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  1. Marcel J. Boumans, Built-in Justification.
    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 (...)
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  2. Marcel J. Boumans, Calibration of Models in Experiments.
    The assessment of models in an experiment depends on their material nature and their function in the experiment. Models that are used to make the phenomenon under investigation visible - sensors - are assessed by calibration. However, calibration strategies assume material intervention. The experiment discssed in this paper is an experiment in economics to measure the influence of technology shocks on business cycles. It uses immaterial, mathematical instruments. It appears that calibration did not work for these kinds of models, it (...)
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  3. Marcel J. Boumans, Grey-Box Understanding in Economics.
    In economics, models are built to answer specific questions. Each type of question requires its own type of models; in other words, it defines the requirements that a model should meet and thereby instructs how the models should be built. An explanation is an answer to a ‘why’-question. In economics, this answer is provided by a white-box model. To answer a ‘how much’-question, which is asking for a measurement, economists can make use of black-box models. Economic phenomena are often (...)
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  4. Marcel J. Boumans, Invariance and Calibration.
    The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. Models function as measuring instruments by transferring observations of an economic system into quantitative facts about that system. These facts are evaluated by their accuracy. Accuracy is achieved by calibration. For calibration standards are needed. Then two strategies can be distinguished. One aims at estimating the invariant (structural) equations of the system. The other is to use known stable facts about (...)
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  5. Marcel J. Boumans, Observations of an Expert.
    This paper discusses the role of expert’s observations in different practices of decision making. In these practices it is never the case that the observations of one sole expert is being used, so discussing the role of expert’s observations implies a discussion of how these observations are combined.
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  6. Marcel J. Boumans, The Difference Between Answering a 'Why' - Question and Answering a 'How Much' - Question.
    Generally, simulations are carried out to answer specific questions. The assessment of the reliability of an answer depends on the kind of question investigated. The answer to a 'why' question is an explanation. The premises of an explanation have to include invariant relationships, and thus the reliability of such answer depends on whether the domain of invariance of the relevant relationships covers the domain of the question. The answer to a 'how much' question is a measurement. A measurement is reliable (...)
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  7. Marcel J. Boumans, Truth Versus Precision.
    A typical difference between social science and natural science is the degree in which control is possible. Strategies in both sciences to obtain true facts are consequently different. Measurement errors are due to background noise. Laboratories are environments in which background conditions can be controlled. As a result, accurate observations { measurement results close to the true values of the measurands { can only be obtained in laboratories. Therefore, measuring instruments are built such that they function as mini laboratories. However, (...)
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  8. Marcel J. Boumans, When Evidence is Not in the Mean.
    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 (...)
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  9. Mary S. Morgan & Marcel J. Boumans, Secrets Hidden by Two-Dimensionality: The Economy as a Hydraulic Machine.
    A long-standing tradition presents economic activity in terms of the flow of fluids. This metaphor lies behind a small but influential practice of hydraulic modelling in economics. Yet turning the metaphor into a three-dimensional hydraulic model of the economic system entails making numerous and detailed commitments about the analogy between hydraulics and the economy. The most famous 3-D model in economics is probably the Phillips machine, the central object of this paper.
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  10. Marcel J. Boumans, Measurement in Economic Systems.
    The metrology literature neglects a strong empirical measurement tradition in economics, which is different from the traditions as accounted for by the formalist representational theory of measurement. This empirical tradition comes closest to Mari's characterization of measurement in which he describes measurement results as informationally adequate to given goals. In economics, one has to deal with soft systems, which induces problems of invariance and of self-awareness. It will be shown that in the empirical economic measurement tradition both problems have been (...)
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