Determinants of Financial Literacy and Financial Inclusion Disparity Within a Region: Evidence from Indonesia

Santoso, Arief Budi; Trinugroho, Irwan; Nugroho, Linggar Ikhsan; Saputro, Nugroho; Purnama, Muhammad Yusuf Indra

doi:10.1166/asl.2016.6706

Cited by 9 publications

(9 citation statements)

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“…For example, individuals with no education have, on average, lower financial literacy than those of high school by 24 percentage points. This is in line with observations from existing studies, such as Santoso et al (2016) and Bucher-Koenen and Lusardi (2011). Similar to ANZ (2008); However, there seems to be evidence that there are marked differences in the level of financial literacy among different occupations.…”

Section: Descriptive Statisticssupporting

confidence: 92%

Financial Literacy and Income Distribution of Rice Farmers

Sanglay

Apat

Sumague

et al. 2021

None

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The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of ADBI, ADB, its Board of Directors, or the governments they represent. ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of their use. Terminology used may not necessarily be consistent with ADB official terms.Working papers are subject to formal revision and correction before they are finalized and considered published.

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Section: Descriptive Statisticssupporting

confidence: 92%

Financial Literacy and Income Distribution of Rice Farmers

Sanglay

Apat

Sumague

et al. 2021

None

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“…First, we include a dummy variable to reflect gender difference (GENDER), taking a value of 1 for male respondents and o for female respondents. Following our previous work (Santoso et al, 2016), we measure education level (EDU) using an interval scale. The last demographic factor is the age of respondents (AGE) as one might argue that the use of a new technology is easier for young people.…”

Section: Methodsmentioning

confidence: 99%

“…Socio-economic condition which reflects living quality (Trinugroho et al, 2015) is represented by the income level (INCOME) which also employs an interval scale. Sub-district characteristics are proxied by the degree of ruralness (RURAL) according to the study of Santoso et al (2016). It is supposed that people in the rural area may perceive themselves less friendly with technologicalbased financial services.…”

Section: Methodsmentioning

confidence: 99%

How Ready Are People for Cashless Society?

Trinugroho

Sawitri

Toro

et al. 2017

Jurnal Keuangan Dan Perbankan

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Financial technology could be an effective tool to achieve financial inclusion. However, it needed a certain level of readiness of society. In this paper, we investigated the determinants of readiness in the implementation of digital financial services which led to cashless society. We did a survey on 993 adults in a province in Indonesia using proportional sampling technique. Estimated using ordinary least square, our empirical results showed that readiness perception had high correlation with the quality of supporting infrastructure. By taking into account some demographic factors, we found that more educated and younger people had high spirit to adopt this system. Evidence showed that men were more enthusiastic in using such technological-based system. However, we did not find an evidence on the difference of readiness perception between those living in rural and those living urban areas. Abstrak Teknologi keuangan dapat menjadi suatu alat yang efektif untuk mencapai inklusi keuangan. Namun, itu memerlukan tingkat kesiapan masyarakat yang cukup. Dalam paper ini, kami meneliti determinan dari kesiapan implementasi layanan keuangan digital yang mendorong pada masyarakat non-tunai. Kami melakukan survei pada 993 orang dewasa in suatu provinsi di Indonesia dengan menggunakan metode pengambilan sampel proporsional. Diestimasi menggunakan ordinary least square, hasil empiris kami menunjukkan bahwa persepsi kesiapan berkorelasi tinggi dengan kualitas dari infrastruktur pendukung. Dengan memasukkan beberapa faktor demografi, kami menemukan bahwa orang yang lebih teredukasi dan lebih muda bersemangat untuk mengadopsi sistem ini. Sedikit bukti ditemukan bahwa laki-laki lebih antusias untuk menggunakan sistem berbasis teknologi tersebut. Namun demikian, kami tidak menemukan bukti mengenai perbedaaan persepsi kesiapan antara mereka yang tinggal di daerah pedesaan dan perkotaan.

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“…Likewise, Trinugroho et al, (2015) examined the determinants of financial deepening in Indonesia but were limited to country-level data and macro variables such as regional gross domestic products and the number of bank branches per province. Sun (2015) also conducted a similar analysis, but the study focused on micro enterprises with revenue less than 300 million/year.. Another research by Santoso et al, (2016) that compared the levels of financial inclusion and financial literacy between rural and urban households.…”

Section: Introductionmentioning

confidence: 99%

Factors Influence Financial Inclusion: Evidence from Indonesian Micro Data

Susilowati¹,

Leonnard²

2019

Etikonomi

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In order to increase access to formal financial institutions, the Indonesian government has issued various national strategies. However, Indonesia's inclusive financial index is still under other ASEAN countries. Therefore, in this study, we investigate the factors that influence financial inclusion in Indonesia. The microdata from global findex 2014 was carried out in this study by using binary logistic regression analysis. The finding indicates that there is a significant positive relationship between individual characteristics, including financial inclusion, constraints to financial inclusion, utilization of financial services motivation, and loan sources. Since the main targets of financial inclusion are the poor, this finding becomes an essential proposition for policies in the banking sector, that besides the factors of gender, age, education, and type of jobs, income is the primary factor that influences access and utilization of financial services. Mainly regarding loans, increased income will increase the opportunities of the poor to getting loans because only high-income groups have collateral in applying for loans.Abstrak. Untuk meningkatkan akses ke lembaga keuangan formal, pemerintah Indonesia mengeluarkan berbagai strategi nasional. Namun, indeks keuangan inklusif Indonesia masih di bawah negara-negara ASEAN lainnya. Oleh karena itu, dalam penelitian ini, kami menyelidiki faktor-faktor yang mempengaruhi inklusi keuangan di Indonesia. Data mikro dari global findex 2014 dianalisis dalam penelitian ini dengan menggunakan analisis regresi. Hasil penelitian menunjukkan bahwa terdapat hubungan positif yang signifikan antara karakteristik individu, inklusi keuangan, kendala inklusi keuangan, penggunaan motivasi layanan keuangan, dan sumber kredit. Karena target utama dari inklusi keuangan di Indonesia adalah kelompok masyarakat miskin, maka hasil penelitian ini menjadi masukan yang penting bagi kebijakan di sektor perbankan, bahwa selain faktor-faktor gender, usia, pendidikan, dan jenis pekerjaan, pendapatan menjadi faktor utama yang mempengaruhi keberhasilan inklusi keuangan. Khususnya mengenai kredit, peningkatan pendapatan akan meningkatkan peluang masyarakat untuk mendapatkan pinjaman, karena hanya kelompok berpendapatan lebih tinggi yang memiliki jaminan dalam mengajukan pinjaman.

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Determinants of Financial Literacy and Financial Inclusion Disparity Within a Region: Evidence from Indonesia

Cited by 9 publications

References 0 publications

Financial Literacy and Income Distribution of Rice Farmers

Financial Literacy and Income Distribution of Rice Farmers

How Ready Are People for Cashless Society?

Factors Influence Financial Inclusion: Evidence from Indonesian Micro Data

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