Theatres have a market bounded by the distance theatregoers are willing to travel to see shows and productions. This paper uses count data models (Poisson regression and negative binomial models) to investigate the determinants of attendance at a regional theatre in England. It uses booking data for 29 theatrical productions supplied by the theatre, and matches this, using postcodes, with census socio-economic information on household characteristics. Socio-economic and travel cost (distance) are used to explore theatregoers attendance, and also to estimate consumer surplus, and to assess whether consumer surplus on ticket sales exceeds the annual government subsidy to the theatre.
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These productions included comedy (e.g. Cattle Call; Brendon Burns), drama classical (e.g. Far From The Madding Crowd; Molora), drama modern (e.g. Delirium), experimental (e.g. My Arm Oak Tree), and family shows (e.g. Gormenghast; Life of Pi) and family Christmas shows (e.g. The Goblin who saved Christmas; Hansel and Gretel).
Alberini, A., & Longo, A. (2006). Combining the travel cost and contingent behaviour methods to value cultural heritage sites: Evidence from Armenia. Journal of Cultural Economics, 30, 287–304.
Ateca-Amestoy, V. (2008). Determining heterogeneous behaviour for theatre attendance. Journal of Cultural Economics, 32, 127–151.
Bedate, A., herrero, L., & Sanz, J. (2004). Economic valuation of the cultural heritage: Application to four case studies in Spain. Journal of Cultural Heritage, 5, 101–111.
Bille-Hansen, T. (1997). The willingness-to-pay for the Royal Theatre in Copenhagen as a public good. Journal of Cultural Economics, 21, 1–28.
Blamey, R. K., Bennett, J. W., & Morrison, M. D. (1999). Yea saying in contingent valuation surveys. Land Economics, 75(1), 126–141.
Borgonovi, F. (2004). Performing arts attendance: An economic approach. Applied Economics, 36, 1871–1885.
Boter, J., Rouwendal, J., & Wedel, M. (2005). Employing travel time to compare the value of competing cultural organisations. Journal of Cultural Economics, 29, 19–33.
Boxall, P., Englin, J., & Adamowicz, V. (2003). Valuing aboriginal artefacts: A combined revealed-stated preference approach. Journal of Environmental Economics and Management, 45, 213–230.
Cameron, A. C., & Trivedi, P. K. (1986). Econometric models based on count data: Comparisons and applications of some estimators and tests. Journal of Applied Econometrics, 1, 29–53.
Cameron, A. C., & Trivedi, P. K. (1996). Count data models for financial data. In G. S. Maddala & C. R. Rao (Eds.), Handbook of statistics (Vol. 14). Amsterdam: Elsevier.
Clawson, M. (1959). Methods for measuring the demand for and value of outdoor recreation. Report No. 10. Resources for the Future, Washington DC.
Clawson, M., & Knetsch, J. L. (1966). Economics of outdoor recreation. Baltimore: John Hopkins University Press.
Colbert, F. (2003). Entrepreneurship and leadership in marketing the arts. International Journal of Arts Management, 6, 1.
Corning, J., & Levy, A. (2002). Demand for live theatre with market segmentation and seasonality. Journal of Cultural Economics, 26, 217–235.
Cuccia, T. (2003). Contingent valuation. In R. Towse (Ed.), A handbook of cultural economics. Cheltenham: Edward Elgar.
Department for Transport (2009). Values of time and operating costs. TAG Unit 3.5.6. Transport Analysis Guidance, Department for Transport, London.
Forrest, D., Grime, K., & Woods, R. (2000). Is it worth subsidising regional repertory theatre? Oxford Economic Papers, 52, 381–397.
Gayo-Cal, M. (2006). Leisure and participation in Britain. Cultural Trends, 15(2), 175–192.
Grisolia, J. M. & Willis K. G. (2010). An evening at the theatre: Using choice experiments to model preferences for theatre and theatrical productions. Applied Economics. December 6, 2010 (iFirst). doi:10.1080/00036841003742637.
