Table 4 Multilevel probit regression models, average marginal effects, [95% CI]

Rural household

Ref

Ref

Ref

Ref

Urban household

0.02 [.02–.03]

0.02 [.02–.03]

0.03 [.02–.03]

0.02 [.02–.03]

Age below 20 yrs (F)

Ref

Ref

Ref

 20–35 yrs. (F)

0.17 [.16–.17]

0.09 [.08–.11]

0.06 [.04–.08]

 above 35 yrs. (F)

0.25 [.25–.26]

0.11 [.10–.13]

0.07 [.05–.09]

Age below 20 yrs (M)

Ref

Ref

 20–35 yrs. (M)

0.16 [.15–.16]

0.03 [−.03–.09]

 above 35 yrs. (M)

0.17 [.16–.17]

0.06 [−.00–.12]

Illiterate (F)

Ref

Ref

Ref

Literate (F)

0.03 [.02–.03]

0.02 [.02–.03]

0.02 [.01–.03]

Illiterate (M)

Ref

Ref

Literate (M)

0.00 [−.00–.01]

0.01 [−.00–.01]

Education: Less then primary (F)

Ref

Ref

Ref

 Secondary or higher (F)

−0.02 [−.02--.01]

− 0.01 [−.02--.00]

0.01

Education: Less then primary (M)

Ref

Ref

 Secondary or higher (M)

−0.02 [−.03–.01]

− 0.01 [−.02 - -.00]

Occupation: none (F)

Ref

Ref

Ref

 white-collar (F)

0.03 [.02–.03]

0.04 [.03–.05]

− 0.01 [−.02–.00]

 blue-collar (F)

0.01 [.01–.02]

0.09 [.09–.10]

0.02 [.01–.02]

 agriculture (F)

−0.03 [−.04--.03]

0.11 [.10–.11]

0.02 [.01–.02]

Occupation: none (M)

Ref

Ref

 white-collar (M)

0.02 [.01–.02]

− 0.02 [−.04 - -.01]

 blue-collar (M)

0.06 [.05–.06]

−0.00 [−.01–.01]

 agriculture (M)

0.04 [.03–.04]

− 0.02 [−.03 - -.00]

Wealth index: very poor

Ref

Ref

Ref

Ref

 poor

−0.00 [−.01–.00]

0.03 [.02–.03]

− 0.03 [−.04--.06]

0.00 [−.00–.01]

 middle

− 0.00 [−.0–.00]

0.06 [.06–.07]

− 0.05 [−.06- -.05]

0.02 [.01–.02]

 rich

− 0.02 [.03–.02]

0.11 [.11–.12]

− 0.07 [−.08 - -.07]

0.02 [.01–.03]

 very rich

− 0.05 [−.06--.05]

0.17 [.17–.18]

− 0.11 [−.12- -.10]

0.00 [−.01–.01]

Household size

− 0.00 [−.00--.00]

− 0.00 [−.00--.00]

− 0.01 [−.01 - -.01]

− 0.01 [.01 - -.01]

Number of living children (F)

0.00 [.00–.00]

0.01 [.01–.01]

0.01 [.00–.01]

Number of living children (M)

0.00[.00–.00]

0.00 [−.00–.00]

Armenia

Ref

Ref

Ref

Ref

Albania

−0.17 [−.18--.15]

0.01 [−.09–.02]

.

.

Burundi

− 0.32 [−.33--.30]

0.14 [.13–.16]

0.10 [.08–.12]

− 0.24 [−.26 - -.21]

Cambodia

−0.17 [−.18--.15]

0.02 [.01–.04]

0.40 [.38–.42]

−0.08 [−.10 - -.06]

Chad

.

0.07 [.05–.08]

− 0.16 [−.18 -. -.14]

.

Congo

−0.25 [−.26--.23]

0.20 [.18–.21]

−0.02 [.04 - -.00]

− 0.34 [−.37 - -.31]

Egypt

.

0.42 [.41–.44]

.

.

Ethiopia

−0.38 [−.39--.36]

− 0.28 [−.29–.26]

−0.21 [−.23 - -.19]

−0.37 [−.39 - -.35]

Gambia

−0.23 [−.24--.21]

0.28 [−.27–.30]

Sample too small

−0.28 [−.31 - -.25]

India

−0.30 [−.31--.28]

−0.24 [−.26--.23]

−0.07 [−.08 - -.05]

−0.24 [−.26 - -.23]

Kenya

−0.29 [−.31--.28]

−0.12 [−.13--.10]

−0.08 [−.10 - -.06]

−0.21 [−.22 - -.19]

Malawi

−0.33 [−.34--.31]

0.34 [.32–.35]

−0.11 [−.13 - -.09]

−0.22 [−.25 - -.20]

Nigeria

−0.42 [−.43--.40]

−0.13 [−.14--.11]

−0.26 [−.28 - -.25]

−0.31 [−.33 - -.29]

Rwanda

−0.37 [.39--.35]

0.19 [.18–.21]

0.05 [.03–.08]

−0.22 [.25 - -.20]

Sierra Leone

−0.19 [−.20–.18]

0.22 [.21–.24]

−0.28 [−.31 - -.26]

−0.24 [−.26 - -.22]

South Africa

−0.12 [−.13--.10]

0.46 [.44–.48]

0.04 [.02–.06]

−0.07 [−.10 - -.04]

Tanzania

−0.32 [−.34--.31]

−0.12 [−.13--.10]

−0.14 [−.16 - -.12]

−0.22 [−.25 - -.19]

Tajikistan

.

−0.06[−.08--.05]

− 0.19 [−.21 - -.17]

.

Timor-Leste

−0.00 [−.02–.01]

−0.38[−.39--.36]

−0.04 [.06 - -.02]

− 0.26 [−.28 - -.23]

Togo

− 0.36 [−.38--.35]

0.22 [.20–.23]

−0.14 [−.16 - -.11]

−0.25 [−.27 - -.22]

Zambia

−0.25 [−.27--.24]

−0.18 [−.20--.17]

0.04 [.02–.06]

−0.14 [−.16 - -.12]

Zimbabwe

−0.26[−.27--.24]

−0.07[−.08--.05]

−0.00 [−.02–.01]

−0.13 [−.15 - -.11]

N

245,835

443,528

172,450

90,578