The Structure of US Food Demand

An exactly aggregable system of Gorman Engel curves for U.S. food consumption is developed and implemented. Box-Cox transformations on prices and income nest functional form. The model nests rank up to rank three. The model is estimated by nonlinear three-stage least squares with annual time series data on 21 foods, 17 nutrients, age and race demographics, and the distribution of income for 1919-1941 and 1947-2000. Results are consistent with full rank three. Point estimates for the Box-Cox parameters on income and prices are 0.86 and 1.09, respectively, strongly rejecting zero and one in both cases. No statistical evidence of serial correlation, specification errors, or parameter instability is found.Aggregation, food demand, functional form, parameter stability, rank, specification errors

Lost sales inventory models with batch ordering and handling costs

In this paper, we integrate inventory and handling into a single model for analysis and optimization of inventory replenishment decisions for a grocery retail store. We consider a retailer who periodically manages his inventory of a single item facing stochastic demand. The retailer may only order in multiples of a xed batch size, the lead time is less than the review period length and all unmet demand is lost, which is a realistic situation for a large part of the assortment of grocery retailers. The replenishment cost includes both xed and variable components, dependent on the number of batches and units in the order. This structure captures the shelf-stacking costs in retail stores. We investigate the optimal policy structure under the long-run average cost criterion. Our results show that it is worthwhile to explicitly take handling costs into account when making inventory decisions. We use parameter values typical for rocery retail environments. For an important subset of the retail assortment, we show that signicant cost reductions exist by explicitly considering handling in the inventory policy. Keywords: Retail inventory control, Handling, Lost sales, Periodic review, Fixed batch size

An Equilibrium Analysis of Real Estate

This paper provides a unified equilibrium approach to valuing a wide variety of commercial real estate lease contracts. Using a game-theoretic variant of real options analysis, the underlying real estate asset market is modeled as a continuous-time Nash equilibrium in which developers make construction decisions under demand uncertainty. Then, using the economic notion that leasing simply represents the purchase of the use of the asset over a specified time frame, I use a contingent-claims approach to value many of the most common real estate leasing arrangements. In particular, the model provides closed-form solutions for the equilibrium valuation of leases with options to purchase, pre-leasing, gross and net leases, leases with cancellation options, ground leases, escalation clauses, lease concessions and sale-leasebacks.

A Theory of Firm Decline

We study the problem of an investor that buys an equity stake in an entrepreneurial venture, under the assumption that the former cannot monitor the latter’s operations. The dynamics implied by the optimal incentive scheme is rich and quite different from that induced by other models of repeated moral hazard. In particular, our framework generates a rationale for firm decline. As young firms accumulate capital, the claims of both investor (outside equity) and entrepreneur (inside equity) increase. At some juncture, however, even as the latter keeps on growing, invested capital and firm value start declining and so does the value of outside equity. The reason is that incentive provision is costlier the wealthier the entrepreneur (the greater is inside equity). In turn, this leads to a decline in the constrained–efficient level of effort and therefore to a drop in the return to investment.Principal Agent, Moral Hazard, Hidden Action, Incentives, Survival, Firm Dynamics

Performance Evaluation of Stochastic Multi-Echelon Inventory Systems: A Survey

Globalization, product proliferation, and fast product innovation have significantly increased the complexities of supply chains in many industries. One of the most important advancements of supply chain management in recent years is the development of models and methodologies for controlling inventory in general supply networks under uncertainty and their widefspread applications to industry. These developments are based on three generic methods: the queueing-inventory method, the lead-time demand method and the flow-unit method. In this paper, we compare and contrast these methods by discussing their strengths and weaknesses, their differences and connections, and showing how to apply them systematically to characterize and evaluate various supply networks with different supply processes, inventory policies, and demand processes. Our objective is to forge links among research strands on different methods and various network topologies so as to develop unified methodologies.Masdar Institute of Science and TechnologyNational Science Foundation (U.S.) (NSF Contract CMMI-0758069)National Science Foundation (U.S.) (Career Award CMMI-0747779)Bayer Business ServicesSAP A