Table 4

Probit estimations

VariablesHas a mobile account (1)Has a mobile account (2)Has a mobile account (3)Has a mobile account (4)
LifeCycle: 18–25 years old−0.0318−0.0462−0.0421−0.0729*
(0.0389)(0.0398)(0.0400)(0.0404)
LifeCycle: 26–35 years old−0.154***−0.115***−0.114***−0.166***
(0.0387)(0.0401)(0.0403)(0.0408)
LifeCycle: 36–49 years old−0.397***−0.298***−0.327***−0.391***
(0.0428)(0.0448)(0.0451)(0.0458)
LifeCycle: 50–64 years old−0.752***−0.599***−0.638***−0.713***
(0.0620)(0.0651)(0.0655)(0.0663)
LifeCycle: Over 65 years old−0.352***−0.287***−0.261***−0.295***
(0.0844)(0.0853)(0.0856)(0.0860)
Female−0.253***−0.243***−0.211***−0.186***
(0.0275)(0.0280)(0.0283)(0.0285)
Are they in the workforce?0.376***0.298***0.282***0.270***
(0.0374)(0.0384)(0.0385)(0.0389)
Secondary school completed 0.478***0.421***0.314***
 (0.0374)(0.0380)(0.0391)
Tertiary education or more completed 0.804***0.667***0.572***
 (0.0436)(0.0458)(0.0467)
Income level: Quin2  0.07650.0817
  (0.0527)(0.0531)
Income level: Quin3  0.126**0.138***
  (0.0510)(0.0514)
Income level: Quin4  0.276***0.281***
  (0.0486)(0.0490)
Income level: Quin5  0.386***0.407***
  (0.0480)(0.0485)
Country category: 2   0.187***
   (0.0364)
Country category: 1   0.441***
   (0.0331)
Constant−0.750***−1.162***−1.313***−1.429***
(0.0468)(0.0567)(0.0652)(0.0677)
LR χ2588.11928.551022.401203.33
Pseudo R0.04860.07750.08530.1004
Observations11,50111,34811,34811,348

Note(s): Standard errors are in parentheses ***p < 0.01, **p < 0.05, *p < 0.1

Column (1) presents the results of a probit model analyzing the availability of a mobile account in relation to life cycle, gender and employment. Columns (2), (3) and (4) show the same probit model with additional control variables: education, income level and country category, added in that sequence. The country category groups countries based on fintech market penetration into three categories

Source(s): Authors’ elaboration

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