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

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  • K. Vela Velupillai

Abstract

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 to 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 Jevons's sceptical vision of induction in the light of MDL; and a complexity interpretation of an undecidable question in dynamics.

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  • K. Vela Velupillai, 2007. "A Stochastic Complexity Perspective of Induction in Economics and Inference in Dynamics," Department of Economics Working Papers 0726, Department of Economics, University of Trento, Italia.
    • Handle: RePEc:trn:utwpde:0726
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