In countries with publicly financed health care systems, waiting time--rather than price--is the rationing mechanism for access to health care services. The normative statement underlying such a rationing device is that patients should wait according to need and irrespective of socioeconomic status or other non-need characteristics. The aim of this paper is to test empirically that waiting times for publicly funded specialist care do not depend on patients' socioeconomic status. Waiting times for specialist care can vary according to the type of medical specialty, type of consultation (review or diagnosis) and the region where patients' reside. In order to take into account such variability, we use Bayesian random parameter models to explain waiting times for specialist care in terms of need and non-need variables. We find that individuals with lower education and income levels wait significantly more time than their counterparts.
BackgroundEgalitarianism and altruism are two ways in which people may have attitudes that go beyond the narrowly defined selfish preferences. The theoretical constructs of egalitarianism and altruism are different from each other, yet there may be connections between the two. This paper explores the empirical relationship between egalitarianism and altruism, in the context of health.MethodsWe define altruism as individual behaviour that aims to benefit another individual in need; and egalitarianism as a characteristic of a social welfare function, or a meta-level preference. Furthermore, we specify a model that explains the propensity of an individual to be egalitarian in terms of altruism and other background characteristics. Individuals who prefer a hypothetical policy that reduces socioeconomic inequalities in health outcomes over another that does not are regarded ‘egalitarian’ in the health domain. On the other hand, ‘altruism’ in the health context is captured by whether or not the same respondents are (or have been) regular blood donors, provided they are medically able to donate. Probit models are specified to estimate the relationship between egalitarianism and altruism, thus defined. A representative sample of the Spanish population was interviewed for the purpose (n = 417 valid cases).ResultsOverall, 75% of respondents are found to be egalitarians, whilst 35% are found to be altruists. We find that, once controlled for background characteristics, there is a statistically significant empirical relationship between egalitarianism and altruism in the health context. On average, the probability of an altruist individual supporting egalitarianism is 10% higher than for a non-altruist person. Regarding the other control variables, those living in high per capita income regions have a lower propensity and those who are politically left wing have a higher propensity to be an egalitarian. We do not find evidence of a relationship between egalitarianism and age, socioeconomic status or religious practices.ConclusionAltruist individuals have a higher probability to be egalitarians than would be expected from their observed background characteristics.
BackgroundAn economic crisis can widen health inequalities between individuals. The aim of this paper is to explore differences in the effect of socioeconomic characteristics on Spaniards’ self-assessed health status, depending on the Spanish economic situation.MethodsData from the 2006–2007 and 2011–2012 National Health Surveys were used and binary logit and probit models were estimated to approximate the effects of socioeconomic characteristics on the likelihood to report good health.ResultsThe difference between high and low education levels leads to differences in the likelihood to report good health of 16.00–16.25 and 18.15–18.22 percentage points in 2006–07 and 2011–12, respectively. In these two periods, the difference between employees and unemployed is 5.24–5.40 and 4.60–4.90 percentage points, respectively. Additionally, the difference between people who live in households with better socioeconomic conditions and those who are in worse situation reaches 5.37–5.46 and 3.63–3.74 percentage points for the same periods, respectively.ConclusionsThe magnitude of the contribution of socioeconomic characteristics to health inequalities changes with the economic cycle; but this effect is different depending on the socioeconomic characteristics indicator that is being measured. In recessive periods, health inequalities due to education level increase, but those linked to individual professional status and household living conditions are attenuated. When the joint effects of individuals’ characteristics are considered, the economic crisis brings about a slight increase in the inequalities in the probability of reporting good health between the two extreme profiles of individuals. The design of public policies aimed at preventing any worsening of health inequalities during recession periods should take into account these differential effects of socioeconomic characteristics indicators on health inequalities.
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