|Owner's Education (1=above secondary)|0.59|0.12|
|---|---|---|
|Prior Experience in Same Type of Business (1=yes)|0.24|0.24|
|Sector Dummy (1=manuf, 0=services (inc. retail))|0.09|0.07|
|Formal Labor Productivity (log)||10.43|
|Informal Labor Productivity (log)||5.56|
|Elevation||1249.02|
|Nighttime Lights Emission||35.46|

_Notes_ : Sampling weights applied. “Formal Micro” covers formal micro-businesses included in the World Bank Micro Enterprise Survey (WBMES), and “Informal” covers businesses included in the World Bank Informal Sector Enterprise Survey (WBISES). Baseline estimates match the closest informal firm to the closest formal firm that was interviewed.

The main variable of interest is the geographic proximity of informal businesses to formal firms. Geographic proximity is captured by the distance to the closest formal firm. Table 2 shows the summary statistics where distance is represented in kilometers.<sup>8</sup> The baseline measure is the distance between informal businesses and the closet formal firms regardless of their size (i.e., combining both firms from WBMES and WBES). Additional distance measures are constructed and explained in detail in the robustness, heterogeneity, and spillover channel sections.<sup>9</sup> A potential endogeneity concern when using geographic proximity is that location choice of firms may be linked with their decision to adopt digital technologies. However, studies have shown that technology transfer is not the only (or main) reason for firms’ location choice.<sup>10</sup> While the decision to locate the business in a specific district may be driven by the owner’s technology adoption consideration (e.g., access to infrastructure), the realization of the location (that is the distance to

> 8 Distances were calculated between each of the 9,039 (which is the sum of all observations across all three surveys) businesses enumerated with one another, after which, the closest formal firm is singled out for the following empirical analysis.

> 9 It is possible that the baseline distance measure is not the best proxy for the geographic proximity between formal and informal firms, as the captured formal firm might not necessarily be the closest one. However, the additional information recorded is essential for us to conduct additional tests to understand the spillover channels. As a robustness, the distances calculated to all enumerated formal firms is used, independent on whether they were surveyed or not, and reported the results in Table 10.

> 10 As suggested by Marshall’s theory, there are three main mechanisms for co-agglomeration: labor market pooling, access to suppliers and consumers, and inter-firm knowledge spillovers. Inter-firm knowledge spillover is often not the main reason for a firm’s co-agglomeration (co-location) decision. For instance, Howard, Newman and Tarp (2016) find that technology transfers are not the most important agglomerative force in Viet Nam. Studying the geographic clustering patterns of formal and informal firms in Cali, Colombia, García Cruz and Moreno-Monroy (2015) show that co-location occurs mainly between small formal and informal firms, rather than with large formal firms. Their results also suggest that technology spillover is not the main determinant of firms’ location decisions. Howard et al. (2016) show that 68 percent of informal businesses are located in existing fixed premises with a majority being located in household premises. These premises are unlikely to have been chosen strategically.

8