Estimation of Dynamic Discrete Choice Models in Continuous Time with an Application to Retail Competition

Peter Arcidiacono, Patrick Bayer, Jason R. Blevins, Paul B. Ellickson

NBER Working Paper No. 18449
Issued in October 2012
NBER Program(s):   IO   TWP

This paper develops a dynamic model of retail competition and uses it to study the impact of the expansion of a new national competitor on the structure of urban markets. In order to accommodate substantial heterogeneity (both observed and unobserved) across agents and markets, the paper first develops a general framework for estimating and solving dynamic discrete choice models in continuous time that is computationally light and readily applicable to dynamic games. In the proposed framework, players face a standard dynamic discrete choice problem at decision times that occur stochastically. The resulting stochastic-sequential structure naturally admits the use of CCP methods for estimation and makes it possible to compute counterfactual simulations for relatively high-dimensional games. The model and method are applied to the retail grocery industry, into which Wal-Mart began rapidly expanding in the early 1990s, eventually attaining a dominant position. We find that Wal-Mart’s expansion into groceries came mostly at the expense of the large incumbent supermarket chains, rather than the single-store outlets that bore the brunt of its earlier conquest of the broader general merchandise sector. Instead, we find that independent grocers actually thrive when Wal-Mart enters, leading to an overall reduction in market concentration. These competitive effects are strongest in larger markets and those into which Wal-Mart expanded most rapidly, suggesting a diminishing role of scale and a greater emphasis on differentiation in this previously mature industry.

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This paper was revised on February 6, 2015

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Document Object Identifier (DOI): 10.3386/w18449

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