IDEAS home Printed from https://ideas.repec.org/a/kap/poprpr/v42y2023i3d10.1007_s11113-023-09785-z.html
   My bibliography  Save this article

Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records

Author

Listed:
  • Joshua R. Goldstein

    (University of California, Berkeley)

  • Maria Osborne

    (University of California, Berkeley)

  • Serge Atherwood

    (University of San Francisco)

  • Casey F. Breen

    (University of California, Berkeley)

Abstract

New advances in data linkage provide mortality researchers with access to administrative datasets with millions of mortality records and rich demographic covariates. Although these new datasets allow for high-resolution mortality research, administrative mortality records often have technical limitations, such as limited mortality coverage windows and incomplete observation of survivors. We describe a method for fitting truncated distributions that can be used for estimating mortality differentials in administrative data. We apply this method to the CenSoc datasets, which link the United States 1940 Census records to Social Security administrative mortality records. Our approach may be useful in other contexts where administrative data on deaths are available. As a companion to the paper, we release the R package gompertztrunc, which implements the methods introduced in this paper.

Suggested Citation

  • Joshua R. Goldstein & Maria Osborne & Serge Atherwood & Casey F. Breen, 2023. "Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(3), pages 1-20, June.
    • Handle: RePEc:kap:poprpr:v:42:y:2023:i:3:d:10.1007_s11113-023-09785-z
    DOI: 10.1007/s11113-023-09785-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11113-023-09785-z
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11113-023-09785-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dan A. Black & Yu-Chieh Hsu & Seth G. Sanders & Lynne Steuerle Schofield & Lowell J. Taylor, 2017. "The Methuselah Effect: The Pernicious Impact of Unreported Deaths on Old-Age Mortality Estimates," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2001-2024, December.
    2. Neil K. Mehta & Irma T. Elo & Michal Engelman & Diane S. Lauderdale & Bert M. Kestenbaum, 2016. "Life Expectancy Among U.S.-born and Foreign-born Older Adults in the United States: Estimates From Linked Social Security and Medicare Data," Demography, Springer;Population Association of America (PAA), vol. 53(4), pages 1109-1134, August.
    3. Zhiliang Ying & Wen Yu & Ziqiang Zhao & Ming Zheng, 2020. "Regression Analysis of Doubly Truncated Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(530), pages 810-821, April.
    4. Lior Rennert & Sharon X. Xie, 2018. "Cox regression model with doubly truncated data," Biometrics, The International Biometric Society, vol. 74(2), pages 725-733, June.
    5. Casey Breen & Joshua R. Goldstein, 2022. "Berkeley Unified Numident Mortality Database: Public administrative records for individual-level mortality research," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(5), pages 111-142.
    6. Alexander, Monica, 2018. "Deaths without denominators: using a matched dataset to study mortality patterns in the United States," SocArXiv q79ye, Center for Open Science.
    7. Breen, Casey & Goldstein, Joshua R., 2022. "Berkeley Unified Numident Mortality Database: Public Administrative Records for Individual-Level Mortality Research," SocArXiv pc294, Center for Open Science.
    8. Mandel, Micha, 2007. "Censoring and TruncationHighlighting the Differences," The American Statistician, American Statistical Association, vol. 61, pages 321-324, November.
    9. Andrew Halpern-Manners & Jonas Helgertz & John Robert Warren & Evan Roberts, 2020. "The Effects of Education on Mortality: Evidence From Linked U.S. Census and Administrative Mortality Data," Demography, Springer;Population Association of America (PAA), vol. 57(4), pages 1513-1541, August.
    10. Jason Fletcher & Hamid Noghanibehambari, 2021. "The Effects of Education on Mortality: Evidence Using College Expansions," NBER Working Papers 29423, National Bureau of Economic Research, Inc.
    11. Lleras-Muney, Adriana & Price, Joseph & Yue, Dahai, 2022. "The association between educational attainment and longevity using individual-level data from the 1940 census," Journal of Health Economics, Elsevier, vol. 84(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Héctor Pifarré i Arolas & José C. Andrade Santacruz & Mikko Myrskylä, 2023. "An overlapping cohorts perspective of lifespan inequality," MPIDR Working Papers WP-2023-046, Max Planck Institute for Demographic Research, Rostock, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Breen, Casey & Goldstein, Joshua R., 2022. "Berkeley Unified Numident Mortality Database: Public Administrative Records for Individual-Level Mortality Research," SocArXiv pc294, Center for Open Science.
