Models are of central importance in many scientific contexts. The centrality of models such as inflationary models in cosmology, general-circulation models of the global climate, the double-helix model of DNA, evolutionary models in biology, agent-based models in the social sciences, and general-equilibrium models of markets in their respective domains is a case in point (the Other Internet Resources section at the end of this entry contains links to online resources that discuss these models). Scientists spend significant amounts of time building, (...) testing, comparing, and revising models, and much journal space is dedicated to interpreting and discussing the implications of models. In short, models are one of the principal instruments of modern science. (shrink)

The view from inside maintains that not only to study and understand, but also to profit from financial markets, it is necessary to get as much knowledge as possible about their internal ‘structure’ and machinery. This view maintains that in order to solve the problems posed by finance, or at least a large part of them, we need first of all a qualitative analysis. Rules, laws, institutions, regulators, the behavior and the psychology of traders and investors are the key elements (...) to the understanding of finance, and stock markets in particular. Accordingly, data and their mathematical analysis are not the crucial elements, since data are the output of a certain underlying structure of markets and their actors. The underlying structure is the ultimate object of the inquiry. This chapter examines how the view from inside raises, and deals with, critical issues such as markets failure, information disclosure, and regulation, the notion of data, performativity, and the study of micro-structures. (shrink)

Many scientific models lack an established representation relation to actual targets and instead refer to merely possible processes, background conditions, and results. This article shows how such models can be appraised. On the basis of the discussion of how-possibly explanations, five types of learning opportunities are distinguished. For each of these types, an example—from economics, biology, psychology, and sociology—is discussed. Contexts and purposes are identified in which the use of a model offers a genuine opportunity to learn. These learning opportunities (...) offer novel justifications for modeling practices that fall between the cracks of standard representationalist appraisals of models. (shrink)

This book explores new findings on the long-neglected topic of theory construction and discovery, and challenges the orthodox, current division of scientific development into discrete stages: the stage of generation of new hypotheses; the stage of collection of relevant data; the stage of justification of possible theories; and the final stage of selection from among equally confirmed theories. The chapters, written by leading researchers, offer an interdisciplinary perspective on various aspects of the processes by which theories rationally should, and descriptively (...) are, built. They address issues such as the role of problem-solving and heuristic reasoning in theory-building; how inferences and models shape the pursuit of scientific knowledge; the relation between problem-solving and scientific discovery; the relative values of the syntactic, semantic, and pragmatic view of theories in understanding theory construction; and the relation between ampliative inferences, heuristic reasoning, and models as a means for building new theories and knowledge. Through detailed arguments and examinations, the volume collectively challenges the orthodox view’s main tenets by characterizing the ways in which the different “stages” are logically, temporally, and psychologically intertwined. As a group, the chapters provide several attempts to answer long-standing questions about the possibility of a unified conceptual framework for building theories and formulating hypotheses. (shrink)

The book offers an interdisciplinary perspective on finance, with a special focus on stock markets. It presents new methodologies for analyzing stock markets’ behavior and discusses theories and methods of finance from different angles, such as the mathematical, physical and philosophical ones. The book, which aims at philosophers and economists alike, represents a rare yet important attempt to unify the externalist with the internalist conceptions of finance.

Economists do more than merely describe an external economic world. They shape it in the image of their theories and models. This idea, following the philosophy of language, puts forward that economic theories are performative, and not only descriptive. This idea has become a powerful critique of the scientificity of economics since it removes the idea of an external world against which our description could be evaluated as truth. If any theory can become true, there are no true theories per (...) se because there is no such thing as a pre-existing economy to describe. Is such a relativist stance a fatality? This is the question at stake in this book. Furthermore, the author asks if any theory is able to ¿perform¿ the social reality, or are there actually some limits to performativity? For philosophers, a performative statement is a statement that cannot fail to mean something, but can fail to do what it calls for. The state of the world may or may not be changed; the performative statement may be happy or unhappy. In economic terms, this can be interpreted as: some theories change the world while some do not. This book argues that this possibility of failure, a perspective previously missing from discussions on the subject, should be at the heart of any definition of failure. Taking on the question of why some theories change the world while others do not, this volume will be of interest to those studying advances courses on the philosophy of economics as well as those studying and researching in the areas of the philosophy of sciences and sociology of science and economics. (shrink)

Economic methodologists most often study the relations between models and reality while focusing on the issues of the model's epistemic relevance in terms of its relation to the ‘real world’ and representing the real world in a model. We complement the discussion by bringing the model's constructive mechanisms or self-implementing technologies in play. By this, we mean the elements of the economic model that are aimed at ‘implementing’ it by envisaging the ways to change the reality in order to bring (...) it more in line with the model. We are thus concerned mainly not with the ways to change the model to ‘fit’ the reality, but rather with the model's own armature that is supposed to transform the world along theoretical lines. The case we study is Arrow–Debreu–McKenzie general equilibrium model. In particular, we show the following: gradient methods and stability could be regarded as constructive mechanisms of general equilibrium modeling in the context of market socialism debates; the obsession of general eq.. (shrink)

