School of Tourism

Airfare elasticities are crucial for policy instruments for the stakeholders of tourism industry. Modellers attempting to estimate these elasticities face several challenges in the absence of microeconomic data on consumer preferences. The aim of this paper is to offer a critical analysis of the practice of computing airfare elasticities from tourism demand studies. It identifies and discusses potential sources of measurement errors in the data and drawbacks that investigators face and assesses their implications for the estimated parameters in the respective models. The use of price of crude oil and distance between origin and destination as proxies for transportation costs are evaluated. It is recommended that authors be more systematic in reporting their results. They need to comment on the limitations of their elasticity estimates since these have repercussions on policy recommendations made based on their results.

The aim of this article is to use dynamic panel data cointegration technique to determine elasticities of tourist arrivals to Australia, using income, real exchange rates, and airfares as demand determinants. Annual data from 1991 to 2007 for arrivals from the 10 main markets are used. Previous studies that applied dynamic panel data sets in the tourism context have used the Arellano—Bond estimation technique. Because this technique produces biased and inconsistent estimates in samples with a small time span, this article uses the corrected least square dummy variable technique to generate unbiased and efficient parameter estimates. The results obtained show that demand is inelastic with respect to its determinants in the short run and elastic in the long run. The main implications of these results are that maintaining destination price competitiveness and consumer satisfaction should be rated very high in the priorities of the Australian tourism industry.

"In spite of the vast and growing literature on tourism demand, outbound tourism remains fairly under-researched. This paper highlights the usefulness of examining determinants of outbound tourism and develops a comprehensive dynamic demand model for international travel from Australia using panel data cointegration technique. The data used are for 47 destinations from 1991 to 2008. The aim is to compute robust demand elasticities. One of the contributions of this paper is that it demonstrates the role that immigration plays in determining international tourist departures from Australia. The estimated short run and long run immigration elasticities are 0.2 and 0.6 respectively.


Keywords

Outbound Tourism Demand, Australia, Dynamic Panel Data Cointegration, Immigration."

The review of literature on outbound tourism reveals that the variable, real exchange rate (RER) has failed to act as an adequate proxy for prices in tourism demand models estimated using Australian data. RER has been systematically found to be statistically insignificant. It is argued here that in spite of the results obtained, it is not reasonable to conclude that Australian travellers are insensitive to changes in the value of their local currency when deciding on the purchase of international trips. It is suggested that, since Australia is an open economy experiencing export-led growth, rising export leads to rising income level while also influencing the real value of the Australian dollar in terms of the currency of its main trading partners. Since income level and RER are affected by common factors such as changes in monetary policies, the inclusion of both in a model of outbound tourism may attenuate the effect of one. This is possible that in previous models of international departures from Australia the use of measures of the country’s income such as GDP or GDP per capita have in fact reduced the effect of RER causing the price of international trips to sound seemingly unimportant in explaining international travel from Australia. On the other hand, as expected income has been found to be a crucial determinant of international departures. This paper develops a competitiveness index (CI) which is then utilised as a proxy for prices in a dynamic panel data model of Australian outbound tourism. International departures to 47 destinations for the period of 1991 to 2008 are considered. The estimation results show that while RER are insignificant and yield an elasticity of -0.004, CI is significant and generates a price elasticity of -0.913. CI clearly outperforms RER as the price variable in the model.

The chapters in this book address the most important established and emerging qualitative and quantitative research methods in tourism. Each chapter is structured to provide information on: the nature of the technique and its evolution; background and types of problems that the technique is designed to handle; applications of the technique to tourism, including discussion of studies that have used the technique and their findings; advantages and limitations of technique conceptually and for policy formulation; and further developments and applications of the technique in tourism research. The chapters are constructed in a way that they provide a detailed overview of the different techniques irrespective of their tourism applications. The volume will appeal to social scientists in general as well as researchers in tourism.

Immigration can potentially influence tourism flows. However, in spite of the vast number of studies on tourism demand modelling, the immigration-tourism linkage has not received much attention in the empirical literature. This paper seeks to address this gap. A dynamic demand model is developed and estimated using data from 1980 to 2008 for the 15 main markets of Australia. The explanatory variables included are income, own price, price of a substitute destination, airfare and immigration. The estimation results empirically establish the connection between immigration and inbound tourism. The short-run and long-run immigration elasticities generated are 0.028 and 0.09 respectively. Additionally this paper demonstrates that omission of prices of substitutes affects the value of the own price elasticity of demand. The results have implications for future research and for stakeholders who can improve the efficiency of their planning exercises by taking into account additional information on immigration trends.


Keywords: Immigration, Tourism Demand, Dynamic Panel Data, Price of Substitutes, Australia.