Nonlinearity, Complexity and Randomness in Economics


Book Description

Nonlinearity, Complexity and Randomness in Economics presents a variety of papers by leading economists, scientists, and philosophers who focus on different aspects of nonlinearity, complexity and randomness, and their implications for economics. A theme of the book is that economics should be based on algorithmic, computable mathematical foundations. Features an interdisciplinary collection of papers by economists, scientists, and philosophers Presents new approaches to macroeconomic modelling, agent-based modelling, financial markets, and emergent complexity Reveals how economics today must be based on algorithmic, computable mathematical foundations










Non-Linear Dynamics, Complexity and Randomness


Book Description

In this paper I make an attempt to describe, discuss and extend a few aspects of the rich mathematical tapestry that can be woven with rigorous notions of non-linear dynamics, complexity and randomness, in terms of"algorithmic mathematics. It is a tapestry that I try to weave with economic analysis, economic theory and economic modelling in mind. All three notions - that is, non-linear dynamics, complexity and randomness - have a rich conceptual, modelling or analytic tradition in core areas of economic theory, both at the micro and macro levels. It is the algorithmic foundation I try to provide for them that could be considered the novel contribution in this paper. Once the algorithmic foundations are in place, it is, for example, almost natural to consider the famed difficulties of obtaining closed form solutions for non-linear, complex or random dynamic models in economics almost a trivial vestige of a pre-simulation era in mathematical modelling.




Coping with the Complexity of Economics


Book Description

Throughout the history of economics, a variety of analytical tools have been borrowed from the so-called exact sciences. As Schoe?er (1955) puts it: “They have taken their mathematics and their ded- tive techniques from physics, their statistics from genetics and agr- omy, their systems of classi?cation from taxonomy and chemistry, their model-construction techniques from astronomy and mechanics, and their methods of analysis of the consequences of actions from en- neering”. The possibility of similarities of structure in mathematical models of economic and physical systems has been an important f- tor in the development of neoclassical theory. To treat the state of an economy as an equilibrium, analogous to the equilibrium of a mech- ical system has been a key concept in economics ever since it became a mathematically formalized science. Adopting a Newtonian paradigm neoclassical economics often is based on three fundamental concepts. Firstly, the representative agent who is a scale model of the whole society with extraordinary capacities, particularly concerning her - pability of information processing and computation. Of course, this is a problematic reduction as agents are both heterogeneous and bou- edly rational and limited in their cognitive capabilities. Secondly, it often con?ned itself to study systems in a state of equilibrium. But this concept is not adequate to describe and to support phenomena in perpetual motion.




Complexity in Economics: Cutting Edge Research


Book Description

In this book, leading experts discuss innovative components of complexity theory and chaos theory in economics. The underlying perspective is that investigations of economic phenomena should view these phenomena not as deterministic, predictable and mechanistic but rather as process dependent, organic and always evolving. The aim is to highlight the exciting potential of this approach in economics and its ability to overcome the limitations of past research and offer important new insights. The book offers a stimulating mix of theory, examples and policy. By casting light on a variety of topics in the field, it will provide an ideal platform for researchers wishing to deepen their understanding and identify areas for further investigation.




Nonlinearity, Chaos, and Complexity


Book Description

Covering a broad range of topics, this text provides a comprehensive survey of the modelling of chaotic dynamics and complexity in the natural and social sciences. Its attention to models in both the physical and social sciences and the detailed philosophical approach make this an unique text in the midst of many current books on chaos and complexity. Part 1 deals with the mathematical model as an instrument of investigation. The general meaning of modelling and, more specifically, questions concerning linear modelling are discussed. Part 2 deals with the theme of chaos and the origin of chaotic dynamics. Part 3 deals with the theme of complexity: a property of the systems and of their models which is intermediate between stability and chaos. Including an extensive index and bibliography along with numerous examples and simplified models, this is an ideal course text.




Shifting Sands


Book Description

The great crash of 2008 and the associated banking crisis have exposed the increasing irrelevance of much mainstream economics and provoked some economists to re-examine their discipline. Linear or linearized models with well-behaved additive stochastic disturbances, based on 'microeconomic foundations' are no longer anywhere near adequate. Non-linearity, complexity and randomness cannot be avoided, and the ideas of the British Emergentists have recently been given a new lease of life. Basing economics on algorithmic foundations provides a means of restoring genuine rigour to economics and, it is hoped, allowing the discipline to respond in a rational and humane way the next time a major crisis looms.




Dynamics Of Complex Systems


Book Description

This book aims to develop models and modeling techniques that are useful when applied to all complex systems. It adopts both analytic tools and computer simulation. The book is intended for students and researchers with a variety of backgrounds.




Complexity Hints for Economic Policy


Book Description

This book considers the benefits of complexity, suggesting that economists should become a bit less certain in their policy conclusions. A broader range of models would include agent-based models, which use computational power to deal with specification of models that are far beyond analytic solution; and non-linear dynamic stochastic models, many of which are beyond analytic solution, but whose nature can be discovered by a combination of analytics and computer simulations.