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Journals / Ekonomi Politika ve Finans Araştırmaları Dergisi / 2026 / Cilt: 11 Sayı: 2

Assessing the AI-ESG Nexus Through a Quantile-Wavelet Analysis

Kantil Wavelet Analiz Yöntemiyle Yapay Zekâ-ESG Bağlantısının Değerlendirilmesi

Aslan Aydoğdu(SİVAS BİLİM VE TEKNOLOJİ ÜNİVERSİTESİ)0000-0001-9732-0614
Umut Uyar(PAMUKKALE ÜNİVERSİTESİ)0000-0001-6217-8283
Pages
694–720
Publication Date
2026-06-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The study provides novel insights for investors and policymakers aiming to understand the dynamic and multi-scale linkages between AI adoption and ESG performance.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study investigates the impact of artificial intelligence (AI) on environmental, social, and governance (ESG) performance and explores how this relationship evolves across the quantile and time-frequency domains.
📊
Key Findings & Data:Using daily data from 2018 to 2025, the analysis applies the Quantile-on-Quantile Regression (QQR), Wavelet Quantile-on-Quantile Regression (WQQR), and Quantile Causality (QC) approaches to examine the influence of the Artificial Intelligence Enabler Index (AII) on the Global ESG Index (ESGI).
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Conclusion & Impact:The study provides novel insights for investors and policymakers aiming to understand the dynamic and multi-scale linkages between AI adoption and ESG performance.
🔬Design:Araştırma Makalesi
📍Scope:2018 Verileri
⚙️Variables:Yapay Zekâ · ESG Performans · Kantil-Kantil Regresyon

Abstract

This study investigates the impact of artificial intelligence (AI) on environmental, social, and governance (ESG) performance and explores how this relationship evolves across the quantile and time-frequency domains. Using daily data from 2018 to 2025, the analysis applies the Quantile-on-Quantile Regression (QQR), Wavelet Quantile-on-Quantile Regression (WQQR), and Quantile Causality (QC) approaches to examine the influence of the Artificial Intelligence Enabler Index (AII) on the Global ESG Index (ESGI). The results based on raw data reveal that the influence of AI on ESG performance is heterogeneous across quantiles, with both positive and negative effects. In the short, medium, and long term, AII positively affects ESGI at the lower and upper quantiles, while exerting negative effects around the median quantiles. The QC findings, consistent with the raw and wavelet-based analyses, indicate that AI has predictive power for ESG performance over the medium and long horizons, but not in the short run. These results underscore that the strategic and holistic integration of AI technologies can play a pivotal role in overcoming ESG challenges and fostering sustainable development. The study provides novel insights for investors and policymakers aiming to understand the dynamic and multi-scale linkages between AI adoption and ESG performance.

Özet

Bu çalışma, yapay zekânın ESG performansı üzerindeki etkisini incelemek ve bu etkinin kantil ve zaman-frekans uzayında nasıl gerçekleştiğini araştırmayı amaçlamaktadır. Bu doğrultuda, 2018-2025 dönemi günlük verileri kullanılarak Yapay Zekâ Endeksi’nin (AII) Küresel ESG Endeksi (ESGI) üzerindeki etkisini analiz etmek için Kantil-Kantil Regresyon (QQR), Wavelet Kantil-Kantil Regresyon (WQQR) ve Kantil Nedensellik (QC) yöntemleri uygulanmıştır. Ham veri sonuçları, AII’nın farklı kantil düzeylerinde ESG performansı üzerinde hem pozitif hem de negatif etkilerinin olduğunu ortaya koymaktadır. Kısa, orta ve uzun vadeli dönemlerde ise AII’nın ESGI performansı üzerinde alt ve üst kantillerde pozitif; orta kantil düzeylerinde ise negatif etkiye sahip olduğu görülmektedir. QG sonuçları, ham verilerle birlikte orta ve uzun vadeli dönemlerde yapay zekânın ESG performansını öngörebildiğini göstermektedir. Ancak kısa vadede yapay zekânın ESG performansı üzerinde nedensel bir öngörü gücü bulunmamaktadır. Yapay zekâ teknolojisinin stratejik ve bütüncül entegrasyonu, ESG zorluklarının aşılmasında ve sürdürülebilir kalkınmanın desteklenmesinde önemli bir rol oynamaktadır. Bu çalışma, yatırımcılar ve politika yapıcılar için önemli öngörüler sunmaktadır.

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Cite This Article

Aydoğdu, A., Uyar, U. (2026). Assessing the AI-ESG Nexus Through a Quantile-Wavelet Analysis. Ekonomi Politika ve Finans Araştırmaları Dergisi, Cilt: 11 Sayı: 2, 694–720. https://doi.org/10.30784/epfad.1936077

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