Probit estimations
| Variables | Has 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 | 0.0765 | 0.0817 | ||
| (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 χ2 | 588.11 | 928.55 | 1022.40 | 1203.33 |
| Pseudo R | 0.0486 | 0.0775 | 0.0853 | 0.1004 |
| Observations | 11,501 | 11,348 | 11,348 | 11,348 |
| Variables | Has 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 | 0.0765 | 0.0817 | ||
| (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 | 588.11 | 928.55 | 1022.40 | 1203.33 |
| Pseudo | 0.0486 | 0.0775 | 0.0853 | 0.1004 |
| Observations | 11,501 | 11,348 | 11,348 | 11,348 |
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
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