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The IAB-SMART-Mobility Module: An Innovative Research Dataset with Mobility Indicators Based on Raw Geodata

Author

Listed:
  • Zimmermann Florian

    (Institute for Employment Research, Nuremberg, Germany)

  • Filser Andreas

    (Institute for Employment Research, Nuremberg, Germany)

  • Haas Georg-Christoph

    (Institute for Employment Research, Nuremberg, Germany)

  • Bähr Sebastian

    (Institute for Employment Research, Nuremberg, Germany)

Abstract

The ubiquity of smartphones has enabled the collection of novel data through their built-in sensors, including geolocation data which can be used to understand mobility behavior. In this project, we leveraged longitudinal geolocation data collected from participants in the 2018 German app study IAB-SMART to develop a set of mobility indicators, such as visited unique locations and traveled distance. The indicators can be linked to the Panel Study Labour Market and Social Security (PASS) survey and administrative employment histories. The resulting novel dataset offers a unique opportunity to study the relationship between mobility and labor market outcomes. This article provides an overview of the study, outlines the data preparation process, and the socio-demographic characteristics of the 398 participants of the IAB-SMART-Mobility module. We present the mobility indicators generated from the geolocation data and provide guidance for accessing the Institute for Employment Research’s (IAB) data.

Suggested Citation

  • Zimmermann Florian & Filser Andreas & Haas Georg-Christoph & Bähr Sebastian, 2024. "The IAB-SMART-Mobility Module: An Innovative Research Dataset with Mobility Indicators Based on Raw Geodata," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 244(5-6), pages 685-698.
    • Handle: RePEc:jns:jbstat:v:244:y:2024:i:5-6:p:685-698:n:1002
    DOI: 10.1515/jbnst-2023-0051
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    References listed on IDEAS

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    1. Florian Keusch & Sebastian Bähr & Georg-Christoph Haas & Frauke Kreuter & Mark Trappmann, 2023. "Coverage Error in Data Collection Combining Mobile Surveys With Passive Measurement Using Apps: Data From a German National Survey," Sociological Methods & Research, , vol. 52(2), pages 841-878, May.
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    3. Alan B. Krueger & Andreas I. Mueller, 2012. "Time Use, Emotional Well-Being, and Unemployment: Evidence from Longitudinal Data," American Economic Review, American Economic Association, vol. 102(3), pages 594-599, May.
    4. Antoni Manfred & Bethmann Arne, 2019. "PASS-ADIAB – Linked Survey and Administrative Data for Research on Unemployment and Poverty," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(4), pages 747-756, August.
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    More about this item

    Keywords

    data manual; geodata; labor market data; PASS data; smartphone data;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    Statistics

    Access and download statistics

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