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The convergence of least squares learning in stochastic temporary equilibrium models

Author

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  • Shurojit Chatterji

    (Centro de Investigación Económica, ITAM, Ave. Camino Santa Teresa 930, México D.F. 10700, MÉXICO)

Abstract

This paper provides conditions for the almost sure convergence of the least squares learning rule in a stochastic temporary equilibrium model, where regressions are performed on the past values of the endogenous state variable. In contrast to earlier studies, (Evans and Honkapohja, 1998; Marcent and Sargent, 1989), which were local analyses, the dynamics are studied from a global viewpoint, which allows one to obtain an almost sure convergence result without employing projection facilities.

Suggested Citation

  • Shurojit Chatterji, 2002. "The convergence of least squares learning in stochastic temporary equilibrium models," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 20(4), pages 837-847.
    • Handle: RePEc:spr:joecth:v:20:y:2002:i:4:p:837-847
    Note: Received: April 7, 2001; revised version: September 5, 2001
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    Citations

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    Cited by:

    1. Shurojit Chatterji & Ignacio N. Lobato, 2010. "Transformations of the state variable and learning dynamics," International Journal of Economic Theory, The International Society for Economic Theory, vol. 6(4), pages 385-403, December.
    2. Chatterji, Shurojit & Lobato, Ignacio N., 2015. "On divergent dynamics with ordinary least squares learning," Journal of Economic Behavior & Organization, Elsevier, vol. 109(C), pages 1-9.

    More about this item

    Keywords

    Least squares learning; Almost sure convergence.;

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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