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Quantile Elasticity of International Tourism Demand for South Korea Using the Quantile Autoregressive Distributed Lag Model

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  • Haiqi Li

    (College of Finance and Statistics, Hunan University, Changsha, 410079 Hunan, PR China and Wang Yanan Institute for Studies in Economics, Xiamen University, PR China)

  • Sung Yong Park

    (Department of Economics, The Chinese University of Hong Kong, Shatin, NT, Hong Kong)

  • Joo Hwan Seo

    (Department of Marketing, George Washington University, Washington, DC, USA)

Abstract

Using the quantile autoregressive model, this paper investigates international inbound tourism demand for South Korea and its determinants. In contrast to previous studies which have dealt with the conditional mean only, the authors examine the effects of covariates at various conditional quantile levels. US and Japanese tourism demand are considered for inbound tourism demand. For US tourism demand, the costs of living in Korea and competing destinations have moderately significant negative effects at very high and low quantiles only, while income does not have any significant effect on tourism demand. On the other hand, for Japanese tourism demand, income has significant positive effects at lower quantiles, and living costs in Korea and competing destinations have significant negative effects at higher quantiles. These results address the heterogeneity in tourism demand analysis.

Suggested Citation

  • Haiqi Li & Sung Yong Park & Joo Hwan Seo, 2011. "Quantile Elasticity of International Tourism Demand for South Korea Using the Quantile Autoregressive Distributed Lag Model," Tourism Economics, , vol. 17(5), pages 997-1015, October.
    • Handle: RePEc:sae:toueco:v:17:y:2011:i:5:p:997-1015
    DOI: 10.5367/te.2011.0083
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    References listed on IDEAS

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    1. Fitzenberger, Bernd, 1998. "The moving blocks bootstrap and robust inference for linear least squares and quantile regressions," Journal of Econometrics, Elsevier, vol. 82(2), pages 235-287, February.
    2. Christine Lim & Michael McAleer, 2001. "Cointegration analysis of quarterly tourism demand by Hong Kong and Singapore for Australia," Applied Economics, Taylor & Francis Journals, vol. 33(12), pages 1599-1619.
    3. Koul, H. L. & Mukherjee, K., 1994. "Regression Quantiles and Related Processes Under Long Range Dependent Errors," Journal of Multivariate Analysis, Elsevier, vol. 51(2), pages 318-337, November.
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    2. Jian-Wu Bi & Tian-Yu Han & Yanbo Yao, 2024. "Collaborative forecasting of tourism demand for multiple tourist attractions with spatial dependence: A combined deep learning model," Tourism Economics, , vol. 30(2), pages 361-388, March.

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