Multinomial Logit Modeling of Financial Inclusion and Financial Literacy of Women MSMEs in Tangerang

This research will examine the determinants of financial literacy and inclusion using sociodemographic variables of women MSMEs in Tangerang. The sociodemographic variables used are education, age, length of business, turnover, source of financing, type of savings, type of credit, credit ceiling, financial literacy score (OJK) and financial inclusion score (OJK). In Indonesia, there has been a lot of research on socio-demographic factors as determinants of financial literacy with mixed and unsatisfactory results, making it less reliable as a research reference. Some of the errors in previous research were that the respondents were not precise enough, for example only students or MSMEs at random. These two things result in the results of entering sociodemographic data being less reliable and ineffective when tested with categorical equation models from the simplest, namely logit, probit and tobit as well as binary logistic to the most complex models such as multinomial logit. Logit, probit and tobit and binary logistics models generally only use two categories of dependent variables, namely 0 if there is no decision or certain condition and 1 if there is a certain decision or condition. Preliminary research data before the Covid 19 pandemic, namely 150 women MSMEs who had unique characteristics in terms of socio-demographic factors as well as levels of literacy and financial inclusion, can be tried to prove empirically that these three variables will play an important role in each other through the multinomial logit categorical equation model according to Bayar et research procedures. al. (2020). The important result to be achieved is that the researcher wants to prove the business potential of women MSME actors in Tangerang, which so far has not been exposed enough to BI UMKM as one of the common market places for all MSME actors in Indonesia. There is a stigma that the low literacy and financial inclusion (OJK) scores of MSME players are a negative effect of less exposure to the business potential of MSME players in the local area. The results of this research succeeded in describing the socio-demographic profile of female MSMEs in Tangerang with several distinctive characteristics, namely the predominance of those with a productive age of 40 - 55 years, the majority having a tertiary education; have a turnover of more than 10-25 million per month and most of them use access to bank and non-bank financial institutions, usually pawnshops, for storage purposes and credit applications. Furthermore, this research succeeded in proposing a categorical equation model with multinomial logistic regression using STATA 13.0 software referring to the research model from Bayar et.al. (2020) and managed to find that socio-demographic variables of financial institutions are always a determining factor in financial inclusion and literacy. The implication is that individual women MSME actors in Tangerang can make financial decisions more quickly considering that they are so close to access to existing financial institutions.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-21
DOI
https://doi.org/10.5281/zenodo.13822589
Primary Topic
Financial Literacy and Behavior
Type
article
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article

Multinomial Logit Modeling of Financial Inclusion and Financial Literacy of Women MSMEs in Tangerang

Zenodo (CERN European Organization for Nuclear Research)
Financial Literacy and Behavior
article

Multinomial Logit Modeling of Financial Inclusion and Financial Literacy of Women MSMEs in Tangerang

article en

Abstract

This research will examine the determinants of financial literacy and inclusion using sociodemographic variables of women MSMEs in Tangerang. The sociodemographic variables used are education, age, length of business, turnover, source of financing, type of savings, type of credit, credit ceiling, financial literacy score (OJK) and financial inclusion score (OJK). In Indonesia, there has been a lot of research on socio-demographic factors as determinants of financial literacy with mixed and unsatisfactory results, making it less reliable as a research reference. Some of the errors in previous research were that the respondents were not precise enough, for example only students or MSMEs at random. These two things result in the results of entering sociodemographic data being less reliable and ineffective when tested with categorical equation models from the simplest, namely logit, probit and tobit as well as binary logistic to the most complex models such as multinomial logit. Logit, probit and tobit and binary logistics models generally only use two categories of dependent variables, namely 0 if there is no decision or certain condition and 1 if there is a certain decision or condition. Preliminary research data before the Covid 19 pandemic, namely 150 women MSMEs who had unique characteristics in terms of socio-demographic factors as well as levels of literacy and financial inclusion, can be tried to prove empirically that these three variables will play an important role in each other through the multinomial logit categorical equation model according to Bayar et research procedures. al. (2020). The important result to be achieved is that the researcher wants to prove the business potential of women MSME actors in Tangerang, which so far has not been exposed enough to BI UMKM as one of the common market places for all MSME actors in Indonesia. There is a stigma that the low literacy and financial inclusion (OJK) scores of MSME players are a negative effect of less exposure to the business potential of MSME players in the local area. The results of this research succeeded in describing the socio-demographic profile of female MSMEs in Tangerang with several distinctive characteristics, namely the predominance of those with a productive age of 40 - 55 years, the majority having a tertiary education; have a turnover of more than 10-25 million per month and most of them use access to bank and non-bank financial institutions, usually pawnshops, for storage purposes and credit applications. Furthermore, this research succeeded in proposing a categorical equation model with multinomial logistic regression using STATA 13.0 software referring to the research model from Bayar et.al. (2020) and managed to find that socio-demographic variables of financial institutions are always a determining factor in financial inclusion and literacy. The implication is that individual women MSME actors in Tangerang can make financial decisions more quickly considering that they are so close to access to existing financial institutions.

Zenodo (CERN European Organization for Nuclear Research)
Tarumanagara University (ID)
Quality Education
Openalex Percentile: Top 42%
Financial Literacy and Behavior
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