Standardly, mental properties like beliefs, desires, fears, etc. are analysed as relations between the agent, to whom the predicate is ascribed, and a proposition, which is the intentional content of this property. According to this relational analysis, having a thought implies having its content present to the mind. This has wide-ranging philosophical implications, e.g. for the possibility of children and animals having intentional mental properties, or for the problem of knowing one’s own thoughts. Further, according to the relational analysis, the (...) causal efficacy of mental properties must be in virtue of their content. This implies that folk-psychological explanations acquire a special status, for they employ mental properties as the explanans of behaviour. Mental properties can be conceived of as causally efficacious, and hence like standard scientific explanans, only if a satisfactory account is provided how they are causally efficacious in virtue of their semantic content. A successful account of this sort, I submit, does not exist as of yet; hence it seems, on the relational account, that folk psychological explanations are non-scientific, if they are explanations at all. (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)

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)

If citizens’ behavior threatens to harm others or seems not to be in their own interest, it is not uncommon for governments to attempt to change that behavior. Governmental policy makers can apply established tools from the governmental toolbox to this end. Alternatively, they can employ new tools that capitalize on the wealth of knowledge about human behavior and behavior change that has been accumulated in the behavioral sciences. Two contrasting approaches to behavior change are nudge policies and boost policies. (...) These policies rest on fundamentally different research programs on bounded rationality, namely, the heuristics and biases program and the simple heuristics program, respectively. This article examines the policy–theory coherence of each approach. To this end, it identifies the necessary assumptions underlying each policy and analyzes to what extent these assumptions are implied by the theoretical commitments of the respective research program. Two key results of this analysis are that the two policy approaches rest on diverging assumptions and that both suffer from disconnects with the respective theoretical program, but to different degrees: Nudging appears to be more adversely affected than boosting does. The article concludes with a discussion of the limits of the chosen evaluative dimension, policy–theory coherence, and reviews some other benchmarks on which policy programs can be assessed. (shrink)

:Proponents of behavioural policies seek to justify them as ‘evidence-based’. Yet they typically fail to show through which mechanisms these policies operate. This paper shows – at the hand of examples from economics and psychology – that without sufficient mechanistic evidence, one often cannot determine whether a given policy in its target environment will be effective, robust, persistent or welfare-improving. Because these properties are important for justification, policies that lack sufficient support from mechanistic evidence should not be called ‘evidence-based’.

Some scholars see interdisciplinarity as a special case of a broader unificationist program. They accept the unification of the sciences as a regulative ideal, and derive from this the normative justification of interdisciplinary research practices. The crucial link for this position is the notion of integration: integration increases the cohesion of concepts and practices, and more specifically of explanations, ontologies, methods and data. Interdisciplinary success then consists in the integration of fields or disciplines, and this constitutes success in the sense (...) that unification is epistemically desirable. In contrast to this account, I defend the thesis that successful interdisciplinary interaction does not necessarily imply the integration of these disciplines. I show this at the hand of two cases. In both the case of evolutionary game theory and the case of hyperbolic discounting, genuine interdisciplinary exchange took place. From both exchanges, the respective economic fields emerged substantially altered – it wasn’t just a juxtaposition of disciplines in which disciplinary identities remained unchanged. Yet in neither case did the disciplines integrate. Rather, they developed their own concepts and methods, their own explanations, own ontologies, and their own views of what proper data standards were. Furthermore, the fields that emerged from these exchanges were very successful, if measured at the hand of properties like explanatory success, increase of control, bibliometrics and grant yields. Thus, I argue, there are cases of interdisciplinary success without integration. (shrink)

Scientists regularly make possibility claims. While philosophers of science are well aware of the distinction between epistemic and objective notions of possibility, we believe that they often fail to apply this distinction in their analyses of scientific practices that employ modal concepts. We argue that heeding this distinction will help further progress in current debates in the philosophy of science, as it shows that the debaters talk about different things, rather than disagree on the same issue. We first discuss how (...) the two notions differ with respect to their epistemology and show that these differences are sometimes ignored in the philosophy of science. We then revisit four current philosophy of science debates about modelling, that are framed in modal terms, to showcase how the distinction significantly clarifies these debates and thereby and helps advance them. (shrink)

ABSTRACTIn his recent book, Rodrik [. Economics rules. Why economics works, when it fails, and how to tell the difference. Oxford University Press] proposes an account of model pluralism according to which multiple models of the same target are acceptable as long as one model is more useful for one purpose and another is more useful for another purpose. How, then, is the right model for the purpose selected? Rodrik roughly outlines a selection procedure, which we formalize to enhance understanding (...) of his account of model pluralism and to advance the critical discussion. (shrink)

