of GBF and SBF.<sup>4</sup> The index varies from 1 to 5, in which 1 represents the use of the most basic technology, and 5 is the adoption of frontier technologies. In the example of Business Administration, a firm that adopts handwritten processes and computers with standard software will have a GBF index of 2 in the extensive margin. As the firm uses two technologies, the survey asks about the most used one. If the most used technology is handwritten processes, the GBF index at the intensive margin is 1. In contrast, if standard software, the intensive margin equals 2. Likewise, if a firm in the Wearing Apparel industry uses laser cutting, a frontier technology, as the most used technology, then it will have an SBF index of 5 at both extensive and intensive margins.

# **2.2 Identifying female-managed businesses**

The FAT survey provides two variables that relate to gender participation in the management of a firm. The first variable indicates whether there are any females among the firm owners, while the second variable identifies whether the top manager is female. Although both variables are highly and significantly correlated (a coefficient of 0.5), the female ownership variable is substantially less precise, as the share of female ownership is not collected in several countries.<sup>5</sup> In contrast, the indicator of FTM shows less measurement errors and more precisely capture if females are involved in the management of firms.

The survey indicates that only 20% of firms are managed by women (Table 1), which is consistent with other findings in the literature. For instance, the World Bank Enterprise Survey reports that, for a representative sample of over 130,000 firms, about 16% are femalemanaged firms. Throughout the analysis, unless otherwise stated, we will refer to female establishments as those managed by female top managers.

The country income level is positively associated with female participation in top managerial positions. Table 1 shows the percents of firms with FTM for the various countries in

> 4See Cirera et al. (2020) for the detailed description of the technology indexes. The authors also provide several robustness checks for technology indexes using alternative cardinalizations.

> 5The survey includes information on ownership shares for Brazil, Senegal, and Viet Nam. Although the correlation coefficient between female participation in ownership and majority ownership (50% or more) by women is also high (0.56), there are large heterogeneities across sectors. For example, firms with any female owner in the Motor Vehicles sector is 73.4%, but only 3.2% has female owners with more than 50% of ownership share. Similarly, the share of firms with at least one female owner is almost three times higher than that with females having majority ownership (50% or more) in the Livestock and Crops sector, and two times higher than that in the Food Processing sector. The large gap between businesses with any female owner and female with 50% or more ownership is also observed in other studies. Using the World Bank Enterprise Survey, Lemma et al. (2023) examine the difference between these variables in Kenya and South Africa. They found that, in Kenya, 47.5% of firms have female participation in ownership, while only 13.2% are women-owned. In the case of South Africa, the gap is much smaller, with 10.6% of female participation in ownership and 8.7% of majority ownership by women.

5