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Any researcher learning a new field of study will naturally have three questions: what, why and how. I would especially recommend Chapters 1 and 2 as guides explaining what makes agent-based macro-modelling unique and why it gives a promise of significant new insights over mainstream approaches. Additionally, but not less importantly, the reader gets a clear exposition of agent-based economics research agenda and trends. This means that the book gives a guide what new contributions would be of interest for the community. Such an understanding is invaluable, especially for young researchers.
Despite its potential attractiveness, agent-based approach to macroeconomics has been struggling for many years to be considered as a fully valid alternative to mainstream Dynamic Stochastic General Equilibrium (DSGE) approach, especially after agent heterogeneity was introduced to the latter framework. One of the major challenges is the lack of a standard reference model employing agent-based methodology. This problem is stressed by several recent reviews in the field (Fagiolo and Roventini (2017), Koloch et al. (2017)). I believe that this book can provide a major step towards this goal. In particular Chapter 2 discusses in detail the "Modellaccio" approach, introduced by Caiani et al. (2016), that has a potential to become such a benchmark.
A strong point of the book is that it takes a hands-on approach. Most of the chapters present theoretical concepts as well as concrete models applying them. This way of presentation is of key value for someone wanting to start developing own agent-based economics models. However, there is one significant downside of the book in this area. It has become a standard requirement that in scientific works presenting simulation models the links to a reference implementation (source code) and experiment results (raw data obtained from the simulation of the model) are provided. This is a crucial requirement for reproducible research in general, but is especially important in an Introduction type of text, where a student would like not only to read about the model but also to actually run it.
Also of importance for a potential reader is to know that Introduction to Agent-Based Economics is a collection not a typical textbook. This has benefits – each chapter can be read independently from others and one can focus on the topic of his interest. However, this also means that there is no single thread of thought the book follows. For instance, Chapter 9 discusses copula modelling which is loosely related with the rest of the book. On the other hand, this gave the editors a natural opportunity to include a discussion of specific, but very important, topics like: expectation modelling, model validation, simulation experiment design or metamodeling in separate chapters, which I appreciated a lot. Additionally, it should be highlighted that the collected texts focus on macro-economy, so personally I would find a title Introduction to Agent-Based Macroeconomics more precise.
In summary, I recommend this book to anybody who wants to investigate how the economy works. It will quickly and comprehensively guide the reader in the state of the art of agent-based approach applied to macroeconomics. The collected texts show where mainstream DSGE models have limitations and why an agent-based approach shows a promise to make amends. It will also equip a scholar with a proper understanding of a toolbox required to successfully develop simulation models like model calibration, validation or experiment design and analysis.
FAGIOLO G. and Roventini A. (2017). Macroeconomic Policy in a DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead, Journal of Artificial Societies and Social Simulation 20(1), 1 http://jasss.soc.surrey.ac.uk/20/1/1.html
KOLOCH G., Kamiński B., Żbikowski M., Antosiewicz M. 2017. Modelling heterogeneous economies – robustness vs. flexibility. Argumenta Oeconomica (in press)
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