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Forecasting accuracy of behavioural models for participation in the arts

Author

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  • Victoria M. Ateca-Amestoy

    () (Department of Economic Analysis II, Universidad del País Vasco / Euskal Herriko Unibertsitatea.)

  • Juan Prieto-Rodriguez

    () (Departament of Economics, University of Oviedo)

Abstract

In this paper, we assess 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 -museum 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 "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 models using bootstrapping techniques to compute the Brier score. Overall, the results indicate good properties of the model in terms of forecasting. Finally, we derive some policy implications from the forecasting capacity of the models, which allows for identification of target populations.

Suggested Citation

  • Victoria M. Ateca-Amestoy & Juan Prieto-Rodriguez, 2012. "Forecasting accuracy of behavioural models for participation in the arts," ACEI Working Paper Series AWP-01-2012, Association for Cultural Economics International, revised Feb 2012.
  • Handle: RePEc:cue:wpaper:awp-01-2012
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    References listed on IDEAS

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    1. Charles B. Weinberg, 1986. "Arts Plan: Implementation, Evolution, and Usage," Marketing Science, INFORMS, vol. 5(2), pages 143-158.
    2. 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 112-120, Se.
    3. 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.
    4. 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.
    5. Claudia Czado & Tilmann Gneiting & Leonhard Held, 2009. "Predictive Model Assessment for Count Data," Biometrics, The International Biometric Society, vol. 65(4), pages 1254-1261, December.
    6. Victoria Ateca-Amestoy, 2008. "Determining heterogeneous behavior for theater attendance," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 32(2), pages 127-151, June.
    7. Francesca Borgonovi, 2004. "Performing arts attendance: an economic approach," Applied Economics, Taylor & Francis Journals, vol. 36(17), pages 1871-1885.
    8. 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.
    9. José Grisolía & Kenneth Willis, 2012. "A latent class model of theatre demand," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(2), pages 113-139, May.
    10. repec:eee:touman:v:32:y:2011:i:3:p:477-481 is not listed on IDEAS
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. VÍctor Blanco & JosÉ BaÑos Pino, 1997. "Cinema Demand in Spain: A Cointegration Analysis," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 21(1), pages 57-75, March.
    16. 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.
    17. Juan Nicolau, 2010. "Culture-sensitive tourists are more price insensitive," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(3), pages 181-195, August.
    18. 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;The Association for Cultural Economics International, vol. 36(2), pages 91-112, May.
    19. 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.
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    Citations

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    Cited by:

    1. Cristina Muñiz & Plácido Rodríguez & María José Suárez, 2017. "Participation in cultural activities: specification issues," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 41(1), pages 71-93, February.
    2. Trilce Navarrete & Karol J. Borowiecki, 2015. "Change in access after digitization: Ethnographic collections in Wikipedia," ACEI Working Paper Series AWP-10-2015, Association for Cultural Economics International, revised Oct 2015.
    3. Calogero Guccio & Domenico Lisi & Anna Mignosa & Ilde Rizzo, 2017. "Has cultural heritage monetary value an impact on visits? An assessment using Italian official data," ACEI Working Paper Series AWP-02-2017, Association for Cultural Economics International, revised Feb 2017.
    4. Martin Falk & Tally Katz-Gerro, 2016. "Cultural participation in Europe: Can we identify common determinants?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 40(2), pages 127-162, May.
    5. Karol Borowiecki & Juan Prieto-Rodriguez, 2015. "Video games playing: A substitute for cultural consumptions?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(3), pages 239-258, August.
    6. Juan Gabriel Brida & Chiara Dalle Nogare & Raffaele Scuderi, 2016. "Frequency of museum attendance: motivation matters," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 40(3), pages 261-283, August.
    7. Beatriz Plaza & Pilar González-Casimiro & Paz Moral-Zuazo & Courtney Waldron, 2015. "Culture-led city brands as economic engines: theory and empirics," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(1), pages 179-196, January.
    8. repec:kap:jculte:v:41:y:2017:i:2:d:10.1007_s10824-017-9295-z is not listed on IDEAS

    More about this item

    Keywords

    Forecasting; count data; prediction intervals; Brier scores; bootstrapping; art participation;

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature

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