Some varieties of robustness

Journal of Economic Methodology 13 (2):219-240 (2006)
It is widely believed that robustness (of inferences, measurements, models, phenomena and relationships discovered in empirical investigation etc.) is a Good Thing. However, there are many different notions of robustness. These often differ both in their normative credentials and in the conditions that warrant their deployment. Failure to distinguish among these notions can result in the uncritical transfer of considerations which support one notion to contexts in which another notion is being deployed. This paper surveys several different notions of robustness and tries to identify why (and in what circumstances) each is valuable or appealing. I begin by discussing the notion of robustness addressed in Aldrich's paper (robustness as insensitivity of the results of inference to alternative specifications) and then discuss how this relates to robustness of derivations, robustness of measurement results, and robustness as a mark of casual as opposed to (merely) correlational relationships.
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DOI 10.1080/13501780600733376
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References found in this work BETA
Clark Glymour (1980). Theory and Evidence. Princeton University Press.
Peter Spirtes, Clark Glymour & Richard Scheines (1996). Causation, Prediction, and Search. British Journal for the Philosophy of Science 47 (1):113-123.

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Citations of this work BETA
J. Kuorikoski, A. Lehtinen & C. Marchionni (2010). Economic Modelling as Robustness Analysis. British Journal for the Philosophy of Science 61 (3):541-567.

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J. Kuorikoski, A. Lehtinen & C. Marchionni (2010). Economic Modelling as Robustness Analysis. British Journal for the Philosophy of Science 61 (3):541-567.
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Sylvia Culp (1994). Defending Robustness: The Bacterial Mesosome as a Test Case. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:46 - 57.
Richard A. Healey (1992). Causation, Robustness, and EPR. Philosophy of Science 59 (2):282-292.

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