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Measuring the economic contribution of tourism to destinations within an input-output framework: some methodological issues

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Abstract

The input-output model is a traditional tool employed in the literature for measuring the contribution of an economic activity within a given territory. In the case of tourism, this methodological framework has been used to estimate the contribution of the tourism sector as a whole, and for specific products in the tourism market, such as cruise visits. The present paper computes the economic contribution of international tourism arriving at three major destinations on the Mediterranean coast of Spain; namely, Barcelona, Palma de Mallorca and Alicante. For each destination, both the country-level and regional-based input-output tables were employed, using the INTERTIO project, a regional input-output framework developed for the Spanish economy by the Lawrence Klein Institute of the Autonomous University of Madrid. The results show important differences in the magnitude of the computed economic effects between the country and regional approaches. To shed more light on the issue, we identify the main sources driving such dissimilar results, including the role of backward linkages of industries and the differing sectoral distributions of initial economic effects. Finally, we point to the role played by specific sectors in the model in amplifying the initial effects by using a centrality analysis of hub-and-authority effects. The methodological discussion in the paper helps to highlight the need for using the regional input-output model when available, and the other additional methodological tools we provide throughout the study for more accurately computing the economic impact of tourism for particular regions or destinations.

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Notes

  1. In short, the spectral radius of the matrix A must be less than unity.

  2. Note that for the production of an additional unit of output, sector j has to buy a1j units of intermediate output from sector 1, a2j units of intermediate output from sector 2, and so on. Therefore, we measure the magnitude of ties between sector j, and the rest of the sectors in the system (including itself) is better characterized by the intensity of usage of output of sector i by sector j (the technical coefficients a1j, a2j, …) than by the absolute value of the intermediate output that each sector supplies to sector j collected in the input-output table (the terms x1j, x2j, …).

  3. The definition of hub and authority centrality can be written in matrix form as

    $$ {\displaystyle \begin{array}{c}\boldsymbol{\upeta} =\alpha \mathbf{A}\boldsymbol{\upupsilon }, \\ {}\boldsymbol{\upupsilon} =\beta {\mathbf{A}}^{\mathrm{T}}\boldsymbol{\upeta} .\end{array}} $$

    After a little algebra, it can be shown that the vectors of hub and authority scores, η and υ, coincide with the principal eigenvectors of the symmetric positive definite matrices ATA and AAT, respectively (Newman 2010).

  4. The GDP deflators are shown in the Appendix (Table A.1).

  5. From equation (3), the total effect on output (Δx) of a change in the final demand (Δy) can be expressed as Δx = BΔy.

  6. The values are normalized for the interval [0,1].

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Acknowledgments

Prof. Andres Artal-Tur wants to thank the financial support received from Groups of Excellence Program of Fundación Séneca, Science and Technology Agency of the Region of Murcia, project 19884/GERM/15.

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Correspondence to Andrés Artal-Tur.

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Artal-Tur, A., Navarro-Azorín, J.M. & Ramos-Parreño, J.M. Measuring the economic contribution of tourism to destinations within an input-output framework: some methodological issues. Port Econ J 19, 243–265 (2020). https://doi.org/10.1007/s10258-019-00167-y

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  • DOI: https://doi.org/10.1007/s10258-019-00167-y

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