Sharp nonparametric bounds are derived for Hicksian compensating and equivalent variations. These 'i-bounds' generalize earlier results of Blundell, Browning and Crawford (2008). We show that their e-bounds are sharp under the Weak Axiom of Revealed Preference (WARP). They do not require...

We provide a nonparametric 'revealed preference' characterization of rational household behavior in terms of the collective consumption model, while accounting for general (possibly non-convex) individual preferences. We establish a Collective Axiom of Revealed Preference (CARP), which provides...

We propose a method to identify bounds (i.e. set identification) on the sharing rule for a general collective household consumption model. Unlike the effects of distribution factors, it is well known that the level of the sharing rule cannot be uniquely identified without strong assumptions on...

We provide a revealed preference analysis of the transferable utility hypothesis, which is widely used in economic models. First, we establish revealed preference conditions that must be satisfied for observed group behavior to be consistent with Pareto efficiency under transferable utility....

We present a nonparametric revealed preference methodology for empirically analyzing collective consumption behavior. First, we introduce an integer programming (IP) methodology for testing data consistency with collective consumption models that account for publicly as well as privately...

It is unlikely that husbands and wives always agree on exactly what public goods to buy. Nor do they necessarily agree on how many hours to work with obvious consequences for the household budget. We therefore model consumption and labor supply behavior of a couple in a non-cooperative setting...

We develop a revealed preference approach to analyze non-unitary consumption models with intrahousehold allocations deviating from the cooperative (or Pareto efficient) solution. At a theoretical level, we establish revealed preference conditions of household consumption models with varying...