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Modelling domestic tourism demand in Australia a dynamic panel data approach

Author

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  • Ghialy Yap

    (Faculty of Business and Law Edith Cowan University, Perth, Australia)

Abstract

Domestic tourism in Australia generates about 74% of total tourism revenue. Given that, this paper examines whether changes in Australian households? income and the prices of domestic travel can influence the demand for domestic travel. It reveals some notable results. First, Australian households will not choose to travel domestically when there is an increase in household income. Second, an increase in the current prices of domestic travel can cause the demand for domestic trips to fall in the next one or two quarters ahead. Finally, the coefficients for lagged dependent variables are negative, indicating perhaps, that trips are made on a periodic basis.

Suggested Citation

  • Ghialy Yap, 2009. "Modelling domestic tourism demand in Australia a dynamic panel data approach," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 1(1), pages 1-11, April.
    • Handle: RePEc:uii:journl:v:1:y:2009:i:1:p:1-11
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    References listed on IDEAS

    as
    1. Kulendran, N. & King, Maxwell L., 1997. "Forecasting international quarterly tourist flows using error-correction and time-series models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 319-327, September.
    2. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    3. Martin, Christine A. & Witt, Stephen F., 1989. "Forecasting tourism demand: A comparison of the accuracy of several quantitative methods," International Journal of Forecasting, Elsevier, vol. 5(1), pages 7-19.
    4. Jae H. Kim & Imad Moosa, 2001. "Seasonal Behaviour of Monthly International Tourist Flows: Specification and Implications for Forecasting Models," Tourism Economics, , vol. 7(4), pages 381-396, December.
    5. Larry Dwyer & Peter Forsyth (ed.), 2006. "International Handbook on the Economics of Tourism," Books, Edward Elgar Publishing, number 2827, December.
    6. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    7. Teresa Garin-Munoz & Teodosio Perez Amaral, 2000. "An econometric model for international tourism flows to Spain," Applied Economics Letters, Taylor & Francis Journals, vol. 7(8), pages 525-529.
    8. Lim, Christine, 2004. "The major determinants of Korean outbound travel to Australia," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(3), pages 477-485.
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    More about this item

    Keywords

    domestic tourism; Australia; households? income; domestic travel;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • L8 - Industrial Organization - - Industry Studies: Services

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