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Modelling International Tourist Arrivals and Volatility: An Application to Taiwan

Author

Listed:
  • Chia-Lin Chang

    (Department of Applied Economics, National Chung Hsing University, Taiwan)

  • Michael McAleer

    (School of Economics and Commerce, University of Western Australia)

  • Dan Slottje

    (FTI Consulting and Department of Economics, Southern Methodist University)

Abstract

International tourism is a major source of export receipts for many countries worldwide. Although it is not yet one of the most important industries in Taiwan (or the Republic of China), an island in East Asia off the coast of mainland China (or the People's Republic of China), the leading tourism source countries for Taiwan are Japan, followed by USA, Republic of Korea, Malaysia, Singapore, UK, Germany and Australia. These countries reflect short, medium and long haul tourist destinations. Although the People's Republic of China and Hong Kong are large sources of tourism to Taiwan, the political situation is such that tourists from these two sources to Taiwan are reported as domestic tourists. Daily data from 1 January 1990 to 30 June 2007 are obtained from the National Immigration Agency of Taiwan. The Heterogeneous Autoregressive (HAR) model is used to capture long memory properties in the data. In comparison with the HAR(1) model, the estimated asymmetry coefficients for GJR(1,1) are not statistically significant for the HAR(1,7) and HAR(1,7,28) models, so that their respective GARCH(1,1) counterparts are to be preferred. These empirical results show that the conditional volatility estimates are sensitive to the long memory nature of the conditional mean specifications. Although asymmetry is observed for the HAR(1) model, there is no evidence of leverage. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for international tourist arrivals to Taiwan are statistically adequate and have sensible interpretations. However, asymmetry (though not leverage) was found only for the HAR(1) model, and not for the HAR(1,7) and HAR(1,7,28) models.

Suggested Citation

  • Chia-Lin Chang & Michael McAleer & Dan Slottje, 2009. "Modelling International Tourist Arrivals and Volatility: An Application to Taiwan," "Marco Fanno" Working Papers 0097, Dipartimento di Scienze Economiche "Marco Fanno".
  • Handle: RePEc:pad:wpaper:0097
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Chia-Lin Chang & Michael Mcaleer, 2012. "Aggregation, Heterogeneous Autoregression And Volatility Of Daily International Tourist Arrivals And Exchange Rates," The Japanese Economic Review, Japanese Economic Association, vol. 63(3), pages 397-419, September.
    6. 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.
    7. Chang, Chia-Yu & Dinh, Tran Ngoc Huy & Benjamin, Pekaric, 2010. "Should SA Tour, A Singapore Travel company, Use External financing to Expand the MICE business in the China and Singapore markets?," MPRA Paper 27549, University Library of Munich, Germany, revised 12 Dec 2010.

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