Submitted:
17 May 2024
Posted:
17 May 2024
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Abstract
Keywords:
1. Introduction

1.1. Objectives and Research Questions of the Study
2. Research Approach
2.1. Database, Keywords, and Inclusion Criteria
| Parameters | Inclusion Criteria | Exclusion Criteria |
|---|---|---|
| Period | Articles published between 1990-2023 were carried out. | Articles published before 1990 |
| Population | Male and Female | Other genders |
| Standard of Comparison | Demographic factors | Non-Demographic factors |
| Study Design | Original articles comprised experimental results | Survey papers, case studies, other than English |
| Methodology | Full text available | Full text not available |
2.2. Quality Assessment
3. Bibliometric Analysis
3.1. Trends of Publication in Time
3.1. Eminent Authors and Their Notable Contributions
3.3. Leading Countries Publishing on Financial Literacy (1990–2023)
4.1. Determinants of Financial Literacy
4.2. Gender Disparity in Financial Literacy
4.3. Probing the Depths of Financial Literacy
5. Unravelling the Unexplored Dimensions of Financial Literacy
6. Epilogue Reflections
References
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| Authors | Total Publications | Total Citation | h-index |
| Mitchell OS | 166 | 8771 | 35 |
| Boyle PA | 150 | 8941 | 41 |
| Xiao JJ | 116 | 4261 | 35 |
| Lusardi A | 75 | 12443 | 40 |
| Serido J | 67 | 2304 | 25 |
| Kadoya Y | 51 | 475 | 14 |
| Khan MSR | 49 | 418 | 12 |
| Shim S | 48 | 3119 | 23 |
| Bennett DA | 24 | 2514 | 67 |
| Title | Cited by, all databases |
| The Economic Importance of Financial Literacy: Theory and Evidence | 4877 |
| An Analysis of Personal Financial Literacy Among College Students | 3072 |
| Planning and Financial Literacy: How Do Women Fare? | 2017 |
| Rural women's access to financial services: Credit, savings, and insurance | 381 |
| Gender differences in financial risk taking: The role of financial literacy and risk tolerance | 258 |
| Financial Literacy among Working Young in Urban India | 229 |
| Financial literacy and retirement planning in Germany | 207 |
| What Explains the Gender Gap in Financial Literacy? The Role of Household Decision Making | 187 |
| Gender, stock market participation, and financial literacy | 163 |
| Gender Disparity in Access to Information: Do Spouses Share What They Know? | 103 |
| Women’s Economic Empowerment through Financial Literacy, Financial Attitude, and Financial Wellbeing | 83 |
| Author (s) | Source of Publication | Publisher | Data source | Sample Size |
| Chen and Garand (2018) | Social Science Quarterly | Wiley | 2012 National Financial Capability Studies data set | 24209 |
| Fonseca and Lord (2020) | Review Of Public Economics | Inst Estudios Fiscales | CFCS | 22204 |
| Preston and Wright (2019) | Economic Record | Wiley | Household, Income and Labour Dynamics in Australia (HILDA) Survey | 16886 |
| Cupák, et. al. (2018) | Economics Letters | Elsevier | OECD/INFE microdata | 12250 |
| Díaz and Jiménez (2021) | Journal Of Women and Aging | Taylor And Francis Group | ECF (prepared by the Bank of Spain) | 7456 |
| Longobardi, et. al. (2018) | Qual Quant | Springer | PISA 2012 survey | 3160 |
| Fonseca, et. al. (2012) | The Journal Of Consumer Affairs | Wiley | Survey data from a national financial literacy study | 2500 |
| Falahati and Paim (2011) | Journal Of American Science | American science organization | Survey data | 2340 |
| Bannier and Neubert (2016) | Economics Letters | Elsevier | 2009 SAVE panel | 2047 |
| Bannierand Schwarz (2018) | Journal Of Economic Psychology | Elsevier | SAVE panel | 1632 |
| Agnew and Agnew (2015) | International Journal Of Consumer Studies | John Wiley and sons ltd. | Survey data | 1588 |
| Koomson, et. al. (2020) | Applied Economics | Taylor And Francis | Survey data | 1441 |
| Almenberg andDerber (2015) | Economics Letters | Elsevier | Survey data on a random sample of 1,300 individuals representative of the Swedish population | 1300 |
| Yu, K. et. al., (2015) | Educational Gerontology | Taylor And Francis Group | Telephone survey data conducted in 2012 by the Public Opinion Programme at the University of Hong Kong | 966 |
