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  • Titill er á ensku The compensating income variation of four sub-optimal health conditions in Switzerland
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  • Útdráttur er á ensku

    Rising health-care costs place the spotlight on the challenge of efficient resource allocation within health-care systems, as well as on efficiency comparisons between health care and other uses of resources. An essential part of tackling this problem is knowledge of the monetary values individuals put on different health states, but this can be achieved by using the compensating income variation method.
    We estimated the value of four sub-optimal health conditions: headache, backache, sleep problems and chronic illness. The estimates were based on data from the Swiss Household Panel, which is a national annual survey conducted since 1999 with information on living conditions and societal change. The rich set of variables in the data enabled the exploration of the robustness of the results across many dimensions. We estimated three different models: Ordinary Least Squares, Fixed Effects and two-stage least squares using mother’s education as an instrument. The data furthermore facilitated exploration of adaption, severity and contained two different well-being measures, allowing for comparisons of results across well-being proxies used.
    All four sub-optimal health conditions had a significant negative association with life satisfaction, with substantial measured compensating income variation, especially for the higher levels of severity. Sleep problems showed the highest compensating income variation of the four sub-optimal health conditions. The fixed effects, and especially instrumented models, generally showed lower compensating income variation for the health conditions compared with earlier studies.
    This study adds to the growing literature on the use of compensating income variation in health and may thus help shed further light on the value individuals put on different health states and thereby aid in efficient resource allocation in health care.

  • 5.4.2018

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