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The measurement of structural ageing - An axiomatic approach

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Abstract

The structural ageing of the population is one of the key global trends of the 21st Century. In this paper, we outline four axioms that, along with easy interpretability, we believe should underpin a theoretically valid measure of structural ageing: (1) population size invariance; (2) strong dominance; (3) weak dominance; and (4) age sensitivity. We then present a class of structural ageing indices that satisfy the axioms and are easily interpretable, with root-mean-squared-age (RMSA) as our preferred measure within the class. Using historical and cross-national data from the World Population Prospects, state-level data from the US Census Bureau, and local-authority-level data from New Zealand, we demonstrate that our preferred measure is correlated with conventional measures of structural ageing. Nevertheless, in each case there are large disparities in ranking for some countries, states, or local authorities between the different measures. These ranking disparities could be highly consequential for the allocation of resources, particularly between states or local areas within countries. Our proposed class of measures may help to avoid these disparities due to their axiomatically-consistent nature. Finally, we present considerations for future extensions of this important work, including the development of equivalent measures based on prospective age.

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  • Michael P Cameron, 2022. "The measurement of structural ageing - An axiomatic approach," Working Papers in Economics 22/04, University of Waikato.
  • Handle: RePEc:wai:econwp:22/04
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    1. Castellucci, Fabrizio & Padula, Mario & Pica, Giovanni, 2011. "The age-productivity gradient: Evidence from a sample of F1 drivers," Labour Economics, Elsevier, vol. 18(4), pages 464-473, August.
    2. Terence C. Cheng & Nattavudh Powdthavee & Andrew J. Oswald, 2017. "Longitudinal Evidence for a Midlife Nadir in Human Well‐being: Results from Four Data Sets," Economic Journal, Royal Economic Society, vol. 127(599), pages 126-142, February.
    3. Sharon M. Oster & Daniel S. Hamermesh, 1998. "Aging And Productivity Among Economists," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 154-156, February.
    4. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    5. Blanchflower, David G. & Oswald, Andrew J., 2008. "Is well-being U-shaped over the life cycle?," Social Science & Medicine, Elsevier, vol. 66(8), pages 1733-1749, April.
    6. Terence C. Cheng & Nattavudh Powdthavee & Andrew J. Oswald, 2017. "Longitudinal Evidence for a Midlife Nadir in Human Well‐being: Results from Four Data Sets," Economic Journal, Royal Economic Society, vol. 127(599), pages 126-142, February.
    7. Costa, Dora L., 1998. "The Evolution of Retirement," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226116082, September.
    8. Warren C Sanderson & Sergei Scherbov & Patrick Gerland, 2017. "Probabilistic population aging," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-12, June.
    9. Warren C. Sanderson & Sergei Scherbov, 2007. "A new perspective on population aging," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 16(2), pages 27-58.
    10. C. Chu, 1997. "Age-distribution dynamics and aging indexes," Demography, Springer;Population Association of America (PAA), vol. 34(4), pages 551-563, November.
    11. Rafael Di Tella & Robert J. MacCulloch & Andrew J. Oswald, 2003. "The Macroeconomics of Happiness," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 809-827, November.
    12. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-231, March.
    13. Wolfgang Lutz & Warren Sanderson & Sergei Scherbov, 2008. "The coming acceleration of global population ageing," Nature, Nature, vol. 451(7179), pages 716-719, February.
    14. John B. Shoven, 2007. "New Age Thinking: Alternative Ways of Measuring Age, Their Relationship to Labor Force Participation, Goverment Policies and GDP," NBER Working Papers 13476, National Bureau of Economic Research, Inc.
    15. Warren C. Sanderson & Sergei Scherbov, 2013. "The Characteristics Approach to the Measurement of Population Aging," Population and Development Review, The Population Council, Inc., vol. 39(4), pages 673-685, December.
    16. Warren C. Sanderson & Sergei Scherbov, 2005. "Average remaining lifetimes can increase as human populations age," Nature, Nature, vol. 435(7043), pages 811-813, June.
    17. Dora L. Costa, 1998. "The Evolution of Retirement: An American Economic History, 1880-1990," NBER Books, National Bureau of Economic Research, Inc, number cost98-1.
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    More about this item

    Keywords

    Population ageing; Structural ageing; Measurement;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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