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Daily Tourist Arrivals, Exchange Rates and Voatility for Korea and Taiwan

Author

Listed:
  • Chia-Lin Chang

    (National Chung Hsing University Taichung)

  • Michael Mcaleer

    (Erasmus University Rotterdam, Tinbergen Institute, University of Tokyo)

Abstract
Both domestic and international tourism are a major source of service export receipts for many countries worldwide, and is also increasingly important in Taiwan. One of the three leading tourism source countries for Taiwan is the Republic of Korea, which is a source of short haul tourism. Daily data from 1 January 1990 to 31 December 2008 are used to model the Korean Won / New Taiwan $ exchange rate and tourist arrivals from Korea to Taiwan, as well as their associated volatility. The sample period includes the Asian economic and financial crises in 1997, and a significant part of the global financial crisis of 2008-09. Inclusion of the exchange rate allows approximate daily price effects on Korean tourism arrivals to Taiwan to be captured. The Heterogeneous Autoregressive (HAR) model is used to capture approximate long memory properties in exchange rates and Korean tourist arrivals, to test whether alternative estimates of conditional volatility are sensitive to the long memory in the conditional mean, and to examine asymmetry and leverage in volatility. The empirical results show that the conditional volatility estimates are not sensitive to the long memory nature of the conditional mean specifications. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for Korean tourist arrivals to Taiwan and the Korean Won / New Taiwan $ exchange rate are statistically adequate and have sensible interpretations. Asymmetry (though not leverage) is found for several alternative HAR models.

Suggested Citation

  • Chia-Lin Chang & Michael Mcaleer, 2009. "Daily Tourist Arrivals, Exchange Rates and Voatility for Korea and Taiwan," Korean Economic Review, Korean Economic Association, vol. 25, pages 241-267.
    • Handle: RePEc:kea:keappr:ker-20091231-25-2-03
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    References listed on IDEAS

    as
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    Cited by:

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    2. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    3. Chaovanapoonphol, Y. & Lim, C. & McAleer, M.J. & Wiboonpongse, A., 2010. "Time Series Modelling of Tourism Demand from the USA, Japan and Malaysia to Thailand," Econometric Institute Research Papers EI 2010-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    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. Agiomirgianakis, George & Serenis, Dimitrios & Tsounis, Nicholas, 2017. "Effective timing of tourism policy: The case of Singapore," Economic Modelling, Elsevier, vol. 60(C), pages 29-38.
    6. Sangram Keshari JENA & Aruna Kumar DASH, 2020. "Does Exchange Rate Volatility Affect Tourist Arrival In India: A Quantile Regression Approach," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 20(2), pages 65-78.
    7. Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Cheong Kin Wan & Jen Sim Ho, 2022. "Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting," JRFM, MDPI, vol. 15(7), pages 1-47, June.
    8. João H. Gonçalves Mazzeu & Helena Veiga & Massimo B. Mariti, 2019. "Modeling and forecasting the oil volatility index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 773-787, December.
    9. 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.
    10. Akhil Sharma & Tarun Vashishat & Abdul Rishad, 2019. "The consequences of exchange rate trends on international tourism demand: evidence from India," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 21(2), pages 270-287, December.

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    More about this item

    Keywords

    Korean Tourist Arrivals; Exchange Rates; Approximate Price Effects; Global Financial Crisis; Asian Economic and Financial Crises; GARCH; GJR; EGARCH; HAR; Approximate Long Memory; Asymmetry; Leverage;
    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
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • 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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