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Estimating the Swedish and Norwegian international tourism demand using (ISUR) technique

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    This paper estimates the demand for tourism to Sweden and Norway for five countries: Denmark, the United Kingdom, Switzerland, Japan, and the United States. For each visiting country, and for Sweden and Norway, we specify separate equations by including relative information. We then estimate these equations using Zellner’s Iterative Seemingly Unrelated Regressions (ISUR). The benefit of this model is that the ISUR estimators utilize the information present in the error correlation of the cross regressions (or equations) and hence are more efficient than single equation estimation methods such as ordinary least squares. Monthly time series data from 1993:01 to 2006:12 are used. The results show that the consumer price index, some lagged dependent variables, and several monthly dummies(representing seasonal effects) have a significant impact on the number of visitors to the SW6 region in Sweden and Tröndelag in Norway. We also find that, in at least some cases, relative prices and exchange rates have a significant effect on international tourism demand.

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    File URL: http://www.vxu.se/ehv/filer/forskning/cafo/wps/Nek_wp12_09.pdf
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    Paper provided by Centre for Labour Market Policy Research (CAFO), School of Business and Economics, Linnaeus University in its series CAFO Working Papers with number 2009:12.

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    Length: 45 pages
    Date of creation: 12 May 2009
    Date of revision:
    Handle: RePEc:hhs:vxcafo:2009_012
    Contact details of provider: Postal: Centre for Labour Market Policy Research (CAFO), School of Business and Economics, Linnaeus University, SE 351 95 Växjö, Sweden
    Phone: +46 470 70 87 64
    Web page: http://lnu.se/research-groups/cafo?l=en

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    1. Ghazi Shukur, 2002. "Dynamic specification and misspecification in systems of demand equations: a testing strategy for model selection," Applied Economics, Taylor & Francis Journals, vol. 34(6), pages 709-725.
    2. Godfrey, Leslie G, 1978. "Testing for Higher Order Serial Correlation in Regression Equations When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1303-10, November.
    3. Breusch, T.S. & Pagan, A.R., . "The Lagrange multiplier test and its applications to model specification in econometrics," CORE Discussion Papers RP -412, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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