Data

The analysis uses a matched employer-employee dataset on micro and small enterprises in Kampala, Uganda, For the purpose of our analysis we constrict the sample to micro enterprises (enterprises with five or less regular workers). This definition only considers regular workers, therefore firm size can, for a small number of cases, exceed five workers if firms hire several casual workers, apprentices or non-paid workers. Fifty-one per cent of our sampled micro enterprises are own-account workers and therefore not included in the analysis.

Data were collected in Kampala, Uganda, in nine survey waves from 2012 to 2018. The sampling strategy followed a two-stage procedure. In a first step, 16 out of 220 geographical business zones of Kampala were randomly selected in 2012. Since many businesses are informal and an official list of businesses does not exist, the sample population was created by going from business to business and collecting basic information about the business. In a second step, out of this sample population, a sample of 450 (500 for 2015-2018) firms was randomly drawn. Firms that dropped out over the years were replaced with firms in the same industry and district if possible.

While firms have a unique identification code, this is not the case for workers. Hence, they could not be tracked over time. This yields a firm panel, with the corresponding information on workers coming in the shape of a repeated cross-section. Reported data cover the firm and all workers engaged in the firm, whether regular worker, casual worker, unpaid family member or business partner. As the analysis focusses on the determinants of workers’

wages, non-paid employees and business partners (who receive a share of the firm’s profit rather than a fixed wage) are excluded from the analysis.

The questionnaire covers firm characteristics and performance measures, personal characteristics and attitudes as well as the household composition of the entrepreneur. Table 15, Table 16 and Table 17 show the summary statistics of the key variables for the sample of observations described above. Education is the only worker characteristic for which we have

Firm performance and workers’ wages: Evidence from microenterprises in Uganda 95

information for all waves. Information on the age and tenure of the worker is only available for 2012; information on the workers’ gender and contract type is available for 2012, 2013 and 2014. Information on the days worked per week of each worker is missing in 2012. Since this information is needed to calculate an hourly wage, the year 2012 is not included in the regression analysis. However, since some information on the employees is only available in 2012, descriptive statistics on workers depicted in Table 17 include data from the 2012 wave.

Most firms (33.6 per cent) are in the ‘Manufacturing (remaining)’ industry. Wages are highest in the ‘Manufacture of printing/paper products and related services’ industry with a median hourly wage of UGX 887 and lowest in the ‘Retail electric, phones, household appliances and related services’ industry (UGX 526 median hourly wage). The printing industry is also the sector with the by far largest capital stock and highest reported profits (UGX 1,322,000 per month), while the ‘Hair dressing and beauty’ and the ‘manufacture of textile/wearing apparel industry’ has the lowest average self-reported profit (UGX 394,000 and UGX 389,000, respectively). The distributions of profits, value added, and capital stock are heavily skewed. Median values are much smaller than the respective means. In terms of monthly hours worked, the industries do not differ largely with an average of 500 total working hours per month. Regarding firm size and firm age, the ‘Manufacturing (remaining)’ industry stands out with an average of 14.25 years in operation and 3.1 workers per firm.

When looking at worker characteristics (Table 17), one can see that 85 per cent of the workers are regular employees, 12 per cent are casual employees while the remaining 2 per cent are apprentices. More than half of the workers have completed secondary education, while 34 per cent only have completed primary education. Seventy-seven per cent of the workers are not related to the entrepreneur. The remaining 23 per cent are direct or extended family members. Thirty per cent of the employees are female (with only 23 per cent of the entrepreneurs being female). Most workers have only an oral (54 per cent) or even no contract (41 per cent). Average tenure is 2 to 5 years while the average worker age is 19-25. Compared to the workers, education of entrepreneurs is more dispersed with about 40 per cent of entrepreneurs having no or only primary education, 43 per cent having completed secondary and 15 per cent having completed tertiary education.

96 Firm performance and workers’ wages: Evidence from microenterprises in Uganda Table 15: Firm characteristics

Firm performance and workers’ wages: Evidence from microenterprises in Uganda 97

Retail clothing, footwear and leather 590.61

(343.63) 547.82 Retail electric phones, household appliances

and related services

743.30

(920.96) 526.04 Retail and wholesale (remaining sectors) 1,767.67

(5,844.72) 577.70

Employee/ worker regular 2,519 85.39

Employee/ worker casual 370 12.54

Apprentice 61 2.07

Relationship to entrepreneur – Total 2,381 100

Non-family member 1,844 77.45

Direct family (siblings, parents) 263 11.05

Extended family (cousins, relatives) 274 11.51

Gender of the employees - Total¹ 817 100

Male 570 69.77

Female 247 30.23

1Information on the workers’ gender and contract type is only available for 2013 and 2014 (2012 not shown).

98 Firm performance and workers’ wages: Evidence from microenterprises in Uganda

Contract type – Total 816 100

No contract 339 41.54

Written contract 32 3.92

Oral contract 445 54.53

Workers’ tenure - Total² 351 100

0 years 35 9.97

1 year 108 40.74

2-5 years 159 45.30

6-10 years 42 11.96

> 10 years 7 1.99

Age of the employee – Total 371 100

14-18 18 4.85

19-25 180 48.52

26-30 124 33.42

31-54 49 13.21

Worker education – Total 2,241 100

No education 87 3.88

Primary education 759 33.87

Secondary education (O-Level, A-Level) 1,198 53.46

Tertiary education (university) 197 8.79

Entrepreneurs’ education – Total 3,004 100

No education 408 13.58

Primary education 840 27.96

Secondary education (O-Level, A-Level) 1,285 42.78

Tertiary education (university) 441 14.68

Other 30 1.00