could be that the relationship observed above between high GDP loss and high excess mortality mainly reflects differences in the level of development of the countries. After adjusting for the differences in the development stage, it might be possible to document the inverse relationship of the lockdown narratives after all.
Figure 2 shows the relationship between excess mortality and GDP loss, controlling for the differences in development levels measured by per capita income at purchasing power parity in 2018.3 The expected inverse relationship described above is also not observable. Instead, the positive correlation remained equally strong.4
The fact that there is a positive correlation between economic loss and excess mortality even after the statistical adjustment for the level of development points towards other factors that must be considered to better understand this positive correlation. Not only specific political decisions affect economic costs and excess mortality but also the general conditions over which decision-makers cannot exert any influence.
From an epidemiological perspective, the initial transmission chains in a country as well as the timing, duration, and intensity of subsequent policy responses, among other factors, play a significant role in determining the further course of the pandemic and the resulting number of deaths and economic costs.5 This is illustrated by the comparable economic costs caused by lockdowns in France and Italy. A preventive lockdown in France resulted in moderate excess mortality, while in Italy the lockdown was a response to a high numbers of cases and high excess mortality.
Long lockdowns are also associated with high social costs. Lockdown fatigue could therefore also help to explain the observed positive correlation. With the duration and intensity of lockdowns, the acceptance of the measures by the population decreases, but the economic costs continue to rise.6
Other non-pharmaceutical intervention measures, such as digital contact tracing and wearing masks, have little economic cost, but may mitigate excess mortality more efficiently.7 8 Comparing East Asian countries, Australia, and New Zealand with Europe suggests that, despite differences in context, ineffective pandemic control may have additionally contributed to higher excess mortality and economic losses.
Politically unchangeable circumstances, such as the length of infection chains to vulnerable populations (for example, due to social structures, housing conditions, culture, and hygiene standards), but also climatic conditions, geographic circumstances such as natural national borders, and viral mutations can influence a country's vulnerability to pandemic-related excess mortality but also economic costs.9
Finally, statistically all countries belong to the "treatment group" because either a lockdown was imposed in one country or lockdowns in other countries affected the change in their own economic growth. Therefore, it is impossible to conclude from the data how economic growth would have evolved had no lockdown measures been imposed and only voluntary behavioral and consumption changes had determined excess mortality and economic performance.
In the common narrative of economic sacrifice, lockdowns are imposed, and negative economic and social consequences are accepted in order to protect human lives. But the data does not confirm this. A simple international comparison between GDP loss and excess mortality in 2020 shows no trade-off. Furthermore, the relationship between the two measures is positive.
The relationship of high excess mortality and high economic losses may depend on circumstances that policy makers and society cannot influence. However, the positive relationship may also be due to ineffective policies to prevent chains of infection. While in some countries lockdowns did broke infection chains in others they have yielded few results and caused unnecessary economic and social pain.
In this respect, the #allesdichtmachen campaign can be interpreted as a response to the inefficiencies of German pandemic policy associated with lockdowns and high economic costs. Hopefully, in the future, people will no longer be burdened by lockdowns, as sufficient protection against excess mortality is achieved through vaccination progress.
1 For a discussion of the "excess mortality" metric, see Immenkötter (2020) and Our World in Data. The number of people who tested positive and died only incompletely describes the impact of the pandemic on human lives, since, among other things, not all Covid-19-related deaths are recorded worldwide, but human lives may also be lost due to lockdowns.
2 A simple linear regression shows a statistically significant positive correlation of 0.87 (p-value 0.015).
3 The values shown represent the residuals of a linear regression of GDP decline on GDP per capita and the residuals of a regression of excess mortality on GDP per capita. The corresponding residuals can be interpreted in each case as GDP loss minus the effect of the level of development, or excess mortality minus the effect of the level of development.
4 The correlation between the two variables is 0.83 compared to 0.87 above.
6 See Goldstein et al. (2021).
7 See Ferretti et al (2020).
9 See, for example, Bayer and Kuhn (2020) for housing conditions.
20.05.2020 - Society & Finance
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