Despite the collection of data from firms of all sizes we limit our study to firms with 5 or more persons engaged because of comparability issues across the two firm censuses that we use (see Kerr and McDougall (2019) for more detail). Since informal firms are included the data we use still covers a much larger fraction of employment than the WBES. Of the firms and workers surveyed in the 2003 NIC firm data that we use, only around 14% of firms employing 52% of total workers would have been eligible for the WBES, by reporting being registered with the Registrar General’s department.

# 3 Data used in the Study

## 3.1 Ghanaian Firm Census Data

This study uses data from two firm censuses undertaken by the Ghana Statistical Service (GSS) to create a district‐industry panel to estimate agglomeration economies in Ghanaian manufacturing. The two censuses used are the National Industrial Census (NIC) of 2003 and the Integrated Business Establishment Survey (IBES) of 2014. Both were collected at the plant level<sup>3</sup> and include data collected on economic activity, employment and location in phase 1. As discussed above, the censuses covered all non‐household‐based firms with a fixed location, and firms located in houses if these had a sign indicating the presence of a firm, whether formal or informal.

For the analysis below, we create a panel of district‐industries using the 110 districts in Ghana in 2003 and 13 sub‐sectors within manufacturing. Average district size is 2200km<sup>2</sup> whilst median size is 1350 km<sup>2</sup> . The standard deviation is roughly 2500, ie there is substantial variation in sizes of districts. The means are equivalent to circles with radii of 27 and 21km respectively. This makes the district mean 50% larger than the mean area of the “ _zones d’emploi_ ” used in Combes (2000) and 100% larger than the mean of the Colombian municipalities used by Duranton (2016), although the mean is 50% smaller than the mean of the Indian districts used in Lall et al (2004).

Both firm censuses subsequently collected much more detailed production data from a nationally representative sample of the firms identified in each census (this sample was called phase two). This production data could be used to explore possible productivity effects of agglomeration but unfortunately is not representative at the district level, as the phase 2 sample was stratified across the 10 regions, sectors and several firm‐size categories only, but not districts. Since we thus do not have a reliable district‐level measure of productivity, we instead study possible effects of agglomeration on employment growth. Because the age of the firm was also asked in phase 1 of the censuses we can also examine the extent to which the location decisions of new firms are influenced by agglomeration forces.

Adjustments and improvements to the firm census data were undertaken for this paper. The NIC and IBES were collected using different industry classification codes, and some districts were split between the censuses. Thus, harmonization of the industrial classifications and districts was required. To harmonize the districts, we matched the IBES districts to the list of districts previously used in the 2003 NIC. This required combining (aggregating) those 2014 districts that had been created by the splitting up of any 2003 districts into a number of smaller (disaggregated) parts. In order to harmonize industry codes, we ensured that both NIC and IBES were matched to ISIC (revision 4) 4‐digit activity codes.

In separate research we have undertaken on the comparability of the Ghana manufacturing firm census data, we have found that there are a number of comparability issues between the 2003 and

> 3 We use ‘plant’ and ‘firm’ interchangeably in this paper.

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