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Tempo and its Tribulations

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  • Kenneth W. Wachter

    (University of California, Berkeley)

Abstract

Bongaarts and Feeney offer alternatives to period life expectancy with a set of demographic measures equivalent to each other under a Proportionality Assumption. Under this assumption, we show that the measures are given by exponentially weighted moving averages of earlier values of period life expectancy. They are indices of mortality conditions in the recent past. The period life expectancy is an index of current mortality conditions. The difference is a difference between past and present, not a ``tempo distortion'' in the present. In contrast, the Bongaarts-Feeney tempo-adjusted Total Fertility Rate is a measure of current fertility conditions, which can be understood in terms of a process of birth-age standardization.

Suggested Citation

  • Kenneth W. Wachter, 2005. "Tempo and its Tribulations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 13(9), pages 201-222.
    • Handle: RePEc:dem:demres:v:13:y:2005:i:9
    DOI: 10.4054/DemRes.2005.13.9
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    References listed on IDEAS

    as
    1. James W. Vaupel, 2005. "Lifesaving, lifetimes and lifetables," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 13(24), pages 597-614.
    2. Hans-Peter Kohler & Dimiter Philipov, 2001. "Variance effects in the bongaarts-feeney formula," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 1-16, February.
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    7. John R. Wilmoth, 2005. "On the relationship between period and cohort mortality," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 13(11), pages 231-280.
    8. Evert van Imhoff & Nico Keilman, 2000. "On the Quantum and Tempo of Fertility: Comment," Population and Development Review, The Population Council, Inc., vol. 26(3), pages 549-553, September.
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    Cited by:

    1. Michel Guillot, 2006. "Tempo effects in mortality," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 14(1), pages 1-26.
    2. Chong It Tan & Jackie Li & Johnny Siu-Hang Li & Uditha Balasooriya, 2016. "Stochastic modelling of the hybrid survival curve," Journal of Population Research, Springer, vol. 33(4), pages 307-331, December.
    3. Janet Currie & Hannes Schwandt, 2015. "Short and Long-Term Effects of Unemployment on Fertility," CEP Discussion Papers dp1387, Centre for Economic Performance, LSE.
    4. Marc Luy, 2005. "The importance of mortality tempo-adjustment: theoretical and empirical considerations," MPIDR Working Papers WP-2005-035, Max Planck Institute for Demographic Research, Rostock, Germany.
    5. Germán Rodriguez, 2006. "Demographic translation and tempo effects," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 14(6), pages 85-110.
    6. Marc Luy, 2006. "Mortality tempo-adjustment," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(21), pages 561-590.
    7. Vladimir Canudas-Romo, 2008. "The modal age at death and the shifting mortality hypothesis," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 19(30), pages 1179-1204.
    8. Joshua R. Goldstein, 2006. "Found in translation?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 14(5), pages 71-84.
    9. Máire Ní Bhrolcháin, 2011. "Tempo and the TFR," Demography, Springer;Population Association of America (PAA), vol. 48(3), pages 841-861, August.

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    More about this item

    Keywords

    life expectancy; standardization; tempo; demographic transition; total fertility rate (TFR);
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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