Türkiye'de İhracat-İthalat Oranını Etkileyen Dinamikler: Ekonometri ve Makine Öğrenmesi Yaklaşımıyla Hibrit Model Önerisi

Year 2022, Volume: 9 Issue: 2, 265 - 291, 29.07.2022

Erdemalp Özden

https://doi.org/10.26650/JEPR1088322

Abstract

Dış ticaretle ilgili göstergeler, geleneksel olarak bir para birimi veya ülkenin gayri safi yurtiçi hasılası’nın oranı olarak ölçülmektedir. Diğer yandan, ihracatın ithalatı karşılama oranı birimsiz bir gösterge olarak, ekonomilerin hem zaman içindeki hem de diğer ülkelerle dış ticaret performanslarını karşılaştırırken daha faydalı sonuçlar vermektedir. Bu çalışmada, bu oranı etkileyen makro ekonomik ve finansal belirleyiciler hem ekonometrik olarak hem de makine öğrenmesi yöntemi kullanılarak incelenmiştir. Bu kapsamda ARDL yöntemi, ilk olarak 2010-2021 yılları arasında normalize GSYİH, döviz kuru, TÜFE, ÜFE, ham petrol ile Türkiye'nin REI oranı arasındaki ilişkiyi aylık olarak araştırmak için kullanılmıştır. Uzun vadeli analiz, TL'nin ABD doları karşısında %1'lik değer kaybının REI oranını 0,7 puan artırdığını göstermiştir. Ek olarak, TÜFE'deki %1'lik bir artış REI'yi 1,9 puan artırırken, ÜFE'deki %1'lik bir artış REI'de -0.8 puanlık bir düşüşe neden olmaktadır. Daha sonra, değişkenler arasındaki örüntü, bir makine öğrenmesi yöntemi olan ikinci dereceden destek vektör makineleri (SVM) ile analiz edilmiştir. Son olarak, yeni ARDL-SVM hibrit yöntemi geliştirilmiş ve değişkenler arasındaki örüntü incelenmiştir. Bulgular, ekonometrik yöntemin değişkenler arasındaki ilişkileri yorumlamada daha geniş bir perspektif sunmasına rağmen, geliştirilen ARDL-SVM yönteminin değişkenler arasındaki örüntüleri daha başarılı şekilde yakaladığını ortaya koymuştur.

Keywords

Uluslararası ticaret, İhracatın ithalata oranı, ARDL, SVM, Türkiye

The Dynamics Affecting the Export-Import Ratio in Turkey: A Hybrid Model Proposal with Econometrics and Machine Learning Approach

Abstract

The indicators related to foreign trade are conventionally measured in a currency or as the ratio of the country's gross domestic products. The ratio of exports to imports, alternatively, provides more useful results when comparing the foreign trade performance of economies both over time and with other countries as a unit-free indicator. In this study, the macroeconomics and financial determinants affecting this ratio are examined both econometrically and using the machine learning method. In this context, the autoregressive distributed lag model method was first used to investigate the relationship between normalized gross domestic products, exchange rate, consumer price index, producer price index, crude oil and Turkey's ratio of exports to imports rate between 2010- 2021, monthly. Long-term analysis showed that the 1% depreciation of the Turkish Liras against the US dollar increased the ratio of exports to imports rate by 0.7 points. In addition, a 1% increase in consumer price index will increase ratio of exports to imports by 1.9 points, while a 1% increase in producer price index will cause a -0.8 point decrease on the ratio of exports to imports. Then, the pattern between the variables was analyzed with quadratic support vector machine, a machine learning method. Finally, the novel ARDL-SVM hybrid method was developed, and the pattern between the variables was examined. The findings revealed that although the econometric method provided a broader scope for interpreting the relationships between variables, the developed ARDL- SVM method successfully captured patterns between variables.

Keywords

International trade, Export to import ratio, ARDL, SVM, Turkey

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