Aguiar, Pongou, and Tondji (2018) propose the Shapley distance as a measure of the extent to which output sharing among the stakeholders of an organization can be considered unfair. It measures the distance between an arbitrary pay profile and the Shapley pay profile under a given technology,...

Given any observed finite sequence of prices, wealth and demand choices, we characterize the relation between its underlying Slutsky matrix norm (SMN) and some popular discrete revealed preference (RP) measures of departures from rationality, such as the Afriat index. We show that testing...

We offer a rationalization of the weak axiom of revealed preference (WARP) and of the weak generalized axiom of revealed preference (WGARP) for both finite and infinite data sets of consumer choice. We call it maximin rationalization, in which each pairwise choice is associated with a local...

We present a new notion of cardinal revealed preference that exploits the expenditure information in classical consumer theory environments with finite data. We propose a new behavioral axiom, Acyclic Enticement (AE), that requires the acyclicity of the cardinal revealed-preference relation. AE...

Given any observed demand behavior by means of a demand function, we quantify by how much it departs from rationality. Using a recent elaboration of the "almost implies near" principle, the measure of the gap is the smallest norm of the correcting matrix that would yield a Slutsky matrix with...

This paper shows that frequently observed violations of IIA (Independence of Irrelevant Alternatives), namely the similarity and attraction effect can be compatible with the maximization of rational preferences and the violations themselves can be used to infer the underlying rational preference...

Measurement error causes a loss of distributional information, preventing the researcher from applying the deterministic revealed-preference tools at the individual level. This paper proposes a new statistical revealed-preference framework that is applicable to such cases. We use our framework...

We study the Shapley wage function, a wage scheme in which a worker's pay depends both on the number of hours worked and on the output of the firm. We then provide a way to measure the distance of an arbitrary wage scheme to this function in limited datasets. In particular, for a fixed...

In this study we introduce a new stochastic choice rule that categorizes objects in order to simplify the choice procedure. At any given trial, the decision maker deliberately randomizes over mental categories and chooses the best item according to her utility function within the realized...

We generalize the stochastic revealed preference methodology of McFadden and Richter (1990) for finite choice sets to settings with limited consideration. Our approach is nonparametric and requires partial choice set variation. We only impose a monotonicity condition on attention first proposed...