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

Author

Listed:
  • Chia-Lin Chang

    (Department of Applied Economics, National Chung Hsing 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)

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 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 Volatility for Korea and Taiwan," CARF F-Series CARF-F-192, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Handle: RePEc:cfi:fseres:cf192
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    File URL: https://www.carf.e.u-tokyo.ac.jp/old/pdf/workingpaper/fseries/199.pdf
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    References listed on IDEAS

    as
    1. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
    2. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
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    4. Michael McAleer & Juan-Angel Jimenez-Martin & Teodosio Pérez-Amaral, 0000. "Has the Basel II Accord Encouraged Risk Management during the 2008-09 Financial Crisis?," Tinbergen Institute Discussion Papers 09-039/4, Tinbergen Institute.
    5. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2008. "A decision rule to minimize daily capital charges in forecasting value-at-risk," Econometric Institute Research Papers EI 2008-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    7. Michael McAleer, 2009. "The Ten Commandments For Optimizing Value‐At‐Risk And Daily Capital Charges," Journal of Economic Surveys, Wiley Blackwell, vol. 23(5), pages 831-849, December.
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    11. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
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    14. 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".
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    18. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper 0548, Institute of Social and Economic Research, Osaka University.
    19. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.
    20. Michael McAleer & Les Oxley, 2002. "The Econometrics of Financial Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 237-243, July.
    21. Divino, Jose Angelo & McAleer, Michael, 2010. "Modelling and forecasting daily international mass tourism to Peru," Tourism Management, Elsevier, vol. 31(6), pages 846-854.
    22. W. K. Li & Shiqing Ling & Michael McAleer, 2002. "Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-269, July.
    23. Lee, Sang-Won & Hansen, Bruce E., 1994. "Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator," Econometric Theory, Cambridge University Press, vol. 10(1), pages 29-52, March.
    24. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
    25. 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.
    26. Jeantheau, Thierry, 1998. "Strong Consistency Of Estimators For Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 14(1), pages 70-86, February.
    27. Michael Mcaleer & Bernardo da Veiga, 2008. "Forecasting value-at-risk with a parsimonious portfolio spillover GARCH (PS-GARCH) model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 1-19.
    28. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. 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.
    2. Yaovarate Chaovanapoonphol & Christine Lim & Michael McAleer & Aree Wiboonpongse, 2010. "Time Series Modelling of Tourism Demand from the USA, Japan and Malaysia to Thailand," CIRJE F-Series CIRJE-F-722, CIRJE, Faculty of Economics, University of Tokyo.
    3. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    4. 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.
    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. 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.
    7. 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.
    8. 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.
    9. 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.
    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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    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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