This study attempts to examine empirically aggregate tourism outflows in the case of Turkey using the time series data for the period 1970-2005. As far as this article is concerned, there exists no previous empirical work dealing with the tourist outflows from Turkey. The previous tourism studies in the case of Turkey, by and large, focus on the inbound tourism demand analyses. As a developing country and an important tourism destination, Turkey has also been a significant source for generating a substantial number of tourists in recent years. Therefore, the tourist outflows from Turkey deserve to be analysed empirically too. The total tourist outflows from Turkey are related to real income and relative prices. The bounds testing to cointegration procedure proposed by Pesaran et al. (2001) is employed to compute the short and long-run elasticities of income and relative prices. An augmented form of Granger causality analysis is conducted amongst the variables of outbound tourist flows, income and relative prices to determine the direction of causality. In the long-run, causality runs interactively through the error correction term from income and relative prices to outbound tourist flows. However, in the short-run, causality runs only from income to outbound tourism flows. The aggregate tourism outflows equation is also checked for the parameter stability via the tests of cumulative sum (CUSUM) and cumulative sum of the squares (CUSUMSQ). The empirical results suggest that income is the most significant variable in explaining the total tourist outflows from Turkey and there exists a stable outbound tourism demand function. The results also provide important policy recommendations.
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number
6765.
Find related papers by JEL classification: E0 - Macroeconomics and Monetary Economics - - General O5 - Economic Development, Technological Change, and Growth - - Economywide Country Studies C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
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