This paper provides arguments to philosophers, scientists, administrators and students for why science students should be instructed in a mandatory, custom-designed, interdisciplinary course in the philosophy of science. The argument begins by diagnosing that most science students are taught only conventional methodology: a fixed set of methods whose justification is rarely addressed. It proceeds by identifying seven benefits that scientists incur from going beyond these conventions and from acquiring abilities to analyse and evaluate justifications of scientific methods. It concludes that (...) teaching science students these skills makes them better scientists. Based on this argument, the paper then analyses the standard philosophy of science curriculum, and in particular its adequacy for teaching science students. It is argued that the standard curriculum on the one hand lacks important analytic tools relevant for going beyond conventional methodology—especially with respect to non-epistemic normative aspects of scientific practice—while on the other hand contains many topics and tools that are not relevant for the instruction of science students. Consequently, the optimal way of training science students in the analysis and evaluation of scientific methods requires a revision of the standard curriculum. Finally, the paper addresses five common characteristics of students taking such a course, which often clash with typical teaching approaches in philosophy. Strategies how best to deal with these constraints are offered for each of these characteristics. (shrink)

Philosophers of science have recently taken care to highlight different modeling practices where scientific models primarily contribute modal information, in the form of for example possibility claims, how-possibly explanations, or counterfactual conditionals. While examples abound, comparatively little attention is being paid to the question of under what conditions, and in virtue of what, models can perform this epistemic function. In this paper, we firstly delineate modal modeling from other modeling practices, and secondly reviewattempts to spell out and explain the epistemic (...) success conditions of modal modeling. The aim is to more clearly expose the respective justificatory strategies of these accounts, and secondly, to identify lacunae where further work is needed. (shrink)

The five studies of this special section investigate the role of models and similar representational tools in interdisciplinarity. These studies were all written by philosophers of science, who focused on interdisciplinary episodes between disciplines and sub-disciplines ranging from physics, chemistry and biology to the computational sciences, sociology and economics. The reasons we present these divergent studies in a collective form are three. First, we want to establish model-exchange as a kind of interdisciplinary event. The five case studies, which are summarized (...) in Section 2 below, show the relevance of this kind. Arguing for the relative unity of these cases will, we hope, re-orient the current debate over interdisciplinarity so as to reflect more appropriately the importance of this kind. We discuss our view of the current state of the debate in Section 3. The evidence from these cases also helps us to develop a taxonomy of interdisciplinary model exchanges in Section 4da taxonomy, we would like to add, that might be useful for the discussion of interdisciplinary exchanges beyond the context of models and their transfer. The second reason for presenting these studies together is that they provide an important source of evidence for the philosophy of science. Over the last three decades, philosophy of science has increasingly differentiated into philosophies of various disciplines. This differentiation in our view has greatly increased our understanding of the scientific practices of the respective disciplines, including the epistemological and methodological standards and conventions on which these practices are based and by which they are evaluated. But it has also made it harder to compare these practices and standards across disciplines. The studies we present here are case studies of interdisciplinary exchange: they focus on the transfer, collaborative construction or parallel use of models and similar representational tools. They therefore provide a unique opportunity to investigate various disciplinary treatments of the same or at least similar representational tools. This allows the identification and comparison of different disciplinary practices and their underlying conventions as well as of the respective normative standards of their evaluation. By tracing the paths along which models travel between disciplines and research fields we can observe to which extent discipline-external practices associated with an adopted tool are retained or replaced by disciplineinternal practices. This generates invaluable information about both disciplinarity and interdisciplinarity. We develop this argument further in Section 5. The third reason for presenting these studies in collective form is that their philosophical analysis also has important normative implications for the notion of interdisciplinarity itself. Too often in the current (non-philosophical) discourse is interdisciplinarity cast as an exclusively integrative project: interdisciplinary exchange is often claimed to be successful only if the involved disciplines become mutually more integrated as a consequence of this process. In contrast to this, many of the cases presented here show that interdisciplinary exchange can be scientifically highly successful, even if at the end of the exchange disciplinary borders remain fully intact. Indeed, borders can be fruitfully crossed without any integration across these borders. Such considerations of divergence in scientific practices and tools offer arguments against a naïve plea for unitarian or non-pluralist versions of interdisciplinarity. Disciplinary divergences may have their justifications, and attempting exchanges that require the reduction of these divergences may consequently not be justified. We pursue this argument further in Section 6. (shrink)

