This paper attempts to develop a financial vulnerability indicator for China as a barometer for the state of financial vulnerability in the Chinese financial market, possibly for real-time application. Twelve variables from different sectors are utilised to extract a common vulnerability component using a dynamic approximate factor model. Through the implementation of a Markovswitching Bayesian vector autoregression (MSBVAR) model, the empirical results indicate that a high-vulnerability episode is associated with substantially lower economic activity, but a low-vulnerability episode does not incur substantial changes in economic activity. Notably, the constructed indicator can serve as a real-time early warning system to signify vulnerabilities in the Chinese financial market.

The fluctuation of oil price tends to have adverse effect on the tourism industry of a nation. This paper investigates the dynamic changes of the inbound tourism market for Fiji and the driving forces of the Fijian tourism cycle. A set of fundamental determinants of tourism demand including international crude oil price has been utilized to predict the Fijian tourism cycle for the period of 2000-2017. The Markov regime-switching model identifies two distinct phases of the Fijian tourism cycle which are an expansion and a recession period. The filtered and smoothed probabilities signalled the Fijian tourism development significantly with the transition probabilities supported. The adequate dating evaluation can offer essential information for policymakers, tourism industry players and even the community in decision making for Fijian tourism to enhance the nation's development.

This study attempts to develop a financial vulnerability indicator serving as a composite indicator for the state of financial vulnerability. The indicator was constructed from 10 variables of macroeconomic, financial and property market by extracting a common vulnerability component through the dynamic approximate factor model. On the feedback and amplification effects, the outcome revealed that financial vulnerability shock catalysed significant negative effects on economic activity in a high-vulnerability regime, while the impact was negligible in periods of low vulnerability. This study highlighted the usefulness of composite indicators as an early warning mechanism to gauge vulnerabilities in the Malaysian financial system.

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This paper aims to investigate Malaysia’s vulnerability to a financial crisis. The methodology employed is an extension of the signals approach based on the original work of Kaminsky and Reinhart (1999). By studying the period from 2000M1 to 2016M9, we construct a financial vulnerability indicator (FVI) to measure the development of vulnerabilities in the Malaysian financial system. Our empirical findings unveil that the causes of crises are multidimensional. Notably, economic slowdown, decline in stock price and weak exports contain good predictive power in assessing financial vulnerability to a crisis. This study highlights the significance of internal and external macroeconomic conditions in determining a country’s vulnerability.