**Definition of variables** Variables are defined as follows. In each census, labor is defined as the total number of paid and unpaid workers plus proprietors.<sup>11</sup> The capital input is defined as a book value of fixed assets. The definition of labor cost includes wages and salaries of workers as well as other benefits. Value added is defined as the difference between the value of production minus cost of raw materials and energy and purchase of services. See Table A1 for the definition of each variable and parameter.

**Data cleaning** These data have been extensively cleaned to remove inconsistencies and ensure crosscountry comparisons.

# **6 Main Results**

## **6.1 Measuring Productivity and Distortions**

Figure 3 plots the distribution of log( _TFPR_ ) and log( _TFPQ_ ) demeaned by industry-specific averages. More specifically, it plots log( _TFPRsi/TFPRs_ ) and log( _TFPQsi/TFPQs_ ), weighted by the value added share of industries. The figure shows that the distribution of TFPQ has a thicker left tail and the TFPR distribution has a fat right tail. Table 2 reports various measures of dispersion of TFPQ and TFPR.

There are several points worth noting. First, the findings suggest that there is a substantial dispersion in firm-level productivity in all the sample countries. A comparison of our results with Hsieh and Klenow (2009) reveals that productivity is more dispersed in our sample countries than in the US, China and India. While all countries exhibit some degree of productivity disparity, the magnitude of this dispersion is particularly striking in Kenya, where many less productive firms coexist with a few very productive firms. This pattern is consistent across different measures: the standard deviation (S.D.), the ratio of the 75th to the 25th percentile (75 _−_ 25), and the ratio of the 90th to the 10th percentiles (90 _−_ 10). To get a sense of the economic magnitude of these numbers, taking the 90th to the 10th spread of TFPQ shows that the productivity gap across establishment is quite high. In Kenya, firms in the 90th percentile of productivity are 290 percent more productive than firms in the 10th percentile, while this gap is 87 percent in Ghana, 39 percent in Ethiopia, and 26 percent in Cˆote d’Ivoire .

The key question is then why the most productive firms have not expanded their production to replace the less productive ones. A multitude of factors may have explained this phenomenon in our sample countries. One way to assess the extent of resource misallocation is to look at the variation in marginal products of inputs across producers. In a frictionless environment, the marginal products of factors should be equalized across firms and this the dispersion of marginal products should be zero. Thus a dispersion in TFPR can be interpreted as an indicative of resource misallocation (Hsieh and Klenow, 2009). Following Hsieh and Klenow (2009), we estimate the dispersion of TFPR, which is geometric average of the marginal products of capital and labor. The findings suggest that the TFPR dispersion across firms in our sample countries is much higher than in India, China, and the US. For example, the ratios of 90th to 10th percentiles of TFPR are 51 in Kenya, 17 in Ghana, 13 in Ethiopia,

> 11Note that unpaid workers account for a large portion of manufacturing employment in SSA in general and in our sample countries in particular.

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