Scientific methods are heuristic in nature. Heuristics are simplifying, incomplete, underdetermined and fallible problem-solving rules that can nevertheless serve certain goals in certain contexts better than truth-preserving algorithms. Because of their goal- and context-dependence, a framework is needed for systematic choosing between them. This is the domain of scientific methodology. Such a methodology, I argue, relies on a form of instrumental rationality. Three challenges to such an instrumentalist account are addressed. First, some authors have argued that the rational choice of (...) at least some methods, namely those supporting belief formation, is not goal-dependent. Second, some authors have observed that some method choices seem intuitively rational, even though relevant goals are lacking. Thirdly, some authors have argued that instrumental rationality itself depends on a goal-independent form of rationality. It is the heuristic nature of scientific methods that affords me the arguments against these challenges. This heuristic-instrumentalist account provides the means-ends analysis needed to evaluate heuristic method choice. The paper thus offers the conceptual basis for a scientific methodology that is both compatible with the heuristic nature of actual scientific practice and also normatively relevant for assessing method choice. (shrink)

The development of evolutionary game theory is closely linked with two interdisciplinary exchanges: the import of game theory into biology, and the import of biologists’ version of game theory into economics. This paper traces the history of these two import episodes. In each case the investigation covers what exactly was imported, what the motives for the import were, how the imported elements were put to use, and how they related to existing practices in the respective disciplines. Two conclusions emerged from (...) this study. First, concepts derived from the unity of science discussion or the unification accounts of explanation are too strong and too narrow to be useful for analysing these interdisciplinary exchanges. Secondly, biology and economics—at least in relation to EGT—show significant differences in modelling practices: biologists seek to link EGT models to concrete empirical situations, whereas economists pursue conceptual exploration and possible explanation.Keywords: Models; Evolutionary game theory; Interdisciplinarity; Unification; Unity of science; Theory import; Biology; Economics. (shrink)

It is often claimed that artificial society simulations contribute to the explanation of social phenomena. At the hand of a particular example, this paper argues that artificial societies often cannot provide full explanations, because their models are not or cannot be validated. Despite that, many feel that such simulations somehow contribute to our understanding. This paper tries to clarify this intuition by investigating whether artificial societies provide potential explanations. It is shown that these potential explanations, if they contribute to our (...) understanding, considerably differ from potential causal explanations. Instead of possible causal histories, simulations offer possible functional analyses of the explanandum . The paper discusses how these two kinds explanatory strategies differ, and how potential functional explanations can be appraised. (shrink)

ArgumentToday's models of temporal discounting are the result of multiple interdisciplinary exchanges between psychology and economics. Although these exchanges did not result in an integrated discipline, they had important effects on all disciplines involved. The paper describes these exchanges from the 1930s onwards, focusing on two episodes in particular: an attempted synthesis by psychiatrist George Ainslie and others in the 1970s; and the attempted application of this new discounting model by a generation of economists and psychologists in the 1980s, which (...) ultimately ended in thediversity of measurements disappointment. I draw four main conclusions. First, multiple notions of temporal discounting must be conceptually distinguished. Second, behavioral economics is not an integration or unification of psychology and economics. Third, the analysis identifies some central disciplinary markers that distinguish modeling strategies in economics and psychology. Finally, it offers a case of interdisciplinary success that does not fit the currently dominant account of interdisciplinarity as integration. (shrink)

This response to Reiss ?explanatory paradox? argues that some economic models might be true, and that many economic models are not intended for providing how-actually explanations, but rather how-possibly explanations. Therefore, two assumptions of Reiss? paradox are not true, and the paradox disappears.

Modelling cannot be characterized as isolating, nor models as isolations. This article presents three arguments to that effect, against Uskali Mäki's account of models. First, while isolation proceeds through a process of manipulation and control, modelling typically does not proceed through such a process. Rather, modellers postulate assumptions, without seeking to justify them by reference to a process of isolation. Second, while isolation identifies an isolation base—a concrete environment it seeks to control and manipulate—modelling typically does not identify such a (...) base. Rather, modellers construct their models without reference to concrete environments, and only later seek to connect their models to concrete situations of the real world. Third, Mäki argues that isolation employs idealization to control for disturbing factors, but does not affect the factors or mechanisms that are supposed to be isolated. However, models typically make idealizing assumptions about the factors and mechanisms that are the focus of investigation. Thus, even the product of modelling often cannot be characterized as isolation. (shrink)

