Can health insurance reduce household vulnerability? Evidence from Viet Nam

Vo, Thang T.; Pham, Van H.

doi:10.1016/j.worlddev.2019.104645

Cited by 26 publications

(31 citation statements)

References 43 publications

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“…Good health is crucial for the development of an economy. Illness incurs multiple economic burdens on the household: (1) treatment and medical care cost of the diseases and (2) the loss of income because of declined labour supply. 1 The increasing cost of health care utilization and the growing number of diseases over time put pressure on weaker and vulnerable sections of the society as they are not able to bear the cost of health care access.…”

Section: Introductionmentioning

confidence: 99%

Determinants of choice of health insurance: Empirical evidence from responses of Indian households

Yadav

Mohanty

2021

Health Planning & Management

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Health insurance has been accepted as one of the channels that can serve the purpose of universalisation of health care and especially useful in the period of health crisis. This is the emerging and challenging sector in India. The present study explores the health insurance penetration in India using the latest two rounds of nationally representative datasets of the National Family Health Survey (2005-06 and 2015-16). This study identifies the covariates of households' participation and their choice for different health insurance schemes, using the average marginal effects of binary and multinomial logit regression models with conditional categories after checking their Kernel density function. The results suggest that health insurance in India is more skewed towards the households belonging to higher wealth quintile and in the front runner states.Age, occupation and education level are also positively associated with health insurance enrolment. The variable 'weighted information index', which is estimated through Principal Component Analysis, is a significant determinant of private health insurance and community-based health insurance, and this also caters to the richer households. The study also identifies several shortcomings of not accessing health insurance, their choices and suggests reforms with the goal of universalization of healthcare. The robustness check has been performed using 20 percent, 50 percent and 80 percent sub-sampling of the models.

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Section: Introductionmentioning

confidence: 99%

Determinants of choice of health insurance: Empirical evidence from responses of Indian households

Yadav

Mohanty

2021

Health Planning & Management

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“…Recognizing this, many development actors pursue programs aimed at giving beneficiaries a 'push' out of poverty trapsoften by way of the transfer of cash or some other productive asset to those 'stuck' in poverty (Asadullah & Ara, 2016). To provide a protective backstop against the impact of poverty traps, development actors also implement free or low-cost programs to address disease, malnutrition, and homelessness (Brass et al, 2018;Vo & Van, 2019). Relatedly, other poverty-alleviation interventions use a more 'promotional' approach that seeks to help those vulnerable to poverty traps from sliding into them in the first place (Larsen & Lilleør, 2014).…”

Section: Alternative Approaches To Poverty Alleviationmentioning

confidence: 99%

“…For many years, approaches to poverty alleviation were predominately focused on structuring more equitable international trade agreements (Morgan, Power, & Weigel, 1993), improving government capacity (Andrews, Pritchett, & Woolcock, 2017), and providing direct aid to address issues related to gender, health, and social exclusion (Brass, Longhofer, Robinson, & Schnable, 2018;Vo & Van, 2019). As such, the topic of poverty fell primarily under the academic purview of economists, political scientists, and sociologists.…”

Section: Introductionmentioning

confidence: 99%

Linking Management Theory with Poverty Alleviation Efforts Through Market Orchestration

Kistruck

Shulist

2020

J Bus Ethics

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“…On the other hand, public insurance financing tends to encourage the behavior of using health facilities excessively. Hence, the type of insurance a household has will differentiate the demand for medical care, as evidenced by Vo and Hoang Van [17]. This paper aims to examine the role of medical costs in the demand for health among urban households.…”

Section: Introductionmentioning

confidence: 99%

Health Demand: Empirical Study of Effective Urban Households Demand in Indonesia

Ichwan

Firmansyah

Jokolelono

2021

Open Access Maced J Med Sci

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BACKGROUND: Grossman's health demand model recognizes medical price as a determinant of the estimation model. This article aims to examine the role of medical expenses in health demand by utilizing the number of sick and disturbed days obtained from Susenas, a survey on the expenditure of household food and non-food consumption conducted by the Central Bureau of Statistics to measure health demand and health insurance as a medical price in a reduction model. Health insurance can replace medical expenses because those who have health insurance face relatively low medical costs and face lower medical prices than those without health insurance. METHODS: Using the Ordinary Least Squares (OLS) estimation technique, sebuah teknik estimasi model regresi for 6,642 households this was obtained through three stages: First, using 71,932 sample households of susenas that relied fully on the Susenas sampling method by BPS; Second, find households that have experienced health problems during the last 6 months; Third, find households that have health expenditures of 24,341. Furthermore, the estimation model is based on 6,642 households identified to be in urban areas using the Ordinary Least Squares (OLS) estimation method. FINDINGS: The health demand estimation model that can be used to determine the behavior of health demand among urban households is limited to households with formal primary school (SD) education levels. Taking advantage of certain wages, age, cigarette expenditure, and sports expenses, it was found that the number of sick days and felt disturbed in the household group that had health insurance was 5.68 days relatively greater than those without health insurance. However, expanding to higher education and older age was found to be 1.47 days and 1.57 days. Aging tends to decrease good health and health insurance tends to increase it. CONCLUSION: It was found that health stocks differed between insured households and households without health insurance in those with aging.

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Can health insurance reduce household vulnerability? Evidence from Viet Nam

Cited by 26 publications

References 43 publications

Determinants of choice of health insurance: Empirical evidence from responses of Indian households

Determinants of choice of health insurance: Empirical evidence from responses of Indian households

Linking Management Theory with Poverty Alleviation Efforts Through Market Orchestration

Health Demand: Empirical Study of Effective Urban Households Demand in Indonesia

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