Some authors claim that minimal models have limited epistemic value (Fumagalli, 2016; Grune-Yanoff, 2009a). Others defend the epistemic benefits of modelling by invoking the role of robustness analysis for hypothesis confirmation (see, e.g., Levins, 1966; Kuorikoski et al., 2010) but such arguments find much resistance (see, e.g., Odenbaugh & Alexandrova, 2011). In this paper, we offer a Bayesian rationalization and defence of the view that robustness analysis can play a confirmatory role, and thereby shed light on the potential of minimal models for hypothesis confirmation. We illustrate our argument by reference to a case study from macroeconomics. At the same time, we also show that there are cases in which robustness analysis is detrimental to confirmation. We characterize these cases and link them to recent investigations on evidential variety (Landes, 2020b, 2021; Osimani and Landes, forthcoming). We conclude that robustness analysis over minimal models can confirm, but its confirmatory value depends on concrete circumstances.

Confirmation by Robustness Analysis: A Bayesian Account / L. Casini, J. Landes. - In: ERKENNTNIS. - ISSN 0165-0106. - (2022). [Epub ahead of print] [10.1007/s10670-022-00537-7]

Confirmation by Robustness Analysis: A Bayesian Account

J. Landes
Ultimo
2022

Abstract

Some authors claim that minimal models have limited epistemic value (Fumagalli, 2016; Grune-Yanoff, 2009a). Others defend the epistemic benefits of modelling by invoking the role of robustness analysis for hypothesis confirmation (see, e.g., Levins, 1966; Kuorikoski et al., 2010) but such arguments find much resistance (see, e.g., Odenbaugh & Alexandrova, 2011). In this paper, we offer a Bayesian rationalization and defence of the view that robustness analysis can play a confirmatory role, and thereby shed light on the potential of minimal models for hypothesis confirmation. We illustrate our argument by reference to a case study from macroeconomics. At the same time, we also show that there are cases in which robustness analysis is detrimental to confirmation. We characterize these cases and link them to recent investigations on evidential variety (Landes, 2020b, 2021; Osimani and Landes, forthcoming). We conclude that robustness analysis over minimal models can confirm, but its confirmatory value depends on concrete circumstances.
Robustness analysis; Minimal models; Agent-based models; Confirmation; Variety of evidence; Stylized facts of finance;
Settore M-FIL/02 - Logica e Filosofia della Scienza
11-mag-2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/938149
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