TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396
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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 Tax Compliance Behaviour and Lab Experiments: A Literature Review(Maliye Bakanligi, 2021) Demirtas, Burak KaganThe purpose of this article is to conduct a literature review of the papers based on laboratory experiments to analyze tax evasion behaviors of individuals. Although experimental studies in economics have become more and more important day by day, there are almost no publications on experimental economics in the Turkish literature. The studies are examined especially in terms of experimental designs because this study also aims to increase awareness about laboratory experiments. This review also discusses the criticism of laboratory experiments and concludes that the results obtained from laboratory experiments are important and it would be beneficial to support them with field experiments.Article Performance Evaluation of Energy Companies With a Novel Integrated Multi- Criteria Decision Making Method(Kafkas University Iibf, 2022-12-27) Madenoglu, Fatma Selen; Unlusoy, Omer Faruk; Yilmaz, CagatayFinancial statements are an important tool for assessing and analyzing an organization's financial performance. Financial performance analysis allows for an accurate and appropriate appraisal of an organization's performance. The evaluation procedure must be thoroughly stated because financial performance indicators represent a company's competitiveness. This study provides a novel integrated multi-criteria decision-making method for analyzing an organization's financial performance. The applicability of the proposed method is assessed employing financial ratios that are integrated to generate a financial performance score for eight well-known Turkish energy companies. The criteria are weighted using the entropy method in the proposed method. The multi- attributive border approximation area comparison (MABAC) method is used to rank the companies. As the weights of the criteria have an impact on the ranking outcomes, a sensitivity analysis of the weights is performed. We also exhibit a comparison analysis of energy company rankings to validate the proposed approach's results using four MCDM methods: ELECTRE, MAUT, TOPSIS, and WASPAS. In addition, an alternative weighting method is also used to evaluate the results. The results show that the proposed method is an effective MCDM for coping with evaluation problems.