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

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

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
Male	[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***
Later year	[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
Male × later year	[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***
Male	[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**
Later year	[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
Male × later year	[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

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