unavailable for other countries, occupation-level scores for the United States can be multiplied with the share of each occupation by industry, region, gender or income group elsewhere.<sup>2</sup> It is also possible to construct a composite index of F2F interactions and HBW, but this entails transforming one of the two measures because the former is continuous and the latter binary.<sup>3</sup> The four tasks that underlie the F2F interactions index with consumers are drawn from the list of “work activities” in the O*NET database. There are potential alternatives, such as “contact with others (face-to-face, by telephone, or otherwise)”, “face-to-face discussions” and “physical proximity”, which derive from the list of “work contexts”. Several authors, including Blinder (2009), caution against their use because “work contexts” are very general, mix many elements, and provide “mechanical” indices. As a result, they are more prone to endogeneity and can fail to capture the relationship between F2F interactions and the quality of remote work.

“Work activities” used in this paper capture the fundamental reasons as to why F2F interactions may be important, e.g. in order to influence others. Hence, in these cases, we know why and for what F2F interactions are necessary, giving a good measure of the implications of remote delivery on the quality of work. Conversely, “work contexts” focus on outcomes rather than fundamental inputs. The risk of endogeneity here is that as firms adjust to the crisis, the outcomes are more likely to change than the inputs. For example, a worker may typically have lots of F2F discussions in normal times, but a firm may invest in ICT due to COVID-19, thereby reducing that outcome. However, the fundamental task (input) remains unchanged by the crisis, such as the need for salespeople to be able to sell and influence others.

Beyond this general caveat, there are specific issues with measures listed in “work contexts” too. A main problem with the variable “contact with others (face-to-face, by telephone, or otherwise)” is the inability to distinguish between the forms of contact. A worker who spends all their time on the phone would have the same score as one who spends all their time in face-to-face discussions. However, the former is unaffected by COVID-19, unlike the latter. Further, the variable “face-to-face discussions”

> 2 If there is reason to believe that the importance of certain tasks by occupation differs significantly from the United States, these data cannot be readily used.

> 3 One way to combine the two is to define a variable that equals 1 if the F2F score is above some threshold (e.g. the median) and zero otherwise. Then aggregating F2F will yield the percentage of jobs requiring face-to-face contact and is hence directly comparable to HBW. Inverting HBW (by taking 1-HBW) and taking a simple or weighted average of the new F2F dummy variable and the inverted HBW measure will then give “the percentage of jobs that require face-to-face contact and cannot be done from home”. An alternative is to simply average the F2F score rescaled between 0-1. This makes the two indices comparable by scale, but not by unit.

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