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Object-Oriented Bayesian Networks for a Decision Support System

Author

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  • Julia Mortera
  • Paola Vicard
  • Cecilia Vergari

Abstract

We study an economic decision problem where the actors are two rms and the Antitrust Authority whose main task is to monitor and prevent rms potential anti-competitive behaviour. The Antitrust Au- thority's decision process is modelled using a Bayesian network whose relational structure and parameters are estimated from data provided by the Authority itself. Several economic variables in uencing this de- cision process are included in the model. We analyse how monitoring by the Antitrust Authority a ects rms cooperation strategies. These are modelled as a repeated prisoners dilemma using object-oriented Bayesian networks, thus enabling integration of rms decision process and external market information.

Suggested Citation

  • Julia Mortera & Paola Vicard & Cecilia Vergari, 2012. "Object-Oriented Bayesian Networks for a Decision Support System," Departmental Working Papers of Economics - University 'Roma Tre' 0144, Department of Economics - University Roma Tre.
    • Handle: RePEc:rtr:wpaper:0144
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    File URL: http://dipeco.uniroma3.it/public/WP%20144.pdf
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    References listed on IDEAS

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    1. Merrill M. Flood, 1958. "Some Experimental Games," Management Science, INFORMS, vol. 5(1), pages 5-26, October.
    2. Steffen L. Lauritzen & Dennis Nilsson, 2001. "Representing and Solving Decision Problems with Limited Information," Management Science, INFORMS, vol. 47(9), pages 1235-1251, September.
    3. James W. Friedman, 1971. "A Non-cooperative Equilibrium for Supergames," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 38(1), pages 1-12.
    4. Joseph B. Kadane & Patrick D. Larkey, 1982. "Subjective Probability and the Theory of Games," Management Science, INFORMS, vol. 28(2), pages 113-120, February.
    5. Kreps, David M. & Wilson, Robert, 1982. "Reputation and imperfect information," Journal of Economic Theory, Elsevier, vol. 27(2), pages 253-279, August.
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    Cited by:

    1. Maria Elena De Giuli & Alessandro Greppi & Marina Resta, 2019. "An Object-Oriented Bayesian Framework for the Detection of Market Drivers," Risks, MDPI, vol. 7(1), pages 1-18, January.
    2. Flaminia Musella & Paola Vicard, 2015. "Object-oriented Bayesian networks for complex quality management problems," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 115-133, January.

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    More about this item

    Keywords

    Antitrust Authority; Bayesian networks; mergers; model integration; prisoners dilemma; repeated games.;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • L40 - Industrial Organization - - Antitrust Issues and Policies - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

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