N. Emrah Aydinonat

Teaching a compulsory, large-scale Philosophy of Economics (PoE) course to economics students presents distinct challenges. Instructors face a heterogeneous student body with varying levels of interest in the topics, diverse occupational goals and a limited philosophical background. Unlike elective courses, for which students self-select based on interest, a compulsory course entails motivating disengaged students and managing their expectations. We put forward the case for a student-oriented approach to teaching PoE, emphasising four key strategies: recognising students’ limited philosophical knowledge, demonstrating the relevance of PoE to their professional and personal lives, using real-world problems to engage them and avoiding the oversimplification of topics. We argue that PoE instruction should account for the distinct characteristics of economics students, moving beyond a supply-driven approach. Our suggestions aim to enhance student engagement and provide practical guidance for instructors navigating the challenges of teaching PoE at scale.

This article critically evaluates Itzhak Gilboa, Andrew Postlewaite, Larry Samuelson, and David Schmeidler’s account of economic models. First, it gives a selective overview of their argument, highlighting their emphasis on similarity and oversight of the role of idealizations in economics. Second, it proposes a sketch of an account of models as arguments and argumentative devices. This account not only sheds light on Gilboa et al.’s approach, including its shortcomings, but also identifies key challenges in model-based inference, suggesting a fresh perspective on the uses of models in economics for diverse objectives.

This article critically evaluates Itzhak Gilboa, Andrew Postlewaite, Larry Samuelson, and David Schmeidler’s account of economic models. First, it gives a selective overview of their argument, highlighting its emphasis on similarity and their oversight of the role of idealizations in economics. Second, it proposes a sketch of an account of models as arguments and argumentative devices. This account not only sheds light on Gilboa et al.’s approach, including its shortcomings, but also identifies key challenges in model-based inference, suggesting a fresh perspective on the uses of models in economics for diverse objectives.

Among the many functions of models, explanation is central to the functioning and aims of science. However, the discussions surrounding modeling and explanation in philosophy have largely remained separate from each other. This chapter seeks to bridge the gap by focusing on the puzzle of model-based explanation, asking how different philosophical accounts answer the following question: if idealizations and fictions introduce falsehoods into models, how can idealized and fictional models provide true explanations? The chapter provides a selective and critical overview of the available strategies for solving this puzzle, mainly focusing on idealized models and how they explain.

This paper discusses the epistemic import of highly abstract and simplified theoretical models using Thomas Schelling’s checkerboard model as an example. We argue that the epistemic contribution of theoretical models can be better understood in the context of a cluster of models relevant to the explanatory task at hand. The central claim of the paper is that theoretical models make better sense in the context of a menu of possible explanations. In order to justify this claim, we introduce a distinction between causal scenarios and causal mechanism schemes. These conceptual tools help us to articulate the basis for modelers’ intuitive confidence that their models make an important epistemic contribution. By focusing on the role of the menu of possible explanations in the evaluation of explanatory hypotheses, it is possible to understand how a causal mechanism scheme can improve our explanatory understanding even in cases where it does not describe the actual cause of a particular phenomenon.

In this Chapter, we address the challenge of explaining institutional change, asking whether the much-criticized rational choice perspective can contribute to the understanding of institutional change in political science. We discuss the methodological reasons why rational choice institutionalism (RCI) often assumes that institutional change is exogenous and discontinuous. We then identify and explore the possible pathways along which RCI can be extended to be more useful in understanding institutional change in political science. Finally, we reflect on what RCI theorizing would look like if it started to take endogenous change seriously: by giving up some of its simplifying assumptions, RCI can be a useful tool for analyzing institutional change, but choosing this path has consequences for the generality of the models in RCI as well as for the style of its theorizing.

We argue that the appraisal of models in social epistemology requires conceiving of them as argumentative devices, taking into account the argumentative context and adopting a family-of-models perspective. We draw up such an account and show how it makes it easier to see the value and limits of the use of models in social epistemology. To illustrate our points, we document and explicate the argumentative role of epistemic landscape models in social epistemology and highlight their limitations. We also claim that our account could be fruitfully used in appraising other models in philosophy and science.

There is a striking contrast between the significance of Harold Hotelling’s contribution to industrial economics and the fact that his location model was invalid, unrealistic and non-robust. It is difficult to make sense of the explanatory value of Hotelling’s model based on philosophical accounts that emphasize logical validity, representational adequacy, and robustness as determinants of explanatory value. However, these accounts are misleading because they overlook the context within which the explanatory value added of a model is apprehensible. We present Hotelling’s model in its historical context and show why it is an important and explanatory model despite its apparent deficiencies.

We compare Guala’s unified theory of institutions with that of Searle and Greif. We show that unification can be many things and it may be associated with diverse explanatory goals. We also highlight some of the important shortcomings of Guala’s account: it does not capture all social institutions, its ability to bridge social ontology and game theory is based on a problematic interpretation of the type-token distinction, and its ability to make social ontology useful for social sciences is hindered by Guala’s interpretation of social institution types as social kinds akin to natural kinds.

Best-selling books such as Freakonomics and The Undercover Economist have paved the way for the flourishing economics-made-fun genre. While books like these present economics as a strong and explanatory science, the ongoing economic crisis has exposed the shortcomings of economics to the general public. In the face of this crisis, many people, including well-known economists such as Paul Krugman, have started to express their doubts about whether economics is a success as a science. As well as academic papers, newspaper columns with a large audience have discussed the failure of economic to predict and explain ongoing trends. The emerging picture is somewhat confusing: economics-made-fun books present economics as a method of thinking that can successfully explain everyday and "freaky" phenomena. On the other hand, however, economics seems to fail in addressing and explaining the most pressing matters related to the field of economics itself. This book explores the confusion created by this contradictory picture of economics. Could a science that cannot answer its own core questions really be used to explain the logic of everyday life? This book was originally published as a special issue of the Journal of Economic Methodology.