We present a statistical test for the hypothesis of (approximate) utility maximization on the basis of nonparametric revealed preference conditions. We take as null hypothesis that the consumer behaves randomly, and we reject this hypothesis only if the data provides sufficient evidence to support the alternative hypothesis of approximate utility maximization. Our statistical test uses a permutation method to operationalize the principle of random consumption behavior. We show that our test (i) is valid for any sample size under the null and (ii) has an asymptotic power of one. We also provide simulated power results and two empirical applications.

We propose a novel nonparametric method to empirically identify economies of scale in multiperson household consumption. We assume consumption technologies that define the public and private nature of expenditures through Barten scales. Our method (solely) exploits preference information revealed by a cross-section of household observations while accounting for fully unobserved preference heterogeneity. An application to data drawn from the US Panel Study of Income Dynamics shows that the method yields informative results on scale economies and intrahousehold allocation patterns. In addition, it allows us to define individual compensation schemes required to preserve the same consumption level in case of marriage dissolution or spousal death.

We compare the empirical performance of unitary and collective labor supply models, using representative data from the Dutch DNB Household Survey. We conduct a nonparametric analysis that avoids the distortive impact of an erroneously specified functional form for the preferences and/or the intrahousehold bargaining process. Our analysis focuses on the goodness of fit of the two behavioral models. To guarantee a fair comparison, we complement this goodness-of-fit analysis with a power analysis. Our results strongly favor the collective approach to modeling the behavior of multiperson households.