Models of labor supply derived from stochastic utility representations and discretized sets of feasible hours of work have gained popularity because they are more practical than the standard approaches based on marginal calculus. In this paper we argue that practicality is not the only feature...

In this paper we discuss a general framework for analyzing labor supply behavior in the presence of complicated budget- and quantity constraints of which some are unobserved. The point of departure is that an individual’s labor supply decision can be considered as a choice from a set of...

In this paper we discuss a general framework for analyzing labor supply behavior in the presence of complicated budget- and quantity constraints of which some are unobserved. The individual’s labor supply decision is viewed as a choice from a set of discrete alternatives (jobs). These jobs are...

This paper analyzes the properties of a particular sectoral labor supply model developed and estimated in Dagsvik and Strøm (2006). In this model, agents have preferences over sectors and latent job attributes. Moreover, the model allows for a representation of the individual choice sets of...

This paper develops analytic results for marginal compensated effects of discrete labor supply models, including Slutsky equations. It matters, when evaluating marginal compensated effects in discrete choice labor supply models, whether one considers wage increase (right marginal effects) or...

Models of labor supply derived from stochastic utility representations and discretized sets of feasible hours of work have gained popularity because they are more practical than the standard approaches based on marginal calculus. In this paper we argue that practicality is not the only feature...

Dagsvik and Karlström (2005) have demonstrated how one can compute Compensating Variation and Compensated Choice Probabilities by means of analytic formulas in the context of discrete choice models. In this paper we offer a new and simplified derivation of the compensated probabilities....