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A Composite Leading Indicator for the Hotel Industry

Author

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  • Candy Mei Fung Tang
  • Nada Kulendran

Abstract

This study constructs composite leading indicators to predict turns in the growth cycle of hotel occupancy for hotels in Hong Kong with different tariffs, as well as for all hotels in Hong Kong. First, a composite leading indicator for each of the top five source markets – mainland China, Taiwan, Japan, the USA and South Korea – was constructed using selected economic variables. Second, a composite leading indicator for all hotel categories in Hong Kong was constructed by combining the leading indicators constructed for each source market, using tourism market share and the cross-correlation coefficient as weightings. Third, the combined composite indicator was compared with the published OECD composite leading indicator and the OECD business survey index, which were constructed using the same weighting methods. In order to identify the best weighting method and to select the best composite leading indicator for different tariff categories of hotels, this study assessed the probability forecasts from the logistic regression leading indicator models using the quadratic probability score (QPS). The result shows that the composite leading indicator combined with tourism market share provides more accurate forecasts than the composite leading indicator combined with the coefficient of correlation.

Suggested Citation

  • Candy Mei Fung Tang & Nada Kulendran, 2011. "A Composite Leading Indicator for the Hotel Industry," Tourism Economics, , vol. 17(3), pages 549-563, June.
    • Handle: RePEc:sae:toueco:v:17:y:2011:i:3:p:549-563
    DOI: 10.5367/te.2011.0052
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    References listed on IDEAS

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    1. Garcia-Ferrer, Antonio & Queralt, Ricardo A., 1998. "Can univariate models forecast turning points in seasonal economic time series?," International Journal of Forecasting, Elsevier, vol. 14(4), pages 433-446, December.
    2. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    4. Nada Kulendran & Kevin K.F. Wong, 2009. "Predicting Quarterly Hong Kong Tourism Demand Growth Rates, Directional Changes and Turning Points with Composite Leading Indicators," Tourism Economics, , vol. 15(2), pages 307-322, June.
    5. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, December.
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    Cited by:

    1. Hsu, Pao-Peng, 2017. "Examination of Taiwan's travel and tourism market cycle through a two-period Markov regime-switching model," Tourism Management, Elsevier, vol. 63(C), pages 201-208.

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