Monte Carlo-Based Bayesian Path Analysis for Modeling Indirect Financial Effects on Literacy in Emerging Markets

Banking literacy is an important foundation in realizing financial inclusion, especially in developing countries such as Indonesia.This study examines the indirect effects of payment instrument use, financial inclusion, and financial capacity on banking literacy, with financial knowledge as a mediator.A Bayesian Parametric Path Analysis approach is used with estimation through Markov Chain Monte Carlo (MCMC) simulation.Primary data were obtained from a national survey of 600 respondents selected through multistage sampling.Results show that the three exogenous variables have significant indirect effects through financial knowledge, with credible intervals of all paths above zero.The Bayesian approach allows flexible estimation and probabilistic interpretation.The findings provide theoretical contributions and practical implications for financial education policies that support the digital transformation of banking services.