CFDP 2224R

Search, Information, and Prices

Author(s): 

Publication Date: March 2020

Revision Date: May 2020

Pages: 60

Abstract: 

Consider a market with identical firms offering a homogeneous good. A consumer obtains price quotes from a subset of firms and buys from the firm offering the lowest price. The “price count” is the number of firms from which the consumer obtains a quote. For any given ex ante distribution of the price count, we obtain a tight upper bound (under first-order stochastic dominance) on the equilibrium distribution of sale prices. The bound holds across all models of firms’ common-prior higher-order beliefs about the price count, including the extreme cases of full information ( firms know the price count) and no information (firms only know the ex-ante distribution of the price count). A qualitative implication of our results is that a small ex ante probability that the price count is one can lead to a large increase in the expected price. The bound also applies in a wide class of models where the price count distribution is endogenized, including models of simultaneous and sequential consumer search.

Keywords: Search, Price Competition, Bertrand Competition, "Law of One Price", Price Count, Price Quote, Information Structure, Bayes Correlated Equilibrium

JEL Classification Codes: D41, D42, D43, D83

JEL Classification Codes: D41D42D43D83

See CFDP Version(s): CFDP 2224