Constraints to women’s financial literacy in Pakistan: A Bayesian hierarchical analysis
DOI:
https://doi.org/10.18800/economia.202601.004Keywords:
Financial literacy, Bayesian hierarchical logistic modeling, Hamiltonian Monte Carlo, No-UTurn Sampler, Odds ratios, Highest posterior density credible intervals, Posterior meanAbstract
This study investigates the determinants of financial literacy among women entrepreneurs in Pakistan’s informal sector and its implications for their entrepreneurial success. Using data from five districts in Punjab, a Bayesian hierarchical logistics model estimated through Hamiltonian Monte Carlo (HMC) and the No-U-Turn Samplers (NUTS) was applied for robust interference. Results show that 55-59 % of respondents were financially literate, with an overall mean of 61 %. Education, access to credit, and business facilities were positively associated with financial literacy, whereas gender-related constrains and lack of formal education had negative effects. Cultural constrained showed mixed influences, and multiple roles had a slight positive impact. The findings highlight the need for targeted financial literacy programs, focusing on budgeting, financial management, and investment skills, to enhance women’s entrepreneurial capacity and support inclusive economic development.
