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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.