TÜRKİYE'YE YÖNELİK TURİZM TALEBİNİN GÖRÜNÜRDE İLİŞKİSİZ REGRESYON MODELLERİ İLE İNCELENMESİ

Günümüzde turizm sektörünün turistik mal ve hizmetlerin talebine etki eden faktörlere karşı aşırı duyarlı olması bu sektördeki talep tahminlerini ve talebe etki eden faktörlerin analizini oldukça önemli duruma getirmektedir. Bu çalışmada Türkiye'nin Turizm alanındaki pazar payının önemli bir bölümünü oluşturan Avrupa ülkelerinin Türkiye'ye yönelik turizm talebinin modellenmesi amaçlanmıştır. Bu amaçla Görünürde İlişkisiz Regresyon Modelleri (GİR) kullanılmış ve bu modeller temel alınarak tahmin edilen parametreler, En Küçük Kareler (EKK) tahminleri ile karşılaştırılmıştır. Ayrıca çalışma kapsamında seçilen Avrupa ülkelerinin Türkiye'ye yönelik turizm talebini etkileyen faktörler incelenmiş ve bu faktörlere göre ülkeler karşılaştırılmıştır. GİR modeli kullanılarak elde edilen parametre tahminlerinin klasik regresyon modeli tahmin tekniklerine kıyasla daha etkin sonuçlar verdiği gözlenmiştir. Bu çalışma, turizm planlamalarının yapılması ve turizm politikalarının belirlenmesinde dünyada yaygın olarak kullanılmayan, Türkiye'deki turizm talep tahmin ve modelleme çalışmalarında yer almamış GİR modelinin bir karar yöntemi olarak kullanılmasını önermektedir.

A REWIEV OF TOURISM DEMAND ON TURKEY VIA SEEMINGLY UNRELATED REGRESSION MODELS

Since the tourism sector is highly sensible to the factors affecting touristic product and services, it gives a significant importance to demand forecasting and analyses of the factors that affect the demand. This study aims to model the tourism demand of European countries, which have an important share of the Turkish tourism market. For this study, Seemingly Unrelated Regression (SUR) Model was used and the forecasting parameters were compared with Ordinary Least Square (OLS) outcomes. Addition to that, factors affecting European Countries' tourism demand was analyzed and these countries were compared according to these factors. As a result of this study, parameter estimates of SUR model are more efficient than classical regression model parameter estimates. This study recommends SUR model, which is not widely used around the world and doesn't take part in studies in Turkey to determine the tourism politics and tourism projection works, can be used as a decision method.

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