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The Intrinsic Estimator, Alternative Estimates, and Predictions of Mortality Trends: A Comment on Masters, Hummer, Powers, Beck, Lin, and Finch

Author

Listed:
  • Manfred Grotenhuis

    (Radboud University)

  • Ben Pelzer

    (Radboud University)

  • Liying Luo

    (University of Delaware)

  • Alexander W. Schmidt-Catran

    (University of Cologne)

Abstract

In this article, we discuss a study by Masters et al. (2014), published in Demography. Masters and associates estimated age, period, and cohort (APC) effects on U.S. mortality rates between 1959 and 2009 using the intrinsic estimator (IE). We first argue that before applying the IE, a grounded theoretical justification is needed for its fundamental constraint on minimum variance of the estimates. We next demonstrate IE’s high sensitivity to the type of dummy parameterization used to obtain the estimates. Finally, we discuss challenges in the interpretation of APC models. Our comments are not restricted to the article in question but pertain generally to any research that uses the IE.

Suggested Citation

  • Manfred Grotenhuis & Ben Pelzer & Liying Luo & Alexander W. Schmidt-Catran, 2016. "The Intrinsic Estimator, Alternative Estimates, and Predictions of Mortality Trends: A Comment on Masters, Hummer, Powers, Beck, Lin, and Finch," Demography, Springer;Population Association of America (PAA), vol. 53(4), pages 1245-1252, August.
    • Handle: RePEc:spr:demogr:v:53:y:2016:i:4:d:10.1007_s13524-016-0476-8
    DOI: 10.1007/s13524-016-0476-8
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    References listed on IDEAS

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    1. Ryan Masters & Robert Hummer & Daniel Powers & Audrey Beck & Shih-Fan Lin & Brian Finch, 2014. "Long-Term Trends in Adult Mortality for U.S. Blacks and Whites: An Examination of Period- and Cohort-Based Changes," Demography, Springer;Population Association of America (PAA), vol. 51(6), pages 2047-2073, December.
    2. Liying Luo, 2013. "Assessing Validity and Application Scope of the Intrinsic Estimator Approach to the Age-Period-Cohort Problem," Demography, Springer;Population Association of America (PAA), vol. 50(6), pages 1945-1967, December.
    3. Leonhard Held & Andrea Riebler, 2013. "Comment on “Assessing Validity and Application Scope of the Intrinsic Estimator Approach to the Age-Period-Cohort (APC) Problem”," Demography, Springer;Population Association of America (PAA), vol. 50(6), pages 1977-1979, December.
    4. Stephen Fienberg, 2013. "Cohort Analysis’ Unholy Quest: A Discussion," Demography, Springer;Population Association of America (PAA), vol. 50(6), pages 1981-1984, December.
    5. Stephen E. Fienberg & James S. Hodges & Liying Luo, 2015. "Letter To the Editor," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 457-457, March.
    6. Christopher Winship & David J. Harding, 2008. "A Mechanism-Based Approach to the Identification of Age–Period–Cohort Models," Sociological Methods & Research, , vol. 36(3), pages 362-401, February.
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    Cited by:

    1. Shih-Yung Su & Wen-Chung Lee, 2019. "Age-period-cohort analysis with a constant-relative-variation constraint for an apportionment of period and cohort slopes," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-21, December.
    2. Liying Luo & James Hodges, 2019. "The Age-Period-Cohort-Interaction Model for Describing and Investigating Inter-Cohort Deviations and Intra-Cohort Life-Course Dynamics," Papers 1906.08357, arXiv.org.
    3. Andrew Bell & Kelvyn Jones, 2018. "The hierarchical age–period–cohort model: Why does it find the results that it finds?," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 783-799, March.
    4. Liying Luo & John Robert Warren, 2023. "Describing and explaining age, period, and cohort trends in Americans’ vocabulary knowledge," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(3), pages 1-34, June.
    5. Patrick Denice, 2017. "Back to School: Racial and Gender Differences in Adults’ Participation in Formal Schooling, 1978–2013," Demography, Springer;Population Association of America (PAA), vol. 54(3), pages 1147-1173, June.
    6. Carlo Giovanni Camarda, 2019. "Smooth constrained mortality forecasting," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(38), pages 1091-1130.

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