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Repeat tourism in Uruguay: modelling truncated distributions of count data

Author

Listed:
  • Brida, Juan Gabriel
  • Pereira, Juan Sebastián
  • Scuderi, Raffaele

Abstract

This paper studies the determinants of repeat visiting in Uruguay, where loyal visitors are a relevant part of the total. From a statistical point of view the number of times a visitor has been to a place constitutes count data. In this regard available information on Uruguay present relevant limitations. Count data is in fact reported only for those who visited the country up to five times, whereas records about the most frequent visitors are collapsed into one residual category. This implies that the classic models for count data such as Poisson or negative binomial cannot be put into consideration. The paper suggest instead the use of a quantile count data regression, that is a model based on measures of location rather than mean values. A set of explanatory variables related to socioeconomic characteristics, features of the journey and composition of the travel party are considered.

Suggested Citation

  • Brida, Juan Gabriel & Pereira, Juan Sebastián & Scuderi, Raffaele, 2012. "Repeat tourism in Uruguay: modelling truncated distributions of count data," MPRA Paper 37140, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:37140
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    References listed on IDEAS

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    1. Alfonso Miranda, 2006. "QCOUNT: Stata program to fit quantile regression models for count data," Statistical Software Components S456714, Boston College Department of Economics, revised 08 Aug 2007.
    2. Machado, Jose A.F. & Silva, J. M. C. Santos, 2005. "Quantiles for Counts," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1226-1237, December.
    3. Campo-Martínez, Sara & Garau-Vadell, Joan B. & Martínez-Ruiz, María Pilar, 2010. "Factors influencing repeat visits to a destination: The influence of group composition," Tourism Management, Elsevier, vol. 31(6), pages 862-870.
    4. Roberto Martínez-Espiñeira & John B. Loomis & Joe Amoako-Tuffour & Joseph M. Hilbe, 2008. "Comparing Recreation Benefits from On-Site versus Household Surveys in Count Data Travel Cost Demand Models with Overdispersion," Tourism Economics, , vol. 14(3), pages 567-576, September.
    5. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, September.
    6. A. Aksu, 2006. "Gap Analysis in Customer Loyalty: A Research in 5-Star Hotels in the Antalya Region of Turkey," Quality & Quantity: International Journal of Methodology, Springer, vol. 40(2), pages 187-205, April.
    7. Assaker, Guy & Vinzi, Vincenzo Esposito & O’Connor, Peter, 2011. "Examining the effect of novelty seeking, satisfaction, and destination image on tourists’ return pattern: A two factor, non-linear latent growth model," Tourism Management, Elsevier, vol. 32(4), pages 890-901.
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    Citations

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    Cited by:

    1. Juan Brida & Marta Disegna & Raffaele Scuderi, 2014. "The behaviour of repeat visitors to museums: review and empirical findings," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2817-2840, September.
    2. Faruk Urak & Nihat Küçük & Abdulbaki Bilgiç & Steven T Yen, 2023. "Modeling censored tourism expenditures in Turkey with non-normal and heteroscedastic errors: An application of the inverse hyperbolic sine double-hurdle model," Tourism Economics, , vol. 29(3), pages 718-741, May.
    3. Abbruzzo, Antonino & Brida, Juan Gabriel & Scuderi, Raffaele, 2014. "Determinants of individual tourist expenditure as a network: Empirical findings from Uruguay," Tourism Management, Elsevier, vol. 43(C), pages 36-45.

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    More about this item

    Keywords

    Repeat tourism; Uruguay; Quantile Regression; Count Data;
    All these keywords.

    JEL classification:

    • N76 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - Latin America; Caribbean
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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