Tourism is an important and fast-evolving economic activity with social, cultural and environmental implications, involving large numbers of small and medium-sized businesses. Its contribution to growth and employment varies widely from one region of the EU to another. In rural regions that are usually remote from the economic centers of their countries, tourism is often one of the main sources of income for the population and a prominent factor in securing an adequate level of employment. In this study, we consider and estimate the most accurate association model of the Categorical Data Analysis (CDAS) for tourism: the total number of trips (absolute value/unit) by main mode of transport used in 13 EU countries. The data used in this study were obtained from the Eurostat and estimated on actual base year from 2004 - 2012. Since the main focus is to have a better understanding of tourism - holidays in 13 EU countries, the analysis of association (ANOAS) table is given in order to ascertain the percentage of the data which is covered by each model. We find and estimate the association model with the best fit and in conclusion we find out that the Row-Column Effects Association Model (RC) of the (M = 8) has the best fit among all.
[1]
Joel C. Nwaubani, Faculty of Social Sciences, Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece.
[2]
Theodora Polizou, Faculty of Social Sciences, Department of Business Administration, University of Macedonia, Thessaloniki, Greece.
[3]
Margarita Palantzidou, Faculty of Theology, School of Theology, Aristotle University of Thessaloniki (AUTh), Thessaloniki, Greece.
[1]
Clogg, C. C. (1990), ANOAS program.
[2]
Diewert, W. Erwin, Exact and Superlative Index Numbers,’’ Journal of econometrics May 1976, 4: 115–45.
[3]
Diewert, W. Erwin, (1995). Axiomatic and Economic Approaches to Elementary Price indexes. NBER Working Paper 5104.
[4]
Eliason Ρ. Scott-Clifford Clogg (1990), Ανάλυσης Διατεταγμένων Δεδομένων (CDAS).
[5]
Fairbanks, Michael. (2000). Changing the Mind of a Nation: Elements in a Process for Creating Prosperity, “in Culture Matters”, Huntington, editors, “New York: Basic Books”, pp.270-281.
[6]
Goodman, L. A., (1979a). Multiple Models for the Analysis of Occupational Mobility Tables and Other Kinds of Cross-Classification Tables. “American Journal of Sociology”, 84:804-819.
[7]
Goodman, L. A., (1979b). Multiple Models for the Analysis of Occupational Mobility Tables and Other Kinds of Cross-Classification Tables. “American Journal of Sociology”, 84:804-819.
[8]
Goodman, L. A., (1981a). Association models and the Bivariate Normal for Contingency Tables with Ordered Categories. Biometrica, 68: 347-55.
[9]
Goodman, L. A., (1981b). Association Models and Canonical Correlation in the Analysis of Cross-Classifications Having Ordered Categories. “Journal of American Statistical Association”, 76:3,20-34.
[10]
Eurostat /JP (2008): European Environment agency, “Eurostat-Tourism statistics at regional level”.
[11]
The United Nations World Tourism Organization’s Yearbook of Tourism Statistics, “World Tourism Organisation (WTO), during the Global Tourism Forum 2011, in Andorra”.
[12]
Haritou A., (2006). “Categorical Data Analysis” (University Press).
[13]
European Travel Commission, European Tourism Insights 2006, ETC Market Intelligence Report No 3/2007, May.
