IDEAS home Printed from https://ideas.repec.org/p/ags/aaea10/61301.html
   My bibliography  Save this paper

Optimal Timing of Cartel Formation Under Uncertainty

Author

Listed:
  • Cai, Xiaowei
  • Stiegert, Kyle W.

Abstract

Understanding how business cartels form and expand is foundational for developing sound deterrence strategies. Past work (i.e. Connor, 2005) has relied on net present value (NPV) methods to evaluate the streams of costs and benefits of forming or joining a cartel. While NPV adequately measure the expected value of future streams of benefits and costs, higher moments of the distribution are also important in understanding agent behavior. Thus, in the presence of uncertainty about future streams and litigation costs, NPV may miss important dimensions that shape the issue. The decision to form or join a cartel is, at least, partially irreversible, because it exposes the firm or its involved managers to litigation on all previous returns and even after the cartel is dissolved. In this study, we rely on the aforementioned irreversible and uncertain nature of cartel participation and returns to develop a real-options framework that examines the optimal decision rules regarding the timing of cartel formation. This leads to suggestions for improved policy tools for antitrust agencies. In our model, all firms outside of a cartel essentially hold the option to form or join a cartel at some point in the future. The option is exercised the day the cartel is formed and has no cash value before that. The payoffs that firms give up by not immediately forming a cartel are weighed against uncertain and partially irreversible forming decision nature. Under the assumption of stochastic market demand, we find a threshold level of demand beyond which the cartel is formed. This threshold is analytically calculated as a function of a number of parameters. We then illustrate the conditions that determine the optimal timing decision of cartel formation by conducting comparative dynamics analysis. The timing of cartel formation is analyzed in both domestic and international settings. The qualitative results are obtained by comparative dynamics analysis and the quantitative results by numerical analysis. The results obtained in this study will assist in the development and improvement of guidelines to deter the formation of cartels by antitrust agencies in both developed and developing nations. In the first scenario of domestic cartel formation, at the beginning of each period, firms will choose to compete when the sunk costs related to a cartel operation are too high, current period demand is too low, and/or the expected duration of collusion is too short. Obviously, the possibilities of cartel formation increase when sunk costs go down, demand increases, or relationships with firms improve the prospects for a longer cartel arrangement. The value of waiting increases with a) increased uncertainty of market demand, b) increase irreversibility, and c) increased number of firms and d) a higher discount rate. We study the effect of demand uncertainty on the expected social welfare of cartel formation. The simulation results suggest that the expected social welfare under uncertainty could be higher than that under certainty. In a second scenario, we study the formation of international cartels. The model considers two markets with demand uncertainty that is either correlated or uncorrelated. The demand shocks in each market are assumed to follow geometric Brownian motion. We calculate the threshold value of demand faced by the cartel and obtain the rules guiding a firm's decision to form an international cartel. The comparative dynamics results obtained in the previous domestic scenario still apply. The simulation results suggest that cartel formation is most likely to occur between firms that come from countries with highly correlated markets and similar expected demand growth.

Suggested Citation

  • Cai, Xiaowei & Stiegert, Kyle W., 2010. "Optimal Timing of Cartel Formation Under Uncertainty," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61301, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea10:61301
    DOI: 10.22004/ag.econ.61301
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/61301/files/11563.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.61301?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    Industrial Organization;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea10:61301. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.