Our socio–economic innovation ecosystem is riddled with ever-increasing complexity, as we are faced with more frequent and intense shocks, such as COVID-19. Unfortunately, addressing complexity requires a different kind of economic governance. There is increasing pressure on economics to not only going beyond its traditional mainstream boundaries but also to tackle real-world problems, such as fostering structural change, enhancing sustained growth, promoting inclusive development in the era of the digital economy, and boosting green growth, while addressing the divide between the financial sector and the real economy. This book demonstrates how to apply complexity science to economics in an effective and instructive way, in the interest of life-enhancing policies. The book revolves around the non-negligible problem of why economics, to date, seems to be inadequate in guiding economic governance to navigate through real and ever-intensifying complex socio–economic and environmental challenges. With its interdisciplinary approach, the book scans the nuanced nexus between complexity and economics by incorporating, as well as transcending, the state-of-the-art literature. It identifies ways to trigger opportunities for behavioural change in the economic profession with respect to how and what to teach, introducing and developing further complexity economics taking into account the configuration of its main principles and outlining the silhouette of next-generation economic governance. The book deciphers recommendations for economic theory, practice, education and economic governance. It will be of interest to students, scholars, academics, think-tank researchers and economic policy practitioners at the national and/or supranational levels.

This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance. It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies. The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks

A lot of economic problems can formulated as constrained optimizations and equilibration of their solutions.Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories. The series is designed to bring together those mathematicians who were seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking for effective mathematical tools for their researchers.