Factors Determining the Demand for Turkish Tourism in (15) Selected Countries : Static Analysis Using Panel Data (pd) for the Period (2003-2021)

Abstract

To identify the factors influencing tourism demand by visitors to Turkey from(15) selected countries during the period (2003-2021), a regression of tourism demand (Y) was conducted, represented by the number of tourists arriving in Turkey, as a dependent variable on (9) explanatory variables influencing Turkish tourism demand using panel data. Three static models were used for regression analysis: the pooled OLS regression model, the fixed effects model and the random effects model. The study used special statistical tests to select the best-estimated model, the (RE) model. The chosen model was subjected to the usual criteria of economic, statistical, and econometric theory to analyze and evaluate the obtained results. It was found that each of the following variables: the percentage of internet users, the growth rate of per capita GDP, trade openness, and the relative prices of tourism in competing tourist countries to Turkey, had a positive impact on demand for Turkish tourism. The results also showed that each of the following variables: the relative prices of tourism in Turkey, and two dummy variables representing the spread of the coronavirus pandemic in 2020 and the military coup in Turkey in 2016, travel costs, and the real exchange rate, hurt demand for Turkish tourism. Overall, the estimation results are consistent with the theoretical criteria and prior expectations of the study. Regarding statistical tests, it was found that some of the explanatory variables individually had no significant impact on tourism demand for the study sample. However, the F test showed that the explanatory variables together had a significant impact on tourism demand. The estimated model was subjected to traditional standard criteria, such as the VIF test for multicollinearity, which showed that this problem did not exist.