Retail Grocery Evolution: What Can We Learn From Store Counts Data?

Abstract

I develop a dynamic oligopoly model to study the evolution of retail grocery: Grocery chains expand at the expense of independent local stores. Model estimation only requires panel data on store counts and market demand, yet it quantifies the determinants of chain stores' entry and the consequences for incumbent stores' profit and survival. A unique feature of the model is that any Markov-perfect equilibrium that survives some intuitive refinements can be quickly computed from low-dimensional contraction mappings. After computation, it is easy to check the uniqueness of the refined equilibrium. These results facilitate fast and reliable counterfactual simulations. I estimate the model using observations of grocery stores' entries and exits in the Netherlands. The average sunk cost of entry can be multiple times more than a store's expected discounted profit, which considerably deters chain stores' expansion. An entering chain store reduces an incumbent local store's net present value between 28% and 58%. A simulation study shows that, given the large sunk cost and demand uncertainty, Dutch chain stores will continue to progress slowly in the coming years. Relaxing restrictions on chain store entry will quicken the destruction of local stores, but, perhaps surprisingly, hurt chain stores' profits.

Keywords: entry and exit, dynamic oligopoly model, Markov-perfect equilibrium, nested-fixed-point algorithm, chain stores, technology adoption, retail grocery.

JEL Classification: L13