IDEAS home Printed from https://ideas.repec.org/b/ces/ifofob/113.html
   My bibliography  Save this book

Rohstoff „Daten“: Volkswirtschaflicher Nutzen von Datenbereitstellung – eine Bestandsaufnahme

Author

Listed:
  • Oliver Falck
  • Johannes Koenen

Abstract

Studie mit finanzieller Unterstützung der IHK für München und Oberbayernim Rahmen des Vertrags zur Erstellung volkswirtschaftlicher Studien. Die Bedeutung der Datenökonomie für die Entwicklung der Wirtschaftsleistung in Deutschland und Europa ist unbestritten. In verschiedenen Märkten lassen sich allerdings – beispielsweise aufgrund von Netzwerkeffekten – Entwicklungen beobachten, die auf Marktversagen hinweisen könnten: Monopolisierungstendenzen, Abschottung und Einrichtung von „Datensilos" oder fehlender Zugang zu Daten und damit Barrieren beim Markteintritt für neue Marktakteure.

Suggested Citation

  • Oliver Falck & Johannes Koenen, 2020. "Rohstoff „Daten“: Volkswirtschaflicher Nutzen von Datenbereitstellung – eine Bestandsaufnahme," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 113.
    • Handle: RePEc:ces:ifofob:113
    as

    Download full text from publisher

    File URL: https://www.ifo.de/DocDL/ifo_Forschungsberichte_113_RohstoffDaten.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wendy C.Y. Li & Makoto Nirei & Kazufumi Yamana, 2018. "Value of Data: There’s No Such Thing as a Free Lunch in the Digital Economy," BEA Working Papers 0164, Bureau of Economic Analysis.
    2. Jaffe, Adam B, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits, and Market Value," American Economic Review, American Economic Association, vol. 76(5), pages 984-1001, December.
    3. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1, March.
    4. Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 38-42, May.
    5. Wolfert, Sjaak & Ge, Lan & Verdouw, Cor & Bogaardt, Marc-Jeroen, 2017. "Big Data in Smart Farming – A review," Agricultural Systems, Elsevier, vol. 153(C), pages 69-80.
    6. Spagnolo, Giancarlo & Calzolari, Giacomo & Felli, Leonardo & Koenen, Johannes & Stahl, Konrad, 2017. "Relational Contracts, Competition and Innovation: Theory and Evidence from German Car Manufacturers," CEPR Discussion Papers 12267, C.E.P.R. Discussion Papers.
    7. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338, December.
    8. Koutroumpis, Pantelis & Leiponen, Aija & Thomas, Llewellyn D W, 2017. "The (Unfulfilled) Potential of Data Marketplaces," ETLA Working Papers 53, The Research Institute of the Finnish Economy.
    9. Imanol Arrieta-Ibarra & Leonard Goff & Diego Jiménez-Hernández & Jaron Lanier & E. Glen Weyl, 2018. "Should We Treat Data as Labor? Moving beyond "Free"," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 38-42, May.
    10. Oliver Falck & Tobias Lohse, 2019. "Transformation into Service Providers and New Specification Profiles in Industry," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(01), pages 43-45, January.
    Full references (including those not matched with items on IDEAS)

    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. Oliver Falck & Johannes Koenen, 2020. "Resource “Data”: Economic Benefits of Data Provision," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(03), pages 31-41, September.
    2. Wagner, Dirk Nicolas, 2020. "The nature of the Artificially Intelligent Firm - An economic investigation into changes that AI brings to the firm," Telecommunications Policy, Elsevier, vol. 44(6).
    3. Cathles, Alison & Nayyar, Gaurav & Rückert, Désirée, 2020. "Digital technologies and firm performance: Evidence from Europe," EIB Working Papers 2020/06, European Investment Bank (EIB).
    4. Teruel Carrizosa, Mercedes & Coad, Alexander & Domnick, Clemens & Flachenecker, Florian & Harasztosi, Péter & Janiri, Mario Lorenzo & Pál, Rozália, 2021. "The birth of new high growth enterprises: Internationalisation through new digital technologies," EIB Working Papers 2021/02, European Investment Bank (EIB).
    5. Anderton, Robert & Jarvis, Valerie & Labhard, Vincent & Morgan, Julian & Petroulakis, Filippos & Vivian, Lara, 2020. "Virtually everywhere? Digitalisation and the euro area and EU economies," Occasional Paper Series 244, European Central Bank.
    6. Colin Wessendorf & Alexander Kopka & Dirk Fornahl, 2021. "The impact of the six European Key Enabling Technologies (KETs) on regional knowledge creation," Papers in Evolutionary Economic Geography (PEEG) 2127, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Sep 2021.
    7. Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Economics, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    8. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
    9. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    10. DUERNECKER Georg & SANCHEZ MARTINEZ Miguel, 2021. "Structural change and productivity growth in the European Union: Past, present and future," JRC Working Papers on Territorial Modelling and Analysis 2021-09, Joint Research Centre.
    11. Combes, Pierre-Philippe & Gobillon, Laurent & Zylberberg, Yanos, 2022. "Urban economics in a historical perspective: Recovering data with machine learning," Regional Science and Urban Economics, Elsevier, vol. 94(C).
    12. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asu Ozdaglar, 2022. "Too Much Data: Prices and Inefficiencies in Data Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 14(4), pages 218-256, November.
    13. Panos Constantinides & Ola Henfridsson & Geoffrey G. Parker, 2018. "Introduction—Platforms and Infrastructures in the Digital Age," Information Systems Research, INFORMS, vol. 29(2), pages 381-400, June.
    14. Vasiliki Koniakou, 2023. "From the “rush to ethics” to the “race for governance” in Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(1), pages 71-102, February.
    15. Andrea Szalavetz, 2019. "Artificial Intelligence-Based Development Strategy in Dependent Market Economies - Any Room amidst Big Power Rivalry?," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 40-54.
    16. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    17. Fossen, Frank M. & Sorgner, Alina, 2021. "Digitalization of work and entry into entrepreneurship," Journal of Business Research, Elsevier, vol. 125(C), pages 548-563.
    18. Mario Benassi & Elena Grinza & Francesco Rentocchini & Laura Rondi, 2022. "Patenting in 4IR technologies and firm performance [Robots and jobs: evidence from US labor markets]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(1), pages 112-136.
    19. Charles M. A. Clark & Aleksandr V. Gevorkyan, 2020. "Artificial Intelligence and Human Flourishing," American Journal of Economics and Sociology, Wiley Blackwell, vol. 79(4), pages 1307-1344, September.
    20. Nicholas Crafts, 2022. "Slow real wage growth during the Industrial Revolution: productivity paradox or pro-rich growth? [Engels’ pause: technical change, capital accumulation, and inequality in the British industrial rev," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 1-13.

    More about this item

    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:ifofob:113. 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/ifooode.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.