Categorical Modeling of Determinants of Financial Inclusion and Financial Literacy of Women MSMEs in Pacitan

Autor: Setyawan, Ignatius Roni, Ishak Ramli, Listyarti, Indra
Rok vydání: 2023
Předmět:
DOI: 10.5281/zenodo.7740599
Popis: Preliminary research data prior to the Covid-19 pandemic, namely that 150 women MSME had unique characteristics in terms of sociodemographic factors and levels of financial literacy and inclusion. It can be empirically proven that these three variables will have an important role in each other through the multiInomial logit categorical equation model according to the Bayar et al. research procedure. al. (2020). The important result to be achieved is that the researchers want to prove the business potential of women SMEs in Pacitan, which so far has not been exposed to BI UMKM as a common market place for all SMEs in Indonesia. There is a stigma that the low financial literacy and inclusion (OJK) score of MSME actors is a negative effect of less exposure to the business potential of MSME actors in the local area. The results of this study succeeded in describing the sociodemographic profile of women MSME in Pacitan with several characteristics, namely the dominance of having a productive age of 40-55 years, the majority having high school education; have a turnover of over 10 million per month and most of them have used access to bank and non-bank financial institutions, usually pawnshops for storage and credit applications. Furthermore, this study succeeded in proposing a categorical equation model with multinomial logistic regression through STATA 13.0 software on the three attributes of low, medium and high financial literacy and inclusion referring to the research model from Bayar et.al. (2020) and managed to find that the sociodemographic variable of age is always a determining factor in each model panel. The implication is that individually, women MSME actors with high financial literacy can make financial decisions more quickly than just participating in mentoring or the community in such area.
Databáze: OpenAIRE