Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Forecasting the Consumer Price Index in Türkiye Using Machine Learning Models: A Comparative Analysis(Gazi Univ, 2025-09-01) Söylemez, İsmet; Ünlü, Ramazan; Nalici, Mehmet ErenThis study utilizes machine learning models to forecast Türkiye's Consumer Price Index (CPI), thereby addressing a critical gap in inflation prediction methodologies. The central research problem involves the forecasting of CPI in a volatile economic environment, which is essential for informed policymaking. The primary objective of this study is to evaluate the performance of three machine learning models, such as Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM), in forecasting CPI over periods ranging from one to six months, utilizing data from 2012 to 2024. The study's unique contribution lies in the application of the \"SelectKBest\" method, which identifies the most relevant indices, thereby enhancing the efficiency of the models. An ensemble method, Averaging Voting, is also employed to combine the strengths of these models, producing more accurate and robust predictions. The findings indicate that while the RF model consistently generates the most accurate forecasts across all shifts, the SVM model demonstrates a particular strength in the domain of short-term predictions. The ensemble model demonstrates a substantial performance improvement, with a R2 value of 0.962 for one-month ahead of estimates and 0.956 for five-month forecasts. This combined approach has been shown to outperform individual models, offering a more reliable framework for CPI forecasting. The findings offer valuable insights for economic policymakers, enabling more precise and stable inflation predictions in Türkiye.Article Citation - WoS: 1Citation - Scopus: 1Impact of Climate Change on Economic Growth in Developing Countries: Unravelling the Moderating Role of Globalization(Springer, 2024-11-27) Ehigiamusoe, Kizito Uyi; Lean, Hooi Hooi; Dogan, Eyup; Binsaeed, Rima H.; Ramakrishnan, SureshThough some empirical works have shown the determinants of economic growth, the research work on the impact of climate change (proxied by carbon emissions and ecological footprint) on economic growth is still scanty especially in developing countries. The attainment of the Sustainable Development Goals (SDG-8 and SDG-13) requires a comprehensive analysis of the nexus between climate change and economic growth. Therefore, this study fills the literature gap by investigating the impact of climate change on economic growth in Malaysia (a country that obtains most of her energy from fossil fuels) and Nigeria (a country that obtains most of her energy from renewable resources) during the 1980-2021 period. Given the intricate relationship among climate change, economic growth and globalization, this study also determines the moderating role of globalization (and its dimensions) on the impact of climate change on economic growth. It employs the Autoregressive Distributed Lag approach to estimate the parameters. The linear model shows that climate change has a negative impact on economic growth in Malaysia and Nigeria albeit the magnitude is larger in Malaysia. The interaction model indicates that globalization and some of its dimensions favorably moderate the detrimental impact of carbon emissions on economic growth but cannot moderate the impact of ecological footprint on economic growth in Malaysia and Nigeria. The marginal effect of carbon emissions on economic growth varies with the level of globalization. This study highlights the implications of the findings and proposes some policy options.Article Citation - Scopus: 3Future of Clean Cooking Energy Access in Emerging Economies by 2030(Springer International Publishing, 2025-03-07) Çakır, Mehmet Ali; Ünlü, Ramazan; Çakir, Sümeyra Çay; Xanthopoulos, PetrosThis study assesses the future of clean energy and technology access for cooking in emerging economic blocs—BRICS, MINT, ASEAN, and MENA—through 2030. Cooking contributes 3% of global greenhouse gas emissions, with over half of household emissions coming from cooking. Therefore, clean cooking energy is critical for sustainability and human health. The study aims to evaluate the likelihood of achieving the UN Sustainable Development Goal of universal clean cooking energy access by 2030 and the 2050 net-zero emissions target. Machine learning techniques, such as support vector regression, gradient boosting, and linear regression, alongside an ensemble approach, provide forecasts for these regions. The findings show a varied outlook. Within ASEAN, two countries are expected to reach 100% clean energy access for cooking by 2030, while two are likely to experience a decline. The MENA region shows stronger progress, with eight countries expected to meet the 2030 target. Among BRICS countries, only India is projected to reach full accessibility, while Russia faces a decline. The MINT countries face challenges, with none expected to meet the target, and Nigeria is projected to experience a decrease in clean energy access. The study concludes that the current trajectory makes achieving the 2030 Sustainable Development Goals and the 2050 net-zero emissions target unlikely for these regions. Policymakers must reassess their strategies and learn from successful countries to improve outcomes. © 2025 Elsevier B.V., All rights reserved.