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Department of Management, Hamburg University of Technology
In the following I will take the perspective of a typical JASSS reader, which is having an interest and a background in social simulation. What does the book have to offer to such a reader? In my opinion, the book offers at least two general insights. First, it provides a good introduction to non-mainstream microeconomics and gives a useful overview of different streams of critical thinking in economics. The reader will find this material particularly in the first six chapters and the last chapter. Chapter 1 provides an overview of the general perspective of the book and some of its core concepts such as direct interdependence of economic agents, different forms of uncertainty, bounded rationality, path dependence and non-ergodicity in processes of change, social rules as well as institutions. Chapters 2-3 are strongly based on game theory. Game theory is introduced as a tool to describe problem structures agents face in their interactions with other agents, while institutions are characterized as solutions to coordination and dilemma problems. I personally appreciate the middle position taken in the book, which emphasizes that the assumption of rationality in game theory is useful for highlighting the structure of interaction problems, while reminding readers of its descriptive inaccuracy for many situations. Chapters 4-6 cover mainstream and non-mainstream models of markets. This includes standard models (e.g., oligopoly models, General Equilibrium Theory), their critiques (e.g., the Mirowski critique) and non-mainstream approaches (e.g., heterogenization and monopolies, Classical Theory of Prices). The latter are introduced after the mainstream approaches and their shortcomings are presented. Hence, the reader is made aware of selected options in economic theorizing and not only presented one, "right way" as in some standard textbooks. Chapter 9 provides a synthesis of the book including a comparison of complexity economics and neoclassical economics and a discussion of complex systems dynamics.
Second, the book links simulation with economic modelling. The authors emphasize the complex nature of economic systems and introduce against this backdrop simulation as “a method to acquire data about the behavior of highly complex systems” (p. 143). Relevant material in this respect can be found especially in Chapters 7-8. Simulation as a method is introduced in Chapter 7. Here, an economist’s perspective of the method as well as its advantages and disadvantages is given. Although I get the impression the authors are quite fond of using the method of simulation to address the problems they describe, they also include statements such as "simulation is not an exact method in a formal-analytical sense, as there is always the possibility that the results do not or only partly match the true behavior of the system under investigation. Therefore, simulation should only be employed if other scientific techniques are not available" (p. 143).
In my opinion, this is either a general problem any model faces, that is, it fails to address relevant aspects of the problem investigated. Or, if the authors by this mean “that simulation does not attempt to investigate any possible state, let alone the possible relations between states of a system” (p. 143), then it would have been more beneficial if the authors would have discussed methods reported in the design of experiments (DOE) literature and their applications to the analysis of simulation model behavior (Lorscheid, Heine and Meyer 2012). DOE techniques can significantly contribute to handle this and other methodological "disadvantages" the book mentions, such as the challenges of understanding and interpreting simulation results or choosing parameter scales. Chapter 8 presents a selection of core models of complexity microeconomics. Here, the reader finds models on the emergence of institutions and cooperation, segregation, increasing returns and technological lock-in, search within fitness landscapes, small-world networks and finally a qualitative model on institutional change.
Apart from the last model by Bush (1987), the typical JASSS reader will probably be familiar with the models described here, as most of these belong to the core literature JASSS articles are based on. At the same time, it would have been desirable to have been shown where more recent literature can be found. This could have included references to JASSS or other journals publishing simulation applications in economics. Again, it seems that JASSS has a stronger impact on computer science, physics and ecology than the social sciences and economics (e.g., Squazzoni and Casnici 2013). I personally also miss a deeper discussion on the validation of simulation models. With respect to economics I see, for instance, potential links to experimental economics, stylized facts or pattern-oriented modeling (Grimm et al 2005).
Overall, I would recommend the book to JASSS readers who are interested in getting an overview of non-mainstream approaches to microeconomics and how they can be linked to simulation. The book is well-written and correctly labelled as intermediate, as it progresses quite fast on some topics. Among the book’s strengths are how it links to game theory and how it relates to standard neoclassical economics. With respect to the presentation of simulation as a method, one will not find something particularly new. Nevertheless, the strong bridge the book builds between microeconomic analyses and simulation as a method is an advisable path for future generations of economists.
GRIMM , V., REVILLA, E., BERGER, U., JELTSCH, F., MOOIJ, W. M., RAILSBACK, S. F., THULKE, H.-H., WEINER, J., WIEGAND, T. & DEANGELIS, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science, Vol. 310, No. 5750, pp. 987-991.
LORSCHEID , I., HEINE, B.-O. & MEYER, M. (2012). Opening the ‘black box’of simulations: increased transparency and effective communication through the systematic design of experiments. Computational and Mathematical Organization Theory, Vol. 18, No. 1, pp. 22-62.
SQUAZZONI, F. & CASNICI, N. (2013). Is social simulation a social science outstation? A bibliometric analysis of the impact of JASSS. Journal of Artificial Societies and Social Simulation, Vol. 16, No. 1, pp. 10, http://jasss.soc.surrey.ac.uk/16/1/10.html
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