Testing for the Significance of Violations of Afriat's Inequalities

Two new nonparametric procedures are developed to evaluate the significance of violations of revealed preference found by standard nonstochastic tests. Our tests with high probability correctly detect utility maximization for data generated with measurement error. The procedures are not very sensitive to misspecifying the amount of error that could have caused the data to violate revealed preference. The tests have power against an alternative of random behavior. Both tests fail to reject the null of rational utility maximization from a monetary dataset that has violations of revealed preference.

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