Development of Income-Related Health Inequality in Europe - The Impact of Different Value Judgements

Detta är en Master-uppsats från Lunds universitet/Nationalekonomiska institutionen

Sammanfattning: This essay estimates the trends in Income-Related Health Inequalities (IRHI) in 11 European countries between 2006 to 2013 and investigates the sensitivity of these trends with respect to different inequality measures. The motivation for this study is both empirically and theoretically driven. Empirically, there have been many studies aiming to quantify and explain IRHI but relatively few have investigated the trends in IRHI. Of those who have, an increasing, to the least, stable trend in IRHI seem to be suggested. However, recent theoretical developments and debates have highlighted technical complications and lately, normative challenges that arises when researchers aim to estimate IRHI using bounded health variables, variables that are commonly used in the literature. Thus, by summarising the most recent theoretical developments in the field of IRHI measurements and applying these different inequality indices in an empirical analysis, this essay contributes to the current literature by, firstly, the trend analysis over time and secondly, and most importantly, by the thorough and transparent empirical design which allow us to perform an extensive sensitivity analysis not previously performed. The results yield IRHI trends that are both increasing (Germany, the Netherlands and Spain) and decreasing (Austria, Sweden, Switzerland, Belgium and Czech Republic) between 2006 to 2013. The sensitivity analysis indicate that most of these findings are robust across different measurements but contain a few examples of different and even opposing changes over time when using different indices. Thus, the results confirm the recent theoretical debate and underline the need for using several measurements when estimating IRHI. The analysis of the consistent trends across measures are explained by the characteristics of the health variable and points to the close link between the results of different measurements and the prevalence of health.

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