[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/zbw/glodps/515.html
   My bibliography  Save this paper

The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve

Author

Listed:
  • de Pedraza, Pablo
  • Vollbracht, Ian
Abstract
This paper presents a theoretical conceptualization of the data economy that motivates more access to data for scientific research. It defines the semicircular flow of the data economy as analogous to the traditional circular flow of the economy. Knowledge extraction from large, inter-connected data sets displays natural monopoly characteristics, which favours the emergence of oligopolistic data holders that generate and disclose the amount of knowledge that maximizes their profit. If monopoly theory holds, this level of knowledge is below the socially desirable amount because data holders have incentives to maintain their market power. The analogy is further developed to include data leakages, data sharing policies, merit and demerit knowledge, and knowledge injections. It draws a data sharing Laffer curve that defines optimal data sharing as the point where the production of merit knowledge is maximized. The theoretical framework seems to describe many features of the data-intensive economy of today, in which large-scale data holders specialize in extraction of knowledge from the data they hold. Conclusions support the use of policies to enhance data sharing and, or, enhanced user-centric data property rights to facilitate data flows in a manner that would increase merit knowledge generation up to the socially desirable amount.

Suggested Citation

  • de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
    • Handle: RePEc:zbw:glodps:515
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/215779/1/GLO-DP-0515.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Liran Einav & Jonathan Levin, 2014. "The Data Revolution and Economic Analysis," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
    3. -, 2014. "A World that Counts: Mobilising the Data Revolution for Sustainable Development," Coediciones, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), number 40319 edited by United Nations.
    4. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    5. Max Boisot & Agustí Canals, 2004. "Data, information and knowledge: have we got it right?," Journal of Evolutionary Economics, Springer, vol. 14(1), pages 43-67, January.
    6. Erik Brynjolfsson & Avinash Collis & Felix Eggers, 2019. "Using massive online choice experiments to measure changes in well-being," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(15), pages 7250-7255, April.
    7. Nestor Duch-Brown, 2017. "Quality discrimination in online multi-sided markets," JRC Working Papers on Digital Economy 2017-06, Joint Research Centre.
    8. Charles I. Jones & Christopher Tonetti, 2020. "Nonrivalry and the Economics of Data," American Economic Review, American Economic Association, vol. 110(9), pages 2819-2858, September.
    9. Bertin Martens, 2016. "An Economic Policy Perspective on Online Platforms," JRC Working Papers on Digital Economy 2016-05, Joint Research Centre.
    10. N/A, 2016. "The UK Economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 235(1), pages 3-3, February.
    11. Nikolaos Askitas & Klaus F. Zimmermann, 2013. "Nowcasting Business Cycles Using Toll Data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(4), pages 299-306, July.
    12. Pedraza Pablo de & Visintin Stefano & Tijdens Kea & Kismihók Gábor, 2019. "Survey vs Scraped Data: Comparing Time Series Properties of Web and Survey Vacancy Data," IZA Journal of Labor Economics, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 8(1), pages 1-23, June.
    13. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
    14. Dirk Bergemann & Alessandro Bonatti, 2019. "Markets for Information: An Introduction," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 85-107, August.
    15. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    16. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Detecting Mortgage Delinquencies," IZA Discussion Papers 5895, Institute of Labor Economics (IZA).
    17. Concha Artola & Fernando Pinto & Pablo de Pedraza García, 2015. "Can internet searches forecast tourism inflows?," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 103-116, April.
    18. Jonathan V. Hall & Alan B. Krueger, 2015. "An Analysis of the Labor Market for Uber's Driver-Partners in the United States," Working Papers 587, Princeton University, Department of Economics, Industrial Relations Section..
    19. N/A, 2016. "The UK Economy," National Institute Economic Review, National Institute of Economic and Social Research, vol. 236(1), pages 49-49, May.
    20. Simon Board & Jay Lu, 2018. "Competitive Information Disclosure in Search Markets," Journal of Political Economy, University of Chicago Press, vol. 126(5), pages 1965-2010.
    21. Nestor Duch-Brown, 2017. "Platforms to business relations in online platform ecosystems," JRC Working Papers on Digital Economy 2017-07, Joint Research Centre.
