Communication in vertical markets: Experimental evidence

Abstract

When an upstream monopolist supplies several competing downstream firms, it may fail to monopolize the market because it is unable to commit not to behave opportunistically. We build on previous experimental studies of this well-known commitment problem by introducing communication. Allowing the upstream firm to chat privately with each downstream firm reduces total offered quantity from near the Cournot level (observed in the absence of communication) halfway toward the monopoly level. Allowing all three firms to chat together openly results in complete monopolization. Downstream firms obtain such a bargaining advantage from open communication that all of the gains from monopolizing the market accrue to them. A simple structural model of Nash bargaining fits the pattern of shifting surpluses well. We conclude with a discussion of the antitrust implications of open communication in vertical markets.

“Nash-in-Nash” Bargaining: A Microfoundation for Applied Work

“…Many of the buyer power, wage bargaining, and health care market papers noted above satisfy these assumptions. In addition, Möllers, Normann, and Snyder (2017) explicitly verify that A.SCDMC and A.LNEXT hold in their application.…”

Using machine learning for communication classification

“…Further, machine coding might not substitute but rather complement human classification. Existing or to-be-established off-the-shelf models for the coding of specific economic concepts can add evidence or a new perspective beyond the manual classification, as is done, for example in Moellers et al (2017) and 1 3…”

“…2 A basic judgment of texts can be made with the help of simple statistics, such as message counts, word counts and word ranks. Moellers et al (2017) fruitfully use those concepts when they experimentally investigate communication in vertical markets. More automated approaches like the Linguistic Inquiry and Word Count program (LIWC) group words in semantic classes such as positive or negative emotions, money, past tense etc.…”

Testing for the emergence of spontaneous order

“…• Descriptive analysis, where the authors use a particular extract from the data in order to make a point, without using any quantitative measures, as in Crockett et al (2009), Kimbrough et al (2008). • Quantitative analysis based on the text rather than human coders, where the text is mined for keywords as in Zhang and Casari (2012), Penczynski (2016), Moellers et al (2017). We have raw data of 16,510 messages from all treatments with communication (536 pages of text).…”