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Table 6 Regression result of banking access and financial literacy.

From: How does financial literacy impact on inclusive finance?

Bank account (DV)

Logit

Probit

A

B

A

B

Profession

 

2.641***

 

1.253***

 

(0.611)

 

(0.290)

Income

 

2.774***

 

1.411***

 

(0.689)

 

(0.342)

Education

 

1.505***

 

0.814***

 

(0.440)

 

(0.231)

Deposit & withdraw ability

6.085

7.495***

3.117

3.915***

(0.659)

(1.016)

(0.288)

(0.484)

DPS & loan

1.176

0.803

0.585

0.448

(0.441)

(0.527)

(0.236)

(0.278)

DPS & loan interest rate

3.295

3.765***

1.517

2.059***

(0.574)

(0.666)

(0.249)

(0.356)

Installment

0.337

0.326

0.100

0.180

(0.253)

(0.304)

(0.135)

(0.169)

Security money

 − 1.603

 − 0.493

 − .607

 − 0.336

(0.523)

(0.592)

(0.249)

(0.301)

_cons

 − 9.72

 − 15.09

 − 4.83

 − 7.67

(1.066)

(2.184)

(0.491)

(1.037)

  1. This model presents the association between financial literacy and banking access. Part A of the logit model shows − 82.60 log-likelihood, LR chi2 (5) is 977.61, and model fits at 85.54% Pseudo R2 value; where part B shows − 61.84 log-likelihood, LR chi2 (8) is 1019.12, and model fits at 89.18% Pseudo R2 value. On the other hand, Part A of the Probit model shows − 83.57 log-likelihood, LR chi2 (5) is 975.66, and the model fits at 85% Pseudo R2 value; where part B shows − 62.88 log-likelihood, LR chi2 (8) is 1017.04, and model fits at 89% Pseudo R2 value. The value of Prob > chi2 is 0 for all models, and the observation of A & B is 852. ***, **, * refer significance level at 99%, 95%, 90%, respectively. The value within the first bracket is the standard error value