firms. This is done in two steps.

First, we calculate the five moments for formal firms as described above: based on the average firm size among formal employers, own-account workers, and employees, the other three percentiles are calculated by imposing the relative position of each percentile to the mean as found in the WBES<sup>10</sup> .

Second, we produce the same calculation for the mean and percentiles of informal firms based on the average firm size of informal firms and then re-scale the percentiles of the informal distribution concerning the same percentiles of the formal size distribution. For this second re-scaling, we use microdata from Burkina Faso, Cameroon, Ghana, Rwanda and Kenya to extract the mean and four percentiles for both formal and informal and obtain the relative size of each percentile from the informal firm size distribution with respect to the same percentile from the formal firm size distribution. For instance, the p25 of the formal firms’ size distribution is 2 in Ghana, and 3 in Kenya, while the same percentile among informal firms is 1 both in Ghana and Kenya. This means that the p25 of the informal firms in Ghana is 1/2 of the p25 of formal firms and 1/3 in Kenya. We produce this calculation also for percentiles p50, p75, and p90 and keep the mean across the five micro-datasets. In the example, this means using 1/3 as the adjustment scalar for the p25 of . informal firms<sup>11</sup> The method we followed has several limitations. First, estimates of the number of firms using employer statistics might not be consistent with estimates of the number of firms from establishment censuses. Second, we are using only five countries and thus imposing the shape of the firm size distribution based on limited information. In further revisions, we expect to include more countries and characterize the differences in the percentiles between formal and informal.

# **3.4 Number of workers by size and formality**

By dividing the number of employees by the number of firms, it is possible to estimate the average firm size in the economy (26 workers per firm in Africa, 33 in the rest of the world). For all the countries for which this calculation is possible, the elasticity to income measured with GDP per capita is 0.13. Bento and Restuccia (2021) estimate an elasticity of 0.3 for an average firm size that includes all people involved in business activities (but only manufacturing and services). In our setting, this would be equivalent to redefining people working for a business as the sum of employees and own-account, and also redefining firms as the sum of employers and own-account. This second definition yields and average firm size of 1.9 workers for the African continent and 7.7 elsewhere. The elasticity to income is 0.48, higher than the one initially estimated, and conceptually closer to the one estimated by Bento and Restuccia (2021).

We employ this framework to impute average firm size by size group and formality status using a model that links firm size in any of these groups to log GDP per capita, log GDP, firm

> 10For countries with no WBES data we use the average relative positions across countries covered by WBES.

> 11The broad assumption is that all countries are re-scaled with the same scaling parameter (momentspecific). It is possible to expect that moment differences between formal and informal vary by country. A further refinement to explore is making the scaling parameter dependent on country’s income level.

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