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Record linkage with complete-count historical census data

Presented by: 
Evan Roberts
Tuesday 13th September 2016 - 10:30 to 11:00
INI Seminar Room 1
Many areas of social science research benefit from being able to follow individuals and families across time, to observe changes in social behavior across at least part of the life course. Since the 1920s, and particularly since World War II longitudinal social surveys have become a common tool of social scientists. Despite their many benefits these surveys only allow us to study a limited number of birth cohorts, and few of these cohorts are entirely deceased. Comparison across multiple cohorts, and across long periods of the life course is not always possible as social scientists must follow their cohorts in real time.

Historical data on past populations allows us to reconstruct life-course panels for past cohorts. In the past few years complete transcriptions of census data from sequential censuses has become available in several countries including Britain, Canada, Iceland, Norway, Sweden, and the United States. The Minnesota Population Center is developing tools to create large datasets of people linked between at least two censuses. There are multiple challenges in creating this form of historical data, centering around the lack of unique identifiers. People must be identified by a combination of characteristics recorded with error including names, birthplaces, date of birth, and ethnic background. Although linkage rates are low by comparison to modern longitudinal surveys it has proved possible to create samples that are reasonably representative of the origin or terminal population. This paper describes the sources used in creating linked census datasets, the domain-specific issues in data linkage, and demonstrates some of the applications of historical longitudinal data in studying social mobility, and mortality in the past.

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University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons