The socioeconomic determinants of health expenditure in OECD: An examination on panel data

Yetim, Birol; İlgün, Gülnur; Çilhoroz, Yasin; Demirci, Şenol; Konca, Murat

doi:10.1080/20479700.2020.1756112

Cited by 24 publications

(7 citation statements)

References 25 publications

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“…As unemployment increased, health expenditure also increased. In the studies carried out by Sposato and Saposnik (2012); Yetim et al (2020) no significant difference was found between health expenditures and unemployment.…”

Section: Discussionmentioning

confidence: 86%

DETERMINANTS of HEALTH EXPENDITURES in THE WORLD: A PANEL DATA ANALYSIS

Koçyiğit¹,

Çilhoroz²

2021

ijbemp

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Health expenditure is the main indicators used by policy makers in the macro and micro environment. This study, it is aimed to reveal the determinants of health expenditures of all countries in the world.No sample selection was made within the scope of the study. The data of all the countries of the world were tried to be accessed. Data collection was carried out with the World Bank database. 2010-2016 panel data of 163 countries were used The obtained data were subjected to Least Squares (OLS) regression analysis, which is a multivariate analysis type. EViews pro19 and SPSS programs were used for analysis. According to the results of these studies health expenditures increase as income, population age over 65, unemployment rate, and urbanization rate increase. It was observed that inflation did not have a statistically notable effect on health expenditures. Developing policies to change the lifestyles of individuals in terms of preventing unemployment in countries, proportional distribution of health services to urban and rural populations and reducing chronic diseases is of great importance in terms of improving health outcomes.

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Section: Discussionmentioning

confidence: 86%

DETERMINANTS of HEALTH EXPENDITURES in THE WORLD: A PANEL DATA ANALYSIS

Koçyiğit¹,

Çilhoroz²

2021

ijbemp

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“…Previous studies have shown that GDP is the most important factor influencing healthcare spending [99][100][101][102][103][104][105][106][107][108]. It was an economic factor.…”

Section: Discussionmentioning

confidence: 99%

Differentiation in Healthcare Financing in EU Countries

2020

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The main aim of this work was to identify and present the situation and changes in the level of expenditure on healthcare in the European Union in the years 2013–2017. This involved an analysis of the available literature on healthcare financing, data from the EUROSTAT database. For this work, the comparative method was used, dynamics indicators were used, the Gini concentration coefficient was calculated, and the degree of concentration was presented using the Lorenz curve. Pearson’s linear correlation coefficients were also used. A descriptive, tabular and graphic method was used to present the test results that were obtained. A high concentration of expenditure on healthcare was found in the EU countries with the largest population and that are the most economically developed. These results also relate to these expenses on a per capita basis. The main factor differentiating the level of healthcare financing was the level of economic development. This regularity was confirmed in the statement of expenditure per capita, the relationship between this expenditure and the value of GDP and the results obtained when calculating the correlation between expenditure and economic development. In addition to the economic situation, an important factor determining the amount of expenditure on healthcare was the percentage of the country’s population that are older people.

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“…The literature widely defines war as a state of armed conflict between group of people or states seeking either economic, political, or other hegemonic benefits [ 33 ] linked by aggressions of extensive duration and magnitude across a wide spectrum, resulting in a societal catastrophe [ 33 , 34 ]. Moreover, the empirical literature also widely documents the various impacts of civil wars and armed conflicts on healthcare indicators.…”

Section: Literature Reviewmentioning

confidence: 99%

The health consequences of civil wars: evidence from Afghanistan

2023

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This study examines the effects of long-run civil wars on healthcare, which is an important component of human capital development and their causality nexus in Afghanistan using the MVAR (modified vector autoregressive) approach and the Granger non-causality model covering data period 2002Q3-2020Q4. The primary results support a significant long-run relationship between variables, while the results of the MVAR model indicate the per capita cost of war, per capita GDP, and age dependency ratio have significantly positive impacts on per capita health expenditures, whereas child mortality rate and crude death rate have negative impacts. The results of the Granger non-causality approach demonstrate that there is a statistically significant bidirectional causality nexus between per capita health expenditure, per capita cost of war, per capita GDP, child mortality rate, crude death rate, and age dependency ratio, while it also supports the existence of strong and significant interconnectivity and multidimensionality between per capita cost of war and per capita health expenditure, with a significantly strong feedback response from the control variables. Important policy implications sourced from the key findings are also discussed.

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The socioeconomic determinants of health expenditure in OECD: An examination on panel data

Cited by 24 publications

References 25 publications

DETERMINANTS of HEALTH EXPENDITURES in THE WORLD: A PANEL DATA ANALYSIS

DETERMINANTS of HEALTH EXPENDITURES in THE WORLD: A PANEL DATA ANALYSIS

Differentiation in Healthcare Financing in EU Countries

The health consequences of civil wars: evidence from Afghanistan

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