İKLİM POLİTİKASI BELİRSİZLİĞİNİN BIST KİMYA PETROL PLASTİK ENDEKSİ ÜZERİNDEKİ ETKİSİ

Abstract

Bu çalışma, iklim politikası belirsizliğinin (CPU) BIST Kimya Petrol Plastik Endeksi (XKMYA) üzerindeki etkisini 2000–2025 dönemine ait aylık veriler kullanarak incelemektedir. CPU verileri Gavriilidis (2021) tarafından geliştirilen endeksten elde edilmiş ve değişkenlerin durağanlık özellikleri ADF birim kök testiyle analiz edilmiştir. Serilerin farklı bütünleşme derecelerine sahip olması nedeniyle geleneksel Granger yaklaşımı yerine Toda–Yamamoto nedensellik testi kullanılmıştır. Bilgi kriterleri doğrultusunda optimal gecikme uzunluğu üç olarak belirlenmiş ve genişletilmiş VAR modeli tahmin edilmiştir. Tanısal testler, modelde anlamlı düzeyde otokorelasyon veya güçlü bir heteroskedastisite sorunu bulunmadığını göstermiştir. Elde edilen ampirik bulgular, CPU’dan XKMYA’ya doğru tek yönlü bir nedensellik ilişkisi olduğunu ortaya koymaktadır. Buna karşılık XKMYA’nın CPU üzerinde herhangi bir nedensel etkisi tespit edilmemiştir. Sonuçlar, küresel iklim politikası belirsizliklerinin Türkiye’de enerji yoğun sektörlerin piyasa performansını etkileyebileceğini göstermekte; bu nedenle sektör firmalarının, yatırımcıların ve politika yapıcıların küresel iklim politikalarındaki gelişmeleri yakından takip etmeleri gerektiğine işaret etmektedir. Ayrıca çalışma, iklim politikası belirsizliğinin finansal piyasalar üzerindeki etkilerini inceleyen literatüre Türkiye örneği açısından katkı sunmaktadır.

Keywords

• İklim Politikası Belirsizliği
• BIST XKMYA
• Nedensellik

THE IMPACT OF CLIMATE POLICY UNCERTAINTY ON THE BIST CHEMICAL PETROL PLASTIC INDEX

Abstract

This study examines the impact of climate policy uncertainty (CPU) on the BIST Chemical Petrol Plastic Index (XKMYA) using monthly data covering the period 2000–2025. CPU data are obtained from the index developed by Gavriilidis (2021), and the stationarity properties of the variables are analyzed using the ADF unit root test. Since the series exhibit different integration orders of integration, the Toda–Yamamoto causality approach was employed instead of the traditional Granger causality test. Based on information criteria, the optimal lag length is determined to be three, and the extended VAR model was estimated. Diagnostic tests indicate no significant autocorrelation or heteroskedasticity, confirming the robustness of the model. Empirical findings reveal a unidirectional causality running from CPU to XKMYA, whereas no causal relationship is detected in the opposite direction. The results suggest that global climate policy uncertainty influences the market performance of energy-intensive sectors in Türkiye. Accordingly, firms in the sector, investors, and policymakers should closely monitor developments in global climate policy when making strategic, financial, and risk-management decisions. Moreover, the study contributes to the literature by providing evidence on the effects of climate policy uncertainty on financial markets within the context of Türkiye.

Keywords

• Climate Policy Uncertainity
• BIST XKMYA
• Causality

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