first wave of the pulse survey differed across countries–collection time averaged around 4 weeks per country and spanned from mid-April through the end of August. The survey captures businesses at different stages of the COVID-19 shock in each country (see Figure A1) and to correct for these differences in the timing of the survey, we also include dummies for the number of weeks before or after the peak of the COVID-19 shock, which we proxy using Google mobility data around transit stations (Google, 2020). For each country, we identify the date when mobility reached the trough and then count the number of weeks between the date of the interview and the trough. For countries where Google mobility data are not available, we predict mobility using the stringency of the lockdown restrictions provided in Hale et al. (2020). We describe this exercise and detail on the harmonization and trimming of variables in the appendix. Finally, to control for differences in the number of observations in each sample, we weight our results using the inverse of the number of observations in each country, that is, each country has the same weight in our summary statistics.<sup>9</sup>

# **3. Impact of the crisis**

The COVID-19 outbreak led many firms to close or reduce operations, with large drop in sales, and significant adjustments in employment, but with large heterogeneity in effects across firms. This section assesses the impact of the outbreak across these three dimensions: operation status, sales, and employment. While operation status (e.g. open or temporary closed) refers to the status of the business at the moment of the interview, the results on sales and employment refer to changes in these variables 30 days before the interview compared to the same period of 2019. Because the survey was implemented in different countries at different time, and those countries were facing diverse stages of the COVID-19 outbreak, the data provide a comprehensive picture of the way businesses have been performing and adjusting under the current crisis.

## **3.1 Operations of the business**

The likelihood of a business being open at the peak of COVID-19 crisis and up to 4 weeks after the peak is under 30%, but it significantly increases to almost 75% or more 6 weeks after the peak. Figure 1 presents the results based on the predicted probability of a firm to be open or partially open, controlling for country, size category, sector, and timing fixed effects.

Yet, tourism and small businesses in general are more likely to be closed. 6 weeks after the peak of the COVID-19 outbreak the predicted probability of being open is still under or around 75% for tourism related businesses, such as accommodation (58%) and food and beverage services (73%) (Figure 2). These are the businesses with lowest probability of being open. There are also differences in terms of size after week 6, with large firms being more likely to be open (89%) compared to micro (79%), small (82%), and medium sized (86%) firms.<sup>10</sup>

> 9In some countries, sampling weights are available in order to produce nationally representative results at the country level, but for comparison purposes, we do not include these weights in the analysis and only weight observations by the inverse of the number of businesses in each sample.

> 10The differences between size groups are statistically significant.

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