Supplemental health insurance and equality of access in Belgium.

It has been suggested that the unequal coverage of different socio-economic groups by supplemental insurance could be a partial explanation for the inequality in access to health care in many countries. We analyse the situation in Belgium, a country with a very broad coverage in compulsory social health insurance and where supplemental insurance mainly refers to extra-billing in hospitals. We find that this institutional background is crucial for the explanation of the effects of supplemental insurance. We find no evidence of adverse selection in the coverage of supplemental health insurance, but strong effects of socio-economic background. A count model for hospital care shows that supplemental insurance has no significant effect on the number of spells, but a negative effect on the number of nights. This is in line with patterns of socio-economic stratification that have been well documented for Belgium. It is also in line with the regulation on extra-billing protecting patients in common rooms. For ambulatory care, we find a positive effect of supplemental insurance on visits to a dentist and on number of spells at a day centre but no effect on visits to a GP, on drugs consumption and on visits to a specialist.Costs; Cost; Risk; Policy; Choice; Insurance; Equality; Belgium;

Reducing socioeconomic health inequalities? A questionnaire study of majorization and invariance conditions

This data accompanies the paper Rohde KIM, Van Ourti T, Soebhag A (2023). "Reducing socioeconomic health inequalities? A questionnaire study of majorization and invariance conditions", Journal of Health Economics, DOI: 10.1016/j.jhealeco.2023.102773. This paper runs a lab experiment in order to study the appeal of basic preference conditions that underpin health inequality indices, including the widely used concentration index. We provide the data and code that allow for replication of the results in the paper. The file Readmefirst.pdf provides more details of the raw source data Final_Data.xlsx. The file replication.do can be run in STATA and replicates all results presented in the paper. Please let us know if you intend to use our data or STATA code

Measuring socio-economic inequality in illhealth using permanent income

In Belgium, income-related inequality in ill-health seems to favour the rich, meaning that the rich are generally in better health than the poor are. Restricting the analysis to subsamples of the Belgian population, slightly modifies the conclusion, i.e. there is no income-related inequality in ill-health among the 65+. Since it is not clear whether the absence in inequality stems from the limited variation in the income of the 65+ (because of welfare benefits) or whether it truly reflects reality, I did the analysis over again using estimates of permanent income instead of income. It turned out that inequality among the 65+ remained very limited indeed, yet robustness checks pointed to the fragility of the results.

Reducing socioeconomic health inequalities? A questionnaire study of majorization and invariance conditions

This data accompanies the paper Rohde KIM, Van Ourti T, Soebhag A (2023). "Reducing socioeconomic health inequalities? A questionnaire study of majorization and invariance conditions", Journal of Health Economics, DOI: 10.1016/j.jhealeco.2023.102773. This paper runs a lab experiment in order to study the appeal of basic preference conditions that underpin health inequality indices, including the widely used concentration index. We provide the data and code that allow for replication of the results in the paper. The file Readmefirst.pdf provides more details of the raw source data Final_Data.xlsx. The file replication.do can be run in STATA and replicates all results presented in the paper. Please let us know if you intend to use our data or STATA code.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Inequity in the face of death

We apply the theory of inequality in opportunity to measure inequity in mortality. Our empirical work is based on a rich dataset for the Netherlands (1998-2007), linking information about mortality, health events and lifestyles. We show that distinguishing between different channels via which mortality is affected is necessary to test the sensitivity of the results with respect to different normative positions. Moreover, our model allows for a comparison of the inequity in simulated counterfactual situations, including an evaluation of policy measures. We explicitly make a distinction between inequity in mortality risks and inequity in mortality outcomes. The treatment of this difference - “luck” - has a crucial influence on the results.status: publishe

Inequity in the face of death

We apply the theory of inequality of opportunity to the measurement of inequity in mortality. Using a rich dataset linking records of mortality and health events to survey data on lifestyles for the Netherlands (1998-2007), we test the sensitivity of estimated inequity to different normative choices and conclude that the location of the responsibility cut is of vital importance. Traditional measures of inequity (such as socioeconomic and regional inequalities) only capture part of more comprehensive notions of unfairness. We show that distinguishing between different routes via which variables might be associated to mortality is essential to the application of different normative positions. Using the fairness gap (direct unfairness), measured inequity according to our implementation of the “control” and “preference” approaches ranges between 0.0229-0.0239 (0.0102-0.0218), while regional and socioeconomic inequalities are smaller than 0.0020 (0.0001). The usual practice of standardizing for age and gender has large effects on measured inequity. Finally, we use our model to measure inequity in simulated counterfactual situations. While it is a big challenge to identify all causal relationships involved in this empirical context, this does not affect our main conclusions regarding the importance of normative choices in the measurement of inequity.status: publishe