This book is devoted to a thorough analysis of the role that models play in the practise of physical theory. The authors, a mathematical physicist and a philosopher of science, appeal to the logicians’ notion of model theory as well as to the concepts of physicists.

This is the classic work upon which modern-day game theory is based. What began as a modest proposal that a mathematician and an economist write a short paper together blossomed, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry (...) it yielded--game theory--has since been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations. And it is today established throughout both the social sciences and a wide range of other sciences. (shrink)

The ArgumentIn its reconstruction of scientific practice, philosophy of science has traditionally placed scientific theories in a central role, and has reduced the problem of mediating between theories and the world to formal considerations. Many applications of scientific theories, however, involve complex mathematical models whose constitutive equations are analytically unsolvable. The study of these applications often consists in developing representations of the underlying physics on a computer, and using the techniques of computer simulation in order to learn about the behavior (...) of these systems. In many instances, these computer simulations are not simple number-crunching techniques. They involve a complex chain of inferences that serve to transform theoretical structures into specific concrete knowledge of physical systems. In this paper I argue that this process of transformation has its own epistemology. I also argue that this kind of epistemology is unfamiliar to most philosophy of science, which has traditionally concerned itself with the justification of theories, not with their application. Finally, I urge that the nature of this epistemology suggests that the end results of some simulations do not bear a simple, straightforward relation to the theories from which they stem. (shrink)

The literature of economic theory, like that of philosophy, abounds in prefaces and prolegomena. Methodology and analysis of concepts take an important place in a science which has not found the sure path of development. But there is no sure path for methodology either. The selfconscious methodology of social science has been largely a borrowing from that of physical science, where procedures have developed to a stage of considerable maturity. But the analogy falls down where guidance is most needed, at (...) the points where social science is most likely to develop new concepts and new types of structure. Philosophers have not been lacking, indeed, to belittle the entire enterprise, and to deny the possibility of anything that could strictly be called social science. (shrink)

This paper argues that the much discussed issue between "scientific realism" and "instrumentalism" has not been clearly drawn. Particular attention is paid to the claim that only realism can "explain" the success of scientific theories and---more especially---the progressively increasing success of such theories in a coherent line of inquiry. This claim is used to attempt to reach a clearer conception of the content of the realist thesis that underlies it; but, it is here contended, that attempt fails, and the claim (...) itself hangs in the air. A series of increasingly sophisticated versions of the "instrumentalist" thesis is considered, and both these and the contentions of realism are placed in relation both to particular examples of scientific development and positions historically maintained by philosophers and by scientists. The author’s conclusion is that, when the positions are assessed against the background of the actual history of science, each of the contrary doctrines, interpreted with excessive simplicity, is inadequate as a theory of the dialectic of scientific development; each, so interpreted, has contributed in important instances to actual damage to investigations by great scientists ; whereas in both the theoretical statements and the actual practice of the most sophisticated philosophers/scientists, important aspects of realism and instrumentalism are present together in such a way that the alleged contradiction between them vanishes. (shrink)

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models is that it is an unsettled question what the epistemic goal of toy modeling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this paper is to (...) precisely articulate and to defend this claim. In particular, we will distinguish between autonomous and embedded toy models, and, then, argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. (shrink)

It is proposed that we use the term “approximation” for inexact description of a target system and “idealization” for another system whose properties also provide an inexact description of the target system. Since systems generated by a limiting process can often have quite unexpected, even inconsistent properties, familiar limit systems used in statistical physics can fail to provide idealizations, but are merely approximations. A dominance argument suggests that the limiting idealizations of statistical physics should be demoted to approximations.

This book on the philosophy of science argues for an empiricism, opposed to the tradition of David Hume, in which singular rather than general causal claims are primary; causal laws express facts about singular causes whereas the general causal claims of science are ascriptions of capacities or causal powers, capacities to make things happen. Taking science as measurement, Cartwright argues that capacities are necessary for science and that these can be measured, provided suitable conditions are met. There are case studies (...) from both econometrics and quantum mechanics. (shrink)

