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The Influence Of The Net-metric And Biblio-metric Variables On The Top Artists Of The Internacional Art Market/La Influencia De Las Variables Red-metricas Y Biblio-metricas En El Mercado Del Arte De Los Principales Artistas A Nivel Internacional

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  • GUADALAJARA, N

    ()
    (Depto. de Economía y Ciencias Sociales. Facultad de Administración y Dirección de Empresas. Instituto de Ingeniería Económica. 3º Piso del Edifi cio 7J. Universidad Politécnica de Valencia. C/ Camino de Vera S/N 46022-Valencia.Telf: 963879474 / 963877032)

  • DE LA POZA, E.

    ()
    (Depto. de Economía y Ciencias Sociales. Facultad de Administración y Dirección de Empresas. Instituto de Ingeniería Económica. 3º Piso del Edifi cio 7J. Universidad Politécnica de Valencia. C/ Camino de Vera S/N 46022-Valencia.Telf: 963879474 / 963877032)

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    Abstract

    The variable Artist influences the market price of a work of art. Both Biblio-metric and Net-metric variables are built using documental and digital sources of information to quantify or measure the variable Artist. The variable Annual Turnover is explained through the Variable Artist.An original database has been built including all transactions of the most quoted artists in terms of turnover in the international auction houses during the period 1997-2005. The proposed regression models show the Annual Turnovers are explained in a 50% and in a 70% by the Biblio-metric variable and the Net-metric variables respectively, which points out the Net metric variables have more relevance as explanatory variables of the Art Market.Also, Pearson correlation coefficients between both kinds of metric variables and the annual turnovers suggest spacing in the time between both kind of metrics Variables. Se han construido variables Biblio-métricas y Red-métricas, utilizando información documental y digital en enero del 2007, para medir o cuantificar el autor y explicar la facturación alcanzada en las casas de subastas en el periodo 1997-2005, con las obras de los primeros artistas del ranking mundial. Los modelos obtenidos por regresión indican un porcentaje de explicación mayor del 50% con la variable Biblio-métrica y de más del 70% con las Red-métricas, lo que indica la mayor oportunidad de estas últimas para explicar el mercado del arte.Asimismo, los coeficientes de correlación de Pearson entre las variables métricas y la facturación anual indican un distanciamiento entre los dos tipos de variables a medida que se aproximan en el tiempo.

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    Bibliographic Info

    Article provided by Estudios de Economía Aplicada in its journal Estudios de Economía Aplicada.

    Volume (Year): 25 (2007)
    Issue (Month): (Abril)
    Pages: 5-22

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    Handle: RePEc:lrk:eeaart:25_1_1

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    Related research

    Keywords: Net-metric variables; biblio-metric variables; ranking of artists; art market; multivariable regression analysis/Variables red-métricas; variables biblio-métricas; ranking artistas; mercado del arte; analisis de regresion multivariante.;

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    1. Victor Ginsburgh & Anne-Françoise Penders, 1997. "Land artists and art markets," ULB Institutional Repository 2013/99276, ULB -- Universite Libre de Bruxelles.
    2. Chanel, O., 1994. "Is Art Market Behavior Predictable?," G.R.E.Q.A.M., Universite Aix-Marseille III 94b08, Universite Aix-Marseille III.
    3. Jianping Mei & Michael Moses, 2002. "Art as an Investment and the Underperformance of Masterpieces," American Economic Review, American Economic Association, American Economic Association, vol. 92(5), pages 1656-1668, December.
    4. Baumol, William J, 1986. "Unnatural Value: Or Art Investment as Floating Crap Game," American Economic Review, American Economic Association, American Economic Association, vol. 76(2), pages 10-14, May.
    5. Werner Pommerehne & Lars Feld, 1997. "The Impact of Museum Purchase on the Auction Prices of Paintings," Journal of Cultural Economics, Springer, Springer, vol. 21(3), pages 249-271, September.
    6. Buelens, Nathalie & Ginsburgh, Victor, 1993. "Revisiting Baumol's 'art as floating crap game'," European Economic Review, Elsevier, Elsevier, vol. 37(7), pages 1351-1371, October.
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