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Quantitative forecasting for Tourisme: OLS and ARIMAX approaches

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  • M. Pulina

    ()

Abstract

The paper analyses, estimates and forecasts the demand for international and domestic tourism to Sardinia (Italy). Monthly data are used for the sample period from 1987 to 2002. Concepts such as seasonal and long run unit roots are employed. Two econometric approaches, the OLS and ARIMAX, are used that give satisfactory results in terms of both the estimation and forecasting phases. A full range of diagnostic tests is provided. An ex-ante forecasting exercise is run for tourism demand to Sardinia for the period between January and December 2003.

Suggested Citation

  • M. Pulina, 2003. "Quantitative forecasting for Tourisme: OLS and ARIMAX approaches," Working Paper CRENoS 200303, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  • Handle: RePEc:cns:cnscwp:200303
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    References listed on IDEAS

    as
    1. Haiyan Song & Peter Romilly & Xiaming Liu, 2000. "An empirical study of outbound tourism demand in the UK," Applied Economics, Taylor & Francis Journals, vol. 32(5), pages 611-624.
    2. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    3. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    4. Franses, Philip Hans, 1991. "Seasonality, non-stationarity and the forecasting of monthly time series," International Journal of Forecasting, Elsevier, vol. 7(2), pages 199-208, August.
    5. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 169-177, April.
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    Keywords

    monthly data; unit roots; ols; arimax;

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