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Dynamic and stochastic structures in tourism demand modeling

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  • Jonas Nordström

Abstract

In this paper we consider a model for international tourism demand. The analysis departure from a utility function that is both dynamic and stochastic. In the model the stochastic component is interpreted as random changes in preferences for goods and services, whereas the dynamic component can be seen as either habit formation or interdependent preferences. The resulting demand functions are estimated as a multivariate state space model, where the stochastic components enter the model as stochastic seasonal and trend components. An application is done for different segments of the Swedish tourism market.
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Suggested Citation

  • Jonas Nordström, 2005. "Dynamic and stochastic structures in tourism demand modeling," Empirical Economics, Springer, vol. 30(2), pages 379-392, September.
    • Handle: RePEc:spr:empeco:v:30:y:2005:i:2:p:379-392
    DOI: 10.1007/s00181-005-0238-8
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    Cited by:

    1. Amitrajeet Batabyal & Hamid Beladi, 2008. "Visitor classification, vehicle breakdowns, and the provision of transport for tourism," Letters in Spatial and Resource Sciences, Springer, vol. 1(2), pages 99-105, December.
    2. Muhammad Chaudhary & Amitrajeet Batabyal, 2009. "A stochastic analysis of alternate ways of scheduling transport for tourists," Letters in Spatial and Resource Sciences, Springer, vol. 2(2), pages 67-75, October.
    3. Amitrajeet Batabyal, 2007. "A probabilistic analysis of a scheduling problem in the economics of tourism," Economics Bulletin, AccessEcon, vol. 12(4), pages 1-7.
    4. Boopen, Seetanah, 2005. "Transport Capital as a Determinant of Tourism Development: A Time Series Approach," MPRA Paper 25402, University Library of Munich, Germany, revised 07 Nov 2006.
    5. Amitrajeet Batabyal, 2009. "An independence result concerning the arrival rate of and the provision of transport to tourists," Economics Bulletin, AccessEcon, vol. 29(1), pages 108-115.
    6. repec:ebl:ecbull:v:12:y:2007:i:4:p:1-7 is not listed on IDEAS
    7. Willem A. Naudé & Andrea Saayman, 2005. "Determinants of Tourist Arrivals in Africa: A Panel Data Regression Analysis," Tourism Economics, , vol. 11(3), pages 365-391, September.
    8. Martin Falk & Xiang Lin, 2018. "Income elasticity of overnight stays over seven decades," Tourism Economics, , vol. 24(8), pages 1015-1028, December.
    9. Yang, Chih-Hai & Lin, Hui-Lin & Han, Chia-Chun, 2010. "Analysis of international tourist arrivals in China: The role of World Heritage Sites," Tourism Management, Elsevier, vol. 31(6), pages 827-837.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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