IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_10540.html
   My bibliography  Save this paper

FamData: Database for Family Business Companies in Germany Covering Company Key Figures and Survey Data

Author

Listed:
  • Johanna Garnitz
  • Annette von Maltzan
  • Klaus Wohlrabe

Abstract

FamData is a database covering family businesses and non-family businesses across various size classes and branches containing structural and financial information. The ifo Institute assembled a business panel with executives from almost 4,000 companies. In addition to the “hard” business data like turnover and number of employees, the database also includes “soft” survey data. The latter one covers information from regular – at least yearly - surveys treating topics like investment behavior, skilled labor shortage or reaction of firms during the Corona pandemic situation and the rise in energy prices observed in 2022.

Suggested Citation

  • Johanna Garnitz & Annette von Maltzan & Klaus Wohlrabe, 2023. "FamData: Database for Family Business Companies in Germany Covering Company Key Figures and Survey Data," CESifo Working Paper Series 10540, CESifo.
    • Handle: RePEc:ces:ceswps:_10540
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10540.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Magdolna Hiersemenzel & Stefan Sauer & Klaus Wohlrabe, 2022. "On the Representativeness of the ifo Business Survey," CESifo Working Paper Series 9863, CESifo.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Garnitz Johanna & von Maltzan Annette & Wohlrabe Klaus, 2025. "FamData: Database for Family Business Companies in Germany Covering Company Key Figures and Survey Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 245(1-2), pages 235-246.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Almut Balleer & Marvin Noeller, 2023. "Monetary Policy in the Presence of Supply Constraints: Evidence from German Firm-Level Data," CESifo Working Paper Series 10261, CESifo.
    2. Nöller, Marvin & Balleer, Almut, 2023. "Monetary Policy in the Presence of Supply Constraints: Evidence from German Firm-level Data," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277638, Verein für Socialpolitik / German Economic Association.
    3. Link, Sebastian, 2024. "The price and employment response of firms to the introduction of minimum wages," Journal of Public Economics, Elsevier, vol. 239(C).
    4. Link, Sebastian & Peichl, Andreas & Roth, Christopher & Wohlfart, Johannes, 2023. "Information frictions among firms and households," Journal of Monetary Economics, Elsevier, vol. 135(C), pages 99-115.
    5. Born, Benjamin & Enders, Zeno & Menkhoff, Manuel & Müller, Gernot & Niemann, Knut, 2022. "Firm Expectations and News: Micro v Macro," CEPR Discussion Papers 17768, C.E.P.R. Discussion Papers.
    6. Balleer, Almut & Noeller, Marvin, 2023. "Monetary policy in the presence of supply constraints: Evidence from German firm-level data," Ruhr Economic Papers 1060, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    7. Dovern, Jonas & Müller, Lena Sophia & Wohlrabe, Klaus, 2023. "Local information and firm expectations about aggregates," Journal of Monetary Economics, Elsevier, vol. 138(C), pages 1-13.
    8. Thomas Licht & Klaus Wohlrabe, 2024. "AI Adoption Among German Firms," CESifo Working Paper Series 11459, CESifo.

    More about this item

    Keywords

    family businesses; micro data; surveys;
    All these keywords.

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_10540. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.