HEC Montréal

About: HEC Montréal is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Context (language use) & Vehicle routing problem. The organization has 1221 authors who have published 5708 publications receiving 196862 citations. The organization is also known as: Ecole des Hautes Etudes Commerciales de Montreal & HEC Montreal.

Household Labor Supply, Sharing Rule and the Marriage Market

Abstract: In this paper we estimate a model of household labor supply based on the collective approach developed by Chiappori (JPE, 1992). This approach assumes that the intra-household decision process leads to Pareto efficient outcomes. Our model extends this theory by allowing the marriage market, and especially the sex ratio, to affect the sharing rule and the household labor supplies. We show that our model imposes new restrictions on the parameters of the labor supply functions. Also, individual preferences and the sharing rule are recovered using an identification procedure that is both simpler and more robust than in Chiappori's initial approach. The model is estimated using PSID data for the year 1988. Our results do not reject the restrictions imposed by the model. Moreover, the sex ratio influences the sharing rule and the labor supply behavior in the directions predicted by the theory. Finally, the impact of individual wage rates suggests that spouses behave in an altruistic manner within the household.

Scenario Tree-Based Heuristics for Stochastic Inventory-Routing Problems

Abstract: In vendor-managed inventory replenishment, the vendor decides when to make deliveries to customers, how much to deliver, and how to combine shipments using the available vehicles. This gives rise to the inventory-routing problem in which the goal is to coordinate inventory replenishment and transportation to minimize costs. The problem tackled in this paper is the stochastic inventory-routing problem, where stochastic demands are specified through general discrete distributions. The problem is formulated as a discounted infinite-horizon Markov decision problem. Heuristics based on finite scenario trees are developed. Computational results confirm the efficiency of these heuristics.