Record linkage in the Cape of Good Hope Panel.

In this article, we describe the record linkage procedure to create a panel from Cape Colony census returns, or opgaafrolle, for 1787–1828, a dataset of 42,354 household-level observations. Based on a subset of manually linked records, we first evaluate statistical models and deterministic algorithm...

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Publicado en:Historical Methods Vol. 53; no. 2; pp. 112 - 130
Autores principales: Rijpma, Auke, Cilliers, Jeanne, Fourie, Johan
Formato: Artículo
Publicado: Taylor & Francis Ltd Apr-Jun2020
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1080/01615440.2018.1517030
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        atl: Record linkage in the Cape of Good Hope Panel.
      aug:
        au:
          Rijpma, Auke
          Cilliers, Jeanne
          Fourie, Johan
        affil:
          Department of History, Utrecht University, Utrecht, Netherlands
          Department of Economic History, Lund University, Lund, Sweden
          Department of Economics, Stellenbosch University, Stellenbosch, South Africa
      su:
        Census
        Taxation statistics
        Tax returns
        Statistical models
        Deterministic algorithms
        Machine learning
        Cape of Good Hope (South Africa)
      sug:
        subj:
          Cape of Good Hope (South Africa)
          Census
          Taxation statistics
          Tax returns
          Statistical models
          Deterministic algorithms
          Machine learning
      keyword:
        machine learning
        micro-data
        panel data
        record linkage
        South Africa
      ab: In this article, we describe the record linkage procedure to create a panel from Cape Colony census returns, or opgaafrolle, for 1787–1828, a dataset of 42,354 household-level observations. Based on a subset of manually linked records, we first evaluate statistical models and deterministic algorithms to best identify and match households over time. By using household-level characteristics in the linking process and near-annual data, we are able to create high-quality links for 84% of the dataset. We compare basic analyses on the linked panel dataset to the original cross-sectional data, evaluate the feasibility of the strategy when linking to supplementary sources, and discuss the scalability of our approach to the full Cape panel.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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