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Being Central and Productive? Evidence from Slovenian Visual Artists in the 19th and 20th Century


  • Andrej Srakar

    () (Institute for Economic Research, Faculty of Economics, University of Ljubljana, Slovenia)

  • Petja Grafenauer

    () (School of Arts, University of Nova Gorica, Nova Gorica, Slovenia)

  • Marilena Vecco

    () (Erasmus University Rotterdam, The Netherlands)


Slovenian art history has received very little (if any) attention from the viewpoint of network theory although there were several examples of artists co-working or working in groups, collectives or even loosely organized clusters (groups from the impressionist Sava in 1904 to postmodern Irwin in 1984). This may be interpreted as a way to acquire better positions in the national and international art circles and on the art market. In our article we use web-based dataset of Slovenska biografija (operated by the Slovenian Academy of Sciences and Arts), which contains data on numerous notable persons throughout Slovenian history to analyze the centrality of individual artistic figures and movements throughout Slovenian art history. We also study the influence of network centrality on cultural production controlling for endogeneity following the instrumental variable approach, proposed in the literature while using a new instrumental variable to solve the problem. Finally, we present results which show that women visual artists used their network positions more intensively than men and provide some first explanations for this observed relationship. In conclusion, we provide some reflections on the importance of these findings for further research work in the area.

Suggested Citation

  • Andrej Srakar & Petja Grafenauer & Marilena Vecco, 2016. "Being Central and Productive? Evidence from Slovenian Visual Artists in the 19th and 20th Century," ACEI Working Paper Series AWP-09-2016, Association for Cultural Economics International, revised Sep 2016.
  • Handle: RePEc:cue:wpaper:awp-09-2016

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    References listed on IDEAS

    1. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 581-603, December.
    2. Borowiecki, Karol Jan, 2013. "Geographic clustering and productivity: An instrumental variable approach for classical composers," Journal of Urban Economics, Elsevier, vol. 73(1), pages 94-110.
    3. John O'Hagan & Karol Jan BOROWIECKI, 2009. "Birth Location, Migration and Clustering of Important Composers: Historical Patterns," Trinity Economics Papers tep0115, Trinity College Dublin, Department of Economics, revised Feb 2015.
    4. Mitchell, Sara, 2019. "London calling? Agglomeration economies in literature since 1700," Journal of Urban Economics, Elsevier, vol. 112(C), pages 16-32.
    5. Wagner, Alfred, 1891. "Marshall's Principles of Economics," History of Economic Thought Articles, McMaster University Archive for the History of Economic Thought, vol. 5, pages 319-338.
    6. Christiane Hellmanzik, 2013. "Does travel inspire? Evidence from the superstars of modern art," Empirical Economics, Springer, vol. 45(1), pages 281-303, August.
    7. Hellmanzik, Christiane, 2010. "Location matters: Estimating cluster premiums for prominent modern artists," European Economic Review, Elsevier, vol. 54(2), pages 199-218, February.
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    More about this item


    Slovenian art history; social network analysis; network centrality; artist productivity; instrumental variables; women visual artists;

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • J49 - Labor and Demographic Economics - - Particular Labor Markets - - - Other
    • N70 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - General, International, or Comparative
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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