Computational Techniques For Modelling Learning In Economics

Computational Techniques for Modelling Learning in Economics offers a critical overview of the computational techniques that are frequently used for modelling learning in economics. It is a collection of papers, each of which focuses on a different way of modelling learning, including the techniques of evolutionary algorithms, genetic programming, neural networks, classifier systems, local interaction models, least squares learning, Bayesian learning, boundedly rational models and cognitive learning models. Each paper describes the technique it uses, gives an example of its applications, and discusses the advantages and disadvantages of the technique. Hence, the book offers some guidance in the field of modelling learning in computation economics. In addition, the material contains state-of-the-art applications of the learning models in economic contexts such as the learning of preference, the study of bidding behaviour, the development of expectations, the analysis of economic growth, the learning in the repeated prisoner's dilemma, and the changes of cognitive models during economic transition. The work even includes innovative ways of modelling learning that are not common in the literature, for example the study of the decomposition of task or the modelling of cognitive learning.

This is an investigation into the processes that are involved in economic learning by categorizing different ways of learning, and using mathematical models for their description. Three learning processes are covered: non-cognitive, routine-based and associative learning.

The explosive growth in computational power over the past several decades offers new tools and opportunities for economists. This handbook volume surveys recent research on Agent-based Computational Economics (ACE), the computational study of economic processes modeled as dynamic systems of interacting agents. Empirical referents for "agents" in ACE models can range from individuals or social groups with learning capabilities to physical world features with no cognitive function. Topics covered include: learning; empirical validation; network economics; social dynamics; financial markets; innovation and technological change; organizations; market design; automated markets and trading agents; political economy; social-ecological systems; computational laboratory development; and general methodological issues. *Every volume contains contributions from leading researchers *Each Handbook presents an accurate, self-contained survey of a particular topic *The series provides comprehensive and accessible surveys

After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on web sites, conferences, and computer software.

The approach to many problems in economic analysis has changed drastically with the development and dissemination of new and more efficient computational techniques. Computational Economic Systems: Models, Methods & Econometrics presents a selection of papers illustrating the use of new computational methods and computing techniques to solve economic problems. Part I of the volume consists of papers which focus on modelling economic systems, presenting computational methods to investigate the evolution of behavior of economic agents, techniques to solve complex inventory models on a parallel computer and an original approach for the construction and solution of multicriteria models involving logical conditions. Contributions to Part II concern new computational approaches to economic problems. We find an application of wavelets to outlier detection. New estimation algorithms are presented, one concerning seemingly related regression models, a second one on nonlinear rational expectation models and a third one dealing with switching GARCH estimation. Three contributions contain original approaches for the solution of nonlinear rational expectation models.

Macroeconomic Modelling has undergone radical changes in the last few years. There has been considerable innovation in developing robust solution techniques for the new breed of increasingly complex models. Similarly there has been a growing consensus on their long run and dynamic properties, as well as much development on existing themes such as modelling expectations and policy rules. This edited volume focuses on those areas which have undergone the most significant and imaginative developments and brings together the very best of modelling practice. We include specific sections on (I) Solving Large Macroeconomic Models, (II) Rational Expectations and Learning Approaches, (III) Macro Dynamics, and (IV) Long Run and Closures. All of the contributions offer new research whilst putting their developments firmly in context and as such will influence much future research in the area. It will be an invaluable text for those in policy institutions as well as academics and advanced students in the fields of economics, mathematics, business and government. Our contributors include those working in central banks, the IMF, European Commission and established academics.

There is no doubt that behavioral economics is becoming a dominant lens through which we think about economics. Behavioral economics is not a single school of thought but representative of a range of approaches, and uniquely, this volume presents an overview of them. The wide spectrum of international contributors each provides an exploration of a central approach, aspect or topic in behavorial economics. Taken together, the whole volume provides a comprehensive overview of the subject which considers both key developments and future possibilities. Part One presents several different approaches to behavioural economics, including George Katona, Ken Boulding, Harvey Leibenstein, Vernon Smith, Herbert Simon, Gerd Gigerenzer, Daniel Kahneman, and Richard Thaler. This section looks at the origins and development of behavioral economics and compares and contrasts the work of these scholars who have been so influential in making this area so prominent. Part Two presents applications of behavioural economics including nudging; heuristics; emotions and morality; behavioural political economy, education, and economic innovation. The Routledge Handbook of Behavioral Economics is ideal for advanced economics students and faculty who are looking for a complete state-of-the-art overview of this dynamic field.

This volume is centered around the issue of market design and resulting market dynamics. The economic crisis of 2007-2009 has once again highlighted the importance of a proper design of market protocols and institutional details for economic dynamics and macroeconomics. Papers in this volume capture institutional details of particular markets, behavioral details of agents' decision making as well as spillovers between markets and effects to the macroeconomy. Computational methods are used to replicate and understand market dynamics emerging from interaction of heterogeneous agents, and to develop models that have predictive power for complex market dynamics. Finally treatments of overlapping generations models and differential games with heterogeneous actors are provided.