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    Rights statement: This is the author’s version of a work that was accepted for publication in Tourism Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Tourism Management, 65, 2017 DOI: 10.1016/j.tourman.2017.09.004

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The estimation and decomposition of tourism productivity

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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The estimation and decomposition of tourism productivity. / Assaf, A. George; Tsionas, Mike.
In: Tourism Management, Vol. 65, 04.2018, p. 131-142.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Assaf, AG & Tsionas, M 2018, 'The estimation and decomposition of tourism productivity', Tourism Management, vol. 65, pp. 131-142. https://doi.org/10.1016/j.tourman.2017.09.004

APA

Assaf, A. G., & Tsionas, M. (2018). The estimation and decomposition of tourism productivity. Tourism Management, 65, 131-142. https://doi.org/10.1016/j.tourman.2017.09.004

Vancouver

Assaf AG, Tsionas M. The estimation and decomposition of tourism productivity. Tourism Management. 2018 Apr;65:131-142. Epub 2017 Oct 7. doi: 10.1016/j.tourman.2017.09.004

Author

Assaf, A. George ; Tsionas, Mike. / The estimation and decomposition of tourism productivity. In: Tourism Management. 2018 ; Vol. 65. pp. 131-142.

Bibtex

@article{d724236494724f268370653ba3ff0dde,
title = "The estimation and decomposition of tourism productivity",
abstract = "This paper estimates a total factor productivity index that allows for a rich decomposition of productivity in the tourism industry. We account for two important characteristics: First, the heterogeneity between multiple tourism destinations, and second, the potential endogeneity in inputs. Importantly we develop our index at the macro level, focusing on cross-country comparisons. Using the Bayesian approach, we test the performance of the model across various priors. We rank tourism destinations based on their tourism productivity and discuss the main sources of productivity growth. We also provide long-run productivity measures and discuss the importance of distinguishing between short-run and long-run productivity measures for future performance improvement strategies.",
keywords = "Tourism productivity, Heterogeneity, Tourism destinations, Bayesian",
author = "Assaf, {A. George} and Mike Tsionas",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Tourism Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Tourism Management, 65, 2017 DOI: 10.1016/j.tourman.2017.09.004",
year = "2018",
month = apr,
doi = "10.1016/j.tourman.2017.09.004",
language = "English",
volume = "65",
pages = "131--142",
journal = "Tourism Management",
issn = "0261-5177",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - The estimation and decomposition of tourism productivity

AU - Assaf, A. George

AU - Tsionas, Mike

N1 - This is the author’s version of a work that was accepted for publication in Tourism Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Tourism Management, 65, 2017 DOI: 10.1016/j.tourman.2017.09.004

PY - 2018/4

Y1 - 2018/4

N2 - This paper estimates a total factor productivity index that allows for a rich decomposition of productivity in the tourism industry. We account for two important characteristics: First, the heterogeneity between multiple tourism destinations, and second, the potential endogeneity in inputs. Importantly we develop our index at the macro level, focusing on cross-country comparisons. Using the Bayesian approach, we test the performance of the model across various priors. We rank tourism destinations based on their tourism productivity and discuss the main sources of productivity growth. We also provide long-run productivity measures and discuss the importance of distinguishing between short-run and long-run productivity measures for future performance improvement strategies.

AB - This paper estimates a total factor productivity index that allows for a rich decomposition of productivity in the tourism industry. We account for two important characteristics: First, the heterogeneity between multiple tourism destinations, and second, the potential endogeneity in inputs. Importantly we develop our index at the macro level, focusing on cross-country comparisons. Using the Bayesian approach, we test the performance of the model across various priors. We rank tourism destinations based on their tourism productivity and discuss the main sources of productivity growth. We also provide long-run productivity measures and discuss the importance of distinguishing between short-run and long-run productivity measures for future performance improvement strategies.

KW - Tourism productivity

KW - Heterogeneity

KW - Tourism destinations

KW - Bayesian

U2 - 10.1016/j.tourman.2017.09.004

DO - 10.1016/j.tourman.2017.09.004

M3 - Journal article

VL - 65

SP - 131

EP - 142

JO - Tourism Management

JF - Tourism Management

SN - 0261-5177

ER -