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Exploring the demographic history of populations with enhanced Lexis surfaces

Author

Listed:
  • Jorge Cimentada

    (Max-Planck-Institut für Demografische Forschung)

  • Sebastian Kluesener

    (Bundesinstitut für Bevölkerungsforschung (BiB))

  • Tim Riffe

    (Euskal Herriko Unibertsitatea (University of the Basque Country))

Abstract

Background: Lexis surfaces are widely used to analyze demographic trends across periods, ages, and birth cohorts. When used to visualize rates or trends, these plots usually do not convey information about population size. The failure to communicate population size in Lexis surfaces can lead to misinterpretations of mortality or other conditions that populations face. For example, high mortality rates at very high ages have historically been experienced by only a small proportion of a population or cohort. Objective: We propose enhanced Lexis surfaces that include a visual representation of population size. The examples we present demonstrate how such plots can give readers a more intuitive understanding of the demographic development of a population over time. Methods: Visualizations are implemented using an R-Shiny application, building upon perception theories. Results: We present example plots for enhanced Lexis surfaces that show trends in cohort mortality and first-order differences in cohort mortality developments. These plots illustrate how adding the cohort size dimension allows us to extend the analytical potential of standard Lexis surfaces. Contribution: Our enhanced Lexis surfaces improve conventional depictions of period, age, and cohort trends in demographic developments of populations. An online interactive visualization tool based on Human Mortality Database data allows users to generate and export enhanced Lexis surfaces for their research. The R code to generate the application (and a link to the deployed application) can be accessed at https://github.com/cimentadaj/lexis_plot.

Suggested Citation

  • Jorge Cimentada & Sebastian Kluesener & Tim Riffe, 2020. "Exploring the demographic history of populations with enhanced Lexis surfaces," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(6), pages 149-164.
    • Handle: RePEc:dem:demres:v:42:y:2020:i:6
    DOI: 10.4054/DemRes.2020.42.6
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    References listed on IDEAS

    as
    1. Christophe Vandeschrick, 2001. "The Lexis diagram, a misnomer," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 4(3), pages 97-124.
    2. Guillaume Vandenbroucke, 2014. "Fertility and Wars: The Case of World War I in France," American Economic Journal: Macroeconomics, American Economic Association, vol. 6(2), pages 108-136, April.
    3. Jonas Schöley & Frans Willekens, 2017. "Visualizing compositional data on the Lexis surface," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 36(21), pages 627-658.
    4. Camarda, Carlo G., 2012. "MortalitySmooth: An R Package for Smoothing Poisson Counts with P-Splines," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(i01).
    5. Easterlin, Richard A., 1987. "Birth and Fortune," University of Chicago Press Economics Books, University of Chicago Press, edition 2, number 9780226180328, December.
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    Cited by:

    1. Tim Riffe & Nikola Sander & Sebastian Kluesener, 2021. "Editorial to the Special Issue on Demographic Data Visualization: Getting the point across – Reaching the potential of demographic data visualization," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(36), pages 865-878.

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    More about this item

    Keywords

    mortality; data visualization; historical demography; Lexis surface;
    All these keywords.

    JEL classification:

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

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