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 - Scopus: 22Transition Towards the Sustainable Development: Unraveling the Effects of Mineral Markets, Belt & Road Initiative, and the Paris Agreement on Green Economic Growth(Elsevier Ltd, 2024-04) Xia, Xiqiang; Chishti, Muhammad Zubair; Dogan, EyupThe Agenda 2030 strongly emphasizes implementing effective and equitable measures to address the urgent challenge of global warming, primarily driven by unsustainable fossil-fuel combustion, and one of its core focuses is Sustainable Development Goal (SDG) – 8, among others. In light of this, the recent article aims to explore the dynamic nexus between minerals (MNR), the Belt and Road Initiative (BRI), the Paris Agreement (PA), green technologies (GT), and green growth, with a specific focus on developing a policy framework for advancing SDG – 8. The study utilizes daily data and advanced econometric tools such as QVAR, Cross-quantileogram, and wavelet-quantile correlation to examine the diverse effects of these factors on green growth across various time horizons. The short-run analysis reveals that MNR, BRI, and GT discourage green growth under most market conditions, except for a few quantiles that exhibit positive or insignificant relationships. In the medium run, impacts are mixed, with both positive and negative effects observed. However, in the long run, MNR, BRI, and GT consistently demonstrate favorable effects on green growth. For PA, short and medium-run effects are mixed, but medium-run results indicate a predominantly positive impact on green growth. In the long run, PA significantly benefits green growth across the majority of market conditions. Overall, the diversified results suggest that minerals, BRI, the Paris Agreement, and green technologies play a crucial role in stimulating green growth to achieve SDG - 8 in the long term. © 2024 Elsevier B.V., All rights reserved.Article Citation - WoS: 204Citation - Scopus: 234The Relationship Between Economic Growth and Electricity Consumption From Renewable and Non-Renewable Sources: A Study of Turkey(Pergamon-Elsevier Science Ltd, 2015-12) Dogan, EyupThe main objective of this study is to analyze the short and long run estimates as well as the causality relationships between economic growth (GR), electricity consumption from renewable sources (RELC) and electricity consumption from non-renewable sources (NRELC) for Turkey in a multivariate model wherein capital (K) and labor (L) are included as additional variables. Using the autoregressive distributed lag (ARDL) approach to cointegration, the Johansen cointegration test and the Gregory-Hansen cointegration test with structural break, we show that GR, RELC, NRELC, K and L are cointegrated. Although NRELC has a long run positive effect on GR, the long run estimate of RELC is negative but insignificant at 5% level of significance. The Granger causality test based on the vector error correction model reveals the evidence of neutrality hypothesis between RELC and GR, and between NRELC and GR in Turkey in the short run. In addition, the Granger causality runs from RELC, NRELC, K and L to GR as well as from GR, RELC, K and L to NRELC in the long run, which supports the existence of growth hypothesis between RELC and GR, and feedback hypothesis between NRELC and GR in the long run. It is advised that policy makers in the Turkish government should continue to reduce the share of electricity consumption from renewable sources and encourage the usage of electricity from non-renewable sources to have sustainable long run growth rates. It is also essential to promote the investment projects to increase the efficiency of electricity generation from non-renewable sources. (C) 2015 Elsevier Ltd. All rights reserved.Article Citation - WoS: 194Citation - Scopus: 217The Impact of Renewable Energy Consumption to Economic Growth: A Replication and Extension of Inglesi-Lotz (2016)(Elsevier, 2020-08) Dogan, Eyup; Altinoz, Buket; Madaleno, Mara; Taskin, DilvinThis study replicates and extends the results presented in a top-cited article in this journal, Inglesi-Lotz (2016), which analyzes the impact of renewable energy consumption to economic growth for the OECD countries by applying the ordinary least squares with fixed effect estimator on the data from 1990 to 2010. By using the same data and methods, this study first produces and compare empirical results with those reported in the original article. Then, it applies a set of new econometric methods on the same data to address heterogeneity in renewable energy and economic growth across the analyzed group of countries. The panel quantile regression estimation shows that the effect of renewable energy consumption on economic growth is positive for lower and lowmiddle quantiles; however, its effect becomes negative for middle, high-middle, and higher quantiles when renewable energy consumption is proxied by the absolute value. Furthermore, a negative impact of renewable energy on economic growth is observed in almost all quantiles when it is proxied by the share of renewable energy consumption to total energy consumption. These results greatly differ from those of the original study (C) 2020 Elsevier B.V. All rights reserved.Article Citation - WoS: 34Citation - Scopus: 41Revisiting the Relationship Between Natural Gas Consumption and Economic Growth in Turkey(Taylor & Francis inc, 2015-01-12) Dogan, E.The objective of this study is to re-analyze the relationship between natural gas consumption (NGC) and economic growth (GR) for Turkey in a multivariate framework by including capital and labor as additional variables because several papers suggest that a bivariate model can suffer from omitted-variables bias. As compared