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Table 6 Regression coefficients for model predicting the residuals from the total scenario regressions in Table 4

From: Analysing global professional gender gaps using LinkedIn advertising data

 

Dependent variable: Residuals from Total scenarios in Table 4

 

ILO professional GGI

ILO total management GGI

ILO senior/middle management GGI

Intercept

0.14

−0.12

−0.63

(0.19)

(0.29)

(0.31)

LinkedIn penetration GGI

−0.67

−0.24

−0.40

(0.04)

(0.07)

(0.09)

GGG labor force GGI

 

0.15

−0.28

 

(0.13)

(0.14)

Proportion LinkedIn users aged 18–24

 

0.47

 
 

(0.29)

 

Internet access GGI

0.84

1.36

1.00

(0.14)

(0.27)

(0.25)

HDI (male)

−0.32

−0.51

 

(0.15)

(0.30)

 

LinkedIn penetration

−0.09

  

(0.02)

  

GGG educational attainment GGI

−0.02

  

(0.27)

  

GGG secondary education enrollment GGI

 

−0.63

0.50

 

(0.23)

(0.27)

Internet penetration

0.08

−0.25

−0.30

(0.07)

(0.13)

(0.10)

GGG tertiary education enrollment GGI

 

0.04

 
 

(0.04)

 

N

129

120

70

Adj. \(R^{2}\)

0.76

0.35

0.47

  1. Note: p<0.1; p<0.05; p<0.01.