Quantitative forecasting for Tourisme: OLS and ARIMAX approaches
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.
|Date of creation:||2003|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.crenos.unica.it/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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 169-77, April.
- 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 1057-72, June.
- 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.
- 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 127-52, April.
- 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.
When requesting a correction, please mention this item's handle: RePEc:cns:cnscwp:200303. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Antonello Pau)
If references are entirely missing, you can add them using this form.