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Impact of Digital Literacy on Financial Outcomes – A Cross-Country Analysis

Author

Listed:
  • Shakeel, Jovera
  • Munir, Shehzil
  • Mirza, Schaff
  • Abdullah, Khan

Abstract

The impact of digital literacy on financial outcomes has been well-explored. However, the onset of AI necessitates a pressing need for more granular, cross-country analyses that incorporate local variations in digital infrastructure and socioeconomic conditions. Using data from three sources in 82 countries, we employ a Directed Acyclic Graph (DAG) to examine both the direct and indirect effects of digital literacy on financial well-being. Our study uses two econometrics models, Ordinary Least Squares Regression (OLS) and Structural Equation Model (SEM), along with the machine learning approach of Random Forests. Our results confirm our initial hypothesis that digital literacy has a positive impact on financial well-being through financial inclusion. Through our models, we find that the indirect link through financial inclusion dominates the direct impact of digital literacy on financial well-being, as it accounts for socioeconomic, institutional, and individual factors.

Suggested Citation

  • Shakeel, Jovera & Munir, Shehzil & Mirza, Schaff & Abdullah, Khan, 2024. "Impact of Digital Literacy on Financial Outcomes – A Cross-Country Analysis," MPRA Paper 123374, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:123374
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    File URL: https://mpra.ub.uni-muenchen.de/123374/1/MPRA_paper_123374.pdf
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    References listed on IDEAS

    as
    1. Umi Widyastuti & Dwi Kismayanti Respati & Vera Intanie Dewi & Abdul Mukti Soma, 2024. "The nexus of digital financial inclusion, digital financial literacy and demographic factors: lesson from Indonesia," Cogent Business & Management, Taylor & Francis Journals, vol. 11(1), pages 2322778-232, December.
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      Keywords

      Digital literacy; Financial access; Economic outcomes; Human capital; Income distribution; Financial inclusion; Financial literacy; Economic development; Technological change; Data analysis;
      All these keywords.

      JEL classification:

      • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
      • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
      • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
      • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
      • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
      • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
      • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
      • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
      • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
      • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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