Repeat tourism in Uruguay: modelling truncated distributions of count data

Juan Brida, Juan Pereyra () and Raffaele Scuderi

Quality & Quantity: International Journal of Methodology, 2014, vol. 48, issue 1, 475-491

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 presents 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 suggests instead modelling the available part of the empirical distribution through quantile count data regression. It is a model based on measures of location rather than mean values, which allows estimating tourists’ behaviour as the number of visits increases. A set of explanatory variables related to budgetary constraints, socioeconomic, trip-related and psychographic characteristics are taken as regressors to the considered count data. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Repeat tourism; Uruguay; Quantile regression; Count data (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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Working Paper: Repeat tourism in Uruguay: modelling truncated distributions of count data (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:spr:qualqt:v:48:y:2014:i:1:p:475-491

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DOI: 10.1007/s11135-012-9782-4

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