Asymmetric causality between Australian inbound and outbound tourism flows

Abstract

We employ the asymmetric version of the Granger causality test to assess how Australian inbound and outbound tourism flows across 49 markets (countries) are driven by the sign-dependent variations in departure series or vice versa. A multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model is also estimated to study the time-varying co-volatility between inbound and outbound tourism growth rates. We find that rising co-volatility spillovers between inbound and outbound tourism are statistically significant for a number of markets. The six markets that are most susceptible to global shocks are China, Hong Kong, Papua New Guinea, Singapore, South Africa and the United Kingdom. China is by far the largest of these markets and, except for the United Kingdom, both arrivals and departures for each of these countries represent growing markets for Australia. We present recommendations for policymakers and destination management organizations (DMOs) to assist in developing customized strategies targeting resilient inbound markets in order to optimize tourism performance and reduce potential losses in times of crisis.