Stochastic growth with a likelihood-increasing estimation process

Nobusumi Sagara ()

Economic Theory, 2006, vol. 28, issue 1, 72 pages

Abstract: We formulate an optimal estimation process in a stochastic growth model with an unknown true probability model. We consider a general reduced model of capital accumulation with an infinite horizon and introduce a learning process in the stochastic dynamic programming. When the only available information is a sample realization generated by a stationary and ergodic stochastic process, we prove that the optimal estimation process based on likelihood-increasing behavior converges to the true probability measure and the likelihood-increasing estimator defines a transition function on the sample space. Copyright Springer-Verlag Berlin/Heidelberg 2006

Keywords: Stochastic growth; Likelihood-increasing estimator; Convergence of probability measures; Consistency; Dependent process. (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:joecth:v:28:y:2006:i:1:p:51-72

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DOI: 10.1007/s00199-005-0619-4

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