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Modelplasticity and Abductive Decision Making

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  • Subhadeep

    (DEEP)

  • Mukhopadhyay

Abstract

`All models are wrong but some are useful' (George Box 1979). But, how to find those useful ones starting from an imperfect model? How to make informed data-driven decisions equipped with an imperfect model? These fundamental questions appear to be pervasive in virtually all empirical fields -- including economics, finance, marketing, healthcare, climate change, defense planning, and operations research. This article presents a modern approach (builds on two core ideas: abductive thinking and density-sharpening principle) and practical guidelines to tackle these issues in a systematic manner.

Suggested Citation

  • Subhadeep & Mukhopadhyay, 2022. "Modelplasticity and Abductive Decision Making," Papers 2203.03040, arXiv.org, revised Mar 2023.
    • Handle: RePEc:arx:papers:2203.03040
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    References listed on IDEAS

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    1. Bradley Efron, 2014. "Estimation and Accuracy After Model Selection," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 991-1007, September.
    2. Simone Cerreia-Vioglio & Lars Peter Hansen & Fabio Maccheroni & Massimo Marinacci, 2020. "Making Decisions under Model Misspecification," Papers 2008.01071, arXiv.org, revised Aug 2022.
    3. Steve Bankes, 1993. "Exploratory Modeling for Policy Analysis," Operations Research, INFORMS, vol. 41(3), pages 435-449, June.
    4. George Box, 2001. "Statistics for discovery," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(3-4), pages 285-299.
    5. Subhadeep Mukhopadhyay & Emanuel Parzen, 2020. "Nonparametric universal copula modeling," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(1), pages 77-94, January.
    6. Thomas W. Keelin & Bradford W. Powley, 2011. "Quantile-Parameterized Distributions," Decision Analysis, INFORMS, vol. 8(3), pages 206-219, September.
    7. Subhadeep Mukhopadhyay, 2021. "Density Sharpening: Principles and Applications to Discrete Data Analysis," Papers 2108.07372, arXiv.org, revised Aug 2021.
    8. James J. Heckman & Burton Singer, 2017. "Abducting Economics," American Economic Review, American Economic Association, vol. 107(5), pages 298-302, May.
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