that there is a premium to exporting per se. Thus, for manufacturers, the benefit from opportunities in sectors amenable to remote work located in countries with better internet penetration is higher for exporters relative to non-exporters. For firms in the services sector, the triple interaction term is not statistically significant. In fact, the coefficient on the interaction term between amenability to remote work and internet penetration is statistically significant only for the sample of non-exporters. Only around 10% of services sector firms in the sample are exporters (Table 4, Panel B).<sup>8</sup> Table 4: **Heterogenous effects, by sector**

|**Panel A.**|**Manufact**|**uring**|||
|---|---|---|---|---|
||Full|Exporters|Non-Exporters|Full|
||(1)|(2)|(3)|(4)|
|Exporter||||3_._230<sup>_∗∗∗_</sup><br>(0_._950)|
|WfH x digital infra.|2_._966<sup>_∗∗∗_</sup>|5_._172<sup>_∗∗∗_</sup>|2_._331<sup>_∗∗_</sup>|1_._465<sup>_∗_</sup>|
||(0_._836)|(1_._710)|(0_._954)|(0_._882)|
|WfH x digital infra. x exporter||||4_._553<sup>_∗∗∗_</sup><br>(1_._466)|
|Country F.E.|Yes|Yes|Yes|Yes|
|Sector F.E.|Yes|Yes|Yes|Yes|
|R-squared|0_._282|0_._303|0_._245|0_._284|
|Observations|21_,_628|6_,_956|14_,_672|21_,_628|

|The F-stat testing the equality of coefcients in c|olumns 2 and|3 is 2.104, with p v|alue 0.147||
|---|---|---|---|---|
|Estimations also control for (log) frm’s size, qu<br>weighted using country weights. Standard error<br>correspond to p_<_0.01, p_<_0.05, p_<_0.1, respectiv<br>|arter F.E, and<br>s in parenthes<br>ely.<br>|Google’s Mobility<br>es. Signifcance le<br>|index. Estimations are<br>vels ***, **, and *,<br>||
|**Panel B. Services**|**(excludin**<br>|**g hospitalit**<br>|**y)**<br>||
||Full|Exporters|Non-Exporters|Full|
||(1)|(2)|(3)|(4)|
|Exporter||||0_._860<br>(0_._798)|
|WfH x digital infra.|0_._793<sup>_∗∗_</sup>|0_._078|1_._104<sup>_∗∗_</sup>|0_._995<sup>_∗∗_</sup>|
||(0_._401)|(0_._958)|(0_._446)|(0_._436)|
|WfH x digital infra. x exporter||||_−_0_._907<br>(0_._784)|
|Country F.E.|Yes|Yes|Yes|Yes|
|<br>Sector F.E.|Yes|Yes|Yes|Yes|
|R-squared|0_._255|0_._330|0_._240|0_._255|
|Observations|37_,_106|5_,_194|31_,_912|37_,_106|

The F-stat testing the equality of coefficients in columns 2 and 3 is 0 _._ 945, with p value 0 _._ 331 Estimations also control for (log) firm’s size, quarter F.E, and Google’s Mobility index. Estimations are weighted using country weights. Standard errors in parentheses. Significance levels ***, **, and *, correspond to p _<_ 0.01, p _<_ 0.05, p _<_ 0.1, respectively.

Our data also provides indicative evidence that the benefits of digitalization on firms’ sales in sectors that are more amenable to remote work have not dissipated since the pandemic started. The coefficient on the interaction between amenability to remote work and digital infrastructure (whether the share of internet users or the number of secure internet servers per 1 million people) (Table 5) is consistently positive and significant after the first quarter April-June 2020 until April-September 2021. This stands in contrast to a study on German firms which finds the impact of regional differences in digital capital endowment and WfH on local employment to be larger in the short-run. After the 8Hospitality services firms were excluded from the sample of Table 4, Panel B, due to the lower prevalence of exporters (6.7% compared to 13.6% or higher in other service categories). If these firms are included, the triple interaction term is negative and statistically significant at the 10% level of significance. This may reflect extended travel restrictions, which persisted long after the lifting of lockdowns, and disproportionately affected hospitality firms dependent on foreign visitors.

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