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APC curvature plots: Displaying nonlinear age-period-cohort patterns on Lexis plots

Author

Listed:
  • Enrique Acosta

    (Max-Planck-Institut für Demografische Forschung)

  • Alyson van Raalte

    (Max-Planck-Institut für Demografische Forschung)

Abstract

Background: The analysis of age-period-cohort (APC) patterns of vital rate changes over time is of great importance for understanding demographic phenomena. Given the limitations of statistical modeling, the use of graphical analyses is often regarded as a more transparent approach to identifying APC effects. Objective: The current paper proposes a Lexis plot for the depiction and analysis of curvature, which is defined as the estimable nonlinear component of age, period, and cohort effects. Methods: In a single visualization, we combine the dynamics of the location, the magnitude, and the spread of nonlinear temporal effects for multiple populations or demographic phenomena. Using vital rates, we provide three examples in which we analyze the APC nonlinear effects of different demographic phenomena. Results: We construct several APC curvature plots to display the following patterns: the modal cohort of excess mortality from drug-related causes by racial/ethnic group in the United States among the baby boomer generations; the modal age of excess mortality in young adults; and the modal age of fertility over cohorts and across populations. Contribution: The use of the APC curvature plot offers more flexibility when analyzing nonlinear APC effects than the use of mathematical models or other Lexis plots.

Suggested Citation

  • Enrique Acosta & Alyson van Raalte, 2019. "APC curvature plots: Displaying nonlinear age-period-cohort patterns on Lexis plots," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(42), pages 1205-1234.
    • Handle: RePEc:dem:demres:v:41:y:2019:i:42
    DOI: 10.4054/DemRes.2019.41.42
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    Cited by:

    1. Phil Mike Jones & Jon Minton & Andrew Bell, 2023. "Methods for disentangling period and cohort changes in mortality risk over the twentieth century: comparing graphical and modelling approaches," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3219-3239, August.
    2. Tim Riffe & Jose Manuel Aburto, 2020. "Lexis fields," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(24), pages 713-726.
    3. Octavio Nicolas Bramajo, 2022. "An Age-Period-Cohort Approach to Analyse Late-Life Depression Prevalence in Six European Countries, 2004–2016," European Journal of Population, Springer;European Association for Population Studies, vol. 38(2), pages 223-245, May.
    4. Enrique Acosta & Alain Gagnon & Nadine Ouellette & Robert R. Bourbeau & Marilia R. Nepomuceno & Alyson A. van Raalte, 2020. "The boomer penalty: excess mortality among baby boomers in Canada and the United States," MPIDR Working Papers WP-2020-003, Max Planck Institute for Demographic Research, Rostock, Germany.

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    More about this item

    Keywords

    data visualization; Lexis plots; curvatures; age-period-cohort effects; nonlinear effects;
    All these keywords.

    JEL classification:

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

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