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A Stochastic Complexity Perspective of Induction in Economics and Inference in Dynamics

  • K. Vela Velupillai

    (Department of Economics, National University of Ireland, Galway)

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    Rissanen's fertile and pioneering minimum description length principle (MDL) has been viewed from the point of view of statistical estimation theory, information theory, as stochastic complexity theory - i.e., a computable approximation of Kolomogorov Complexity - or Solomonoff's recursion theoretic induction principle or as analogous to Kolmogorov's sufficient statistics. All these - and many more - interpretations are valid, interesting and fertile. In this paper I view it from two points of view: those of an algorithmic economist and a dynamical system theorist. From these points of view I suggest, first, a recasting of Jevon's sceptical vision of induction in the light of MDL; and a complexity interpretation of an undecidable question in dynamics

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    Paper provided by National University of Ireland Galway, Department of Economics in its series Working Papers with number 0127.

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    Date of creation: 2007
    Date of revision: 2007
    Handle: RePEc:nig:wpaper:0127
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