Gujarati, D. (2003). Basic econometrics. Boston: McGraw-Hill.
Hellerstein, D. (1991). Using count data models in travel cost analysis with aggregate data. American Journal of Agricultural Economics, 73(3), 860–866.
Hellerstein, D. (1995). Welfare estimation using aggregate and individual-observation models: A comparison using Monte Carlo techniques. American Journal of Agricultural Economics, 77, 620–630.
Hoehn, J. P., & Randall, A. (1989). Too many proposals pass the benefit cost test. American Economic Review, 79, 544–551.
Levy-Garboua, L., & Montmarquette, C. (2002). The demand for the arts. In R. Towse (Ed.), A handbook of cultural economics. Cheltenham: Edward Elgar.
Martin, F. (1994). Determining the size of museum subsidies. Journal of Cultural Economics, 18, 255–270.
McKean, J. R., Johnson, D. M., & Walsh, R. G. (1995). Valuing time in travel cost demand analysis: An empirical investigation. Land Economics, 71(1), 96–105.
Needleman, L. (1976). Valuing other people’s lives. The Manchester School, 44, 309–342.
Perman, R., Ma, Y., McGilvray, J., & Common, M. (2003). Natural resource and environmental economics. London: Pearson.
Poor, J., & Smith, J. (2004). Travel cost analysis of a cultural heritage site: The case of historic St. Mary’s City of Maryland. Journal of Cultural Economics, 28, 217–229.
Prayaga, P., Rolfe, J., & Sinden, J. (2006). A travel cost analysis of the value of special events: Gemfest in Central Queensland. Tourism Economics, 12, 403–420.
Rouwendal, J., & Boter, J. (2009). Assessing the value of museums with a combined discrete choice/count data model. Applied Economics, 41, 1417–1436.
Seaman, B. (2005). Attendance and public participation in the performing arts: A review of the empirical literature. Andrew Young School of Policy Studies, Georgia State University, Working paper 05-03.
Smith, V. K., & Karou, Y. (1990). Signals or noise? Explaining the variation in recreation benefit estimates. American Journal of Agricultural Economics, 72(2), 419–433.
Snowball, J. (2008). Measuring the value of culture: Methods and examples in cultural economics. Germany: Springer.
Throsby, D. (1994). The production and consumption of the arts: A view of cultural economics. Journal of Economic Literature, 32(3), 1–28.
Throsby, D. (2001). Economics and culture. Cambridge: Cambridge University Press.
Willis, K. G. (1991). The recreational value of the forestry commission estate in Great Britain: A Clawson-Knetsch travel cost analysis. Scottish Journal of Political Economy, 38, 58–75.
Willis, K. G., & Garrod, G. D. (1991a). An individual travel-cost method of evaluating forest recreation. Journal of Agricultural Economics, 42, 33–42.
Willis, K. G., & Garrod, G. D. (1991b). Valuing open access recreation on inland waterways: On-site recreation surveys and selection effects. Regional Studies, 25(6), 511–524.
Willis, K., & Snowball, J. (2009). Investigating how the attributes of live theatre productions influence consumption choices using conjoint analysis: The example of the National Arts Festival, South Africa. Journal of Cultural Economics, 33(3), 167–184.
This work is funded by the Arts and Humanities Research Council and the Arts Council England [Grant: AHRC Fellowship in Economic Impact Assessment of Arts and Humanities]. We would like to thank Edmund Nickols, Director of Theatre Operations at Northern Stage, for his support of this research and to Jamie Corbett, Data Manager at Northern Stage, for supplying the bookings data for the study.
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Willis, K.G., Snowball, J.D., Wymer, C. et al. A count data travel cost model of theatre demand using aggregate theatre booking data. J Cult Econ 36, 91–112 (2012). https://doi.org/10.1007/s10824-011-9157-z
- Travel cost
- Theatre demand
- Consumer surplus