Modelling and forecasting Australian domestic tourism

Abstract

In this paper, we model and forecast Australian domestic tourism demand. We use a regression framework to estimate important economic relationships for domestic tourism demand. We also identify the impact of world events such as the 2000 Sydney Olympics and the 2002 Bali bombings on Australian domestic tourism. To explore the time series nature of the data, we use innovation state space models to forecast the domestic tourism demand.Combining these two frameworks, we build innovation state space models with exogenous variables. These models are able to capture the time series dynamics in the data, as well as economic and other relationships. We show that these models outperform alternative approaches for short-term forecasting and also produce sensible long-term forecasts. The forecasts are compared with the official Australian government forecasts, which are found to be more optimistic than our forecasts.

Sentiment, mood and outbound tourism demand

“…Overall, the impact of ICS shocks on outbound tourism demand seems to be negligible, although this does not hold during economic downturns. This contradicts the findings of Athanasopoulos and Hyndman (2008) and Yap and Allen (2011), who maintain that consumer confidence is an important determinant of domestic tourism demand yet it does corroborate with the findings of Gounopoulos et al (2012).…”

“…Indeed, they find this index to be an effective short-term predictor for the US domestic travel volume. Later studies report similar findings when using household debt as a proxy for consumer confidence in relation to Australian domestic tourism demand (Athanasopoulos & Hyndman, 2008;Yap & Allen, 2011).…”

Tourism and regional income inequality: Evidence from China

“…Consistent with the aforementioned conclusion, several studies focusing on Australia (Athanasopoulos & Hyndman, 2008), Peru (O'Hare & Barrett, 1999), South Africa (Cornelissen, 2005) and China (Bowden, 2005) have suggested that tourism spatial polarization, which is treated as enlarging the existing inequalities, is mainly correlated with international rather than domestic tourism. Developing domestic tourism should facilitate a broader geographical spread of benefits, as domestic tourists are more likely than international tourists to visit regional and remote areas.…”

A Bound Test Approach to Cointegration of Tourism Demand

“…A number of the existing empirical studies have used tourist arrivals/departures [12][13][14][15] and tourism receipts/expenditures as dependent variables [16,17] . The number of overnight stays and the average length of stay have also been studied, but much less frequently [18] .…”

“…Mervar [17] implied that the real exchange rate and transportation costs are not statistically significant and the political instability negatively affects tourism demand for Croatian destinations. Hyndman [18] studied the number of visitor nights based on the main purpose of travel: Holiday, visiting friends and relatives, business and other from first quarter of 1998 to second quarter of 2005 for Australia. They found that the negative relationship between the lag of the growth rate of DPI (the price index for domestic holiday travel and accommodation) and positive relationship between growth of Gross Domestic Product (GDP) and holiday travel.…”