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A multivariate nonlinear analysis of tourism expenditures

  • Marta Disegna

    ()

    (Free University of Bolzano, School of Economics and Management.)

  • Fabrizio Durante

    ()

    (Free University of Bolzano, School of Economics and Management.)

  • Enrico Foscolo

    ()

    (Free University of Bolzano, School of Economics and Management.)

Independence among different tourism expenditure categories is the most convenient hypothesis for modeling decision–making processes. Nevertheless, the best-suited framework would require dependence among expenditures in order to face individual budget and ordered choices. To this end we provide a new multivariate copula-based logit model with explanatory variables. We applied our tools to the expenditures of the foreign tourists visiting South–Tyrol (Northern Italy), and we underlined the need to go beyond usual independence assumption in order to get more realistic results. The obtained findings are useful for policy makers, marketing experts, and local government in order to know how visitors allocate their travel budget; moreover, they can been exploited to improve the touristic supply by means of ad–hoc promotions, advertising, touristic packages, and attractions.

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Paper provided by School of Economics and Management at the Free University of Bozen in its series BEMPS - Bozen Economics & Management Paper Series with number BEMPS10.

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Length: 28 pages
Date of creation: Jun 2013
Date of revision:
Handle: RePEc:bzn:wpaper:bemps10
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  1. Cragg, John G, 1971. "Some Statistical Models for Limited Dependent Variables with Application to the Demand for Durable Goods," Econometrica, Econometric Society, vol. 39(5), pages 829-44, September.
  2. Marius Hofert & Martin Maechler, . "Nested Archimedean Copulas Meet R: The nacopula Package," Journal of Statistical Software, American Statistical Association, vol. 39(i09).
  3. Trivedi, Pravin K. & Zimmer, David M., 2007. "Copula Modeling: An Introduction for Practitioners," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(1), pages 1-111, April.
  4. Peter J. Danaher & Michael S. Smith, 2011. "Modeling Multivariate Distributions Using Copulas: Applications in Marketing," Marketing Science, INFORMS, vol. 30(1), pages 4-21, 01-02.
  5. Brida, Juan Gabriel & Scuderi, Raffaele, 2012. "Determinants of tourist expenditure: a review of microeconometric models," MPRA Paper 38468, University Library of Munich, Germany.
  6. Junyi Zhang & Lili Xu & Akimasa Fujiwara, 2012. "Developing an integrated scobit-based activity participation and time allocation model to explore influence of childcare on women’s time use behaviour," Transportation, Springer, vol. 39(1), pages 125-149, January.
  7. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  8. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
  9. Amemiya, Takeshi, 1974. "Multivariate Regression and Simultaneous Equation Models when the Dependent Variables Are Truncated Normal," Econometrica, Econometric Society, vol. 42(6), pages 999-1012, November.
  10. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-71, July.
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