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Abduction in economics: a conceptual framework and its model

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Abstract

We discuss in this paper the scope of abduction in Economics. The literature on this type of inference shows that it can be interpreted in different ways, according to the role and nature of its outcome. We present a formal model that allows to capture these various meanings in different economic contexts.

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Notes

  1. We do not use the word complexity as a technical term, but as it is understood in colloquial speech, i.e., something intricate that calls for thorough and possible inexact assessments to understand it.

  2. A subsequent problem would be to clarify what is the meaning of cause for Peirce. For example, he criticizes the “grand principle of causation” (Peirce et al. 1931–1958, p. 6.68). However, dealing with this topic is beyond the scope of this paper.

  3. Peirce’s notion of truth is another topic the paper will not deal with. For more on this topic see Haack (1977).

  4. Therefore, it remains clear that abduction in economics is mostly “model-based” rather than “sentential”. For the meaning of these notions see Magnani (2009).

  5. This might be a reason for why formal logicians, until recently, did not intensively study abduction in contrast to the other forms of inference.

  6. For a precise characterization of these notions see Shoenfield (1967).

  7. For more on this see Aumann (1999a, b), in which the semantic (mathematical and statistical) approach, which is more natural for economists, is shown to be quite distinct from the syntactic (first-order logic) one.

  8. This follows in a logic defined over a hypergraph in which the observations constitute the nodes and sets of observations under the relation \(\mathcal{R}\) the hyperedges (Kolany 1993).

  9. See Simon (1968).

  10. We dispense here with the detailed expression of the structures.

  11. For a lore of statistical evidence about the behavior of the Argentinean inflation during the last decades see Dabús (2000).

  12. See, for example, Haken (1988).

  13. Critically self-organized systems consist of a number of coupled components. The state of the components in a period plus the external shocks determines the state of the components in the next period. See Bak (1997).

  14. A chaotic process (different from an ergodic process) converges to what is called a strange attractor even if trajectories that began being close to each other tend to diverge. In the average, great increases in a given stage of the evolution of the system have to be compensated by decreases in the future.

  15. Which can be checked out in Tohmé et al. (2005).

  16. Because a model in which these prices differ involves a larger number of true formulas.

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Acknowledgments

We thank Eleonora Cresto, Daniel Heymann, Andoni Ibarra, Larry Moss and two anonymous referees for their useful comments. We are particularly grateful for the permanent encouragement to pursue this topic by the late Ana Marostica. The usual caveat applies.

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Tohmé, F., Crespo, R. Abduction in economics: a conceptual framework and its model. Synthese 190, 4215–4237 (2013). https://doi.org/10.1007/s11229-013-0268-2

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