The tourism market is inextricably linked to a nation’s economy. There is scant evidence, but growing interest, in the context of tourism, in using the composite leading indicator approach, despite it having been widely applied in the business cycle. The aim of this study is to construct a tourism cycle indicator (TCI) to anticipate the cyclical movements of tourism development. The time duration investigated spanned approximately two decades from 2000 to 2017. Apart from utilising the composite leading indicator approach, a filtering extraction method, a dating algorithm for turning point detection and directional accuracy and binomial tests, this study also included Markov regime switching as well, for identifying the transition probabilities. The empirical findings revealed that the movement of the constructed TCI was consistently in advance of the reference series, international tourist arrivals (TA), in Fiji, with an average lead time of 2.75 months. Moreover, the transition
probabilities that resulted from the Markov regime-switching model indicated that the duration of the transition from one regime to another was on average 12.86 months. These empirical estimation analysis results highlighted the potential ability of the leading indicator to predict the outlook of the tourism market, additionally, the information gained from the macroeconomic perspective should be useful for policy planning, risk monitoring, and community development
