Measuring avoidable health inequality with Realisation of Conditional Potential Life Years (RCPLY)

Dennis Petrie, Kam Ki Tang, D. S. Prasada Rao

    Research output: Working paperDiscussion paper

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    In a series of papers (Tang, Chin and Rao, 2008; and Tang, Petrie and Rao 2006 & 2007), we have tried to improve on a mortality-based health status indicator, namely age-at-death (AAD), and its associated health inequality indicators that measure the distribution of AAD. The main contribution of these papers is to propose a frontier method to separate avoidable and unavoidable mortality risks. This has facilitated the development of a new indicator of health status, namely the Realization of Potential Life Years (RePLY). The RePLY measure is based on the concept of a “frontier country” that, by construction, has the lowest mortality risks for each age-sex group amongst all countries. The mortality rates of the frontier country are used as a proxy for the unavoidable mortality rates, and the residual between the observed mortality rates and the unavoidable mortality rates are considered as avoidable morality rates. In this approach, however, countries at different levels of development are benchmarked against the same frontier country without considering their heterogeneity. The main objective of the current paper is to control for national resources in estimating (conditional) unavoidable and avoidable mortality risks for individual countries. This allows us to construct a new indicator of health status – Realization of Conditional Potential Life Years (RCPLY). The paper presents empirical results from a dataset of life tables for 167 countries from the year 2000, compiled and updated by the World Health Organization. Measures of national average health status and health inequality based on RePLY and RCPLY are presented and compared.
    Original languageEnglish
    PublisherUniversity of Dundee
    Publication statusPublished - 2009

    Publication series

    NameDundee Discussion Papers in Economics
    PublisherUniversity of Dundee
    ISSN (Print)1473-236X


    • Mortality risk
    • Avoidable deaths
    • Health inequality
    • Data envelopment analysis
    • Stochastic frontier analysis

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