THE IMPACT OF R&D, PATENTS, AND EDUCATION ON ECONOMIC GROWTH: A MACHINE LEARNİNG (CART) ANALYSIS FROM A KNOWLEDGE ECONOMY PERSPECTIVE

Öz

This study aims to analyze the effects of key components of the knowledge economy-R&D expenditures, patent production, and education level-on economic growth in Türkiye. Annual data covering the period 1996-2022 are employed, and a machine learning-based regression tree (CART) approach is utilized for the analysis. This method enables a more comprehensive evaluation of economic growth dynamics by capturing nonlinear relationships and interactions among variables. The findings indicate that economic growth in Türkiye does not follow a fixed and linear pattern; rather, it is shaped by threshold effects and interactions between variables. The results reveal that R&D expenditures are the primary determinant of growth, while the impacts of patents and education vary depending on the level of R&D. At lower levels of R&D, patent production plays a more significant role, whereas at higher levels, education becomes more influential. Overall, the findings suggest that knowledge-based factors interact in a complementary manner and jointly support economic growth.

Anahtar Kelimeler

• knowledge economic
• machine learning
• education

AR-GE, PATENT VE EĞİTİMİN EKONOMİK BÜYÜME ÜZERİNDEKİ ETKİSİ: BİLGİ EKONOMİSİ PERSPEKTİFİNDEN MAKİNE ÖĞRENMESİ (CART) ANALİZİ

Öz

Bu çalışma, Türkiye’de bilgi ekonomisinin temel bileşenleri olan Ar-Ge harcamaları, patent üretimi ve eğitim düzeyinin ekonomik büyüme üzerindeki etkilerini analiz etmeyi amaçlamaktadır. Bu kapsamda 1996-2022 dönemine ait yıllık veriler kullanılmış ve analiz sürecinde makine öğrenmesi temelli regresyon ağacı (CART) yöntemi uygulanmıştır. Söz konusu yöntem, değişkenler arasındaki doğrusal olmayan ilişkileri ve etkileşimleri ortaya koyabilme özelliği sayesinde ekonomik büyüme dinamiklerinin daha kapsamlı bir biçimde değerlendirilmesine olanak sağlamaktadır. Elde edilen bulgular, Türkiye’de ekonomik büyümenin sabit ve doğrusal bir yapıdan ziyade, belirli eşik değerleri ve değişkenler arası etkileşimler çerçevesinde şekillendiğini göstermektedir. Analiz sonuçlarına göre Ar-Ge harcamaları büyümenin temel belirleyicisi olarak öne çıkarken, bu değişkene bağlı olarak patent ve eğitim faktörlerinin etkisi farklılaşmaktadır. Düşük Ar-Ge düzeylerinde patent üretimi, yüksek düzeylerde ise eğitim değişkeni daha belirleyici hale gelmektedir. Bulgular, bilgi temelli unsurların birbirini tamamlayan bir yapı içerisinde büyümeyi desteklediğini ortaya koymaktadır.

Anahtar Kelimeler

• bilgi ekonomisi
• makine öğrenmesi
• eğitim

Kaynakça

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