Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi

Abstract

Öz: Tourism sector is an important revenue, exchange and employment source for economies thanks to its forward and backward linkages. Due to these multifaceted impacts, countries are striving to develop the tourism sector and achieve a competitive advantage. Since the 1980s, Turkey has invested in the tourism sector by adopting a tourism-led growth strategy, and consequently that has become one of the world's leading destinations. 1.1 million tourist came to Turkey in 1980 and revenues of 0.327billionwascreated.In2018,thenumberoftouristsincreasedto45.8millionandtourismrevenueto 34.5 billion. The strengthening of global tourism flows in time and the fact that the tourism sector became important for the economies led to an expansion in the analysis of the economic effects of the tourism sector. Most of the empirical studies on the subject are constitute from the demand function estimation and the effect of tourism on economic growth. In the available studies, classical (frequency) inference is the standard method has been applied. There has been no study in which Bayesian inference approach has been applied, which has become increasingly popular in recent years. This study aims to contribute to the literature by considering the impact of tourism on GDP in a Bayesian framework. The findings show that this relation is sensitive to the form of the prior distribution used. While a non-informative (Jeffrey’s type) prior distribution is used, it is seen that tourism has enhancing effect on the GDP, but no significant effect is observed when inverted-gamma and multivariate prior distribution is used.