| Chen and Volpe (1998) | Financial Services Review | Jai Press | Students of Ohio State University | 924 |
| Author(s) | Methodology | Study Design | Type of Study | Target Group |
| Díaz and Jiménez | OLS | Cross-sectional study | Quantitative Study | Women |
| Koomson, et. al., | OLS | RCT | Empirical study | women |
| Naiwen, et. al., | Self-administered questionnaireSPSS and Smart PLS data analysis toolsPLS-Multi group analysis | Cross-sectional study | Quantitative study | men and women working in textile industry |
| Younas and Rafay | Mixed-methods approach using semi-structured questionnaires, selected interviews, and focus groups | Cross-sectional study | Descriptive Study | Women Borrowers |
| Aristei and Gallo | nonlinear Blinder-Oaxaca decomposition | Cross-sectional | Quantitative Study | men and women working in textile industry |
| Fonseca and Lord | Descriptive analysisOaxaca-Blinder decomposition | Cross-sectional survey | Empirical | Adults |
| Koomson,et al. | Linear probability model | RCT | Empirical study | Beneficiaries of poverty reduction interventions |
| Kumari, et. al., | Quantitative approach using Structural Equation Modeling (SEM) | Positivist research paradigm | Empirical study | Rural Poor women |
| Preston and Wright | Oaxaca-Blinder decompositionregression analysis | Cross-sectional study | Empirical | Adults |
| Chen and Garand | OLS multinomial logit models | Quantitative research | Empirical study | Men and Women |
| Cupák, et. al. | Blinder-Oaxaca | Quantitative research design | Comparative study | Adults |
| Longobardi, et. al. | Educational Production Function (EPF)Unconditional Quantile Regression (UQR)Blinder-Oaxaca decomposition | Cross-sectional study | Quantitative Study | Students of age 15 |
| Bannier and Schwarz | Descriptive analysisMultiple Regression | Cross-sectional study | Quantitative research | German Households |
| Farrar, et. al. | Logistic regression model | RCT | Quantitative study | UK women and men of prostate retirement age |
| Adam | Descriptive statisticsChi-square test t-test | Cross-sectional | Quantitative study | Business students |
| Migheli and Moscarola | Difference-in-differences approachRegression Analysis | RCT | Empirical | Children aged 8-9 |
| Bannier and Neubert | Linear probability regression model | Survey data analysis | Empirical Study | Male and Female |
| Driva, et. al. | Field Survey | Cross-sectional | Quantitative | 13-15 year old teenagers |
| Haque and Zulfiqar | Non-Probability (Convenient Sampling) | Survey-based study | Quantitative Study | Working women in non-financial sectors |
| Bonga and Mlambo | Electronic survey using the Monkey Survey site | Cross-sectional study | Descriptive study | Women |
| Agnew and Agnew | OLS regression analysisChi-square analysis | Cross-sectional study | Quantitative study | Students (school and tertiary levels) |
| Almenberg and Derber | Probit regressionsOLS regressions | Cross-sectional study | Quantitative study | Adults |
| Yu, K. et. Al., | Multiple regression analysist-testschi-square tests | Cross-sectional study | Quantitative study | Workers |
| Agnew and Harrison | Descriptive statistics | Cross-national comparative study | Quantitative | Students from business and science streams |
| Njaramba, et. al., | Qualitative case study approach using semi-structured interviews, survey questionnaires | Single exploratory case study | Qualitative research | Migrant African-Australian women entrepreneurs in the Cairns region |
| Moon, et. al., | Descriptive statisticst-testone-way ANOVAhierarchical multiple regression analysis | Cross-sectional study | Empirical Study | University Students |
| Fonseca, et. Al., | Blinder-Oaxaca Decomposition | Cross-sectional study | Empirical study | Adults |
| Falahati and Paim | Stratified sampling | - | Comparative study | College students |
| Fletschner and Mesbah | Probit modelsbivariate probit model | - | Observational | Rural couples |
| Lusardi and Mitchell | 2004 HRS module | cross-sectional | empirical | Women of age 50+ |
| Chen and Volpe | Self-Structured QuestionnaireLogistic Regression | Cross-sectional | Observational | College Students |
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