We revisit the recent revealed preference analysis of sophisticated quasi-hyperbolic consumers by Blow et al. [(2021), “Non-parametric Analysis of Time-Inconsistent Preferences”, The Review of Economic Studies, 88, 2687–2734] (BBC). We show that BBC’s revealed preference test is too lax. There are non-rationalizable data that would pass their test. A basic problem with their test is that it requires finding a certain endogenous elasticity, without regard to the rationalizing utility. Their approach motivates a more stringent test, also based on first-order conditions, that would connect the endogenous elasticity and utility: We show that this test is also too lax. Aside from testing, we also discuss the possibility of recovering model parameters. We show that, even when discount factors are exactly identified, the approach followed in BBC allows for incorrect parameter values to lie in their identified set.

We provide the first behavioral characterization of nested logit, a foundational and widely applied discrete-choice model, through the introduction of a nonparametric version of nested logit that we call “nested stochastic choice” (NSC). NSC is characterized by a single axiom that weakens independence of irrelevant alternatives on the basis of revealed similarity to allow for the similarity effect. Nested logit is characterized by an additional menu-independence axiom. Our axiomatic characterization leads to a practical, data-driven algorithm that identifies the true nest structure from choice data. We also discuss limitations of generalizing nested logit by studying the testable implications of cross-nested logit.