Changing preferencesis a phenomenonoften invoked but rarely properlyaccounted for. Throughout the history of the social sciences, researchers have come against the possibility that their subjects’ preferenceswere affected by the phenomenato be explainedor by otherfactorsnot taken into accountin the explanation.Sporadically, attempts have been made to systematically investigate these in uences, but none of these seems to have had a lasting impact. Today we are still not much further with respect to preference change than we were at the middle of the last (...) century. This anthology hopes to provide a new impulse for research into this important subject. In particular, we have chosen two routes to amplify this impulse. First, we stress the use of modellingtechniquesfamiliar from economicsand decision theory. Instead of constructing complex, all-encompassing theories of preference change, the authors of this volume start with very simple, formal accounts of some possible and hopefully plausible mechanism of preference change. Eventually, these models may nd their way into larger, empirically adequate theories, but at this stage, we think that the most importantwork lies in building structure.Secondly,we stress the importance of interdisciplinary exchange. Only by drawing together experts from different elds can the complex empirical and theoretical issues in the modelling of preference change be adequately investigated. (shrink)

The notion of bounded rationality has recently gained considerable popularity in the behavioural and social sciences. This article surveys the different usages of the term, in particular the way ‘anomalosus’ behavioural phenomena are elicited, how these phenomena are incorporated in model building, and what sort of new theories of behaviour have been developed to account for bounded rationality in choice and in deliberation. It also discusses the normative relevance of bounded rationality, in particular as a justifier of non‐standard reasoning and (...) deliberation heuristics. For each of these usages, the overview discusses the central methodological problems. (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)

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)

Policymakers increasingly draw on scientific methods, including simulation modeling, to justify their decisions. For these purposes, scientists and policymakers face an extensive choice of modeling strategies. Discussing the example of smallpox epidemiology, this paper distinguishes three types of strategies: Massive Simulation Models (MSMs), Abstract Simulation Models (ASMs) and Macro Equation Models (MEMs). By analyzing some of the main smallpox epidemic models proposed in the last 20 years, it discusses how to justify strategy choice with reference to the core characteristics of (...) these respective strategies. First, I argue that MEMs often suffice for policy purposes, and need to be replaced only if they are insufficiently robust. Such robustness results, however, only requires the use of ASMs, not MSMs. Second, I argue that although MSMs have larger potentials than ASMs in various dimensions, they are also more likely to fail—and that in many cases, this probability of failing outweighs their higher potential. In particular, these dimensions include the representation of the relevant target, the accurate measurement of the relevant parameters, the number of parameters included, the number of mechanisms modeled simultaneously, and the ways of dealing with structural uncertainty. While this in no way excludes the prospect that some MSMs provide good justifications for policy decisions, my arguments caution against a general preference for MSMs over ASMs for policy decision purposes in general and vaccination problems in particular. (shrink)

The modelling of bounded rationality is currently pursued by approaches that exhibit a wide diversity of methodologies. This special issue collects five contributions that discuss different methodological aspects of these approaches. In our introduction, we map the variety of methodological positions with respect to three questions. First, what kinds of evidence do the respective approaches consider relevant for modelling bounded rationality? Second, what kind of modelling desiderata do the respective approaches focus on? And third, how do the respective approaches justify (...) the normative validity of bounded rationality? To broaden the picture, we not only discusss the five contributions of this issue, but also include relevant positions from the extant literature. (shrink)

A lot of philosophy taught to science students consists of scientific methodology. But many philosophy of science textbooks have a fraught relationship with methodology, presenting it either a system of universal principles or entirely permeated by contingent factors not subject to normative assessment. In this paper, I argue for an alternative, heuristic perspective for teaching methodology: as fallible, purpose- and context-dependent, subject to cost-effectiveness considerations and systematically biased, but nevertheless subject to normative assessment. My pedagogical conclusion from this perspective is (...) that philosophers should aim to teach science students heuristic reasoning: strategies of normative method choice appraisal that are sensitive to purposes, contexts, biases and cost-effectiveness considerations; and that we should do so by teaching them exemplars of such reasoning. I illustrate this proposal at the hand of three such exemplars, showing how they help students to appreciate the heuristic nature of both methods and methodology, and to normatively assess method choice in such circumstances. (shrink)

Behavioral welfare economics assigns different roles to preferences than either non-behavioral forms of welfare economics or theories outside of the domain of welfare economics. In particular...

