Pathways to Carbon Neutrality in the United States: Evaluating Private AI Investment, Financial Development, and Macroeconomic Forces

Abstract

This study analyzes the impact of private investment in artificial intelligence (PAI) and financial development (FD) on carbon dioxide (CO₂) emissions in the United States as well as the contribution of foreign direct investment (FDI), economic growth, and population growth. The analysis uses the annual data of 1996-2022 to test the short- and long-run dynamics using the STIRPAT framework with the ARDL bounds testing technique. The ARDL methodology is confirmed through unit root analyses, which support the presence of a mixed-order integration. The findings indicate that GDP, FDI, and population growth serve as principal factors influencing CO2 emissions in both the short and long term, thereby suggesting that environmental pressures persist amidst economic and demographic progression. In contrast, PAI has a negative and statistically significant impact on emissions, which underscores the prospects of developed technologies to increase energy efficiency and contribute to environmental sustainability. FD also helps minimize emissions in the long run, which highlights the beneficial impact of financial systems in facilitating cleaner patterns of investment. Further, the results of Granger causality indicate numerous unidirectional relationships, especially between GDP, PAI, FDI, population and CO₂ emissions.

Keywords

• Private AI Invesment
• Financial Development
• Carbon Emissions
• STIRPAT Model
• ARDL Approach

Amerika Birleşik Devletleri'nde Karbon Nötrlüğüne Giden Yollar: Özel Yapay Zeka Yatırımlarının, Finansal Gelişmenin ve Makroekonomik Güçlerin Değerlendirilmesi

Öz

Bu çalışma, özel yapay zekâya yatırımların (ÖYZ) ve finansal kalkınmanın (FK) Amerika Birleşik Devletleri'ndeki karbondioksit (CO₂) emisyonları üzerindeki etkisini ve ayrıca yabancı doğrudan yatırımın (DYY), ekonomik büyümenin ve nüfus artışının katkısını analiz etmektedir. Analiz, 1996-2022 yılları arasındaki yıllık verileri kullanarak, ARDL sınır testi tekniği ile STIRPAT çerçevesini kullanarak kısa ve uzun vadeli dinamikleri test etmektedir. ARDL metodolojisi, karma dereceli entegrasyonun varlığını destekleyen birim kök analizleri ile doğrulanmıştır. Bulgular, GSYİH, DYY ve nüfus artışının hem kısa hem de uzun vadede CO₂ emisyonlarını etkileyen temel faktörler olduğunu ve böylece ekonomik ve demografik ilerlemeye rağmen çevresel baskıların devam ettiğini göstermektedir. Buna karşılık, ÖYZ'nin emisyonlar üzerinde negatif ve istatistiksel olarak anlamlı bir etkisi vardır; bu da gelişmiş teknolojilerin enerji verimliliğini artırma ve çevresel sürdürülebilirliğe katkıda bulunma potansiyelini vurgulamaktadır. FK ayrıca uzun vadede emisyonları en aza indirmeye yardımcı olur; bu da finansal sistemlerin daha temiz yatırım modellerini kolaylaştırmadaki faydalı etkisini vurgulamaktadır. Ayrıca, Granger nedensellik analizinin sonuçları, özellikle GSYİH, ÖYZ, DYY, nüfus ve CO₂ emisyonları arasında çok sayıda tek yönlü ilişki olduğunu göstermektedir.

Anahtar Kelimeler

• Özel Yapay Zeka Yatırımları
• Finansal Gelişme
• Karbon Emisyonlar
• STIRPAT Modeli
• ARDL Yaklaşımı

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