times more likely). These stark differences suggest that more policy research work is needed to understand the constraints facing women in their productive use of DTs, and what can be done to overcome these constraints.

Regarding corelates of performance, a greater range of more sophisticated DT uses based on internetenabled computers or smartphones relative to DT uses based on only 2G phones are conditionally associated with higher job levels. There is a positive progression in the number of more internetenabled DTs associated in turn with higher productivity, sales, and job levels. Six internet-enabled and three non-internet-enabled DT uses are the only significant conditional correlates of higher job levels. Firms using accounting and inventory control/POS software are associated with a roughly 1.6-person larger firm size (0.47 and 0.44 log points, respectively) than those not using them. There is a tension between higher productivity and increased employment. Firms characterized by the highest productivity are not generators of high employment, and vice versa. While this tension between high-productivity, skill-intensive technologies (automation) and jobs has been emphasized among SMEs and large enterprises, this is the first evidence of such tension among microenterprises. Formal “scale” (high sales and jobs) firms are more strongly associated with the use of internet-enabled DTs than formal and informal high-productivity firms. A relevant policy research question is whether alleviating constraints in greater use of DTs among high-productivity firms could enable them to expand their scale in line with their higher productivity.

Regarding determinants of adoption, over seven of ten non-users indicate that lack of attractiveness (“no need”) is the main constraint to productive use of DTs. A relevant policy question is whether this is mainly because there are no apps available that are useful to them in their local language that meet their productive needs, because their general skill level does not enable them to understand how they could productively use available apps, because the available quality of service is so poor that access to internet is not useful to them, or due to some other reason. The most important conditional correlates of smartphone and computer adoption among available variables are related to having a loan, having electricity, having business linkages with big firms as customers (being embedded in value chains that require upgrading), and relevant skills (managers having vocational training). More policy research work is needed to better understand what policies may be effective and appropriate to increase adoption and more intensive productive use of DTs across SSA countries.

As was emphasized in the introduction, while the data set used in this paper provides a wealth of information difficult to find elsewhere on microenterprises, the fact that it consists of a single cross section prevents causality from being inferred from the presented results. Importantly, it precludes any analysis of firm dynamics. Repeated implementation of the same survey, by following the same enterprises over time, would increase the amount of information for causal inference of the adoption decision, the impact of DTs on performance and firm growth, as well as on determinants of firm exit, and the differential impacts for formal versus informal enterprises. Given that one of the major problems faced by microenterprises in SSA is that few of them grow into competitive mid-sized or large companies, such a panel data set would provide valuable information to understand why this is so and whether the more widespread use of DTs for productive purposes can be effectively used to circumvent the associated barriers. Providing support for such future additional surveys would constitute an 33