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Estimating the Swedish and Norwegian International Tourism Demand using ISUR Technique

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Author Info
Salman, Khalik (Mid Sweden University)
Arnesson, Leif (Mid Sweden University)
Sörensson, Anna (Mid Sweden University)
Shukur, Ghazi () (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)
Abstract

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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Publisher Info
Paper provided by Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies in its series Working Paper Series in Economics and Institutions of Innovation with number 198.

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Length: 55 pages
Date of creation: 28 Sep 2009
Date of revision:
Handle: RePEc:hhs:cesisp:0198

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Postal: CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology, SE-100 44 Stockholm, Sweden
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Related research
Keywords: tourism demand; significant factors; Iterative Seemingly Unrelated Regressions (ISUR);

Find related papers by JEL classification:
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Recreation; Tourism

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  1. 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. [Downloadable!] (restricted)
  2. Shukur, Ghazi, 2002. "Dynamic Specification and Misspecification in Systems of Demand Equations: A Testing Strategy for Model Selection," Applied Economics, Taylor and Francis Journals, vol. 34(6), pages 709-25, April. [Downloadable!] (restricted)
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This page was last updated on 2009-11-23.


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