At the intersection between statistical physics and rigorous econometric analysis, this powerful new framework sheds light on how innovation and competition shape the growth and decline of companies and industries. Analyzing various sources of data including a unique micro level database which collects historic data on the sales of more than 3,000 firms and 50,000 products in 20 countries, the authors introduce and test a model of innovation and proportional growth, which relies on minimal assumptions and accounts for the empirically observed regularities. Through a combination of extensive stochastic simulations and statistical tests, the authors investigate to what extent their simple assumptions are falsified by empirically observable facts. Physicists looking for application of their mathematical and modelling skills to relevant economic problems as well as economists interested in the explorative analysis of extensive data sets and in a physics-orientated way of thinking will find this book a key reference.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
S. V. Buldyrev is Professor of Physics at Yeshiva University. His research interests span theoretical and computational statistical physics and its applications to various complex systems, physical chemistry, material science and biological physics.
F. Pammolli is Professor of Economics and Management at Politecnico di Milano. He served as the Founding Rector of the IMT School for Advanced Studies and is currently a member of the Investment committee of the European Fund for Strategic Investments at the European Investment Bank in Luxembourg. His research interests span the analysis of a variety of complex industrial and technological systems, with particular reference to pharmaceuticals and the life sciences.
M. Riccaboni is Professor of Economics and Director of the Ph.D. Track in Economics, Networks and Business Analytics at the IMT School for Advanced Studies Lucca. His current research focuses on industrial organization, network analysis and the economics of innovation, with particular reference to the life sciences.
H. E. Stanley is William Fairfield Warren Distinguished Professor and Director of the Center for Polymer Studies at Boston University. He is one of the founding fathers of econophysics, a pioneer of interdisciplinary science and has made seminal contributions to the field of statistical physics. He is a member of the US National Academy of Sciences and a recipient of numerous awards throughout his career.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. At the intersection between statistical physics and rigorous econometric analysis, this powerful new framework sheds light on how innovation and competition shape the growth and decline of companies and industries. Analyzing various sources of data including a unique micro level database which collects historic data on the sales of more than 3,000 firms and 50,000 products in 20 countries, the authors introduce and test a model of innovation and proportional growth, which relies on minimal assumptions and accounts for the empirically observed regularities. Through a combination of extensive stochastic simulations and statistical tests, the authors investigate to what extent their simple assumptions are falsified by empirically observable facts. Physicists looking for application of their mathematical and modelling skills to relevant economic problems as well as economists interested in the explorative analysis of extensive data sets and in a physics-orientated way of thinking will find this book a key reference. A new framework looking at growth and decline in business firms. For researchers and graduate students in natural sciences applying their expertise in the analysis of socio economic phenomena. Analogously, it will serve economists interested of learning physics approaches for analysis and modelling of large data sets at different granularities. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781107175488
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