In this study, Don Ross explores the relationship of economics to other branches of behavioral science, asking, in the course of his analysis, under what interpretation economics is a sound empirical science. The book explores the relationships between economic theory and the theoretical foundations of related disciplines that are relevant to the day-to-day work of economics -- the cognitive and behavioral sciences. It asks whether the increasingly sophisticated techniques of microeconomic analysis have revealed any deep empirical regularities -- whether technical (...) improvement represents improvement in any other sense. Casting Daniel Dennett and Kenneth Binmore as its intellectual heroes, the book proposes a comprehensive model of economic theory that, Ross argues, does not supplant, but recovers the core neoclassical insights, and counters the caricaturish conception of neoclassicism so derided by advocates of behavioral or evolutionary economics. Because he approaches his topic from the viewpoint of the philosophy of science, Ross devotes one chapter to the philosophical theory and terminology on which his argument depends and another to related philosophical issues. Two chapters provide the theoretical background in economics, one covering developments in neoclassical microeconomics and the other treating behavioral and experimental economics and evolutionary game theory. The three chapters at the heart of the argument then apply theses from the philosophy of cognitive science to foundational problems for economic theory. In these chapters, economists will find a genuinely new way of thinking about the implications of cognitive science for economics, and cognitive scientists will find in economic behavior, a new testing site for the explanations of cognitive science. (shrink)

Latour is a world famous and widely published French sociologist who has written with great eloquence and perception about the relationship between people, science, and technology. He is also closely associated with the school of thought known as Actor Network Theory. In this book he sets out for the first time in one place his own ideas about Actor Network Theory and its relevance to management and organization theory.

There is not, of course, a one-to-one relation between policy conclusions and the conclusions of positive economics; if there were, there would be no ...

Although Considered By A Few Critics That The Sentence Structures Of The Book Are Quite Incomprehensible And Almost Unbearable To Read, The Book Is An Essential ...

For this second edition, the editors have returned to Austin's original lecture notes, amending the printed text where it seemed necessary.

Things and Their Place in Theories Our talk of external things, our very notion of things, is just a conceptual apparatus that helps us to foresee and ...

The foundation for a system of morals, this 1749 work is a landmark of moral and political thought. Its highly original theories of conscience, moral judgment, and virtue offer a reconstruction of the Enlightenment concept of social science, embracing both political economy and theories of law and government.

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)

First published in 1986. Routledge is an imprint of Taylor & Francis, an informa company.

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)

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)

This paper considers in detail the ontological and normative presuppositions of the state-contingent approach to pricing commodities first introduced by Arrow in his model of general equilibrium under uncertainty, which became a milestone in the theory of finance. By contextualizing Arrow’s fundamental contribution and subsequent developments in finance, it demonstrates how this new conceptual framework implied certain technologies—both intellectual and financial. In showing how theoretical thinking about finance was underlying institutional developments in finance, this paper complements the familiar narrative of (...) the performativity of economics. (shrink)

This paper intends to bring Austinian themes into methodological discussion about models. Using Austinian conceptual vocabulary, I argue that models perform actions in and outside of the academic field. This multiplicity of fields induces a variety of felicity conditions and types of performed actions. If for example, an inference from a model is judged according to some epistemological criteria in the scientific field, the representation of the world which the model carries will not be judged by the same criteria outside (...) the scientific field. A model can be considered as a standard in a strict scientific framework, while not being used as part of public policies, or vice versa. However, we focus on the dynamics between different fields. (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)

