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‘Homo economicus’ as an intuitive statistician (2): Bayesian diagnostic learning

In: Rationality, bounded rationality and microfoundations

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  • Reza Salehnejad

Abstract

The bounded rationality programme views the economy as a society of intuitive statisticians. The key for the success of this programme is the existence of a ‘tight enough’ theory of statistical inference. We have so far shown that there is no entirely data-driven algorithm that receives a finite sample of data and yields the model that best approximates the process generating the data. Learning an interpretable model of a choice situation requires starting with a parametric probability model. To analyse the programme further, we now examine the possibility of a ‘tight enough’ theory of learning within the general framework of the Bayesian theory, which is primarily a theory of parametric inference.

Suggested Citation

  • Reza Salehnejad, 2007. "‘Homo economicus’ as an intuitive statistician (2): Bayesian diagnostic learning," Palgrave Macmillan Books, in: Rationality, bounded rationality and microfoundations, chapter 4, pages 106-164, Palgrave Macmillan.
    • Handle: RePEc:pal:palchp:978-0-230-62515-0_5
    DOI: 10.1057/9780230625150_5
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