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The Cycles Approach

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  • Jose Alvaro Rodrigues-Neto

Abstract

The cycles approach uses graph theory and linear algebra to study models of knowledge, characterized by a state space, a set of players and their partitions. In finite state spaces, there is a simple formula for the cyclomatic number; i.e., the dimension of cycle spaces of a model. We prove that the cyclomatic number is the minimum number of cycle equations that must be checked to guarantee the existence of a common prior, and explain why some cycle equations are automatically satisfied. If the cyclomatic number is zero, a common prior always exists, regardless of the probabilistic information given by players.posteriors. There is an isomorphism taking cycles into cycle equations; adding cycles is the counterpart of multiplying the corresponding cycle equations. With these tools, we study the processes of learning and forgetting, as well as properties of sub models (i.e., restricting attention to a proper subset of players), and decompositions of the set of players in subsets. We analyze how individual learning translates into more common knowledge or cycle destruction.

Suggested Citation

  • Jose Alvaro Rodrigues-Neto, 2011. "The Cycles Approach," ANU Working Papers in Economics and Econometrics 2011-547, Australian National University, College of Business and Economics, School of Economics.
  • Handle: RePEc:acb:cbeeco:2011-547
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    File URL: https://www.cbe.anu.edu.au/researchpapers/econ/wp547.pdf
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    References listed on IDEAS

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    1. Milgrom, Paul & Stokey, Nancy, 1982. "Information, trade and common knowledge," Journal of Economic Theory, Elsevier, vol. 26(1), pages 17-27, February.
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    18. Barelli, Paulo, 2009. "Consistency of beliefs and epistemic conditions for Nash and correlated equilibria," Games and Economic Behavior, Elsevier, vol. 67(2), pages 363-375, November.
    19. Ng, Man-Chung, 2003. "On the duality between prior beliefs and trading demands," Journal of Economic Theory, Elsevier, vol. 109(1), pages 39-51, March.
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    Cited by:

    1. Rodrigues-Neto, José Alvaro, 2012. "The cycles approach," Journal of Mathematical Economics, Elsevier, vol. 48(4), pages 207-211.
    2. Hellwig, Martin F., 2013. "From posteriors to priors via cycles: An addendum," Economics Letters, Elsevier, vol. 118(3), pages 455-458.
    3. Luciana C. Fiorini & José A. Rodrigues-Neto, 2014. "Self-Consistency and Common Prior in Non-Partitional Knowledge Models," ANU Working Papers in Economics and Econometrics 2014-621, Australian National University, College of Business and Economics, School of Economics.
    4. José Rodrigues-Neto, 2014. "Monotonic models and cycles," International Journal of Game Theory, Springer;Game Theory Society, vol. 43(2), pages 403-413, May.
    5. José A. Rodrigues‐Neto, 2015. "Monotonic Knowledge Models, Cycles, Linear Versions and Auctions with Differential, Finite Information," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 25-37, June.
    6. Fiorini, Luciana C. & Rodrigues-Neto, José A., 2017. "Self-consistency, consistency and cycles in non-partitional knowledge models," Mathematical Social Sciences, Elsevier, vol. 87(C), pages 11-21.
    7. José Alvaro Rodrigues-Neto, 2012. "Cycles of length two in monotonic models," ANU Working Papers in Economics and Econometrics 2012-587, Australian National University, College of Business and Economics, School of Economics.

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    More about this item

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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