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Assessing the Value of Museums with a Combined Discrete Choice / Count Data Model

Author

Listed:
  • Jan Rouwendal

    (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

  • Jaap Boter

    (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

Abstract

We develop a model for museum visits and estimate it on a large sample of holders of a museum card that provides free access to all museums. Our model distinguishes two stages, referring to the determination of the number of trips and destination choice and can deal with an effect of income on destination choice. We use a mixed logit model for destination choice and a count data model for explaining the number of trips. The model implies that welfare analyses should not only take into account the change in the logsum variables, but also changes in the number of trips. In our empirical application we find substantial local interest effects that cause a correlation between the attractiveness of a museum and its distance to the residential location of the visitor. The ranking of museums on the basis of their estimated attractiveness differs substantially from that based on the change in income that would be needed to compensate for its disappearance.

Suggested Citation

  • Jan Rouwendal & Jaap Boter, 2005. "Assessing the Value of Museums with a Combined Discrete Choice / Count Data Model," Tinbergen Institute Discussion Papers 05-039/3, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20050039
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    Cited by:

    1. Christiaan Behrens & Nathalie McCaughey, 2015. "Loyalty Programs and Consumer Behaviour: The Impact of FFPs on Consumer Surplus," Tinbergen Institute Discussion Papers 15-048/VIII, Tinbergen Institute.
    2. Laurent Callot & Johannes Tang Kristensen, 2014. "Vector Autoregressions with Parsimoniously Time Varying Parameters and an Application to Monetary Policy," CREATES Research Papers 2014-41, Department of Economics and Business Economics, Aarhus University.
    3. 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.
    4. Ruben Loon & Tom Gosens & Jan Rouwendal, 2014. "Cultural heritage and the attractiveness of cities: evidence from recreation trips," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 38(3), pages 253-285, August.
    5. Victoria Ateca Amestoy, 2013. "Demand for cultural heritage," Chapters, in: Ilde Rizzo & Anna Mignosa (ed.), Handbook on the Economics of Cultural Heritage, chapter 4, pages i-i, Edward Elgar Publishing.
    6. 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.
    7. Truong, Truong P. & Hensher, David A., 2014. "Linking discrete choice to continuous demand in a spatial computable general equilibrium model," Journal of choice modelling, Elsevier, vol. 12(C), pages 21-46.
    8. Giacomo Pignataro, 2011. "Performance Indicators," Chapters, in: Ruth Towse (ed.), A Handbook of Cultural Economics, Second Edition, chapter 46, Edward Elgar Publishing.
    9. Bhat, Chandra R., 2022. "A new closed-form two-stage budgeting-based multiple discrete-continuous model," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 162-192.
    10. Bhat, Chandra R., 2022. "A closed-form multiple discrete-count extreme value (MDCNTEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 65-86.

    More about this item

    Keywords

    museums; travel cost method; two stage budgeting;
    All these keywords.

    JEL classification:

    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock

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