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Aggregation, Heterogeneous Autoregression and Volatility of Daily International Tourist Arrivals and Exchange Rates

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  • Chang, C-L.
  • McAleer, M.J.

Abstract

Tourism is a major source of service receipts for many countries, including Taiwan. The two leading tourism countries for Taiwan, comprising a high proportion of world tourist arrivals to Taiwan, are Japan and USA, which are sources of short and long haul tourism, respectively. As it is well known that a strong domestic currency can have adverse effects on international tourist arrivals, daily data from 1 January 1990 to 31 December 2008 are used to model the world price and US$ / New Taiwan $ and Yen/ New Taiwan $ exchange rates, and tourist arrivals from the world, USA and Japan to Taiwan, as well as their associated volatility. The sample period includes the Asian economic and financial crises in 1997, and part of the global financial crisis of 2008-09. Inclusion of the exchange rate allows approximate daily price effects on world, US and Japanese tourist arrivals to Taiwan to be captured. The Heterogeneous Autoregressive (HAR) model does not reproduce the theoretical hyperbolic decay rates associated with fractionally integrated (or long memory) time series models, but it can nevertheless approximate quite accurately and parsimoniously the slowly decaying correlations associated with such models. The HAR model is used to approximate long memory properties in daily exchange rates and international tourist arrivals, to test whether alternative short and long run estimates of conditional volatility are sensitive to the approximate long memory in the conditional mean, to examine asymmetry and leverage in volatility, and to examine the effects of temporal and spatial aggregation. The empirical results show that the conditional volatility estimates are not sensitive to the approximate long memory nature of the conditional mean specifications. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for world, US and Japanese tourist arrivals to Taiwan, and the world price and US$ / New Taiwan $ and Yen/ New Taiwan $ exchange rates, are statistically adequate and have sensible interpretations. Asymmetry (though not leverage) is found for several alternative HAR models for the world, US and Japanese tourist arrivals to Taiwan. For policy purposes, these empirical results suggest that an arbitrary choice of data frequency or spatial aggregation will not lead to robust findings as they are generally not independent of the level of aggregation used.

Suggested Citation

  • Chang, C-L. & McAleer, M.J., 2010. "Aggregation, Heterogeneous Autoregression and Volatility of Daily International Tourist Arrivals and Exchange Rates," Econometric Institute Research Papers EI 2010-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:18331
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    References listed on IDEAS

    as
    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. Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2009. "Optimal Risk Management Before, During and After the 2008-09 Financial Crisis," Documentos de Trabajo del ICAE 2009-20, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
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    6. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
    7. 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.
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    11. 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.
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    19. 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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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    2. Martins, Luís Filipe & Gan, Yi & Ferreira-Lopes, Alexandra, 2017. "An empirical analysis of the influence of macroeconomic determinants on World tourism demand," Tourism Management, Elsevier, vol. 61(C), pages 248-260.
    3. Chia-Lin Chang & Thanchanok Khamkaew & Michael McAleer, 2010. "Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia," CIRJE F-Series CIRJE-F-735, CIRJE, Faculty of Economics, University of Tokyo.
    4. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Risks, MDPI, vol. 6(4), pages 1-18, September.
    5. Pat Obi & Robert L. Martin & Greg Chidi Obi, 2016. "Tourism: the untapped goldmine in the Gold Coast," Tourism and Hospitality Management, University of Rijeka, Faculty of Tourism and Hospitality Management, vol. 22(1), pages 17-28, May.
    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. Irandoust, Manuchehr, 2019. "On the relation between exchange rates and tourism demand: A nonlinear and asymmetric analysis," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    8. Chang, Chia-Lin & Hsu, Hui-Kuang & McAleer, Michael, 2013. "Is small beautiful? Size effects of volatility spillovers for firm performance and exchange rates in tourism," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 519-534.
    9. 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.
    10. Manu Sharma & Geetilaxmi Mohapatra & A. K. Giri, 2022. "Examining the macro-determinants of tourist arrivals in India," SN Business & Economics, Springer, vol. 2(8), pages 1-18, August.
    11. Chih-Yuan Lin & Mateus Lee, 2020. "Taiwan’s opening policy to Chinese tourists and cross-strait relations: The impacts on inbound tourism into Taiwan," Tourism Economics, , vol. 26(1), pages 27-44, February.

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    More about this item

    Keywords

    EGARCH; G32; GARCH; GJR; HAR; approximate long memory; asymmetry; leverage; daily effects; exchange rates; global financial crisis; international tourist arrivals; spatial aggregation; temporal aggregation; weekly effects;
    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

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