Akademik Veri Yönetim Sistemi
AI Derivatives and Quantum Techonologies The 7th International Spring Conferences, İstanbul, Türkiye, 24 - 25 Mayıs 2025, cilt.73, ss.54, (Özet Bildiri)
This study evaluates the impact of artificial intelligence (AI) methods
on econometric analysis processes. Over the past decade, the increasing
use of AI and machine learning techniques in economics and finance has
prompted a transformation in traditional econometric approaches. Based on a
comprehensive literature review, the analysis addresses how AI-based methods
contribute to prediction accuracy, variable selection, and causal inference. In
Turkey, applications have focused on modeling economic indicators using
Artificial Neural Networks (ANN), Support Vector Machines (SVM), System
Generalized Method of Moments (S-GMM), and Light Gradient Boosting
Machine (LightGBM). Globally, these methods have demonstrated superior
performance in forecasting inflation, analyzing growth, and testing causality,
compared to classical models. However, classical econometric models still
maintain a complementary role in terms of interpretability and theoretical
grounding. In conclusion, AI is not entirely replacing econometric methods
but reshaping them. Thus, hybrid modeling that integrates both approaches is
recommended for future research