Description
Book SynopsisTurbulence in Economics presents the economy as an evolutionary process, economics as a realistic science and reintroduces history as fundamental to understanding economic processes. It examines cycles and fluctuations in economic history from the point of view of turbulence in the physical sciences, (specifically hydrodynamics), and argues that an evolutionary approach is required for a better understanding of historical economic processes.
Economic time is marked by a succession of long periods of economic expansion and depression, separated by deep structural changes. These periods represent distinct forms of organization of social relations, science and technology, cultural trends and political and social institutions. This is accepted by historians but rejected in orthodox economics. In this book the author challenges this and argues that the divorce between economics and history limits the ability of economics to explain reality. Within this inquiry into the crisis of orthodox economics the author considers Keynes's, Mitchell's and Schumpeter's critiques of neoclassical economics. The author then compares these to the contributions of Frisch and Wicksell, and examines recent studies of chaos, nonlinear and complex dynamics to explain the historical development of modern economics.
This book will be welcomed by economic historians, historians of economic thought, institutional and evolutionary economists and those interested in chaos, complexity and modern methodology.
Trade Review'Louca's book is a brilliant and convincing demonstration of the importance of deliberate and conscious attention to epistemology. . . This is an invaluable book for all those who wish to learn from the legacy of both Schumpeter and Keynes.’Table of ContentsContents: Introduction Part I: The Evolutionary Metaphors in the Reconstruction of Economics Part II: The Rocking Horse Part III: Bounded Heresies Part IV: Dr Panglaoss Hunted by the Snarks Conclusion: Complexity, The Condition of the World References Index
