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Robust Estimates of the Impacts of Broadcasting on Match Attendance in Football

Author

Listed:
  • Babatunde Buraimo

    (University of Central Lancashire)

  • David Forrest

    (University of Salford)

  • Robert Simmons

    (Lancaster University)

Abstract
The paper employs data from 2,884 matches, of which 158 were televised, in the second tier of English football (currently known as The Football League Championship). It builds a model of the determinants of attendance that is designed to yield estimates of the proportionate changes in the size of crowds resulting from games being shown on either free-to-air or subscription based channels. The model has two innovatory features. First, it controls for the market size of home and away teams very precisely by including local population measures constructed from the application of GIS software and information on competition from other clubs. Second, it employs the Hausman-Taylor random effects estimator in order to take explicit account of the endogeneity of the television coverage variable and of other variables typically included in earlier studies based on ordinary least squares or fixed effects models of attendance. The Hausman-Taylor estimates of the impact of broadcasting are greater than those reported in such studies. In the case of free-to-air television, the negative impact is estimated as over 20 percent but for subscription television, which carried most of the transmissions, the negative effect was only of the order of 5 percent.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Babatunde Buraimo & David Forrest & Robert Simmons, 2006. "Robust Estimates of the Impacts of Broadcasting on Match Attendance in Football," IASE Conference Papers 0637, International Association of Sports Economists.
  • Handle: RePEc:spe:cpaper:0637
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    References listed on IDEAS

    as
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    Cited by:

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    2. Francesco Addesa & Alexander John Bond, 2021. "Determinants of stadium attendance in Italian Serie A: New evidence based on fan expectations," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-18, December.
    3. Raul Caruso & Marco Di Domizio, 2015. "La Serie A In Televisione E Allo Stadio: Presentazione Del Dataset Audiball 1.0," Rivista di Diritto ed Economia dello Sport, Centro di diritto e business dello Sport, vol. 11(1), pages 161-185, maggio.
    4. Budzinski, Oliver & Feddersen, Arne, 2015. "Grundlagen der Sportnachfrage: Theorie und Empirie der Einflussfaktoren auf die Zuschauernachfrage," Ilmenau Economics Discussion Papers 94, Ilmenau University of Technology, Institute of Economics.
    5. Isabel Artero & Eduardo Bandrés, 2018. "The Broadcasting Demand for the Spanish National Soccer Team," Journal of Sports Economics, , vol. 19(7), pages 934-959, October.
    6. Raul Caruso & Francesco Addesa & Marco Di Domizio, 2019. "The Determinants of the TV Demand for Soccer: Empirical Evidence on Italian Serie A for the Period 2008-2015," Journal of Sports Economics, , vol. 20(1), pages 25-49, January.
    7. Mongeon, Kevin & Winfree, Jason, 2012. "Comparison of television and gate demand in the National Basketball Association," Sport Management Review, Elsevier, vol. 15(1), pages 72-79.
    8. Grant Allan & Graeme Roy, 2008. "Does Television Crowd Out Spectators?," Journal of Sports Economics, , vol. 9(6), pages 592-605, December.
    9. Alexander John Bond & Francesco Addesa, 2020. "Competitive Intensity, Fans’ Expectations, and Match-Day Tickets Sold in the Italian Football Serie A, 2012-2015," Journal of Sports Economics, , vol. 21(1), pages 20-43, January.
    10. Kshitija Dixit & Rupayan Pal, 2010. "The impact of group incentives on performance of small firms: Hausman-Taylor estimates," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(6), pages 403-414.

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    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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