In several accounts of what models are and how they function a specific view dominates. This view contains the following characteristics. First, there is a clear-cut distinction between theories, models and data and secondly, empirical assessment takes place after the model is built. This view in which discovery and justification are disconnected is not in accordance with several practices of mathematical business-cycle model building. What these practices show is that models have to meet implicit criteria of adequacy, such as satisfying (...) theoretical, mathematical and statistical requirements, and be useful for policy. In order to be adequate, models have to integrate enough items to satisfy such criteria. These items include besides theoretical notions, policy views, mathematisations of the cycle and metaphors also empirical data and facts. So, the main thesis of this chapter is that the context of discovery is the successful integration of those items that satisfy the criteria of adequacy. Because certain items are empirical data and facts, justification can be built-in. (shrink)

v. 1. Reflection & mystery -- v. 2. Faith & reality.

Research in the field of Empirical Ethics (EE) uses a broad variety of empirical methodologies, such as surveys, interviews and observation, developed in disciplines such as sociology, anthropology, and psychology. Whereas these empirical disciplines see themselves as purely descriptive, EE also aims at normative reflection. Currently there is literature about the quality of empirical research in ethics, but little or no reflection on specific methodological aspects that must be considered when conducting interdisciplinary empirical ethics. Furthermore, poor methodology in an EE (...) study results in misleading ethical analyses, evaluations or recommendations. This not only deprives the study of scientific and social value, but also risks ethical misjudgement. (shrink)

Libertarian paternalism involves the idea that it is justified to shape the context in which people make important choices in a way that they are nudged to options that would be better for them, wh...

Environmental pollution and greenhouse gas emissions that contribute to climate change have adverse impacts on global health. Somewhat paradoxically, health care systems that aim to prevent and cure disease are themselves major emitters and polluters. In this paper we develop a justification for the claim that solidaristic health care systems should include sustainability as one of the criteria for determining which health interventions are made available or reimbursed – and which not. There is however a complication: most adverse health effects (...) due to climate change do occur elsewhere in the world. If solidarity would commit us to take care of everyone’s health, worldwide, it might imply that solidaristic health system cannot justifiably restrict universal access to their own national populations. In response we explain health solidarity is to be considered as a moral ideal. Such an ideal does not specify what societies owe to whom, but it does have moral implications. We argue that ignoring sustainability in political decision making about what health care is to be offered, would amount to betrayal of the ideal of solidarity. (shrink)

The European Corporate Sustainability Framework (ECSF) is, among other concepts, based on a phase-wise development approach as described by Clare Graves' Levels of Existence Theory. As much as corporate sustainability has a sequence of adequate interpretations, aligned with each development level, also the notion of business excellence can be defined at multiple levels, as this paper demonstrates. Furthermore, the authors analyze the current EFQM Excellence Model for particular biases towards various development levels and suggest a new and innovative two-step approach (...) to assessing organizational performance with respect to organizational excellence (OE) and corporate sustainability. According to the organization's ambition, the assessment is either limited to a shareholder approach, mainly focusing at optimal usage of resources, or it also includes an additional assessment format based on the stakeholder approach, with specific reference to the organization's performance on the financial, social and ecological bottom line. This paper demonstrates the need and feasibility of an EFQM-Based assessment tool with a combined focus on corporate sustainability and OE. (shrink)

In the social sciences we hardly can create laboratory conditions, we only can try to find out which kinds of experiments Nature has carried out. Knowledge about Nature's designs can be used to infer conditions for reliable predictions. This problem was explicitly dealt with in Haavelmo's (1944) discussion of autonomous relationships, Friedman's (1953) as-if methodology, and Simon's (1961) discussions of nearly-decomposable systems. All three accounts take Marshallian partitioning as starting point, however not with a sharp ceteris paribus razor but with (...) the blunt knife of negligibility assumptions. As will be shown, in each account reflection on which influences are negligible, for what phenomena and for how long, played a central role. (shrink)

Glenn Harrison [Journal of Economic Methodology, 2013, 20, 103–117] discusses four related forms of methodological intolerance with respect to field experiments: field experiments should rely on some form of randomization, should be disconnected from theory, the concept of causality should only be defined in terms of observables, and the role of laboratory experiments is dismissed. As is often the case, the cause of intolerance is ignorance, as it is here. To acquire knowledge about potential influences, which we need for both (...) the evaluation of internal and external validity of experimental results, we cannot do without theory. A purely empiricist methodology will be unable to give us sufficient understanding of the validity of these results. An account of causality only based on directly observed things, is an account based on factual influences only. This account will be too restricted, because it will not deal with the unobserved potential influences, which we need – again – for the evaluat... (shrink)

