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Title: IPUMS Multigenerational Longitudinal Panel

Citation Type: Miscellaneous

Publication Year: 2019

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Abstract: IPUMS-MLP will consist of nine censuses covering the entire U.S. population enumerated between 1850 and 1940 linked with public historical administrative data from Social Security, the military, and vital registration. The linked database will be invaluable for analyzing the impact of early life conditions on health and well-being in later life, and the large scale of the resource will allow study of very small population subgroups. IPUMS-MLP is not designed to answer any particular scientific question. Rather, we plan general-purpose data infrastructure, a permanent resource that can be continuously expanded to incorporate the latest data sources as they become available, ensuring its usage for decades to come. Former Census Bureau Director Robert Groves drew an insightful distinction between “designed data” and “organic data” [1]. Designed data, such as censuses and surveys, are created entirely to obtain information. Organic data are byproducts of transactions, including administrative records generated by Social Security, Medicare, the Internal Revenue Service, and the Armed Forces. Research on population aging currently relies primarily on designed data, despite the enormous potential of organic data to enrich our analyses. Groves argued that “the biggest payoff will lie in new combinations of designed data and organic data, not in one type alone.” Used in isolation, organic data have profound limitations that reduce their usefulness. They tend to be voluminous but shallow; they often are unrepresentative of the general population; and they frequently omit basic information about demographic behavior, economic status, education, work, and living conditions. IPUMS-MLP will enrich large sources of organic data—including Social Security, Medicare, and military records—by linking them to a century of designed census and survey data, thereby overcoming limitations of the organic data sources. Linking individuals from childhood to old age and death through both designed and organic data allows study of aging as a process over the entire life course, not just over a few years. Indeed, IPUMS-MLP will enable investigators to extend longitudinal analysis beyond individual life histories to investigate and understand processes of change over multiple generations [2]. In his 2010 presidential address to the Population Association of America, Robert Mare [3] argued that “the study of intergenerational mobility and most population research are governed by a two generation (parent-to offspring) view of intergenerational influence, to the neglect of the effects of grandparents and other ancestors and nonresident contemporary kin.” Mare called for the development of sources and methods that will support analysis of change over multiple generations. IPUMS-MLP will meet this need, allowing investigators to trace records back across multiple generations and making it possible for the first time to study the transmission of characteristics and behavior across centuries.

Url: https://users.pop.umn.edu/~ruggles/Articles/MLP Paper_5-15.pdf

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Authors: Ruggles, Steven; Fitch, Catherine; Goeken, Ron; Hacker, J. David; Helgertz, Jonas; Roberts, Evan; Sobek, Matt; Thompson, Kelly; Warren, John Robert; Wellington, Jacob

Publisher: IPUMS

Data Collections: IPUMS USA - Ancestry Full Count Data

Topics: Population Data Science

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