While in medicine, comparison of the data supplied by a clinical syndrome with the data supplied by the biological system is used to arrive at the most accurate diagnosis, the same cannot be said of financial economics: the accumulation of statistical results that contradict the Brownian hypothesis used in risk modelling, combined with serious empirical problems in the practical implementation of the Black-Scholes-Merton model, the benchmark theory of mathematical finance founded on the Brownian hypothesis, has failed to change the Brownian (...) representation, which has endured for more than fifty years despite the extent of its invalidation by experience. Without any statistical foundations, one mathematical representation has become the established approach, acting in the minds of practitioners as a “prenotion” in the sense the word is used by Durkheim, i.e. a “schematic, summary representation” which has produced a kind of spontaneous epistemology. The question arises of the persistence of this mathematical representation, which has been the basis for every financial risk modelling approach: how can its long life be explained? How was this spontaneous epistemology formed, and why did it prove to be so persistent? To address this question and offer an answer, I will test the various dynamics of scientific knowledge used with reference to financial modelling. All these dynamics are specific ways of describing the relationship between knowledge of a phenomenon and the phenomenon itself. Observing that it is impossible for the positivist approach to solve the financial puzzle, I turn to the three principal postpositivist dynamics, developed by Kuhn, Lakatos and Quine. I shall try to make to speak these representations of science for financial research, in order to reflect on the dominance of the Brownian representation in finance. We shall see that none of the epistemologies examined can explain why the Brownian representation continues to be used in mathematical finance research. I shall then propose an alternative hypothesis, concerning a significant pervading mental model that has irrigated both academics and practitioners in the financial sector: the “principle of continuity” introduced into economics by Marshall in. I consider that this principle of continuity has become a “persistent idea” in the form of a viral approach to representations, and I give this persistent idea the metaphorical name of the “Brownian virus”. Then, to explain the spread of this Brownian virus through the financial sector, the contamination of financial practices by this mental representation founded on the principle of continuity, I introduce the concept of the “financial Logos”, a discourse that structures practices and organisations, calculations, prudential regulations and accounting standards, leading to a general financialisation of society from the 1980s onwards. (shrink)

I examine the role that mathematics plays in understanding and modelling finance, especially stock markets, and how philosophy affects it. To this end, I explore how mathematics penetrates finance via physics, constructing a ‘financial physics’, and I outline the philosophical backgrounds of this process, in particular the ‘philosophy of equilibrium’ and that of critical points or ‘out-of-equilibrium’. I discuss the main characteristics and a few weaknesses of these mathematizations of financial systems, notably econometrics and econophysics, and I compare the two (...) ways, top-down and bottom-up, of building mathematical approaches to finance. The top-down approach is the most used and the most conservative. I argue that it guarantees a mathematical account, but it is less effective than the more difficult bottom-up approach, which is more appropriate and which may end up without a mathematical account of financial phenomena. I then consider two important issues raised by a mathematical approach to finance, that is, the performative and the reversing side of mathematics, and an ethics of mathematics. In the first case I argue that mathematics not only can be a performative device, but it also enables ‘reversing’ dynamics, that is, a mathematical model may become not a representational tool, but a device of social engineering—a mathematical way of investigating what are the initial conditions and processes needed to obtain an intended result. In the second case I argue that this specific relation between mathematical modelling and prediction raises an ethical question in finance, namely, a responsible construction and use of the mathematical models provided by a financial physics. (shrink)

The paper examines connections between ontology and finance. The ontological debates concerning the role of finance are examined between two opposing schools of thought that can be labelled, very broadly, ‘instrumentalist’ and ‘realist’. These two schools of thought have had momentous repercussions in understanding what is a good society. Each school defines Nature in particular ways which can be explored using ontology and philosophical insight. Our theoretical investigation aims to accommodate Nature in community financial deliberations. A positive role for government (...) is advocated to finance environmental infrastructure initiatives. For example, precautionary strategies to address climate change must be funded. New roles for finance and government are proposed to align human relationships with Nature. Environmental precautionary principles must be developed in conjunction with finance theory to maintain decent standards of living for all. Reliance on impersonal market forces will not be enough to save the planet given the power of some over the many in the neoliberal arena. (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)

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)

The view from inside improves our understanding on market failure and regulation failure in financial market. The EMH fails to understand the causes of financial bubbles and crashes. Behavioral finance introduces insight from psychology. The heuristic and biases approach studied behavioral asymmetry in static environment that leads to market irrationality and information distortion. The fast and frugal thinking in decision-making further explore more complex situation under changing environment. They argue that soft-paternalistic regulation is needed under information overload. The most critical (...) issue is information uncertainty and complexity. Lacking information in frequency domain is the main barrier in managing business cycles. Data form inside reveals current limitations of financial data mainly in the short-term price changes. Microstructure studies show that pricing process is shaped by trading rules. Quantitative analysis reveals severe instability in high frequency trading and derivative market. Feasible regulation should aim to encourage new technology and sustainable growth, rather than protect obsolete technology and short-term speculation. The most fundamental challenge to sustainable economic order is the excessive size of the derivative markets that crowding out investment in real economy. This is a more severe issue than the climate change. (shrink)

We discuss in this paper the scope of abduction in Economics. The literature on this type of inference shows that it can be interpreted in different ways, according to the role and nature of its outcome. We present a formal model that allows to capture these various meanings in different economic contexts.