Health Care Expenditure and GDP in Oil Exporting Countries: Evidence From OPEC Data, 1995-2012

Abstract

Background:There is a large body of literature examining income in relation to health expenditures. The share of expenditures in health sector from GDP in developed countries is often larger than in non-developed countries, suggesting that as the level of economic growth increases, health spending increase, too.Objectives:This paper estimates long-run relationships between health expenditures and GDP based on panel data of a sample of 12 countries of the Organization of the Petroleum Exporting Countries (OPEC), using data for the period 1995-2012.Patients & Methods:We use panel data unit root tests, cointegration analysis and ECM model to find long-run and short-run relation. This study examines whether health is a luxury or a necessity for OPEC countries within a unit root and cointegration framework.Results:Panel data analysis indicates that health expenditures and GDP are co-integrated and have Engle and Granger causality. In addition, in oil countries that have oil export income, the share of government expenditures in the health sector is often greater than in private health expenditures similar developed countries.Conclusions:The findings verify that health care is not a luxury good and income has a robust relationship to health expenditures in OPEC countries.

Healthcare Financing and Health Outcomes: Analysis of Oil-Producing Countries in Africa

“…Nikoloski and Amendah (2017) empirically affirmed that neonate and neonatal mortalities across 14 African countries are not significantly affected by private health spending. Other notable empirical results related to this study affirmed that expenditure on health from the public to health sector from oil export earnings in oil countries is frequently more than private health expenditure in identical developed countries and that environmental pollution and female participation in labour force had a negative impact on health outcomes (Fazaeli et al,2016& Kulkarni, 2016.…”

“…A clear understanding of C02 emissions having negative effect on life expectancy is possible since emissions could degenerate into different diseases that are life-threatening. The result of the C02 and health outcome under life expectancy could be said to be affirmative as Fazaeli et al (2016) and Kulkarni (2016) also confirm similar outcomes. A further examination of this table shows that for maternal mortality only per capita income is found statistically significant.…”

“…Few studies have used comprehensive descriptive analysis for cross country data to compare the level of healthcare financing across the countries in the same region (Nwakanma, 2013;Asbu et al, 2017, Nikoloski & Amendah, 2017, while panel pooled or fixed Ordinary Least Squares (OLS) to account for endogeneity was adopted by Gani (2008), Farag et al (2013), Akinci et al (2014, Kulkarni (2016) and Bein et al (2017). However, some studies claimed that it is good to account for cross-section dependence and heterogeneity with the inclusion of cointegration relationship among variables, which called for the application of two-stage least squares (2SLS), Error Correction Model (ECM), Linear Mixed Model, Panel Autoregressive distributed lag, fully modified ordinary least squares (FMOLS) and panel cointegration test (Martin et al,2009;Anyanwu and Erhijakpor,2009;Kim and Lane 2013;Fazaeli et al, 2016;Rana et al, 2018). Other methods applied are logistic regression for state analysis and OLS for single country analysis (Riman and Akpan, 2012;Edeme et al, 2017).…”

Health care expenditure and environmental pollution: a cross-country comparison across different income groups

“…There are fewer cross-country studies available for non-OECD countries. Amongst these, Fazaeli et al (2016) consider countries in the Organization of the Petroleum Exporting Countries (OPEC), Samadi and Homaie (2013) Economic Cooperation Organization (ECO) countries, and Khan and Mahumud (2015) South-East Asian countries. Conversely, a significant volume of literature exists in explaining the persistent increase in healthcare expenditure over time.…”

Patterns and determinants of health care spending in denizens of urban slums from peri-industrial area of Hyderabad

“…Though many social assistance and social security schemes are functional through public health care sector, still various estimates claims out of pocket expenditures constitutes around three quarters of health care expenditures in India. 3,4 In the absence of insurance, an illness not only reduces welfare directly, but it also increases the risk of impoverishment due to high treatment expenditures, forcing the family below poverty line. The literature around out-of-pocket payments and its impact on the economic status of households has grown tremendously over the past.…”