2021
DOI: 10.1186/s42506-021-00086-x
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Predictors of catastrophic out-of-pocket health expenditure in rural Egypt: application of the heteroskedastic probit model

Abstract: Background Out-of-pocket (OOP) health expenditure is a pressing issue in Egypt and far exceeds half of Egypt’s total health spending, threatening the economic viability, and long-term sustainability of Egyptian households. Targeting households at risk of catastrophic health payments based on their characteristics is an obvious pathway to mitigate the impoverishing impacts of OOP health payments on livelihoods. This study was conducted to identify the risk factors of incurring catastrophic healt… Show more

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Cited by 10 publications
(7 citation statements)
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“…The chi-square statistic was 259, which showed that the total variables of the models are statistically significant differences from 0 and are significant. Given that the estimation of the selection equations was conducted based on the bivariate probit method, the coefficients obtained in these two equations are only suitable for examining the direction of effects (22,23). The marginal effects were used to examine the a Source: Author's findings effect of each of the independent variables on the probability of health insurance purchasing and purchasing from the health market, the results of which were presented in the sixth column of Table 2.…”
Section: Resultsmentioning
confidence: 99%
“…The chi-square statistic was 259, which showed that the total variables of the models are statistically significant differences from 0 and are significant. Given that the estimation of the selection equations was conducted based on the bivariate probit method, the coefficients obtained in these two equations are only suitable for examining the direction of effects (22,23). The marginal effects were used to examine the a Source: Author's findings effect of each of the independent variables on the probability of health insurance purchasing and purchasing from the health market, the results of which were presented in the sixth column of Table 2.…”
Section: Resultsmentioning
confidence: 99%
“…Abdel-Rahman et al, reported that in Egypt, urban areas have captured the largest percentage of public health spending, whereas rural areas have invariably received less attention and are poorly funded which can explain the differences detected between the anthropometric measurements and nutritional data of the studied urban and rural areas. Moreover, rural areas are characterized by low levels of income, education, and economic development [22]. Additionally, Sharaf and Rashad [23] suggested earlier that while child health has improved tremendously in Egypt, socioeconomic discrepancies remain considerable which can explain the more undernutrition burden in rural areas.…”
Section: Discussionmentioning
confidence: 99%
“…Since the values of the explained variable in this paper are discrete data, regression by the Ordinary Least Squares (OLS) method will cause bias in the results. Therefore, we referred to Abdel-Rahman et al [44] and Sun and Lyu [45] using a panel Probit regression to explore the relationship between the core explanatory variables and the explained variable. We also fit a mediating effect model and used this model to examine the influence mechanism of housing security and catastrophic health expenditures.…”
Section: Methodsmentioning
confidence: 99%