Second, we use the World Bank’s Informal Enterprise Survey (IES) to profile firms. Firms included in this survey are, by definition, informal, i.e., the businesses are not registered with their governments.<sup>16</sup> The IES is conducted only with manufacturing or services firms in main urban areas. We use the most recent Mozambique, Zambia, and Zimbabwe surveys for our analysis,<sup>17</sup> which follow a sampling strategy that allows for the generation of sample weights.<sup>18</sup> Third, we use geospatial big data and a national Census extract to analyze how the urban environment correlates with employment types. The Mozambique Census was collected in 2017 and provides detailed information on employment type and geo-location at the neighborhood level. A 10 percent extract was shared by the statistical department. Four geospatial big data sets were utilized, each providing data for 1 km by 1 km tessellation (grid) of the country. First, the NASA’s Earth Observatory raster dataset<sup>19</sup> provides a measure of annual nighttime light brightness composites.<sup>20</sup> Second, the University of Michigan's High Resolution Electricity Access (HREA) data uses the aforementioned nighttime lights data and machine learning techniques to estimate electrification access between 2012 and present. Third, the WorldPop raster provides information on population density, building characteristics, and an urbanization composite at 1 km by 1 km tessellations. Fourth, the Open CellID database provides locations of cell phone towers.

# **2.1 Defining Employment Types to Classify Workers**

Inspired by Danquah et al (2019), we create a classification of six urban employment types using the GMD. We use information on workers’ employment category in their main job to classify workers as employees, self-employed or employers. To assign formality status to employees, we use variables that indicate receipt of labor benefits (social security payments, paid annual leave, paid sick leave) and wages, as per ILO (2018).<sup>21</sup> This relates to

> 16 The definition of formal registration varies by country.

> 17 In Mozambique, the survey covers three cities (Beira, Maputo, and Nampula). In Zambia, the IES was carried out in three cities (Kitwe, Lusaka, and Ndola), while in Zimbabwe, it covered one city (Harare). Table A1 in the Appendix lists the survey and year used for each country.

> 18 The IES collected prior to 2017 did not use a sample frame that could be used to generate sample weights. A key challenge for conducting a representative sample survey of informal sector businesses is the lack of a proper sampling frame of establishments. These businesses, by definition, are not registered with government agencies. However, they tend to cluster in certain geographic areas, such as low-income residential areas. Starting in 2017, the IES implemented Adaptive Cluster Sampling (area-based sampling) in which starting grids (usually squares) are selected. All informal businesses in selected squares are enumerated, using a short-form questionnaire, and a randomly selected subset of the enumerated businesses receive the long-form questionnaire.

> 19 A raster is an image file, where each position in the image is an x-y coordinate with a functional mapping to a specific value. They are also called GeoTIFF (Tagged Image File Format) Rasters or tif files.

> 20 The variable is generated from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite (~463 meter resolution).

> 21 The employment category and labor benefits variables pertain to the previous week, or the last year if information on the previous week is not available.

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