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)

When social scientists began employing evolutionary game theory (EGT) in their disciplines, the question arose what the appropriate interpretation of the formal EGT framework would be. Social scientists have given different answer, of which I distinguish three basic kinds. I then proceed to uncover the conceptual tension between the formal framework of EGT, its application in the social sciences, and these three interpretations. First, I argue that EGT under the biological interpretation has a limited application in the social sciences, chiefly (...) because strategy replication often cannot be sensibly interpreted as strategy bearer reproduction in this domain. Second, I show that alternative replication mechanisms imply interpersonal comparability of strategy payoffs. Giving a meaningful interpretation to such comparisons is not an easy task for many social situations, and thus limits the applicability of EGT in this domain. Third, I argue that giving a new interpretation both to strategy replication and selection solves the issue of interpersonal comparability, but at the costs of making the new interpretation incompatible with natural selection interpretations of EGT. To the extent that social scientists seek such a natural selection interpretation, they face a dilemma: either face the challenge that interpersonal comparisons pose, or give up on the natural selection interpretation. By identifying these tensions, my analysis pleas for greater awareness of the specific purposes of EGT modelling in the social sciences, and for greater sensitivity to the underlying microstructure on which the evolutionary dynamics and other EGT solution concepts supervene. (shrink)

Philosophers of science studying scientific practice often consider it a methodological requirement that their conceptualization of "model" closely connects with the understanding and use of models by practicing scientists. Occasionally, this connection has been explicitly made (Hutten 1954, Suppes 1961, Morgan and Morrison 1999, Bailer-Jones 2002, Lehtinen and Kuorikoski 2007, Kuorikoski 2007, Morgan 2012a). These studies have been dominated by a focus on the—relatively similar forms of—mathematical models in physics and economics. Yet it has become increasingly evident that the way (...) models are conceptualized is very different in some other sciences, where philosophers' accounts of models' characteristics and .. (shrink)

While broadly in agreement with the conclusion that the exponentially discounted utility model (EDU) is not a universally valid rationality standard, I want to defend some intertemporal rationality criteria related to EDU, which Craig Callender might not share. My commentary explores the tension between these intuitions and Callender's arguments. In the first place, I show that many of the concerns that he raises are in fact compatible with intertemporal consistency (and sometimes even with EDU). Secondly, I rebut those arguments that (...) directly challenge consistency. I conclude that while we disagree on the rationality of consistency, we can nevertheless agree on its non-universality and its limited justification of policy interventions. (shrink)

:In this paper, we analyse the difference between two types of behavioural policies – nudges and boosts. We distinguish them on the basis of the mechanisms through which they are expected to operate and identify the contextual conditions that are necessary for each policy to be successful. Our framework helps judging which type of policy is more likely to bring about the intended behavioural outcome in a given situation.

We argue that behavioural public policies (BPP) should be categorized by the kind of mechanism through which they operate, not by the kind of treatment they implement. Reviewing the energy consumption BPP literature, we argue (i) that BPPs are currently categorized by treatment; (ii) that treatment-based categories are subject to mechanistic heterogeneity: there is substantial variation of mechanisms within each treatment type; and (iii) that they also display mechanistic overlap: there is substantial overlap between mechanisms across treatment types. Consequently, current (...) categorizations of BPPs do not reveal the conditions of their efficacy and should be revised to better reflect mechanistic information. (shrink)

In their recently published book Nudge (2008) Richard H. Thaler and Cass R. Sunstein (T&S) defend a position labelled as ‘libertarian paternalism’. Their thinking appeals to both the right and the left of the political spectrum, as evidenced by the bedfellows they keep on either side of the Atlantic. In the US, they have advised Barack Obama, while, in the UK, they were welcomed with open arms by the David Cameron's camp (Chakrabortty 2008). I will consider the following questions. What (...) is Nudge? How is it different from social advertisement? Does Nudge induce genuine preference change? Does Nudge build moral character? Is there a moral difference between the use of Nudge as opposed to subliminal images to reach policy objectives? And what are the moral constraints on Nudge? (shrink)

In pretending therefore to explain the principles of human nature, we in effect propose a compleat system of the sciences, built on a foundation almost entirely new, and the only one upon which they can stand with any security.

