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231206 ||| eng |
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|a 9783031438646
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|a Gherghina, Ştefan Cristian
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|a Quantitative Methods in Finance
|h Elektronische Ressource
|b Exploring the Drivers of Sustainable Economic Growth in the EU
|c by Ştefan Cristian Gherghina
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| 250 |
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|a 1st ed. 2023
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2023, 2023
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| 300 |
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|a XXV, 205 p. 32 illus., 30 illus. in color
|b online resource
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| 505 |
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|a Chapter 1. Related Literature - Focus on Sustainable Economic Growth -- Chapter 2. A Panel Data Regression Approach Towards the Drivers of Sustainable Economic Growth -- Chapter 3. A Vector Error Correction Model (Vecm) Approach -- Chapter 4. A Principal Component Analysis Approach Towards Assessing Sustainable Economic Growth -- Chapter 5. A Data Envelopment Analysis Approach Towards Evaluating Sustainable Economic Growth -- Chapter 6. A Cluster Analysis Towards Exploring Sustainable Economic Growth
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| 653 |
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|a Financial Services
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| 653 |
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|a Corporate Environmental Management
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| 653 |
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|a Mathematics in Business, Economics and Finance
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| 653 |
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|a Finance
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| 653 |
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|a Economic development
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| 653 |
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|a Economic Growth
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| 653 |
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|a Social sciences / Mathematics
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| 653 |
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|a Financial Economics
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| 653 |
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|a Financial services industry
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| 653 |
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|a Industrial management / Environmental aspects
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
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|a Sustainable Finance
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| 028 |
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|a 10.1007/978-3-031-43864-6
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| 856 |
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|u https://doi.org/10.1007/978-3-031-43864-6?nosfx=y
|x Verlag
|3 Volltext
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|a 332
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| 520 |
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|a This book explores certain social and environmental drivers of sustainable economic growth for European Union countries (EU-27) and United Kingdom (UK) in the context of the UN 2030 Agenda for Sustainable Development. The author provides a comprehensive overview of the factors that impact and facilitate sustainable economic growth and discusses the complex set of factors involved in sustainable economic development. Special attention is given to quantitative frameworks and empirical modelling, with the main focus on panel data regression models and vector error correction model approach. Furthermore, the book develops ratings of sustainable economic growth for each of the explored countries, by employing data mining techniques such as principal component analysis. Also, the data envelopment analysis non-parametric methodology towards assessing sustainable economic growth is investigated, as well as the cluster analysis in order to classify the selected nations according to sustainableeconomic growth. The book appeals to policy-makers and academics targeting to learn more about the characteristics of sustainable economic growth
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