Forecasting accuracy of behavioural models for participation in the arts
This paper assesses the forecasting performance of count data models applied to arts attendance. We estimate participation models for two artistic activities that differ in their degree of popularity – museums and jazz concerts – with data derived from the 2002 release of the Survey of Public Participation in the Arts for the United States. We estimate a finite mixture model – a zero-inflated negative binomial model – that allows us to distinguish between “true” non-attendants and “goers” and their respective behaviour regarding participation in the arts. We evaluate the predictive (in-sample) and forecasting (out-of-sample) accuracy of the estimated model using bootstrapping techniques to compute the Brier score. Overall, the results indicate the model performs well in terms of forecasting. Finally, we draw certain policy implications from the model’s forecasting capacity, thereby allowing the identification of target populations.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jones, D.F. & Collins, A. & Hand, C., 2007. "A classification model based on goal programming with non-standard preference functions with application to the prediction of cinema-going behaviour," European Journal of Operational Research, Elsevier, vol. 177(1), pages 515-524, February.
- VÍctor Blanco & JosÉ BaÑos Pino, 1997. "Cinema Demand in Spain: A Cointegration Analysis," Journal of Cultural Economics, Springer, vol. 21(1), pages 57-75, March.
- Fernandez-Blanco, Victor & Orea, Luis & Prieto-Rodriguez, Juan, 2009. "Analyzing consumers heterogeneity and self-reported tastes: An approach consistent with the consumer's decision making process," Journal of Economic Psychology, Elsevier, vol. 30(4), pages 622-633, August.
- Charles B. Weinberg & Kenneth M. Shachmut, 1978. "ARTS PLAN: A Model Based System for Use in Planning a Performing Arts Series," Management Science, INFORMS, vol. 24(6), pages 654-664, February.
- Juan Nicolau, 2010. "Culture-sensitive tourists are more price insensitive," Journal of Cultural Economics, Springer, vol. 34(3), pages 181-195, August.
- Andreasen, Alan R & Belk, Russell W, 1980. " Predictors of Attendance at the Performing Arts," Journal of Consumer Research, Oxford University Press, vol. 7(2), pages 112-20, Se.
- José Grisolía & Kenneth Willis, 2012. "A latent class model of theatre demand," Journal of Cultural Economics, Springer, vol. 36(2), pages 113-139, May.
- K. Willis & J. Snowball & C. Wymer & José Grisolía, 2012. "A count data travel cost model of theatre demand using aggregate theatre booking data," Journal of Cultural Economics, Springer, vol. 36(2), pages 91-112, May.
- Alan Collins & Chris Hand & Andrew Ryder, 2005. "The lure of the multiplex? The interplay of time, distance, and cinema attendance," Environment and Planning A, Pion Ltd, London, vol. 37(3), pages 483-501, March.
- Juan Prieto-Rodriguez & Desiderio Romero-Jordán & José Felix Sanz-Sanz, 2005. "Is a tax cut on cultural goods consumption actually desirable? A microsimulation analysis applied to Spain," Fiscal Studies, Institute for Fiscal Studies, vol. 26(4), pages 549-575, December.
- Victoria Ateca-Amestoy, 2008. "Determining heterogeneous behavior for theater attendance," Journal of Cultural Economics, Springer, vol. 32(2), pages 127-151, June.
- Francesca Borgonovi, 2004. "Performing arts attendance: an economic approach," Applied Economics, Taylor & Francis Journals, vol. 36(17), pages 1871-1885.
- Charles B. Weinberg, 1986. "Arts Plan: Implementation, Evolution, and Usage," Marketing Science, INFORMS, vol. 5(2), pages 143-158.
- Daniel S. Putler & Shilpa Lele, 2003. "An Easily Implemented Framework for Forecasting Ticket Sales to Performing Arts Events," Marketing Letters, Springer, vol. 14(4), pages 307-320, December.
- Chris Hand & Guy Judge, 2012. "Searching for the picture: forecasting UK cinema admissions using Google Trends data," Applied Economics Letters, Taylor & Francis Journals, vol. 19(11), pages 1051-1055, July.
- Lessmann, Stefan & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2012. "A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction," European Journal of Operational Research, Elsevier, vol. 218(1), pages 163-174.
- R. Winkler & Javier Muñoz & José Cervera & José Bernardo & Gail Blattenberger & Joseph Kadane & Dennis Lindley & Allan Murphy & Robert Oliver & David Ríos-Insua, 1996. "Scoring rules and the evaluation of probabilities," TEST- An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(1), pages 1-60, June.
When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:229:y:2013:i:1:p:124-131. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If references are entirely missing, you can add them using this form.