A COMPARISON OF TWO METHODS FOR TESTING THE UTILITY MAXIMIZATION HYPOTHESIS WHEN QUANTITY DATA ARE MEASURED WITH ERROR

The Generalized Axiom of Revealed Preference (GARP) can be violated because of random measurement errors in the observed quantity data. We study two tests proposed by Varian (1985) and de Peretti (2004), which test GARP within an explicit stochastic framework. Both tests compute adjusted quantity data that are compliant with GARP. We compare and contrast the two tests in theoretical terms and in an empirical application. The empirical application is based on testing a large group of monetary assets for the United States over multiple sample periods spanning 1960–1992. We found that both tests provided reasonable results and were largely consistent with each other.