Abstract
We provide conditions under which ambiguity fades away in sampling with replacement from the same “ambiguous” urn.
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We wish to thank Paolo Ghirardato, Marco Scarsini, an anonymous referee, and especially Larry Epstein for helpful comments. The financial support of MIUR is gratefully acknowledged.
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Marinacci, M. Learning from ambiguous urns. Statistical Papers 43, 143–151 (2002). https://doi.org/10.1007/s00362-001-0092-5
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DOI: https://doi.org/10.1007/s00362-001-0092-5