Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2022The Dynamics Affecting the Export-Import Ratio in Turkey: A Hybrid Model Proposal with Econometrics and Machine Learning Approach
Özden, Erdemalp
The indicators related to foreign trade are conventionally measured in a currency or as the ratio of the country's gross domestic products. The ratio of exports to imports, alternatively, provides more useful results when comparing the foreign trade performance of economies both over time and with other countries as a unit-free indicator. In this study, the macroeconomics and financial determinants affecting this ratio are examined both econometrically and using the machine learning method. In this context, the autoregressive distributed lag model method was first used to investigate the relationship between normalized gross domestic products, exchange rate, consumer price index, producer price index, crude oil and Turkey's ratio of exports to imports rate between 2010-2021, monthly. Long-term analysis showed that the 1% depreciation of the Turkish Liras against the US dollar increased the ratio of exports to imports rate by 0.7 points. In addition, a 1% increase in consumer price index will increase ratio of exports to imports by 1.9 points, while a 1% increase in producer price index will cause a -0.8 point decrease on the ratio of exports to imports. Then, the pattern between the variables was analyzed with quadratic support vector machine, a machine learning method. Finally, the novel ARDL-SVM hybrid method was developed, and the pattern between the variables was examined. The findings revealed that although the econometric method provided a broader scope for interpreting the relationships between variables, the developed ARDL-SVM method successfully captured patterns between variables.
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İncele - Kitap BölümüYalnız künye2021An Unsupervised Learning Framework to Analyze the Economic Impact of Covid-19: An Application on the Most Affected Countries
Özden, Erdemalp
- MakaleAçık Erişim2021Scopus SJRQ1The effect of sustainable development on economics complexity in oecd countries; [El efecto del desarrollo sostenible en la complejidad económica de los países de la ocde]
Yaprakli, Sevda; Özden, Erdemalp
Economic complexity showing a holistic measure of countries' economic productive power and characteristics has become a new tool for understanding the dynamics of the economy. Examining the relationship between sustainable development and this new tool is vital in determining new policies. By applying panel data of OECD countries covering different development levels from 1996 to 2017 to a data-driven dynamic econometric model, the research provides fresh insight between sustainable development and economic complexity. The results indicate that economic complexity is significantly affected by sustainable developments’ economic indicators such as GDP, FDI, R&D expenditure, social indicators such as human development, income inequality, and environmental indicators such as production-based CO2 emissions, renewable energy consumption, and greenhouse gas. The research, consequently, suggests that switching to technology and knowledge-based production processes, expanding qualified production factor capacity, raising social living standards, and making investments in the green economy will foster economic complexity while ensuring stable sustainability.
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