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Rationalizing Rational Expectations? Tests and Deviations

Author: Xavier D'Haultfoeuille; Christophe Gaillac; Arnaud Maurel; NBER Working Papers - York University.; National Bureau of Economic Research.
Publisher: Cambridge, Mass. National Bureau of Economic Research 2018.
Series: Working paper series (National Bureau of Economic Research), no. w25274.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
In this paper, we build a new test of rational expectations based on the marginal distributions of realizations and subjective beliefs. This test is widely applicable, including in the common situation where realizations and beliefs are observed in two different datasets that cannot be matched. We show that whether one can rationalize rational expectations is equivalent to the distribution of realizations being a  Read more...
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Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Xavier D'Haultfoeuille; Christophe Gaillac; Arnaud Maurel; NBER Working Papers - York University.; National Bureau of Economic Research.
OCLC Number: 1078759586
Notes: November 2018.
Description: 1 online resource.
Series Title: Working paper series (National Bureau of Economic Research), no. w25274.
Responsibility: Xavier D'Haultfoeuille, Christophe Gaillac, Arnaud Maurel.

Abstract:

In this paper, we build a new test of rational expectations based on the marginal distributions of realizations and subjective beliefs. This test is widely applicable, including in the common situation where realizations and beliefs are observed in two different datasets that cannot be matched. We show that whether one can rationalize rational expectations is equivalent to the distribution of realizations being a mean-preserving spread of the distribution of beliefs. The null hypothesis can then be rewritten as a system of many moment inequality and equality constraints, for which tests have been recently developed in the literature. Next, we go beyond testing by defining and estimating the minimal deviations from rational expectations that can be rationalized by the data. In the context of structural models, we build on this concept to propose an easy-to-implement way to conduct a sensitivity analysis on the assumed form of expectations. Finally, we apply our framework to test for and quantify deviations from rational expectations about future earnings, and examine the consequences of such departures in the context of a life-cycle model of consumption.

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