Testing theories with learnable and predictive representations

Nabil I. Al-Najjar, Alvaro Sandroni, Rann Smorodinsky and Jonathan Weinstein ()

Journal of Economic Theory, 2010, vol. 145, issue 6, 2203-2217

Abstract: We study the problem of testing an expert whose theory has a learnable and predictive parametric representation, as do standard processes used in statistics. We design a test in which the expert is required to submit a date T by which he will have learned enough to deliver a sharp, testable prediction about future frequencies. We show that this test passes an expert who knows the data-generating process and cannot be manipulated by a uninformed one. Such a test is not possible if the theory is unrestricted.

Keywords: Learning; Expert; testing (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:145:y:2010:i:6:p:2203-2217

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