This volume examines the limitations of mathematical logic and proposes a new approach to logic intended to overcome them. To this end, the book compares mathematical logic with earlier views of logic, both in the ancient and in the modern age, including those of Plato, Aristotle, Bacon, Descartes, Leibniz, and Kant. From the comparison it is apparent that a basic limitation of mathematical logic is that it narrows down the scope of logic confining it to the study of deduction, without (...) providing tools for discovering anything new. As a result, mathematical logic has had little impact on scientific practice. Therefore, this volume proposes a view of logic according to which logic is intended, first of all, to provide rules of discovery, that is, non-deductive rules for finding hypotheses to solve problems. This is essential if logic is to play any relevant role in mathematics, science and even philosophy. To comply with this view of logic, this volume formulates several rules of discovery, such as induction, analogy, generalization, specialization, metaphor, metonymy, definition, and diagrams. A logic based on such rules is basically a logic of discovery, and involves a new view of the relation of logic to evolution, language, reason, method and knowledge, particularly mathematical knowledge. It also involves a new view of the relation of philosophy to knowledge. This book puts forward such new views, trying to open again many doors that the founding fathers of mathematical logic had closed historically. (shrink)

In this topical section, we highlight the next step of research on modeling aiming to contribute to the emerging literature that radically refrains from approaching modeling as a scientific endeavor. Modeling surpasses “doing science” because it is frequently incorporated into decision-making processes in politics and management, i.e., areas which are not solely epistemically oriented. We do not refer to the production of models in academia for abstract or imaginary applications in practical fields, but instead highlight the real entwinement of science (...) and policy and the real erosion of their boundaries. Models in decision making – due to their strong entwinement with policy and management – are utilized differently than models in science; they are employed for different purposes and with different constraints. We claim that “being a part of decision-making” implies that models are elements of a very particular situation, in which knowledge about the present and the future is limited but dependence of decisions on the future is distinct. Emphasis on the future indicates that decisions are made about actions that have severe and lasting consequences. In these specific situations, models enable not only the acquisition of knowledge (the primary goal of science) but also enable deciding upon actions that change the course of events. As a result, there are specific ways to construct effective models and justify their results. Although some studies have explored this topic, our understanding of how models contribute to decision making outside of science remains fragmentary. This topical section aims to fill this gap in research and formulate an agenda for additional and more systematic investigations in the field. (shrink)

Didier Sornette boldly applies his varied experience in many areas to propose a simple, powerful, and general theory of how, why, and when stock markets crash.

Around the globe, economists affect markets by saying what markets are doing, what they should do, and what they will do. Increasingly, experimental economists are even designing real-world markets. But, despite these facts, economists are still largely thought of as scientists who merely observe markets from the outside, like astronomers look at the stars. Do Economists Make Markets? boldly challenges this view. It is the first book dedicated to the controversial question of whether economics is performative--of whether, in some cases, (...) economics actually produces the phenomena it analyzes.The book's case studies--including financial derivatives markets, telecommunications-frequency auctions, and individual transferable quotas in fisheries--give substance to the notion of the performativity of economics in an accessible, nontechnical way. Some chapters defend the notion; others attack it vigorously. The book ends with an extended chapter in which Michel Callon, the idea's main formulator, reflects upon the debate and asks what it means to say economics is performative.The book's insights and strong claims about the ways economics is entangled with the markets it studies should interest--and provoke--economic sociologists, economists, and other social scientists.In addition to the editors and Callon, the contributors include Marie-France Garcia-Parpet, Francesco Guala, Emmanuel Didier, Philip Mirowski, Edward Nik-Khah, Petter Holm, Vincent-Antonin Lépinay, and Timothy Mitchell. (shrink)

Many scientific models are non-representational in that they refer to merely possible processes, background conditions and results. The paper shows how such non-representational models can be appraised, beyond the weak role that they might play as heuristic tools. Using conceptual distinctions from the discussion of how-possibly explanations, six types of models are distinguished by their modal qualities of their background conditions, model processes and model results. For each of these types, an actual model example – drawn from economics, biology, psychology (...) or sociology – is discussed. For each case, contexts and purposes are identified in which the use of such a model offers a genuine opportunity to learn – i.e. justifies changing one’s confidence in a hypothesis about the world. These cases then offer novel justifications for modelling practices that fall between the cracks of standard representational accounts of models. (shrink)