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Review 2: "Infection Risk at Work, Automatability, and Employment"

This preprint develops a model to examine the elevated risk of automation due to COVID-19 restrictions and illness sequelae. In particular, it looks at the differential risk for automation that different industries face.

Published onNov 26, 2023
Review 2: "Infection Risk at Work, Automatability, and Employment"

RR:C19 Evidence Scale rating by reviewer:

  • Strong. The main study claims are very well-justified by the data and analytic methods used. There is little room for doubt that the study produced has very similar results and conclusions as compared with the hypothetical ideal study. The study’s main claims should be considered conclusive and actionable without reservation.

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Review:

Automation does not affect everybody equally. There are some occupations at higher risk. This indeed happened during COVID-19 for automable occupations with a high viral risk infection. Using data from Austria, this paper tests whether automable occupations with a high viral risk infection are more substitutable when COVID-19 occurred. The paper shows this indeed happened. 

The paper is very interesting and straightforward. I think is an important contribution. The model is simple and how it is explained, it is clear what the paper wants to test. Then, the regression models follow the theoretical model. Although I think the paper is very good, I have some small suggestions:

  1. How much of the development of the model is necessary? I would suggest to streamline the model part, and send everything you can to supplementary materials. The key assumption is equation (4). If we assume perfect substitution, then it follows that any change in relative prices (or in our case risk infection) will change relative employment, as shown in equation (12). Thus, you can discuss the main assumptions of the model and its implications more briefly.

  2. Econometric results in Table 2 show a lear significant result in the variable of interest. But Figure 1 Panel A (employment) is not significant (different from zero) for any value of infection risk. This is confusing because Table 2 says the results are in logs, but the figure says marginal effect. Is it a new regression? This figure needs more explanation to fully understand it. 

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