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

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  • K. Vela Velupillai

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

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 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

Suggested Citation

  • K. Vela Velupillai, 2007. "A Stochastic Complexity Perspective of Induction in Economics and Inference in Dynamics," Working Papers 0127, National University of Ireland Galway, Department of Economics, revised 2007.
  • Handle: RePEc:nig:wpaper:0127
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    1. Fidrmuc, Jan, 2004. "Migration and regional adjustment to asymmetric shocks in transition economies," Journal of Comparative Economics, Elsevier, vol. 32(2), pages 230-247, June.
    2. Kahanec, Martin & Zimmermann, Klaus F., 2008. "International Migration, Ethnicity and Economic Inequality," IZA Discussion Papers 3450, Institute for the Study of Labor (IZA).
    3. Bauer, Thomas K. & Zimmermann, Klaus F., 1999. "Report No. 3: Assessment of Possible Migration Pressure and its Labour Market Impact Following EU Enlargement to Central and Eastern Europe," IZA Research Reports 3, Institute for the Study of Labor (IZA).
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