This paper uses the notion of augmented utility to summarize models of utility maximization (MUM). The models covered include non-separable utility maximization and common behavioral models of discounting. Moreover, the paper provides as novel special cases necessary and sufficient conditions...

This paper derives a novel representation of the exponential discounting model that allows me to set identify the discount factor while accounting for ostensible deviations from optimal behavior. I interpret these deviations as a by-product of measurement error. My approach uses a revealed...

This paper takes a revealed preference approach for set identifying the discount factor in the exponential discounting model. My methodology allows for measurement error in prices and full heterogeneity in preferences. Using longitudinal data from checkout scanners, I obtain bounds on the...

This note provides a nonparametric test for dynamic discrete random utility models (DDRUM). The methodology can be used to understand the welfare implications of price changes in demand data when there is no uncertainty for consumers that have preferences over product characteristics or discrete...

We analyze consumer demand behavior using Dynamic Random Utility Model (DRUM). Under DRUM, a consumer draws a utility function from a stochastic utility process in each period and maximizes this utility subject to her budget constraint. DRUM allows unrestricted time correlation and cross-section...

This paper provides new identification results for a large class of (static) consumer problems that contain (production) functions in the budget constraints. I show that the mere structure of the consumer problem is sufficient to nonparametrically identify the part of the production functions...