This book assesses the main interrelationships between economic growth processes, life cycle sustainability assessment approaches, and new technologies in the framework of digital transition. In other words, it aims to highlight how sustainability assessment methodologies and artificial intelligence can better support different actors for more sustainable economic growth. Readers of the book would benefit from diverse perspectives on the contributions of evaluation methodologies and digital technologies to more sustainable economic growth. This is important especially for students, policymakers and public institutions. Economic growth is analysed using the concepts of sigma and beta convergence from neoclassical theory and the Verdoorn law of Keynesian development. For sustainability assessments, the book considers methodologies associated with social life cycle assessment and life cycle cost analysis. In the context of digital technologies, special emphasis is given to machine and deep learning approaches.

This book assesses the main interrelationships between economic growth processes, life cycle sustainability assessment approaches, and new technologies in the framework of digital transition. In other words, it aims to highlight how sustainability assessment methodologies and artificial intelligence can better support different actors for more sustainable economic growth. Readers of the book would benefit from diverse perspectives on the contributions of evaluation methodologies and digital technologies to more sustainable economic growth. This is important especially for students, policymakers and public institutions. Economic growth is analysed using the concepts of sigma and beta convergence from neoclassical theory and the Verdoorn law of Keynesian development. For sustainability assessments, the book considers methodologies associated with social life cycle assessment and life cycle cost analysis. In the context of digital technologies, special emphasis is given to machine and deep learning approaches.

Technological advance is the key driving force behind economic growth, argues Richard Nelson. Drawing on a deep knowledge of economic and technological history as well as the tools of economic analysis, he exposes the intimate connections among government policies, science-based universities, and the growth of technology.

This textbook by Hendrik Van den Berg on Economic Growth and Development presents a long-awaited synthesis of Development Economics and Growth Theory. It also incorporates the recent contributions to our understanding of economic growth from the fields of economic history and the new institutional economics. By basing its analysis on the recent advances in growth theory, the book offers a unified approach to all episodes of economic growth for countries at all levels of development and throughout history. Students will be comfortable with an analysis that enables them to understand economic growth in their own country as well as in economies very different from their own. The unified theoretical framework greatly facilitates students understanding of the process of economic growth, and the many cases and examples highlight the fascinating diversity of our world.

Why are some nations rich and others poor? What are the sources of long-run economic development and growth? How can living standards be increased? In this book, Klaus Gründler empirically analyses these central economic questions and puts a particular emphasis on the role of technology, inequality, and political institutions. To substantiate his empirical studies, he introduces a new method to compute composite measures and indices that is based on mathematical algorithms from the field of machine learning.

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Productivity, Technology and Economic Growth presents a selection of recent research advances on long term economic growth. While the contributions stem from both economic history, macro- and microeconomics and the economics of innovation, all papers depart from a common viewpoint: the key factor behind long term growth is productivity, and the latter is primarily driven by technological change. Most contributions show implicitly or explicitly that technological change is at least partly dependent on growth itself. Furthermore, technology appears to interact strongly with investment in physical and human capital as well as with changes in historical, political and institutional settings. Together these papers are an up-to-date account of the remarkable convergence in theoretical and empirical work on productivity and growth over the past decades. The first part deals with the characteristics of growth regimes over longer periods, ranging from 20 years to two centuries. The next four chapters study the determinants of productivity growth and, in some cases, productivity slowdown during the last quarter of the twentieth century. The final five chapters focus on the role of technology and innovation as the key determinants of growth. Productivity, Technology and Economic Growth is, therefore, a welcome collection for academic scholars and graduate students in economics, history and related social sciences as well as for policy makers.