to the findings of Isik (2010), who previously investigated the short-and long-run relationships between GR and NGC using a bivariate model, we find that the magnitude of the coefficient estimate of NGC become substantially smaller in the long-run and the sign of short-run estimate of NGC shift to negative after accounting for capital and labor as well. In addition to that covered by Isik (2010), we investigate the direction of causality between GR and NGC using the vector error correction model Granger causality approach, and reveal the evidence of feedback hypothesis for Turkey.Article Citation - WoS: 41Citation - Scopus: 43Re-Estimating the Interconnectedness Between the Demand of Energy Consumption, Income, and Sustainability Indices(Springer Heidelberg, 2019-07-10) Ozcan, Burcu; Tzeremes, Panayiotis; Dogan, EyupIn this study, we analyze the time-varying causality linkages between energy consumption, economic growth, and environmental degradation in 33 Organization for Economic Co-operation and Development countries, spanning the period 2000 to 2013. The curve causality approach provides evidence of a significant environmental Kuznets curve in 25 countries in the case of the ecological footprint and in 23 countries in the case of the Environmental Performance Index. However, out of them, only Italy, Slovakia, and South Korea have traditional environmental Kuznets curve, in the form of an inverted U-shaped curve. For the remaining countries, different forms of curves are valid. In particular, an N-shaped curve appears to be valid between income and environmental degradation for nearly half of the sample, i.e., for Austria, Belgium, Chile, Estonia, Finland, France, Germany, Hungary, Luxembourg, Netherlands, Sweden, Switzerland, New Zealand, Turkey, and the USA. Additionally, bidirectional causality relationships are confirmed among all covariates in most countries. In view of the results, some crucial policy implications would be suggested, such as sustainable development that aims to make a balance between economic growth and environmental protection.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 - WoS: 21Citation - Scopus: 21How Does Technological Innovation Moderate the Environmental Impacts of Economic Growth, Natural Resource Rents and Trade Openness(Academic Press Ltd- Elsevier Science Ltd, 2024-12) Ehigiamusoe, Kizito Uyi; Dogan, Eyup; Ramakrishnan, Suresh; Binsaeed, Rima H.The objective of this study is to unravel the linear impacts of economic growth, technological innovation, natural resource rents and trade openness on carbon emissions in Malaysia during 1980-2021. It also unveils the moderating role of technological innovation on the impacts of economic growth, natural resource rents and trade openness on carbon emissions. It further analyses the nonlinear relationship between technological innovation and carbon emissions. It estimates the parameters with the Autoregressive Distributed Lag model technique. The results of the linear model reveal that economic growth, natural resource rents and trade openness contributes to carbon emissions while technological innovation mitigates carbon emissions. The disaggregated analysis of natural resource rents indicates that oil rents, natural gas rents and coal rents intensify carbon emissions while mineral rents and forest rents do not contribute to carbon emissions. The disaggregated analysis of trade openness shows that exports worsen carbon emissions while imports have tenuous effect. The disaggregated analysis of technological innovation indicates that innovation by non-residents mitigate carbon emissions while innovation by residents do not alleviate carbon emissions. Moreover, evidence from the interaction model reveals that technological innovation can favourably mitigate the adverse impacts of economic growth and trade openness on carbon emissions albeit it cannot alleviate the impact of natural resource rents on carbon emissions. Besides, the nonlinear model indicates a U-shaped relationship between technological innovation and carbon emissions. Unlike previous studies that typically focused on the direct impacts of these variables, this study unravels the impacts of the disaggregated components as well as provides insights into the moderating and nonlinear effects of technological innovation on carbon emissions. The implication of this study is that efforts to achieve a carbon-neutral economy should consider the direct and indirect impacts of economic growth, technological innovation, natural resource rents and trade openness. It is recommended for Malaysia to encourage technological innovation in her quest to abate the adverse environmental impacts of economic activities.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.Article Citation - WoS: 58Citation - Scopus: 67Analyzing the Tourism-Energy Nexus for the Top 10 Most-Visited Countries(MDPI, 2017-10-30) Isik, Cem; Dogan, Eyup; Ongan, Serdar; Dogan, EyüpBy using the Emirmahmutoglu-Kose bootstrap Granger non-causality method, this study explores the directions of causality among tourist arrivals, tourism receipts, energy consumption and economic growth for the top 10 most-visited countries (France, the USA, Spain, China, Italy, Turkey, Germany, the United Kingdom, Russia, and Mexico) in the world. This study finds a variety of causal directions between the pair of analyzed variables for each country and the panel. Since cross-sectional dependence exists across the top countries for the analyzed variables, the bootstrap Granger causality test that accounts for the mentioned issue in the estimation process presumably produces reliable and accurate outputs. Further results and policy implications are discussed in this empirical study.