Pegadaian and the grassroots economy: Propensity score matching analysis of market expansion potential to support MSMEs financing
DOI:
https://doi.org/10.61511/jembar.v4i1.2026.3554Keywords:
msmes, pegadaian, propensity score matchingAbstract
Background: Financial inclusion is a driver for economic growth in Indonesia, yet many micro and small enterprises (MSEs) face barriers due to collateral requirements and low financial literacy. This study aims to quantify the untapped market potential and evaluate the feasibility of transitioning borrowers from high-risk informal fintech to formal pawn-based services. Literature suggests that while digital finance expands access, usage divides persist in rural areas. Methods: Utilizing household-level microdata from the March 2024 National Socio-Economic Survey/Survei Sosial Ekonomi Nasional (SUSENAS), this study focuses on a sample of 5,769 MSE households. Analytical methods involve propensity score matching (PSM) with a nearest neighbor algorithm to identify "twins" in the potential group who share identical risk and asset profiles with existing Pegadaian clients. Findings: Results from Scenario 1 (n=118 treated observations) identify an expansion market exceeding 420,000 households characterized by high motorcycle ownership. Assuming an average micro-pawn loan of IDR 5 million per household, this identified expansion segment represents a potential credit disbursement opportunity exceeding IDR 2.1 trillion. Scenario 2 (n=29 treated observations) identifies a rescue market of over 3,200 households currently using high-cost online lending. While Scenario 1 achieves optimal covariate balance, post-matching balance in Scenario 2 exhibits slight deterioration, necessitating a more cautious interpretation of the rescue segment. Geospatial analysis discovers a spatial asymmetry, where market density is concentrated in Sumatra and Bali–Nusa Tenggara rather than Java. Conclusion: Pegadaian must pivot toward culturally adaptive expansion in outer regions to bridge the service-speed gap exploited by fintech competitors. Novelty/Originality of this article: The novelty lies in the pioneering data-driven estimation of the "Rescue Market" using PSM, providing a risk-adjusted roadmap for formalizing tech-savvy but financially vulnerable borrowers.
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