Forecasting accuracy of behavioural models for participation in the arts
AbstractThis 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.
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Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 229 (2013)
Issue (Month): 1 ()
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Web page: http://www.elsevier.com/locate/eor
Forecasting; Count data; Brier scores; Bootstrapping; Cultural participation;
Other versions of this item:
- 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, the Association for Cultural Economics International, revised Feb 2012.
- Prieto Rodríguez, Juan & Ateca Amestoy, Victoria María, 2012. "Forecasting accuracy of behavioural models for participation in the arts," DFAEII Working Papers 2012-01, University of the Basque Country - Department of Foundations of Economic Analysis II.
- D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
- Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature
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