IDEAS home Printed from https://ideas.repec.org/p/frz/wpaper/wp2018_20.rdf.html
   My bibliography  Save this paper

Power-Laws in Art. From Renaissance to Contemporary Art

Author

Listed:
  • Federico Etro
  • Elena Stepanova

Abstract

We provide evidence of a cubic law of art prices that hints to a general pattern for the distribution of artistic talent. The persistence across heterogeneous markets from historical ones to contemporary art auctions of a power law in the distribution of the average price per artist suggests the possibility of a universal law for talent distribution. We explore scale-free networks of teacher-students to investigate the diffusion of talent over time.

Suggested Citation

  • Federico Etro & Elena Stepanova, 2018. "Power-Laws in Art. From Renaissance to Contemporary Art," Working Papers - Economics wp2018_20.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    • Handle: RePEc:frz:wpaper:wp2018_20.rdf
    as

    Download full text from publisher

    File URL: https://www.disei.unifi.it/upload/sub/pubblicazioni/repec/pdf/wp20_2018.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
    2. Federico Etro & Elena Stepanova, 2016. "Entry of painters in the Amsterdam market of the Golden Age," Journal of Evolutionary Economics, Springer, vol. 26(2), pages 317-348, May.
    3. Etro, Federico, 2018. "The Economics of Renaissance Art," The Journal of Economic History, Cambridge University Press, vol. 78(2), pages 500-538, June.
    4. Federico Etro & Elena Stepanova, 2015. "The Market for Paintings in Paris between Rococo and Romanticism," Kyklos, Wiley Blackwell, vol. 68(1), pages 28-50, February.
    5. Federico Etro & Elena Stepanova, 2017. "Art Auctions and Art Investment in the Golden Age of British Painting," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(2), pages 191-225, May.
    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. Etro, Federico & Stepanova, Elena, 2021. "Art return rates from old master paintings to contemporary art," Journal of Economic Behavior & Organization, Elsevier, vol. 181(C), pages 94-116.
    2. Etro, Federico & Marchesi, Silvia & Stepanova, Elena, 2020. "Liberalizing art. Evidence on the Impressionists at the end of the Paris Salon," European Journal of Political Economy, Elsevier, vol. 62(C).
    3. Etro, Federico & Stepanova, Elena, 2018. "Power-laws in art," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 217-220.
    4. Federico Etro & Elena Stepanova, 2017. "Art collections and taste in the Spanish Siglo de Oro," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 41(3), pages 309-335, August.
    5. Etro, Federico, 2018. "The Economics of Renaissance Art," The Journal of Economic History, Cambridge University Press, vol. 78(2), pages 500-538, June.
    6. Federico Etro & Elena Stepanova, 2017. "Art Auctions and Art Investment in the Golden Age of British Painting," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(2), pages 191-225, May.
    7. Etro, Federico, 2024. "Art and Markets in the Greco-Roman World," The Journal of Economic History, Cambridge University Press, vol. 84(2), pages 432-478, June.
    8. Anne-Sophie V. Radermecker & Koenraad Brosens, 2023. "Valuing European tapestry: from riches to rags," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(3), pages 359-406, September.
    9. Anne-Sophie Radermecker & Koenraad Brosens, 2023. "Valuing European tapestry: from riches to rags," ULB Institutional Repository 2013/371370, ULB -- Universite Libre de Bruxelles.
    10. Elena Stepanova, 2019. "The impact of color palettes on the prices of paintings," Empirical Economics, Springer, vol. 56(2), pages 755-773, February.
    11. Edward Oczkowski, 2021. "The catalogue raisonné and art auction prices: the case of Berthe Morisot," Empirical Economics, Springer, vol. 61(3), pages 1669-1687, September.
    12. Abduraimova, Kumushoy, 2022. "Contagion and tail risk in complex financial networks," Journal of Banking & Finance, Elsevier, vol. 143(C).
    13. SAITO Yukiko, 2013. "Role of Hub Firms in Geographical Transaction Network," Discussion papers 13080, Research Institute of Economy, Trade and Industry (RIETI).
    14. Foellmi, Reto & Martínez, Isabel Z., 2014. "Volatile Top Income Shares in Switzerland? Reassessing the Evolution Between 1981 and 2009," CEPR Discussion Papers 10006, C.E.P.R. Discussion Papers.
    15. Dominik Prochniewicz & Jacek Kudrys & Kamil Maciuk, 2022. "Noises in Double-Differenced GNSS Observations," Energies, MDPI, vol. 15(5), pages 1-18, February.
    16. Ross Richardson & Matteo G. Richiardi & Michael Wolfson, 2015. "We ran one billion agents. Scaling in simulation models," LABORatorio R. Revelli Working Papers Series 142, LABORatorio R. Revelli, Centre for Employment Studies.
    17. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
    18. Harmenberg, Karl, 2024. "A simple theory of Pareto-distributed earnings," Economics Letters, Elsevier, vol. 234(C).
    19. Da Silva, Sergio, 2009. "Does Macroeconomics Need Microeconomic Foundations?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-11.
    20. Chen, Zhimin & Ibragimov, Rustam, 2019. "One country, two systems? The heavy-tailedness of Chinese A- and H- share markets," Emerging Markets Review, Elsevier, vol. 38(C), pages 115-141.

    More about this item

    Keywords

    Power laws; Art prices; Talent distribution; Scale-free networks;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature

    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:frz:wpaper:wp2018_20.rdf. 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: Giorgio Ricchiuti (email available below). General contact details of provider: https://edirc.repec.org/data/defirit.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.