Synthetic data for open and reproducible methodological research in social sciences and official statistics

Jan Pablo Burgard (), Jan-Philipp Kolb (), Hariolf Merkle () and Ralf Münnich ()
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Jan Pablo Burgard: Universität Trier
Jan-Philipp Kolb: GESIS
Hariolf Merkle: Universität Trier
Ralf Münnich: Universität Trier

AStA Wirtschafts- und Sozialstatistisches Archiv, 2017, vol. 11, issue 3, No 6, 233-244

Abstract: Abstract Open and reproducible research receives more and more attention in the research community. Whereas empirical research may benefit from research data centres or scientific use files that foster using data in a safe environment or with remote access, methodological research suffers from the availability of adequate data sources. In economic and social sciences, an additional drawback results from the presence of complex survey designs in the data generating process, that has to be considered when developing and applying estimators. In the present paper, we present a synthetic but realistic dataset based on social science data, that fosters evaluating and developing estimators in social sciences. The focus is on supporting comparable and reproducible research in a realistic framework providing individual and household data. The outcome is provided as an open research data resource.

Keywords: Open and reproducible research; Open data; Household data; Simulation experiments; Vergleichbare und reproduzierbare Forschung; Open Data; Haushaltsdaten; Simulationsstudien (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s11943-017-0214-8

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