standard deviation of this prediction as a measure of uncertainty.

Our measure differs from the original one developed by Altig et al. (2020b) in two ways. First, it elicits only three scenarios with subjective probability distributions over the establishment’s future sales growth instead of five scenarios. Second, it focuses on a shorter horizon of 6 months instead of 12 months.<sup>18</sup> Previous research showed that this measure of uncertainty is predictive of future growth and significantly correlated with recent news about the firm’s growth expectations. We report here five main findings based on our results.

First, we find that on average businesses expectations are three times more pessimistic than those in the United States (US) with an average expected sales growth of about -9% in the cross-country dataset and -3% in the United States. Moreover, businesses are significantly more uncertain than businesses in the United States as the average growth rate of uncertainty is close to 21% which is about 4 times larger than uncertainty among US businesses.<sup>19</sup> Second, a striking finding is that uncertainty is broad-based and cuts across all firms irrespective of their size, and strikingly similar across sectors too, as shown in Figure 19 and Figure 20, with the exception of the hospitality industry (food preparation services and accommodation) where the situation is significantly worse.

Third, expectations and uncertainty clearly reflect the firm-level experience at the micro level as firms that experienced larger sales drop in the last 30 days are both more pessimistic (i.e. expect lower sales growth in the future) and have higher uncertainty (Figure 21). Similarly, at the macro level, the size of the shock experienced at the country level is correlated with both expectations and uncertainty as businesses in those countries hit by a larger crisis (as measured by the magnitude of the mobility drop) are significantly more pessimistic and have higher uncertainty (Figure 22).<sup>20</sup> Fourth, while country characteristics, proximity to the peak of the crisis, and sectoral characteristics all matter to explain expectations, these are much less important in explaining uncertainty which is largely explained by firm-level unobserved characteristics (Figure 23 and Figure 24). In other words, as shown by Figure 24, the variation in the uncertainty between country-size-subsector groups is smaller than the variation between firms within these groups.

Finally, expectations and uncertainty have an immediate connection with jobs and welfare. In fact, we find that those businesses that are pessimistic or have higher uncertainty are significantly more likely to have fired more workers (Figure 25).

# **7. Conclusions**

The results from the business pulse surveys draw a sobering picture on the impact of the shock. Firms have been severely affected by the COVID-19 pandemic, often through multiple shocks at the same time. Not only do firms report a significant drop in sales, but the financial situation is

> 18The reasons for these differences are due mainly to the fact that we implemented our survey over the phone and with many entrepreneurs that had varying levels of literacy, and we had more stringent needs in terms of simplification and time.

> 19The comparison with the United States is relative to expected sales growth ranging between -3% and 0% as reported by Atlanta FED Uncertainty Survey available here.

> 20To measure severity, countries in the dataset are sorted into quartiles based on the drop in mobility at the peak of the crisis.

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