Skip to main content

Table 7 Regressions for job outcomes based on pooled country-level data

From: Gender gaps in the path to adulthood for young females and males in six African countries from the 1990s to the 2010s

Coefficient Burkina Faso Ethiopia Ghana Kenya Tanzania Uganda
If individual has a professional, managerial, technical or clerical (white-collar) job
 Male 0.016** 0.013 0.032* 0.003 0.011* − 0.002
[0.007] [0.009] [0.018] [0.011] [0.006] [0.009]
 Later year 0.037*** 0.029*** 0.062*** − 0.026*** 0.027*** 0.041***
[0.006] [0.004] [0.010] [0.007] [0.003] [0.009]
 Male × later year 0.014* − 0.003 0.012 0.066*** 0.002 − 0.020
[0.008] [0.010] [0.021] [0.012] [0.008] [0.013]
N 9710 14,520 5648 16,742 6977 6692
r2 0.048 0.092 0.081 0.028 0.046 0.041
 Female baseline value 0.015 0.025 0.037 0.115 0.015 0.033
If individual works in agriculture
 Male 0.314*** 0.405*** 0.237*** 0.233*** 0.265*** 0.220***
[0.019] [0.017] [0.022] [0.013] [0.019] [0.020]
 Later year − 0.120*** − 0.109*** − 0.090*** − 0.126*** 0.146*** 0.044**
[0.016] [0.008] [0.012] [0.009] [0.011] [0.020]
 Male × later year − 0.158*** 0.013 − 0.107*** − 0.129*** − 0.271*** 0.015
[0.022] [0.018] [0.025] [0.015] [0.026] [0.028]
N 9710 14,520 5648 16,742 6977 6692
r2 0.303 0.355 0.308 0.106 0.353 0.207
 Female baseline value 0.380 0.371 0.318 0.195 0.421 0.439
  1. Sample: respondents aged 21–29 years in the DHS survey. The dependent variable takes the value 1 if the respondent works in a white-collar job/agriculture and zero if not. Controls include year-specific age dummies, regional dummies interacted with urban/rural, household size and number of household members less than 5 years. ***, ** and *reflect conventional significance at 1, 5 and 10% levels