Household financial vulnerability in Indonesia: Measurement and determinants

Noerhidajati, Sri; Purwoko, Agung Bayu; Werdaningtyas, Hesti; Kamil, Amalia Insan; Dartanto, Teguh

doi:10.1016/j.econmod.2020.03.028

Cited by 47 publications

(50 citation statements)

References 8 publications

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“…Even “ financial vulnerability ” as a term is used interchangeably with terms such as financial fragility (Ampudia et al, 2016 ), financial distress (Anderloni et al, 2012 ), financial debt burden (Poh & Sabri, 2017 ), and financial over indebtedness (Daud et al, 2019 ). Many different variables are applied to indicate financial vulnerability, but one aspect that seems present in all studies is debt, (Anderloni et al, 2012 ; Bankowska et al, 2017 ; Daud et al, 2019 ; Leika & Marchettini, 2017 ; Noerhidajati et al, 2021 ), and in many cases, unsecured debt (e.g., credit card debt and other consumer debt) (Anderloni et al, 2012 ; Fuenzalida & Tagle, 2009 ; Lusardi et al, 2020 ). This kind of debt makes a household particularly vulnerable to adverse shocks such as job loss, reduction in working hours, illness, and the death of a bread winner.…”

Section: Literature Reviewmentioning

confidence: 99%

Financial Vulnerability, Financial Literacy, and the Use of Digital Payment Technologies

Seldal

Nyhus

2022

J Consum Policy

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The purpose of this study is to test the notion that the use of digital payment methods, such as paying with a mobile phone, increases the risk of financial vulnerability. Research from the USA indicates such a relationship, and we study whether this finding can be generalized to other countries. Motivated by recent changes in EU legislation related to financial transactions, we also examine willingness to use social media companies for money transfers along with sharing bank account information with third-party financial services. Exploiting data collected from a representative sample of the Norwegian adult population (n = 2202), we identify differences in financial behaviour and characteristics between users and nonusers of different digital payment methods. In contrast to US studies, we find that mobile payment users were less financially vulnerable than nonusers and those women were more likely users of digital payment technologies than men. Younger generations and those with low financial literacy were more financially vulnerable than others, although we did not find this to be related to the use of mobile payment or other digital payment methods. The results show that there is a need for more research from different countries outside of the USA to obtain an understanding of the consequences of increased digitalization of financial services. In addition, as COVID-19 has shifted a vast amount of spending online and these newer payment technologies have become more available, we need to gain a better understanding of how they influence financial behaviour.

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Section: Literature Reviewmentioning

confidence: 99%

Financial Vulnerability, Financial Literacy, and the Use of Digital Payment Technologies

Seldal

Nyhus

2022

J Consum Policy

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“…Another reason identified by Xiao et al (2005) Babiarz et al (2013) found an increased likelihood of an increase in debt faced by uninsured households or having an insurance scheme that provides restrictive health coverage. Noerhidajati et al (2021), Zinman (2009) found a strong relationship between credit card borrowing and households' financial conditions. Shrivastava et al (2019) argued that when a family faces financial hardship, this can lead to stress and adversely impact mental wellbeing.…”

Section: Literature Reviewmentioning

confidence: 94%

Borrowing for health, sustainability, credit card use and ownership: a study of 74 countries

Naidu¹,

Zhao²,

Pandaram³

et al. 2021

JESI

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With the rising cost of healthcare, most households are resorting to out-of-pocket financing or borrowing to finance the high cost of health care. Intuitively, healthcare's rising cost is a global concern and is subject to a thorough economic debate. The Sustainable Development Goals (SDGs) 3 focuses on health care financing for all ages to promote everyone's healthy lifestyle. There are two objectives of this study, and these are as follows: (1) Examine the relationship between borrowing for health or medical purposes and credit card use and ownership, and (2) Explore the significant gender differences concerning borrowing for health or medical purposes. Data for this study was collected from the Global Findex Database and analyzed using the Eviews8 and Microsoft Excel software. The findings from this study confirmed that borrowing for health or medical purposes, primary education, or less (% age 15+) has a statistically significant impact on credit card ownership and usage in high-income countries. There was no relationship of this nature evident in the case of low-income countries. There are significant differences between borrowing for health or medical reasons between males and females in Austria and Lithuania. Both Austria and Lithuania are high-income countries, but in the case of low-income countries, significant gender differences were found for Madagascar and Nepal. This study is timely and has contributed immensely to the existing literature.

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“…By contrast, transient poverty occurs in specific periods and can last relatively short. Health conditions, job status, disasters, price shocks, drop in income, or unseen financial needs can explain transient poverty (Bayudan-Dacuycuy & Lim, 2013;Noerhidajati et al, 2020).…”

Section: Chronic Povertymentioning

confidence: 99%

Poverty Dynamics in Indonesia: The Prevalence and Causes of Chronic Poverty

Sugiharti¹,

Purwono²,

Esquivias³

et al. 2022

JPSS

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This study aims to determine the chronicity of poverty in Indonesia using the equally distributed equivalent (EDE) poverty gap method, tracking Indonesian households in 2007 and 2014. The results indicate that the largest component of poverty among households was chronic (77%). Compared to transient poverty, chronic poverty is more common across individuals. Unlike previous studies, we used data at the district level to measure the poverty line, discovering that the cost of poverty inequality is lower than often reported. This decision is because disaggregated data (poverty line) can show a more realistic poverty threshold. Using a quantile regression approach, we found evidence that age, gender, employment status, and education were significant factors of chronicity. Other significant factors of chronic poverty include large household size, having no access to services (finance, electricity, information, and mobility), and having limited or no assets. Casual employment in the agricultural sector and living in rural areas increase the probability of poverty, although not necessarily chronic. Poverty alleviation programs, therefore, need to target the right causes as exposure to poverty varies across households.

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Household financial vulnerability in Indonesia: Measurement and determinants

Cited by 47 publications

References 8 publications

Financial Vulnerability, Financial Literacy, and the Use of Digital Payment Technologies

Financial Vulnerability, Financial Literacy, and the Use of Digital Payment Technologies

Borrowing for health, sustainability, credit card use and ownership: a study of 74 countries

Poverty Dynamics in Indonesia: The Prevalence and Causes of Chronic Poverty

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