It's easy to see that coronavirus infection has negative productivity effects. People who are infected are unable to work at first, and even after they return, their work performance is likely to be negatively affected for a while. However, working out how much productivity is negatively affected is difficult, because individual productivity is often difficult to measure, and infection with coronavirus may or may not be symptomatic. Measuring only the productivity effects on symptomatic cases would tend to over-estimate the actual effect of a coronavirus infection.
In a new working paper, Kai Fischer (Heinrich Heine University), James Reade (University of Reading), and Benedikt Schmal (Heinrich Heine University) look at the impacts on professional football (soccer) players in two top professional leagues in Europe (the Bundesliga in Germany, and Serie A in Italy). Their focus on footballers is important, because as they note:
...we are able to differentiate precisely between infected and non-infected individuals as the soccer leagues implemented rigid regimes of frequent and systematic testing for all players.
So, that gets around any problems of asymptomatic players resulting in over-estimated effect sizes. Productivity can also be precisely measured. Fischer et al. use the number of passes in a game. They justify this measure as:
Productivity can rather be considered as a function of various health aspects; mainly physical measures, for example acceleration, condition, and endurance, but also the cognitive capability to position oneself optimally on the pitch. The number of passes is related to all of these measures, which is why we base our analysis on this parameter. We consider COVID-19 as a shock to the underlying health aspects, that consequently causes a deterioration in performance.
Fischer et al. use a difference-in-differences format, essentially comparing infected players before and after their coronavirus infection, with the performance for uninfected control players. They use a variety of public sources to identify infected players, and over the period they consider (up to the middle of July 2021):
There have been 81 true-positive tests among players in Germany and 176 in Italy until mid of July 2021. We can clearly identify 76 players in Germany and 157 in Italy...
257 infections among 1,406 players imply that 18% of all players got infected until mid of July 2021.
That appears to be a similar infection rate than among the general population of the same age. Importantly, vaccination of players only started after the conclusion of the 2020/21 football season. Their dataset then includes 72,807 game observations on 1406 players over the 2019/20 and 2020/21 seasons (including 40,607 observations of players who played at least some game time). Looking at the effects on productivity, Fischer et al. find on the extensive margin that:
...players have a 5.7 percentage points lower probability to play. However, effects appear to be mechanical, mainly driven by the first weeks after an infection, when quarantine breaks do not allow a player to participate in a match. The observed drop in playing frequency becomes insignificant quickly, but does not fully return to its former level. These results indicate that players marginally experience persistent effects on their likelihood to play...
So, infected players are less likely to play, both immediately during their infection period, and somewhat afterwards (although the latter is not statistically significant). Similarly:
Immediately after the infection and his return on the pitch, a player spends on average 6 minutes less on the field than before – this corresponds to a decrease by almost ten percent... The effect is visible right after an infection but quite long-lasting. Only after approximately 150 days or five months minutes played return to a level which does not significantly differ from pre-infection match times.
So, infected players play less time, even when they are playing. In terms of in-game productivity (measured by the number of passes), Fischer et al. find:
...a highly significant static difference-in-differences effect of -5.1 percent. Hence, we can precisely identify a deterioration in work performance following a cured COVID-19 infection. This effect is not transient but actually remains notably negative in course of time.
So in addition to playing less, when they are playing, infected players are less productive. Note that these results control for the number of minutes played, so the reduction in the number of passes isn't a result of playing less time. Digging a bit further, they find that:
...especially players of an age above 30 face the strongest performance drops of above ten percent. In comparison, younger players up to 25 years are only affected marginally.
That result would seem to make sense, if older players' fitness is affected more severely, or older players take longer to recover from their infection. Also, in relation to fitness:
...performance declines over the course of a match. While the effect seems to be stable at around -3% in the first thirty minutes, post-infected players face a deterioration of some additional three percentage points in later phases. Such a downward trend would be in line with COVID-19 affecting player’s endurance.
Fischer et al. also demonstrate that the effect of coronavirus is larger than for other respiratory illnesses (such as colds or flu), as well as other minor injuries. They also show some suggestive evidence that there are negative spillover effects on other members of the team, from an infected player's poorer performance.
Overall, this suggests that there are significant and long-lasting negative productivity effects of coronavirus infection. That in turn suggests that the estimated negative economic impacts of the coronavirus pandemic may have been underestimated, if they fail to consider longer-term productivity impacts.
[HT: Marginal Revolution]
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