Built-in justification

Boumans, Marcel

doi:10.1017/cbo9780511660108.005

Cited by 137 publications

(81 citation statements)

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“…Model construction is an integration process (Boumans 1999) which requires choosing some form of representation. Economists already learn about theory and the world when arranging di erent elements to create a new model.…”

Section: Resultsmentioning

confidence: 99%

“…The relation to both theory and the real world derives from model construction where aspects of theory and the real world as well as outside elements like analogies and stories come in. Boumans (1999) provides such an account of model building which points out that building a model is a process that integrates various pieces including theoretical notions, empirical ®ndings, metaphors, mathematizations , etc.…”

Section: Model Accounts In the Modern Methodological Literaturementioning

confidence: 99%

“…The construction of the IS-LM model is a good example to underline Boumans's (1999) account of model construction that is illuminated by the analogy of baking a cake without a recipe. Boumans explains that`[i]f you want to bake a cake and you don't have a recipe, [ .…”

Section: Ingredientsmentioning

confidence: 99%

“…This paper is intended as one step towards achieving the ultimate goal of providing answers to these questions. Conscious of the vast variety in the way economists build and use models, I consider a speci®c but crucial example of model building, the construction of the ®rst version of the IS-LM model, and use it as a litmus test to throw light on issues raised in model accounts of the modern methodological literature written by Boumans (1999), Gordon (1991), Hausman (1992), Hughes (1997), Klamer and Leonard (1994), Morgan and Morrison (1999), Morgan ( , 1999b and Psillos (1995) which are all concerned with models of (economic) theorists rather than with econometric models and empirical work. By critically assessing which elements of these accounts ®t to Hicks's model, I seek to contribute to an explanation why and how economists build models.…”

Section: Introductionmentioning

confidence: 99%

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Building and using economic models: a case study analysis of the IS-LL model

Dohmen¹

2002

Journal of Economic Methodology

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This paper critically assesses several model accounts written in the 1990s by epistemologists and philosophers of science by relating them to a speci®c but crucial example of model building, namely construction of the ®rst version of the IS-LM model, and examining in how far these accounts apply to this case. Thereby the paper contributes to answering why and how economists build models. The view crystallizes that economists build models not only to facilitate the conceptual exploration of theory, but also to inform our understanding of the world. Elements of model building, such as analogies, metaphors, stories, theoretical notions, empirical ®ndings and mathematizations, but also the mode of representation shape the model and largely determine how much can be learned about theory and the real world by using the model as a tool.

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Section: Resultsmentioning

confidence: 99%

Section: Model Accounts In the Modern Methodological Literaturementioning

confidence: 99%

Section: Ingredientsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Building and using economic models: a case study analysis of the IS-LL model

Dohmen¹

2002

Journal of Economic Methodology

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“…. 6 A historical example is discussed by Laudan and Leplin (1991), who describe how empirical evidence of magnetic striping in magmatic material on ocean floors was regarded as providing indirect confirmation of the hypothesis that continents had undergone significant climate changes throughout geological history. The two propositions, at first sight, seem to have little to do with each other, but they can be linked by Alfred Wegener's continental drift thesis and the theory of plate tectonics: If continental shelves do indeed move relative to one another along suboceanic faults where new geological material is constantly being formed, then one would expect to find both magnetic striping on ocean floors (caused by the -independently known -multiple reversals the Earth's magnetic field has undergone in the past) and variation in a continent's climate as it moves across different latitudes.…”

Section: Coherence and Cross-model Justificationmentioning

confidence: 99%

Rigorous results, cross-model justification, and the transfer of empirical warrant: the case of many-body models in physics

Gelfert

2008

Synthese

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This paper argues that a successful philosophical analysis of models and simulations must accommodate an account of mathematically rigorous results. Such rigorous results may be thought of as genuinely modelspecific contributions, which can neither be deduced from fundamental theory nor inferred from empirical data. Rigorous results provide new indirect ways of assessing the success of models and simulations and are crucial to understanding the connections between different models. This is most obvious in cases where rigorous results map different models on to one another. Not only does this put constraints on the extent to which performance in specific empirical contexts may be regarded as the main touchstone of success in scientific modelling, it also allows for the transfer of warrant across different models. Mathematically rigorous results can thus come to be seen as not only strengthening the cohesion between scientific strategies of modelling and simulation, but also as offering new ways of indirect confirmation.

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The epistemic, ethical, and political dimensions of uncertainty in integrated assessment modeling

Beck

Krueger

2016

WIREs Climate Change

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Integrated assessment models (IAMs) of global climate change that combine representations of the economic and the climate system have become important tools to support policymakers in their responses to climate change. Yet, IAMs are built in the face of pervasive uncertainty, both scientific and ethical, which requires modelers to make numerous choices in model development. These modeling choices have epistemic, ethical, and political dimensions. First, modeling choices determine how well our current (lack of ) knowledge about the elements and processes of the modeled system is represented. Second, modeling choices have ethical implications, for example, the choice of a social discount rate, which is well documented. For other modeling choices, the ethical assumptions and implications are more subtle. Third, climate-economic models are not produced and used in a political vacuum; they shape and are shaped by the social relations they are embedded in. We review findings from various literatures to unpack the complex intersection of science, ethics, and politics that IAMs are developed and used in. This leads us to suggest theoretical frameworks that may enable an integrated epistemic-ethical-political understanding of IAMs and increase transparency about all three dimensions of model uncertainties. © 2016 The Authors. WIREs Climate Change published by Wiley Periodicals, Inc. How to cite this article:WIREs Clim Change 2016Change , 7:627-645. doi: 10.1002 INTRODUCTION U ncertainty is omnipresent in all policy decisions regarding whether, when, and how to respond to climate change. A common distinction is between scientific uncertainty and ethical uncertainty. Scientific uncertainty exists because our knowledge about the causes, processes, and consequences of climate change is incomplete. Ethical uncertainty exists because it is not clear what frameworks we should apply to address the ethical questions raised by climate change, including questions of historic responsibility, distribution of adaptation and mitigation costs, and of future emission allowances. Scientists broadly agree that there is a divergence between (1) the distribution of the historic responsibility for greenhouse gas (GHG) emissions, which mainly lies with past and present generations in industrialized countries in the Global North, and (2) the anticipated exposure and vulnerability to its effects, which is expected to be most severe for future generations in developing countries with low income in the Global South. Integrated assessment models (IAMs) of global climate change that combine representations of the economic and the climate system have become important tools to support policymakers in their responses to climate change (See Box 1). Yet, the existence of scientific and ethical uncertainty requires modelers to make numerous choices in model development: choices about model scope, equations, parameter values, and output presentation. These modeling decisions have epistemic, ethical, and political dimensions. First, modeling choices determ...

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Built-in justification

Cited by 137 publications

References 0 publications

Building and using economic models: a case study analysis of the IS-LL model

Building and using economic models: a case study analysis of the IS-LL model

Rigorous results, cross-model justification, and the transfer of empirical warrant: the case of many-body models in physics

The epistemic, ethical, and political dimensions of uncertainty in integrated assessment modeling

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