"Though this be madness, yet there is method in't." Hamlet , act II, scene ii Abstract: Inherent normativity is the claim that intentional action explanations necessarily have to comply with normatively understood rationality constraints on the ascribed propositional attitudes. This paper argues against inherent normativity in three steps. First, it presents three examples of actions successfully explained with propositional attitudes, where the ascribed attitudes violate relevant rationality constraints. Second, it argues that the inference rules that systematise propositional attitudes are qualitatively (...) different from rationality constraints both in their justification and their recipients. Third, it rejects additional conditions on propositional attitudes, which purport to necessitate a normative commitment. Thus, inherent normativity is rejected; and with it the claim that intentional action explanations differ substantially from other explanations because they are inherently normative. (shrink)

We construct a model of rational choice under risk with biased risk judgement. On its basis, we argue that sometimes, a regulator aiming at maximising social welfare should affect the environment in such a way that it becomes ‘less safe’ in common perception. More specifically, we introduce a bias into each agent’s choice of optimal risk levels: consequently, in certain environments, agents choose a behaviour that realises higher risks than intended. Individuals incur a welfare loss through this bias. We show (...) that by deteriorating the environment, the regulator can motivate individuals to choose behaviour that is less biased, and hence realises risk levels closer to what individuals intended. We formally investigate the conditions under which such a Beneficial Safety Decrease—i.e. a deteriorating intervention that has a positive welfare effect—exists. Finally, we discuss three applications of our model. (shrink)

Economists evaluate their models in terms of credibility. For example, Rothschild and Stiglitz argued from a model of a completive insurance market that under the “plausible” (632) assumption of information asymmetry, one can “credibly” infer the non-existence of equilibria in specific situations – despite the fact that, as they admit, the real ‘market … for insurance is probably not competitive’ (648).1 Another example is Richard Thaler’s column on anomalies of (micro-) economic theory. From 1987 to 2001, he headed every article (...) with the following sentence: ‘An empirical result is anomalous if it is difficult to rationalize, or if implausible assumptions are necessary to explain it within the paradigm’.2 Or, yet another example, Hans Lind concludes in a survey of mathematical models of rent control that ‘what is shown in the model[s]…is just one type of argument…for why a certain story is more credible than a competing story. (shrink)

Ever since game theory has become a dominant mode of investigation in economics, critics have pointed out that it is a formally strong but empirically weak, if not empty, practice.1 We argue against the empirical irrelevance of game theory by investigating the architecture of game theoretic explanations more closely. In particular, we study the role of game models, and find that they assume the role of mediators as autonomous relaters of theory and phenomena. We further argue that stories play an (...) essential part in the mediating function of models: stories that recount the phenomena in such a way that it becomes compatible with the theoretical framework. Contrary to some claims, these stories are subject to evaluation by various criteria, some of which are criteria derived from intuitive judgment. These criteria provide the means to judge whether a model represents a phenomenon or not. Through good stories, phenomena can therefore be related to highly abstract models. Applied game theory, we conclude, has therefore empirical content by representing phenomena in an abstract fashion. (JEL B4,C7. Keywords: Economic methodology, Game theory.). (shrink)

This paper discusses the meaning of expressed preference statements. A holistic explanation of preferences is proposed: preference relations between propositions are explained by preference relations over worlds. Only those world-preferences function as explanans which are maximally similar to the actual world, and which are maximally similar to each other. The concept of similarity as intuitive is rejected, and is interpreted instead with reference to causal structure: 'closest to the actual world' is interpreted as compatible with the causal structure of the (...) actual world, and 'most similar to each other' as sharing the same causal background conditions. (shrink)

This paper discusses the meaning of expressed preference statements. A holistic explanation of preferences is proposed: preference relations between propositions are explained by preference relations over worlds. Only those world-preferences function as explanans which are maximally similar to the actual world, and which are maximally similar to each other. The concept of similarity as intuitive is rejected, and is interpreted instead with reference to causal structure: 'closest to the actual world' is interpreted as compatible with the causal structure of the (...) actual world, and 'most similar to each other' as sharing the same causal background conditions. (shrink)

Richard Bradley’s Bayesian model of preference kinematics is compared with Sven Ove Hansson’s AGM-style model of preference revision. Both seek to model the revision of preference orders as a consequence of retaining consistency when some preferences change. Both models are often interpreted normatively, as giving advice on how an agent should revise her preferences. I raise four criticisms of the Bayesian model: it is unrealistic; it neglects an important change mechanism; it disregards endogenous information relevant to preference change, in particular (...) about similarity and incompleteness; and its representational framework, when expanded with similarity comparisons, may give misleading advice. These criticisms are based on a principle of conservatism, and on two proposals of similarity metrics for the Bayesian model. The performance of the Bayesian model, with and without the similarity metrics, is then tested in three different cases of preference change, and compared to the performance of the AGM model. (shrink)