Parametric and non-parametric data-driven analytics for socioeconomic challenges in a contemporary world
DOI:
https://doi.org/10.51359/2965-4661.2023.259300Keywords:
Data Analytics, Econometrics, Operations Research , Data Envelopment Analysis, Time Series Analysis, regression models, Natural Language Processing, Sentiment AnalysisAbstract
The rapid advancement of artificial intelligence and data-driven technologies have presented novel opportunities for addressing complex socioeconomic challenges in the contemporary world. By harnessing diverse datasets and employing sophisticated analytical techniques, researchers, policymakers, and practitioners can gain profound insights into the root causes of socioeconomic challenges and devise innovative strategies to promote inclusive development and sustainable growth. In this editorial, I share some perspectives on exploring the application of non-parametric and parametric data-driven analytics methodologies (Data Envelopment Analysis and Econometric Models) as powerful tools for understanding and resolving multifaceted issues that impact societies globally, and what I believe to be the future of these methods. Readers of Socioeconomic Analytics will be able to find those interesting methodologies as empirical applications in the journal's inaugural and forthcoming issues.References
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