The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. There are two different approaches to deal with the justification of a model: an axiomatic and an empirical approach. The axiomatic approach verifies whether a given relational structure satisfies certain axioms to secure homomorphic mapping. The empirical approach conceives models to function as measuring instruments by transferring observations of a phenomenon under investigation into quantitative facts about that phenomenon. These facts (...) are evaluated by their accuracy and precision. Precision is generally achieved by least squares methods and accuracy by calibration. For calibration standards are needed. Then two polar strategies can be distinguished: white-box modeling and black-box modeling. The first strategy of modeling aims at estimating the invariant equations of the phenomenon, thereby fulfilling Hertz’s correctness requirement. The latter strategy of modeling is to use known stable facts about the phenomenon to adjust the model parameters, thereby fulfilling Hertz’s appropriateness requirement. For this latter strategy, the requirement of models as homomorphic mappings has been dropped. Where one will find the axiomatic approach more often used for measurement in the laboratory, the empirical approach is more appropriate for measurement outside the laboratory. The reason for this is that for measurement of phenomena outside the laboratory, one also needs to take account of the environment to achieve accurate results. Environments are generally too relation-rich for an axiomatic approach, which are only applicable for relation-poor systems. The white-box modeling strategy, reflecting the complexity of the environment due to its correctness requirement, will, however, lead to immensely large models. To avoid this problem, modular design is an appropriate strategy to reduce this complexity. Modular design is a grey-box modeling strategy. Grey-box models are assemblies of modules; these are black boxes with standard interface. It should be noted that the structure of the assemblage need not be homomorphic to the relations describing the interaction between phenomenon and environment. These three modeling strategies map out the possible designs for computer simulations as measuring instruments. Whether a simulation is based on a white-box, grey-box or black-box model is only determined by the relationship between the phenomenon and its environment and not by e.g. its materiality or physicality. (shrink)

Recently, there has been an effort to make libertarianism compatible with a redistributive inheritance tax: When the tax is levied, the taxpayer in question is already dead and as such she cannot be a bearer of rights. The state is therefore allowed to redistribute the (value of) the estate according to some distributive principle. I consider (and finally dismiss) four successive arguments, each concluding that the state is allowed to use the estate for redistributive purposes. I show that neither of (...) them is able to reconcile (right-) libertarianism with a redistributive inheritance tax. Instead of trying to square the circle, proponents of such a tax should meet the theoretical essentials of (right-) libertarianism head-on. (shrink)

Generally, rational decision-making is conceived as arriving at a decision by a correct application of the rules of logic and statistics. If not, the conclusions are called biased. After an impressive series of experiments and tests carried out in the last few decades, the view arose that rationality is tough for all, skilled field experts not excluded. A new type of planner's counsellor is called for: the normative statistician, the expert in reasoning with uncertainty par excellence. To unravel this view, (...) the paper explores a specific practice of clinical decision-making, namely Evidence-Based Medicine. This practice is chosen, because it is very explicit about how to rationalize practice. The paper shows that whether a decision-making process is rational cannot be assessed without taking into account the environment in which the decisions have to be taken. To be more specific, the decision to call for new evidence should be rational too. This decision and the way in which this evidence is obtained are crucial to validate the base rates. Rationality should be model-based, which means that not only the isolated decision-making process should take a Bayesian updating process as its norm, but should also model the acquisition of evidence (priors and tests results) as a rational process. (shrink)

In der vorliegenden Arbeit wird eine normative Analyse und Verteidigung der Erbschaftssteuer unternommen. Zunächst wird eine egalitaristische Argumentation für die Steuer entfaltet. Aufgrund ihrer progressiven Struktur ist die Erbschaftssteuer ein geeignetes Instrument, um der wachsenden ökonomischen Ungleichheit entgegenzuwirken und letztlich verschiedene egalitäre Ideale (politische Gleichheit, Chancengleicheit etc.) zu befördern. Anschließend wird untersucht, wie aus normativer Perspektive zu beurteilen ist, dass der Erblasser bei Erhebung der Steuer nicht mehr lebt. Die restliche Arbeit besteht in einer Auseinandersetzung mit den wichtigsten Einwänden gegen (...) die Erbschaftssteuer. So wird oft behauptet, diese verletze die natürlichen Eigentumsrechte des Erblassers bzw. des Erben und sie ignoriere zudem die Verdienstansprüche des Erblassers. Schließlich sei die Steuer aus diversen "familien-basierten" Erwägungen abzulehnen. Nicht nur werden diese Einwände erfolgreich zurückgewiesen; ferner wird gezeigt, dass einige der, diesen Argumenten zugrundeliegenden, Prinzipien selbst zur Verteidigung einer egalitären Erbschaftssteuer (also einer Erbschaftssteuer, die aus egalitären Prinzipien folgt) herangezogen werden können. (shrink)

In de economische wetenschap worden vragen beantwoord met behulp van modellen. Voor ieder type vraag bestaat een eigen klasse van modellen. Het type vraag bepaalt de eisen waaraan het model moet voldoen en geeft daarbij aan hoe de modellen gemaakt dienen te worden. Dit artikel behandelt de vraag die gesteld wordt om tot begrip te komen: de ‘hoezo-vraag’. Om duidelijk te maken welke modellen hoezo-vragen impliceren zal dit type vraag vergeleken worden met ‘waarom-vragen’ en ‘hoeveelvragen’. Het antwoord op een waarom-vraag (...) is een verklaring. Het antwoord op een hoeveel-vraag is een meetresultaat. (shrink)

When observing or measuring phenomena, errors are inevitable, one can only aspire to reduce these errors as much as possible. An obvious strategy to achieve this reduction is by using more precise instruments. Another strategy was to develop a theory of these errors that could indicate how to take them into account. One of the greatest achievements of statistics in the beginning of the 19th century was such a theory of error. This theory told the practitioners that the best thing (...) they could do is taking the arithmetical mean of their observations. This average would give them the most accurate estimate of the value they were searching for. Soon after its invention, this method made a triumphal march across various sciences. However, not in all sciences one stood waving aside. This method, namely, only worked well when the various observations were made under similar circumstances and when there were very many of them. And this was not the case for e.g. meteorology and actuarial science, the two sciences discussed in this paper. (shrink)