It is usually supposed that the central limit theorem explains why various quantities we find in nature are approximately normally distributed—people's heights, examination grades, snowflake sizes, and so on. This sort of explanation is found in many textbooks across the sciences, particularly in biology, economics, and sociology. Contrary to this received wisdom, I argue that in many cases we are not justified in claiming that the central limit theorem explains why a particular quantity is normally distributed, and that in some (...) cases, we are actually wrong. 1 Introduction2 Normal Distributions and the Central Limit Theorem2.1 Normal distributions2.2 The central limit theorem2.3 Terminology3 Explaining Normality3.1 Loaves of bread3.2 Varying variances and probability densities3.3 Tensile strengths and problems with summation3.4 Products of factors and log-normal distributions3.5 Transforming factors and sub-factors3.6 Transformations of quantities3.7 Quantitative genetics3.8 Inference to the best explanation4 Maximum Entropy Explanations5 Conclusion. (shrink)

Some have argued that chance and determinism are compatible in order to account for the objectivity of probabilities in theories that are compatible with determinism, like Classical Statistical Mechanics (CSM) and Evolutionary Theory (ET). Contrarily, some have argued that chance and determinism are incompatible, and so such probabilities are subjective. In this paper, I argue that both of these positions are unsatisfactory. I argue that the probabilities of theories like CSM and ET are not chances, but also that they are (...) not subjective probabilities either. Rather, they are a third type of probability, which I call counterfactual probability. The main distinguishing feature of counterfactual-probability is the role it plays in conveying important counterfactual information in explanations. This distinguishes counterfactual probability from chance as a second concept of objective probability. (shrink)

More Heat Than Light is a history of how physics has drawn some inspiration from economics and also how economics has sought to emulate physics, especially with regard to the theory of value. It traces the development of the energy concept in Western physics and its subsequent effect upon the invention and promulgation of neoclassical economics. Any discussion of the standing of economics as a science must include the historical symbiosis between the two disciplines. Starting with the philosopher Emile Meyerson's (...) discussion of the relationship between notions of invariance and causality in the history of science, the book surveys the history of conservation principles in the Western discussion of motion. Recourse to the metaphors of the economy are frequent in physics, and the concepts of value, motion, and body reinforced each other throughout the development of both disciplines, especially with regard to practices of mathematical formalisation. However, in economics subsequent misuse of conservation principles led to serious blunders in the mathematical formalisation of economic theory. The book attempts to provide the reader with sufficient background in the history of physics in order to appreciate its theses. The discussion is technically detailed and complex, and familiarity with calculus is required. (shrink)

Large changes of financial market prices without exogenous causes deviate significantly from the Gaussian behavior of random variables. This indicates that financial markets should be treated as complex systems, for which nonlinear interactions of its subunits/agents are crucial. I focus on how the complex systems perspective impacts the notion of explanations in economics. The mechanistic model seems to fit the bill, but problems surface on closer scrutiny. One characteristic of complex systems is that their behavior is surprisingly independent from microscopic (...) details. Thus, mechanistic explanations in the microreductionist manner seem unavailable. Despite these conflicts, I defend a modified structural mechanistic approach. (shrink)

Earman and Roberts claim that there is neither a persuasive account of the truth-conditions of ceteris paribus laws, nor of how such laws can be confirmed or disconfirmed. I will give an account of the truth conditions of ceteris paribus laws in physics in terms of dispositions. It will meet the objections standardly raised against such an account. Furthermore I will elucidate how ceteris paribus laws can be tested in physics. The essential point is that physics provides methodologies for dealing (...) with disturbing factors. For this reason disturbing factors need not be listed explicitly in law-statements. In virtue of the methodologies it is possible to test how systems would behave if the disturbing factors were absent. I will argue that this suffices to establish the tenability of the dispositional account of ceteris paribus laws. (shrink)

It is argued that one can learn from minimal economic models. Minimal models are models that are not similar to the real world, do not resemble some of its features, and do not adhere to accepted regularities. One learns from a model if constructing and analysing the model affects one’s confidence in hypotheses about the world. Economic models, I argue, are often assessed for their credibility. If a model is judged credible, it is considered to be a relevant possibility. Considering (...) such relevant possibilities may affect one’s confidence in necessity or impossibility hypotheses. Thus, one can learn from minimal economic models. (shrink)

Much of the literature on "ceteris paribus" laws is based on a misguided egalitarianism about the sciences. For example, it is commonly held that the special sciences are riddled with ceteris paribus laws; from this many commentators conclude that if the special sciences are not to be accorded a second class status, it must be ceteris paribus all the way down to fundamental physics. We argue that the (purported) laws of fundamental physics are not hedged by ceteris paribus clauses and (...) provisos. Furthermore, we show that not only is there no persuasive analysis of the truth conditions for ceteris paribus laws, there is not even an acceptable account of how they are to be saved from triviality or how they are to be melded with standard scientific methodology. Our way out of this unsatisfactory situation to reject the widespread notion that the achievements and the scientific status of the special sciences must be understood in terms of ceteris paribus laws. (shrink)

