Resumen de Estimation of Tourism Demand in Turkey: a Pooled Cross-Section Time Series Analysis
This study uses regression analysis of pooled cross-section (nine countries) and time series (20 years) data for the purpose of identifying and confirming the determinants of tourism demand in Turkey. Three versions of the basic regression model (OLS, TSCS, and COV) have been utilized to study three hypotheses: there are positive relationships between tourism on the one hand, and income, exchange rate, and population of the tourist-generating countries on the other. The results of this study provide support for all of the hypothesized relationships. The implication is that tourism will remain volatile as an industry, reacting quickly to changes, particularly in economic conditions, signaled by changes in exchange rates and income. The hypotheses have also been studied for different subsets of interest. The results indicate that there may be differences between higher and lower income tourist-generating countries in terms of differences in significance of the explanatory variables. Hence, tourists from different countries may be responsive to different factors, a finding that has important implications in targeting tourist promotion efforts.
