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Tourism Forecasting And Tackling Fluctuating Patterns: A Composite Leading Indicator Approach

Author

Listed:
  • SOH Ann-Ni

    (Faculty of Economics and Business, University Malaysia Sarawak, Malaysia)

  • PUAH Chin-Hong

    (Faculty of Economics and Business, University Malaysia Sarawak, Malaysia)

  • ARIP M. Affendy

    (Faculty of Economics and Business, University Malaysia Sarawak, Malaysia)

Abstract

A growing interest is surfacing toward the non-linearities in tourism demand forecasting. This paper aims to construct a tourism composite indicator to anticipate the cyclical movement for the tourism demand in Fiji. The time duration tackled in the current study is under the span of approximately two decades from 2000 to 2017. Apart from an indicator construction approach and turning point dating algorithm, we proposed a two regime Markov switching model to analyse the Fijian tourism cycle. The empirical results revealed the composite leading indicator accorded a signalling approach for Fijian tourism demand with an average lead time of 2.75 months. Furthermore, the prior-recognition of the tourism economic transition with adequate dating evaluation of the tourism cycle is obtained from the filtered probabilities through the Markov switching models.

Suggested Citation

  • SOH Ann-Ni & PUAH Chin-Hong & ARIP M. Affendy, 2020. "Tourism Forecasting And Tackling Fluctuating Patterns: A Composite Leading Indicator Approach," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 15(2), pages 192-204, August.
    • Handle: RePEc:blg:journl:v:15:y:2020:i:2:p:192-204
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    File URL: http://eccsf.ulbsibiu.ro/RePEc/blg/journl/15214soh.pdf
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    Citations

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    Cited by:

    1. Ann-Ni Soh & Chin-Hong Puah & Meng-Chang Jong, 2022. "Macroeconomic Determinants of Tourism Demand in Malaysia: A Markov Switching Regression Approach," Business Management and Strategy, Macrothink Institute, vol. 13(2), pages 95-107, December.
    2. Jong, Meng-Chang & Soh, Ann-Ni, 2021. "Responsible Recovery from COVID-19: An Empirical Overview of Tourism Industry," MPRA Paper 107661, University Library of Munich, Germany.
    3. El houssin Ouassou & Hafsa Taya, 2022. "Forecasting Regional Tourism Demand in Morocco from Traditional and AI-Based Methods to Ensemble Modeling," Forecasting, MDPI, vol. 4(2), pages 1-18, April.
    4. Ann-Ni Soh & Chin-Hong Puah & Mohammad Affendy Arip, 2023. "A Bibliometric Analysis on Tourism Sustainable Competitiveness Research," Sustainability, MDPI, vol. 15(2), pages 1-14, January.
    5. Jong, Meng-Chang, 2020. "Empirical Review on Tourism Demand and COVID-19," MPRA Paper 103919, University Library of Munich, Germany.
    6. Soh, Ann-Ni, 2020. "A Review on the Leading Indicator Approach towards Economic Forecasting," MPRA Paper 103854, University Library of Munich, Germany.

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