Repeat tourism in Uruguay: modelling truncated distributions of count data
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.
|Date of creation:||06 Mar 2012|
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- 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.
- 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.
- 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, 04.
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