Abstract
Bay laurel and thyme are products that have an important potential in international trade. According to the average of the last five years, exports in the "ginger, saffron, turmeric (curcuma), thyme, bay leaves, curry and other spices" group reached over 2.5 billion dollars in the world. Turkey has exported over $ 109 million for this product group. A large part of Turkey's exports over $ 109 million belongs to the bay laurel and thyme. In this study, it was tried to estimate the 2019-2023 period with the help of models created by using the data of the amount of bay laurel and thyme export and the income data obtained from the export in the period of 2010-2018. Each series was evaluated separately. In this context, firstly, it was determined whether the seasonality effect in the series and then, predicted values were obtained by regression analysis. As a result of the study, it was found that the data were seasonally affected. It is expected that Turkey’s bay laurel export volume in 2023 will be about 17.7 thousand tons and it will generate approximately 49.6 million dollars in revenue from these exports. Moreover, it is expected that thyme export and the revenue will be 21 thousand tons and 84.7 million dollars, respectively.
Highlights
It was tried to estimate the 2019-2023 period with the help of models created by using the data of the amount of bay laurel and thyme export and the income data obtained from the export in the period of 2010-2018
It is expected that thyme export and the revenue will be 21 thousand tons and 84.7 million dollars, respectively
Gazi Üniversitesi Orman Fakültesi Dergisi, 3(1), 46-72
Summary
Regresyon analizi bir bağımlı değişken ile bir ve birden fazla bağımsız değişken arasındaki ilişkilerin matematiksel eşitlik ile açıklanması olup, değişkenler arasındaki ilişki doğrusal ise doğrusal regresyon doğrusal değilse doğrusal olmayan regresyon olarak isimlendirilmektedir. Doğrusal regresyon y = β0 + β1x + ε denklemi ile ifade edilmektedir. Burada β0 ve β1 değerleri hesaplanan anakütle parametreleri ve ε hata terimidir. Şayet β0 ve β1 değerleri bilinmiyorsa, anakütleden bir örneklem alınarak anakütlenin parametreleri hakkında istenen bilgiler üretilir. Tahmini değerler olarak ise b0 veb kullanılmaktadır. Doğrusal regresyondaki parametre tahmini en küçük kareler tekniği (Least Squares Method) ile yapılmaktadır. Bu yöntemle serpilme diyagramında görülen noktaların doğruya uzaklıkları bulunmakta ve bunların toplamı minimize edilmektedir (Kalaycı, 2016)
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