    2. Goldstein, Joshua R. & Osborne, Maria & Atherwood, Serge & Breen, Casey, 2022. "Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records," SocArXiv efdzh, Center for Open Science.
    3. Hamid Noghanibehambari & Farzaneh Noghani, 2023. "Long‐run intergenerational health benefits of women empowerment: Evidence from suffrage movements in the US," Health Economics, John Wiley & Sons, Ltd., vol. 32(11), pages 2583-2631, November.
    4. Casey F. Breen, 2023. "Late-Life Changes in Ethnoracial Self-identification: Evidence from Social Security Administrative Data," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(1), pages 1-18, February.
    5. Noghanibehambari, Hamid & Engelman, Michal, 2022. "Social insurance programs and later-life mortality: Evidence from new deal relief spending," Journal of Health Economics, Elsevier, vol. 86(C).
    6. Risto Conte Keivabu & Ugofilippo Basellini & Emilio Zagheni, 2022. "Racial disparities in deaths related to extreme temperatures in the United States between 1993 and 2005," MPIDR Working Papers WP-2022-028, Max Planck Institute for Demographic Research, Rostock, Germany.
    7. Casey Breen & Joshua R. Goldstein, 2022. "Berkeley Unified Numident Mortality Database: Public administrative records for individual-level mortality research," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(5), pages 111-142.
    8. Hamid Noghanibehambari & Jason Fletcher, 2023. "Childhood exposure to birth registration laws and old‐age mortality," Health Economics, John Wiley & Sons, Ltd., vol. 32(3), pages 735-743, March.
    9. Lior Rennert & Sharon X. Xie, 2022. "Cox regression model under dependent truncation," Biometrics, The International Biometric Society, vol. 78(2), pages 460-473, June.
    10. Bella Vakulenko‐Lagun & Micha Mandel & Rebecca A. Betensky, 2020. "Inverse probability weighting methods for Cox regression with right‐truncated data," Biometrics, The International Biometric Society, vol. 76(2), pages 484-495, June.
    11. Janice Compton & Robert A Pollak, 2021. "The life expectancy of older couples and surviving spouses," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-13, May.
    12. Kaarina Reini & Jan Saarela, 2021. "Life Expectancy of the Ethnically Mixed: Register-Based Evidence from Native Finns," IJERPH, MDPI, vol. 18(7), pages 1-10, March.
    13. Jing Zhao & Xiaoru Zuo & Chun-Ping Chang, 2023. "More economic growth with the better public health? Evidence from Western China," Economic Change and Restructuring, Springer, vol. 56(2), pages 1083-1112, April.
    14. Alexander, Monica, 2018. "Deaths without denominators: using a matched dataset to study mortality patterns in the United States," SocArXiv q79ye, Center for Open Science.
    15. Hélène Benveniste & Jesús Crespo Cuaresma & Matthew Gidden & Raya Muttarak, 2021. "Tracing international migration in projections of income and inequality across the Shared Socioeconomic Pathways," Climatic Change, Springer, vol. 166(3), pages 1-22, June.
    16. Mary J. Lopez & Sita Slavov, 2020. "Do immigrants delay retirement and social security claiming?," Applied Economics, Taylor & Francis Journals, vol. 52(10), pages 1105-1123, February.
    17. Peng Liu & Kwun Chuen Gary Chan & Ying Qing Chen, 2023. "On a simple estimation of the proportional odds model under right truncation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(3), pages 537-554, July.
    18. Read, Jen'nan Ghazal & West, Jessica S. & Kamis, Christina, 2020. "Immigration and health among non-Hispanic whites: The impact of arrival cohort and region of birth," Social Science & Medicine, Elsevier, vol. 246(C).
    19. Lleras-Muney, Adriana & Price, Joseph & Yue, Dahai, 2022. "The association between educational attainment and longevity using individual-level data from the 1940 census," Journal of Health Economics, Elsevier, vol. 84(C).
    20. Saul Justin Newman, 2018. "Errors as a primary cause of late-life mortality deceleration and plateaus," PLOS Biology, Public Library of Science, vol. 16(12), pages 1-12, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:poprpr:v:42:y:2023:i:3:d:10.1007_s11113-023-09785-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.