    22. Benjamin Reed Shiller, 2013. "First Degree Price Discrimination Using Big Data," Working Papers 58, Brandeis University, Department of Economics and International Business School, revised Jan 2014.
    23. Azzellini, Dario & Greer, Ian & Umney, Charles, 2019. "Limits of the platform economy: Digitalization and marketization in live music," Working Paper Forschungsförderung 154, Hans-Böckler-Stiftung, Düsseldorf.
    24. David Evans, 2013. "Economics Of Vertical Restraints For Multi-Sided Platforms," CPI Journal, Competition Policy International, vol. 9.
    25. Askitas, Nikos & Zimmermann, Klaus F., 2011. "Health and Well-Being in the Crisis," IZA Discussion Papers 5601, Institute of Labor Economics (IZA).
    26. Cristiano Codagnone & Bertin Martens, 2016. "Scoping the Sharing Economy: Origins, Definitions, Impact and Regulatory Issues," JRC Working Papers on Digital Economy 2016-01, Joint Research Centre.
    27. Nestor Duch-Brown & Bertin Martens & Frank Mueller-Langer, 2017. "The economics of ownership, access and trade in digital data," JRC Working Papers on Digital Economy 2017-01, Joint Research Centre.
    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. Pablo Pedraza & Ian Vollbracht, 2023. "General theory of data, artificial intelligence and governance," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    2. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    3. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    4. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    5. Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2022. "Data brokers co-opetition [The impact of big data on firm performance: an empirical investigation]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 820-839.
    6. MARTENS Bertin, 2020. "An economic perspective on data and platform market power," JRC Working Papers on Digital Economy 2020-09, Joint Research Centre.
    7. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
    8. Bertin Martens & Alexandre de Streel & Inge Graef & Thomas Tombal & Nestor Duch-Brown, 2020. "Business-to-Business data sharing: An economic and legal analysis," JRC Working Papers on Digital Economy 2020-05, Joint Research Centre.
    9. Petros E. Ioannatos, 2021. "Brexit or Euro for the UK? Evidence from Panel Data," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 63(1), pages 117-138, March.
    10. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    11. Nestor Duch-Brown, 2017. "The competitive landscape of online platforms," JRC Working Papers on Digital Economy 2017-04, Joint Research Centre.
    12. Jung-Suk Yu & M. Kabir Hassan & Abdullah Mamun & Abul Hassan, 2014. "Financial Sectors Reform and Economic Growth in Morocco: An Empirical Analysis," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 13(1), pages 69-102, April.
    13. repec:zbw:rwidps:0030 is not listed on IDEAS
    14. Kawalec Paweł, 2020. "The dynamics of theories of economic growth: An impact of Unified Growth Theory," Economics and Business Review, Sciendo, vol. 6(2), pages 19-44, June.
    15. Iamsiraroj, Sasi, 2016. "The foreign direct investment–economic growth nexus," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 116-133.
    16. Siemiński, Paweł & Hadyński, Jakub & Poczta, Walenty, 2020. "Diversification Of Human Capital Resources In Rural And Urban Areas In Poland," Roczniki (Annals), Polish Association of Agricultural Economists and Agribusiness - Stowarzyszenie Ekonomistow Rolnictwa e Agrobiznesu (SERiA), vol. 2020(1).
    17. Eckstein, Zvi & Zilcha, Itzhak, 1994. "The effects of compulsory schooling on growth, income distribution and welfare," Journal of Public Economics, Elsevier, vol. 54(3), pages 339-359, July.
    18. Kumar, Sanjesh & Singh, Baljeet, 2019. "Barriers to the international diffusion of technological innovations," Economic Modelling, Elsevier, vol. 82(C), pages 74-86.
    19. Johannes W. Fedderke & John M. Luiz, 2005. "Does Human Generate Social and Institutional Capital? Exploring Evidence From Time Series Data in a Middle Income Country," Working Papers 029, Economic Research Southern Africa.
    20. Günther Rehme, 2007. "Education, Economic Growth and Measured Income Inequality," Economica, London School of Economics and Political Science, vol. 74(295), pages 493-514, August.
    21. Blomström, Magnus & Kokko, Ari, 2003. "Human Capital and Inward FDI," CEPR Discussion Papers 3762, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    Big data; Artificial Intelligence; Government;
    All these keywords.

    JEL classification:

    • H1 - Public Economics - - Structure and Scope of Government
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • P48 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - Legal Institutions; Property Rights; Natural Resources; Energy; Environment; Regional Studies

    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:zbw:glodps:515. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/glabode.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.