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The Fundamental Equation in Tourism Finance

Author

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  • Michael McAleer

    (Department of Quantitative Finance, National Tsing Hua University, Hsinchu 30013, Taiwan
    Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam 3000 DR, The Netherlands
    Tinbergen Institute, Amsterdam and Rotterdam, The Netherlands
    Department of Quantitative Economics, Complutense University of Madrid, Spain)

Abstract

The purpose of the paper is to present the fundamental equation in tourism finance that connects tourism research to empirical finance and financial econometrics. The energy industry, which includes, oil, gas and bio-energy fuels, together with the tourism industry, are two of the most important industries in the world today in terms of employment and generating income. The primary purpose in attracting domestic and international tourists to a country, region or city is to maximize tourism expenditure. The paper will concentrate on daily tourism expenditure, regardless of whether such data might be readily available. If such data are not available, a practical method is presented to calculate the appropriate data.

Suggested Citation

  • Michael McAleer, 2015. "The Fundamental Equation in Tourism Finance," JRFM, MDPI, vol. 8(4), pages 1-6, December.
    • Handle: RePEc:gam:jjrfmx:v:8:y:2015:i:4:p:369-374:d:61108
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    References listed on IDEAS

    as
    1. Chia-Lin Chang & Michael McAleer & Christine Lim, 2010. "Modelling the Volatility in Short and Long Haul Japanese Tourist Arrivals to New Zealand and Taiwan," Working Papers in Economics 10/40, University of Canterbury, Department of Economics and Finance.
    2. Divino, J.A. & McAleer, M.J., 2008. "Modelling sustainable international tourism demand to the Brazilian Amazon," Econometric Institute Research Papers EI 2008-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Chia-Lin Chang & Thanchanok Khamkaew & Roengchai Tansuchat & Michael McAleer, 2011. "Interdependence of International Tourism Demand and Volatility in Leading ASEAN Destinations," Tourism Economics, , vol. 17(3), pages 481-507, June.
    4. Chang, Chia-Lin & Hsu, Hui-Kuang & McAleer, Michael, 2014. "The impact of China on stock returns and volatility in the Taiwan tourism industry," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 381-401.
    5. Divino, Jose Angelo & McAleer, Michael, 2010. "Modelling and forecasting daily international mass tourism to Peru," Tourism Management, Elsevier, vol. 31(6), pages 846-854.
    6. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
    7. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    8. Suhejla Hoti & Michael McAleer & Riaz Shareef, 2005. "Modelling Country Risk and Uncertainty in Small Island Tourism Economies," Tourism Economics, , vol. 11(2), pages 159-183, June.
    9. Medeiros, Marcelo C. & McAleer, Michael & Slottje, Daniel & Ramos, Vicente & Rey-Maquieira, Javier, 2008. "An alternative approach to estimating demand: Neural network regression with conditional volatility for high frequency air passenger arrivals," Journal of Econometrics, Elsevier, vol. 147(2), pages 372-383, December.
    10. Shareef, Riaz & McAleer, Michael, 2008. "Modelling international tourism demand and uncertainty in Maldives and Seychelles: A portfolio approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 459-468.
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    Citations

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    Cited by:

    1. Anastasios Zopiatis & Christos S. Savva & Neophytos Lambertides & Michael McAleer, 2016. "Tourism stocks in times of crises: An econometric investigation of non-macro factors," Documentos de Trabajo del ICAE 2016-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Chia-Lin Chang & Shu-Han Hsu & Michael McAleer, 2018. "An Event Study Analysis of Political Events, Disasters, and Accidents for Chinese Tourists to Taiwan," Sustainability, MDPI, vol. 10(11), pages 1-77, November.
    3. Daniela Firoiu & George H. Ionescu & Roxana Bădîrcea & Luminița Vochița & Maria Enescu, 2019. "Sustainable Development of Mountain Hotels through the Implementation of International Management Standards: The Romanian Case," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    4. Chang, C-L. & Hsu, S.-H. & McAleer, M.J., 2018. "Asymmetric Risk Impacts of Chinese Tourists to Taiwan," Econometric Institute Research Papers EI2018-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Chia-Lin Chang & Hui-Kuang Hsu & Michael McAleer, 2017. "A Tourism Financial Conditions Index for Tourism Finance," Challenges, MDPI, vol. 8(2), pages 1-17, September.
    6. Chang, C-L. & Hsu, S.-H. & McAleer, M.J., 2018. "Risk Spillovers in Returns for Chinese and International Tourists to Taiwan," Econometric Institute Research Papers 18-031/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Chang, C-L. & Hsu, S.-H. & McAleer, M.J., 2018. "An Event Study of Chinese Tourists to Taiwan," Econometric Institute Research Papers 2018-003/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Anastasios Zopiatis & Christos S. Savva & Neophytos Lambertides & Michael McAleer, 2017. "Tourism Stocks in Times of Crises: An Econometric Investigation of Unexpected Non-macroeconomic Factors," Tinbergen Institute Discussion Papers 17-052/III, Tinbergen Institute.

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    More about this item

    Keywords

    tourism research; tourism finance; growth in tourism; returns on tourism; volatility; fundamental equation; empirical finance; financial econometrics;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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