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Determinants of the Taiwanese tourist hotel industry cycle

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  • Chen, Ming-Hsiang

Abstract

This paper contributes to the tourism literature by examining determinants of the Taiwanese tourist hotel industry (THI) cycle. This study uses a Markov-switching model (MSM) proposed by Hamilton (1989) to analyze the Taiwanese tourist hotel industry cycle. The MSM decomposes the tourist hotel industry cycle into two distinct states: high-growth and low-growth (HGS and LGS). The mean growth rate of HGS is 1.5% and the average growth rate of LGS is 0.07% during the period from December 1999 to February 2011. The corresponding standard deviations in the two regimes are 0.008% and 0.038%, implying that HGS is more stable than LGS. Moreover, the probability of staying in HGS is 94% and the probability of remaining in LGS is 65%. The expected durations of HGS and LGS are about 16 and 3 months, respectively. Further, the paper investigates the factors that keep the THI in HGS. Empirical test results show that growth in the international tourism market and industrial production growth rate are two key factors that keep the THI in HGS, but the SARS outbreak in 2003 has had an adverse effect.

Suggested Citation

  • Chen, Ming-Hsiang, 2013. "Determinants of the Taiwanese tourist hotel industry cycle," Tourism Management, Elsevier, vol. 38(C), pages 15-19.
  • Handle: RePEc:eee:touman:v:38:y:2013:i:c:p:15-19
    DOI: 10.1016/j.tourman.2013.01.003
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    1. Jian Yang & Yinggang Zhou & Zijun Wang, 2010. "Conditional Coskewness in Stock and Bond Markets: Time-Series Evidence," Management Science, INFORMS, vol. 56(11), pages 2031-2049, November.
    2. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    3. Chen, Ming-Hsiang, 2010. "The economy, tourism growth and corporate performance in the Taiwanese hotel industry," Tourism Management, Elsevier, vol. 31(5), pages 665-675.
    4. 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.
    5. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
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    Cited by:

    1. Yun-Huan Lee & William S. Chang, 2016. "Analyzing the effects of economic factors on modeling the diffusion of foreign exchange earnings from tourism in Taiwan," Tourism Economics, , vol. 22(5), pages 1126-1131, October.
    2. 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.
    3. Gu, Xinhua & Wu, Jie & Guo, Haizhen & Li, Guoqiang, 2018. "Local tourism cycle and external business cycle," Annals of Tourism Research, Elsevier, vol. 73(C), pages 159-170.
    4. Liu, Yan & Cheng, Xian & Liao, Stephen Shaoyi & Yang, Feng, 2023. "The impact of COVID-19 on the tourism and hospitality Industry: Evidence from international stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).

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