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Monetizing Longevity Gains under Welfare Interdependencies: An Exploratory Study

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Abstract

Whereas existing indicators of standards of living neglect the dependence of individual well-being on other people’s welfare, this paper aims at constructing an income-based indicator taking welfare interdependencies into account. For that purpose, an extension of Usher’s longevity-adjusted income measure is developed, where the selfish representative agent is replaced by a two-generation representative household, whose members are connected by altruistic links. Longevity-adjusted income figures are shown, for the U.S. (1901–1999), to be significantly sensitive to the postulated altruism, so that conventional measures, by neglecting joint survival achievements, may underestimate actual improvements in living conditions. Methodological issues raised by the inclusion of interdependencies are also discussed, such as the increased difficulty, for indicators, to reflect the complexity and diversity of preferences.

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Notes

  1. See the survey in Bergstrom (1997).

  2. See Costa and Steckel (1997), Sandberg and Steckel (1997), Crafts (1997 2002), Nordhaus (2003), Becker et al. (2005).

  3. On the definition of altruism, see Eisenberg and Miller (1987).

  4. See Schokkaert and Van Ootegem (2000) for empirical evidence on private donations.

  5. On the difficulty to measure friendship and sociability, see Mercklé (2004).

  6. A survey on the willingness to provide financial assistance in Japan reveals that, while about 92% of respondents would help their children, and 86–89% would help their parents, only 19 % would help friends, and only 1.5% would help complete strangers (see Horioka 2001).

  7. On Fig. 1, \(d_{j}^{i}\) denotes the probability of death for person i at period j.

  8. The scenario ‘long life’ has a probability (\(1-d_{0}^{m}\)), while ‘short life’ has a probability \(d_{0}^{m}\) (under \(d_{1}^{m}=d_{1}^{w}= 1\)).

  9. This equality occurs also when a society is fully disconnected (n i = 0 for all i). In the case of fully isolated people, one cannot distinguish an altruistic person from an egoistic one.

  10. More formally, it is the ratio of the marginal utility of a rise in the risk of death for a family member over the marginal utility of an increase in the risk of death for the person himself.

  11. We shall thus assume that the VSL is an estimate of the MRS between mortality risk and consumption as far as the private part of individual welfare is concerned.

  12. On those difficulties, see Jones-Lee (1989), Viscusi (1993) and Viscusi and Aldy (2003).

  13. Sources (for age-specific probabilities of death): Human Life-Table Database [2005]; calculations of joint survival curves by the author.

  14. The probability of survival up to age 50 of a new-born boy has grown from 0.57 to 0.91 over that period.

  15. Sources for real GDP statistics per head: Maddison (2004). Sources for population structures: The Human Mortality Database (available online at http://www.mortality.org/).

  16. Throughout this Section, longevity-adjusted income figures are based on population-weighted ‘single’ average life expectancies (men and women) for 10 age-groups (0—5 years, 6–17, 18–24, 25–34, 35–44, 45–54, 55–64, 65–74, 75–84, 85–104), which are computed on the basis of age-specific and gender-specific life expectancies (with weights reflecting the demographic importance of each age and gender within each age-group).

  17. Population-weighted joint life expectancies statistics are computed on the basis of the average survival conditions of the 10 age-groups mentioned above, with weights reflecting the demographic importance of each sub-case. For convenience, it is supposed that parents belong—unlike children—to the same age-group.

  18. Family-structure parameters are based on the statistics from the U.S. Census Bureau (2005) on the size and composition of households.. The choice to rely on household statistics rather than on family statistics comes from the fact that the precise age and gender compositions of families are not available, so that the most adequate approach is to rely on household data, which cover the entire country, and, then, use age-structure statistics to derive the age and gender composition of the average household.

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Acknowledgements

The author wishes to thank Pierre Pestieau, Jean-Pierre Urbain and two anonymous referees for their helpful suggestions.

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  1. Centre of Research in Public Economics and Population Economics (CREPP), UER Economie, HEC, FNRS, University of Liege, Boulevard du Rectorat, 7, bâtiment B31, Sart-Tilman, Liege, 4000, Belgium

    Gregory Ponthiere

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Ponthiere, G. Monetizing Longevity Gains under Welfare Interdependencies: An Exploratory Study. J Fam Econ Iss 28, 449–469 (2007). https://doi.org/10.1007/s10834-007-9066-7

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