What can we learn from “minimal” economic models? I argue that learning from such models is not limited to conceptual explorations—which show how something could be the case—but may extend to explanations of real economic phenomena—which show how something is the case. A model may be minimal qua certain world-linking properties, and yet “not-so-minimal” qua learning, provided it is externally valid. This, in turn, depends on using the right principles for model building and not necessarily “isolating” principles. My argument is (...) buttressed by a case study from computational economics, namely, two agent-based models of asset pricing. (shrink)

Ever since David Hume, empiricists have barred powers and capacities from nature. In this book Cartwright argues that capacities are essential in our scientific world, and, contrary to empiricist orthodoxy, that they can meet sufficiently strict demands for testability. Econometrics is one discipline where probabilities are used to measure causal capacities, and the technology of modern physics provides several examples of testing capacities (such as lasers). Cartwright concludes by applying the lessons of the book about capacities and probabilities to the (...) explanation of the role of causality in quantum mechanics. (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

Approaches to explanation -- Causal and explanatory relevance -- The kairetic account of /D making -- The kairetic account of explanation -- Extending the kairetic account -- Event explanation and causal claims -- Regularity explanation -- Abstraction in regularity explanation -- Approaches to probabilistic explanation -- Kairetic explanation of frequencies -- Kairetic explanation of single outcomes -- Looking outward -- Looking inward.

'Microphysicalism', the view that whole objects behave the way they do in virtue of the behaviour of their constituent parts, is an influential contemporary view with a long philosophical and scientific heritage. In _What's Wrong With Microphysicalism?_ Andreas Hüttemann offers a fresh challenge to this view. Hüttemann agrees with the microphysicalists that we can explain compound systems by explaining their parts, but claims that this does not entail a fundamentalism that gives hegemony to the micro-level. At most, it shows that (...) there is a relationship of determination between parts and wholes, but there is no justification for taking this relationship to be asymmetrical rather than one of mutual dependence. Hüttemann argues that if this is the case, then microphysicalists have no right to claim that the micro-level is the ultimate agent: neither the parts nor the whole have 'ontological priority'. Hüttemann advocates a pragmatic pluralism, allowing for different ways to describe nature. _What's Wrong With Microphysicalism?_ is a convincing and original contribution to central issues in contemporary philosophy of mind, philosophy of science and metaphysics. (shrink)

The paper reviews statistical models for money, wealth, and income distributions developed in the econophysics literature since the late 1990s. By analogy with the Boltzmann-Gibbs distribution of energy in physics, it is shown that the probability distribution of money is exponential for certain classes of models with interacting economic agents. Alternative scenarios are also reviewed. Data analysis of the empirical distributions of wealth and income reveals a two-class distribution. The majority of the population belongs to the lower class, characterized by (...) the exponential (“thermal”) distribution, whereas a small fraction of the population in the upper class is characterized by the power-law (“superthermal”) distribution. The lower part is very stable, stationary in time, whereas the upper part is highly dynamical and out of equilibrium. (shrink)

Financial theory is in trouble. Market crashes and high volatility are only too familiar to everyone, although the standard theories predict that they hardly ever occur. According to the well-known and (partly due to its simplicity) still widely used random-walk model, the probabilities for price changes of, say, stocks should result in a Gaussian distribution. However, experience tells us that large changes occur far more often than ‘allowed’ by a Gaussian distribution. New models are needed which lead to realistic probability (...) distributions. ‘Econophysicists’ are particularly active in this field by constructing microscopic models of financial markets on the basis of various ideas and tools from physics. But in which sense do these models contribute scientific explanations? In this paper I will investigate what and how one exemplary econophysics model explains. (shrink)

This paper explores various functions of idealizations in quantum field theory. To this end it is important to first distinguish between different kinds of theories and models of or inspired by quantum field theory. Idealizations have pragmatic and cognitive functions. Analyzing a case-study from hadron physics, I demonstrate the virtues of studying highly idealized models for exploring the features of theories with an extremely rich structure such as quantum field theory and for gaining some understanding of the physical processes in (...) the system under consideration. (shrink)