Where A consists of a series of age fixed effects; R represents sector-level fixed effects; L is comprised of location dummies; and F consists of firm-level characteristics. LHS indicates the appropriate dependent variable, indicating measures of firm size, growth measures, and job quality (here as proxied by average wage bill); firm-level co-variates in F’ will also be adapted when necessary based on the specifications. Results from employment-weighted regressions are found in the Annex.

# **_Results_**

Table 4 presents survey-weighted regression results with the dependent variable being the (log of) full-time permanent employees at the end of fiscal year 2012. Fixed effects for sector and location are included and align with the categories of stratification for the survey design.<sup>19</sup> Age category fixed effects are included for categories defined as 0–5; 6–10; 11–20; and 21+ years.<sup>20</sup> Due to concerns of endogeneity with firm size and to be in-line with growth measure categories, age category dummies are determined as of the time of the recall variable for growth rates, that is as of fiscal year 2010. As firm size at birth — that is the number of employees as the start of operations — has been shown to largely explain variation in firm size (Ayyagari et al 2015), it is included in all regressions as well. Controls for foreign ownership (of at least 10 percent) and exporting status (also at a level of 10 percent or more) are included, as is the share of workers with a secondary education as a proxy for labor skill level.

The table shows a positive and significant relationship between firm size and labor productivity; this is as expected in an efficient market,<sup>21</sup> in that the result indicates that more productive firms are also those that tend to employ more employees on average. While statistically significant, though, a comparatively lower magnitude of the coefficient belies limited economic significance: that is, a 10 percent increase in labor productivity is only associated with approximately firm size that is only 0.4 percent higher (col. 3). As shown above, Ghana’s formal private sector is characterized by a multitude of very small firms as well as a handful of very large ones. To examine if either end of this spectrum is driving results, we run regressions both excluding large and then micro firms (columns 4 and 5, respectively). Column 4, which excludes large firms (those with at least 100 employees), demonstrates an even lower magnitude, an elasticity of under 0.3 percent associated with 10 percent higher labor productivity, indicating that the relationship between size and productivity is in part driven by firms in the upper end of the size distribution (though the relationship remains significant). In fact, when the very smallest micro firms are excluded (column 5), the magnitude of the coefficient notably doubles to an elasticity of 0.075.

> 19 For sector, these are manufacturing: basic and fabricated metals/machinery and equipment; chemicals, plastics, and rubber; food; and other. Services include: retail; other services. By location, these categories are: Accra; Tema; the North; and Takoradi.

> 20 A similar categorical approach is used by Ayyagari et al 2015.

> 21 Revenues per worker (labor productivity) are winsorized at the 2.5% tail ends of the distribution to account for possible outlier values.

15