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Interdependence of International Tourism Demand and Volatility in Leading ASEAN Destinations

Author

Listed:
  • Chia-Ling Chang

    (Department of Applied Economics, National Chung Hsing University)

  • Thanchanok Khamkaew

    (Faculty of Economics, Maejo University)

  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo)

  • Roengchai Tansuchat

    (Faculty of Economics, Maejo University)

Abstract

International and domestic tourism are leading economic activities in the world today. Tourism has been known to generate goods and services directly and indirectly, attract foreign currency, stimulate employment, and provide opportunities for investment. It has also been recognized as an important means for achieving economic development. Substantial research has been conducted to evaluate the role of international tourism, and its associated volatility, within and across various economies. This paper applies several recently developed models of multivariate conditional volatility to investigate the interdependence of international tourism demand, as measured by international tourist arrivals, and its associated volatility in the four leading destinations in ASEAN, namely Indonesia, Malaysia, Singapore and Thailand. Each of these countries has attractive tourism characteristics, such as significant cultural and natural resources. Shocks to international tourism demand volatility could affect, positively or negatively, the volatility in tourism demand of neighbouring countries. The empirical results should encourage regional co-operation in tourism development among ASEAN member countries, and also mobilize international and regional organizations to provide appropriate policy actions.

Suggested Citation

  • Chia-Ling Chang & Thanchanok Khamkaew & Michael McAleer & Roengchai Tansuchat, 2009. "Interdependence of International Tourism Demand and Volatility in Leading ASEAN Destinations," CARF F-Series CARF-F-190, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Handle: RePEc:cfi:fseres:cf190
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    3. Michael McAleer, 2015. "The Fundamental Equation in Tourism Finance," JRFM, MDPI, vol. 8(4), pages 1-6, December.
    4. Lin, Boqiang & Wesseh, Presley K. & Appiah, Michael Owusu, 2014. "Oil price fluctuation, volatility spillover and the Ghanaian equity market: Implication for portfolio management and hedging effectiveness," Energy Economics, Elsevier, vol. 42(C), pages 172-182.
    5. Chhorn, Theara & Chaiboonsri, Chukiat, 2017. "Modelling and Forecasting Tourist Arrivals to Cambodia: An Application of ARIMA-GARCH Approach," MPRA Paper 83942, University Library of Munich, Germany, revised 27 Dec 2017.
    6. Arouri, Mohamed El Hedi & Jouini, Jamel & Nguyen, Duc Khuong, 2012. "On the impacts of oil price fluctuations on European equity markets: Volatility spillover and hedging effectiveness," Energy Economics, Elsevier, vol. 34(2), pages 611-617.
    7. Zhou Bo & Yang Bi & Li Hengyun & Qu Hailin, 2017. "The spillover effect of attractions," Tourism Economics, , vol. 23(4), pages 731-743, June.
    8. Jie Yin & Yahua Bi & Yingchao Ji, 2020. "Structure and Formation Mechanism of China-ASEAN Tourism Cooperation," Sustainability, MDPI, vol. 12(13), pages 1-19, July.
    9. Ngene, Geoffrey & Post, Jordin A. & Mungai, Ann N., 2018. "Volatility and shock interactions and risk management implications: Evidence from the U.S. and frontier markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 181-198.
    10. Agya Atabani Adi, 2017. "Returns Effect, Shocks and Volatility Transmission between Foreign Exchange-Stock Markets in Nigeria," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 3(1), pages 29-38, March.
    11. Taotao Deng & Yukun Hu, 2019. "Modelling China’s outbound tourist flow to the ‘Silk Road’: A spatial econometric approach," Tourism Economics, , vol. 25(8), pages 1167-1181, December.
    12. Mohamed Fakhfekh & Ahmed Ghorbel & Nadhem Selmi & Nejib Hachicha, 2017. "Dependence between oil price volatility, Islamic and conventional Dow Jones indexes: Implication for portfolio management and hedging effectiveness," Journal of Asset Management, Palgrave Macmillan, vol. 18(1), pages 29-48, January.
    13. Manuela, Wilfred S. & de Vera, Manuel J., 2015. "The impact of government failure on tourism in the Philippines," Transport Policy, Elsevier, vol. 43(C), pages 11-22.
    14. Nguyen, Quang Hai, 2024. "Modeling the volatility of international air freight: A case study of Singapore using the SARIMAX-EGARCH model," Journal of Air Transport Management, Elsevier, vol. 117(C).
    15. Balli, Hatice Ozer & Tsui, Wai Hong Kan & Balli, Faruk, 2019. "Modelling the volatility of international visitor arrivals to New Zealand," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 204-214.
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    More about this item

    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
    • F50 - International Economics - - International Relations, National Security, and International Political Economy - - - General
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East

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