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The book includes stylized and simple agent-based models which explain stylized facts (such as boom and bust cycles), the mathematical foundations of nonlinear dynamic systems (i.e., bifurcations, multiple equilibriums, and chaos), an introduction to the theory of heterogeneous and switching expectations as well as an empirical validation of the heterogeneous and switching expectations hypothesis utilizing the S&P500 stock market data and laboratory experiments.
The book is of interest for students, researchers and policy makers as it presents complexity essentials, which are necessary to build market models that are closer to reality than traditional macro-finance models. Unlike the latter, more realistic models allow for better managing and understanding crises in a complex and global economy. This book can be viewed as an excellent textbook for graduates. It provides a comprehensive and very up to date overview of the topic of nonlinear economic dynamics. In the preface, Hommes states that the book, indeed, is based on material that was used in teaching a course on nonlinear economic dynamics over many years.
The book is divided into 8 chapters. The opening chapter introduces the topic, summarizes the rest of the book in an excellent way and clarifies the basic framework. The second and third chapters introduce the important mathematical foundations for treating nonlinear dynamics. More precisely, the second chapter focuses on one-dimensional nonlinear dynamic systems, while the third chapter presents two-dimensional variants of such systems. By dealing with various forms of stability, chaos and many bifurcations, these chapters cover the most important tools for nonlinear dynamics for researchers and policy makers.
In chapter 4, Hommes discusses to which extent different forms of homogeneous expectations have an impact on the dynamics in the nonlinear Cobweb model. While in chapter 4, a closer outlook at models with homogenous agents and alternative forms of building expectations are considered, chapter 5 investigates the case of heterogeneous expectations. Based on Brock and Hommes (1997)), a framework for switching between rules to form expectations that are based on evolvement and reinforcement learning is introduced. Furthermore, this chapter focuses on interactions between rules of heterogeneous expectations as well as the macro outcome resulting from such interactions. Chapter 6 takes up on the previously presented ideas and develops a financial market application with heterogeneous and switching expectations where prices and beliefs co-evolve over time, and terms it adaptive belief system. Chapter 7 discusses the empirical validation of such a type of models, by comparing it to real financial time series.
The final chapter focuses on the empirical validation of the expectation hypothesis with laboratory experimental data. Moreover, it discusses whether models, which contain switching heterogeneous expectations, are consistent with the data gathered in experiments. In particular, some learning-to-forecast experiments are discussed. At the individual (micro) level, human subjects are in charge of forecasting prices (e.g., assets). At the aggregate (macro) level, the market price is influenced by individual expectations.
I think that JASSS readers, particularly those who are interested in adaptive and heterogeneous expectations in complex economic systems, will benefit from reading this book. It provides an up to date overview of all the most relevant topics that revolve around nonlinear dynamic systems and contributes to the understanding of how heterogeneous and switching expectations lead to dynamic systems and so to economic fluctuations. The heterogeneous expectations model is of paramount relevance as it can be easily validated against experimental laboratory data on the micro as well as on the macro level. In my opinion, this is the most important contribution of this book. However, in general, it pushes the reader towards the challenge of a more general theory of heterogeneous expectations.
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