Table 3

Determinants of income levels

IVsSEMOLSLogit
(1)(2)(3)
Fintech usage0.056**0.055** 
 (2.141)(2.093) 
Fintech usage: Low vs high  −1.186***
   (9.548)
Financial literacy0.067***0.066*** 
 (5.744)(5.662) 
Financial literacy: lower vs  −1.099***
higher than average  (17.029)
Gender (Male = 1)−0.003−0.002 
 (−0.035)(−0.031) 
Female vs male  0.066
   (0.077)
Age0.0520.052 
 (1.393)(1.384) 
Under 25 vs over 45 years old  −0.759*
   (3.644)
Education0.154*0.151* 
 (1.660)(1.608) 
University vs Master or higher  0.237
   (0.349)
Marital status (Married = 1)−0.026−0.026 
 (−0.307)(−0.304) 
Single vs married  0.177
   (0.423)
Work experience0.077*0.080* 
 (1.797)(1.805) 
Work experience: less vs more  −0.986
   (1.405)
Explorer trait0.243***0.049 
 (2.971)(1.061) 
Explorer trait: less vs much  −0.074
   (0.022)
Intercept/-2 Log Likelihood 1.808***571.14
R2/Adjusted R2/Pseudo R20.1210.1050.172
Chi-square/F Change0.094***7.585***612.18***
Df1820

Note(s): ***: p < 1%; **: p < 5%, *: p < 10%. Dependent variable: Income levels. t-test in the parenthesis. SEM indicator: AGFI = 0.998; RFI = 0.993, TLI = 1.074; RMSEA = 0.004

Source(s): Authors’ own work

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