Table 5 Probit estimations between Has...

Table 5

Probit estimations between Has used a mobile account and determinants

Variables	Has used a mobile account (1)	Has used a mobile account (2)	Has used a mobile account (3)	Has used a mobile account (4)
LifeCycle: 18–25 years old	−0.189***	−0.260***	−0.259***	−0.258***
LifeCycle: 18–25 years old	(0.0449)	(0.0463)	(0.0467)	(0.0469)
LifeCycle: 26–35 years old	−0.383***	−0.394***	−0.393***	−0.398***
LifeCycle: 26–35 years old	(0.0442)	(0.0459)	(0.0463)	(0.0465)
LifeCycle: 36–49 years old	−0.527***	−0.520***	−0.572***	−0.586***
LifeCycle: 36–49 years old	(0.0482)	(0.0506)	(0.0512)	(0.0515)
LifeCycle: 50–64 years old	−0.939***	−0.909***	−0.983***	−0.998***
LifeCycle: 50–64 years old	(0.0638)	(0.0685)	(0.0693)	(0.0698)
LifeCycle: Over 65 years old	−0.241*	−0.156	−0.150	−0.193
LifeCycle: Over 65 years old	(0.140)	(0.142)	(0.143)	(0.143)
Female	−0.181***	−0.196***	−0.150***	−0.144***
Female	(0.0300)	(0.0310)	(0.0315)	(0.0316)
Are they in the workforce?	0.360***	0.312***	0.304***	0.283***
Are they in the workforce?	(0.0437)	(0.0453)	(0.0456)	(0.0458)
Secondary school completed		0.714***	0.625***	0.603***
Secondary school completed		(0.0506)	(0.0513)	(0.0518)
Tertiary education or more completed		1.280***	1.089***	1.095***
Tertiary education or more completed		(0.0539)	(0.0560)	(0.0564)
Income level: Quin2			0.109*	0.104
Income level: Quin2			(0.0656)	(0.0659)
Income level: Quin3			0.160**	0.162**
Income level: Quin3			(0.0626)	(0.0629)
Income level: Quin4			0.409***	0.402***
Income level: Quin4			(0.0588)	(0.0591)
Income level: Quin5			0.579***	0.566***
Income level: Quin5			(0.0576)	(0.0579)
Country category: 2				−0.284***
Country category: 2				(0.0414)
Country category: 1				0.0669*
Country category: 1				(0.0391)
Constant	0.129**	−0.589***	−0.832***	−0.731***
Constant	(0.0549)	(0.0731)	(0.0847)	(0.0881)
LR χ²	510.83	1158.14	1329.08	1428.23
Pseudo R	0.0491	0.1122	0.1287	0.1383
Observations	7,509	7,449	7,449	7,449

Variables	Has used a mobile account (1)	Has used a mobile account (2)	Has used a mobile account (3)	Has used a mobile account (4)
LifeCycle: 18–25 years old	−0.189***	−0.260***	−0.259***	−0.258***
LifeCycle: 18–25 years old	(0.0449)	(0.0463)	(0.0467)	(0.0469)
LifeCycle: 26–35 years old	−0.383***	−0.394***	−0.393***	−0.398***
LifeCycle: 26–35 years old	(0.0442)	(0.0459)	(0.0463)	(0.0465)
LifeCycle: 36–49 years old	−0.527***	−0.520***	−0.572***	−0.586***
LifeCycle: 36–49 years old	(0.0482)	(0.0506)	(0.0512)	(0.0515)
LifeCycle: 50–64 years old	−0.939***	−0.909***	−0.983***	−0.998***
LifeCycle: 50–64 years old	(0.0638)	(0.0685)	(0.0693)	(0.0698)
LifeCycle: Over 65 years old	−0.241*	−0.156	−0.150	−0.193
LifeCycle: Over 65 years old	(0.140)	(0.142)	(0.143)	(0.143)
Female	−0.181***	−0.196***	−0.150***	−0.144***
Female	(0.0300)	(0.0310)	(0.0315)	(0.0316)
Are they in the workforce?	0.360***	0.312***	0.304***	0.283***
Are they in the workforce?	(0.0437)	(0.0453)	(0.0456)	(0.0458)
Secondary school completed		0.714***	0.625***	0.603***
Secondary school completed		(0.0506)	(0.0513)	(0.0518)
Tertiary education or more completed		1.280***	1.089***	1.095***
Tertiary education or more completed		(0.0539)	(0.0560)	(0.0564)
Income level: Quin2			0.109*	0.104
Income level: Quin2			(0.0656)	(0.0659)
Income level: Quin3			0.160**	0.162**
Income level: Quin3			(0.0626)	(0.0629)
Income level: Quin4			0.409***	0.402***
Income level: Quin4			(0.0588)	(0.0591)
Income level: Quin5			0.579***	0.566***
Income level: Quin5			(0.0576)	(0.0579)
Country category: 2				−0.284***
Country category: 2				(0.0414)
Country category: 1				0.0669*
Country category: 1				(0.0391)
Constant	0.129**	−0.589***	−0.832***	−0.731***
Constant	(0.0549)	(0.0731)	(0.0847)	(0.0881)
LR χ²	510.83	1158.14	1329.08	1428.23
Pseudo R	0.0491	0.1122	0.1287	0.1383
Observations	7,509	7,449	7,449	7,449

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 use of a mobile account and 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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