Academic journal article Economic Inquiry

Information Sharing and Tacit Collusion in Laboratory Duopoly Markets

Academic journal article Economic Inquiry

Information Sharing and Tacit Collusion in Laboratory Duopoly Markets

Article excerpt


Economists have long believed that enhanced information about demand conditions or rival actions can play an important role in facilitating collusion, for example because it simplifies detection of chiselers (Stigler [1964]). An extensive theoretical literature examines the incentives for non-cooperative firms to share information through a trade association about some uncertain parameter (see Sakai [1990; 1991] for a survey). Firms in these models may "cooperate" by sharing information in the trade association, even though most authors assume that the firms choose non-cooperative strategies in the product market. Under these conditions, Vives [1984] shows that with demand uncertainty, substitute goods and quantity competition, each firm's dominant strategy is to conceal information from its rivals. Therefore, under these conditions non-cooperative firms will not find it in their interests to form an information-sharing arrangement such as a trade association. Because non-cooperative firms should not wish to share information, Clarke [1983, 392] concludes that "information-pooling mechanisms like trade associations can be considered prima facie evidence that firms are illegally cooperating to restrict output." However, Kirby [1988] shows that non-cooperative firms will want to share information if cost functions are sufficiently quadratic. Moreover, Hviid [1989] demonstrates that non-cooperative firms will prefer to share information if they are sufficiently risk averse.

These models typically assume that firms interact once and identify the static, subgame perfect Nash Equilibrium (NE) of the two-stage information sharing game. This is sensible when the goal is to focus on a narrow set of non-cooperative equilibria, because the set of non-cooperative equilibria becomes very large in these models in the more complex repeated game. However, repeated interaction between competing firms seems more relevant for empirical applications, especially for providing policy insight for trade associations that permit long-term interactions among firms.

Unfortunately, empirical work in this area based on field data is challenging because the information different decision-makers possess, and the corresponding residual uncertainty they face, are typically difficult to identify. This paper uses a different empirical approach. We use a series of laboratory duopoly markets to examine the impact of demand uncertainty on sellers' output choices. Specifically, we examine the importance of information sharing in facilitating tacit collusion under conditions of demand uncertainty.(1) Our experiment employs repeated interaction between fixed pairs of subjects, trading the ability to directly test the static models for a more realistic, policy-relevant study of outcomes in the repeated game.(2) Our results indicate the extent to which results from static theory carry over to the repeated environment, and can help guide future theory for dynamic oligopoly models of information sharing.

The experiment includes four distinct treatment conditions. In the primary treatment, sellers face uncertain demand but can eliminate uncertainty through voluntary, mutual information sharing. Three control treatments identify the reasons for voluntary information sharing and determine if it leads to more collusive outcomes. The first two control treatments eliminate sellers' information sharing opportunities. In the first control treatment sellers always remain uncertain about demand when choosing output, while in the second control treatment sellers always have perfect demand information. We refer to these control treatments respectively as Forced No Sharing and Forced Sharing throughout the paper. The third control treatment sharply reduces collusion incentives by truncating demand while still allowing voluntary information transmission. We refer to this control treatment as the Truncated Demand treatment.

The results, briefly stated, are as follows. …

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