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...

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,...

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...

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...

The random utility model (RUM, McFadden and Richter, 1990) has been the standard tool to describe the behavior of a population of decision makers. RUM assumes that decision makers behave as if they maximize a rational preference over a choice set. This assumption may fail when consideration of...

This paper studies nonparametric identification and counter- factual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities and prices are latent rendering standard approaches inapplicable. Instead, we require observation of profits or...