Table 1 Variable definitions and summary statistics for the regression models.
From: Determinants of financial inclusion gaps in Pakistan and implications for achieving SDGs
Variables | Description | Type | Mean | Standard deviation |
|---|---|---|---|---|
Dependent variables | ||||
Ownership of financial products | Whether the respondent owns any financial product | Binary | 0.24 | 0.43 |
Usage of financial products | Usage of any financial product | Binary | 0.58 | 0.49 |
Independent variables | ||||
Gender | 1 for female and 0 for male respondents | Categorical | 0.50 | 0.50 |
Young | 1 if respondent’s age is 15–24 years, 0 otherwise | Binary | 0.26 | 0.44 |
Middle | 1 if respondent’s age is between 24 and 59, 0 otherwise | Binary | 0.60 | 0.49 |
Old | If respondents is 50 years or older | Binary | 0.15 | 0.35 |
Edu_primary | 1 if the respondent has completed primary education, otherwise 0 | Binary | 0.59 | 0.49 |
Edu_secondary | 1 if the respondent has completed secondary education, otherwise 0 | 0.33 | 0.47 | |
Edu_tertiary | 1 if the respondent has completed tertiary education, otherwise 0 | 0.08 | 0.27 | |
Inc_q1 | Represents the poorest 20% (1st quintile), otherwise 0 | Ordinal/categorical | 0.16 | 0.36 |
Inc_q2 | Represents the second 20% (2nd quintile), otherwise 0 | 0.15 | 0.36 | |
Inc_q3 | Represents to the middle 20% (3rd quintile), otherwise 0 | 0.20 | 0.40 | |
Inc_q4 | Represents the fourth 20% (4th quintile), otherwise 0 (fourth 20%), 0 otherwise | 0.21 | 0.41 | |
Inc_q5 | Refers to the richest 20% (5th quintile), otherwise 0 | 0.28 | 0.45 | |
Employment | 1 if the respondent is part of the workforce, otherwise 0 | Binary | 0.44 | 0.50 |
Location | 1 for urban residents, 0 for rural dwellers | Categorical | 0.63 | 0.48 |
N | 1002 | |||
