Dynamic Optimization Under Uncertainty: Non-convex Feasible Set

Majumdar, Mukul; Mitra, Tapan; Nyarko, Yaw

doi:10.1007/978-1-349-08633-7_19

Cited by 36 publications

(33 citation statements)

References 14 publications

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“…It should perhaps be stressed that convexity assumptions have not appeared in the discussion of this section so far. Of course, in models of optimization, F i is the optimal transition of the system from one state into another, and non-convexity may lead to a failure of the splitting condition (see Majumdar, Mitra and Nyarko (1989) for details).…”

Section: A Stochastic Stability Theorem In a Descriptive Modelmentioning

confidence: 99%

Markov Processes Generated by Random Iterates of Monotone Maps: Theory and Applications

Majumdar

Hall²

2009

Perspectives in Mathematical Sciences I

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractThe paper is a review of results on the asymptotic behavior of Markov processes generated by i.i.d. iterates of monotone maps. Of particular importance is the notion of splitting introduced by Dubins and Freedman (1966). Some extensions to more general frameworks are outlined, and, finally, a number of applications are indicated. *This paper is primarily based on my research with Professor Rabi Bhattacharya over a number of years. No formal acknowledgement to his influence is adequate. Thanks are due to the referee for a careful reading and suggestions on expository changes.

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Section: A Stochastic Stability Theorem In a Descriptive Modelmentioning

confidence: 99%

Markov Processes Generated by Random Iterates of Monotone Maps: Theory and Applications

Majumdar

Hall²

2009

Perspectives in Mathematical Sciences I

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“…We should stress that Markov Chains generated by iid maps arise "naturally" not only in descriptive dynamic economics, but also in the context of dynamic optimization under uncertainty, particularly when one wishes to study the evolution of states generated by an optimal policy function (see Majumdar, Mitra and Nyarko (1989 Example 2. This example is motivated by the remarks of Solow in his celebrated paper (1956) and the subsequent work of Day (1982).…”

Section: Models Of Growth and Cyclesmentioning

confidence: 99%

Estimating the stationary distribution of a Markov chain

Athreya

Majumdar

2004

Studies in Economic Theory

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“…We look at a "canonical" example and show how Corollay 3.1 can be applied. A complete list of references to the earlier literature which owes much to the pioneering efforts of Brock and Mirman, is in Majumdar, Mitra and Nyarko (1989). As a matter of notation, for any function h on S into S, we write h (n) for the…”

Section: Stability Of Invariant Distributions In Models Of Economic Gmentioning

confidence: 99%

Random dynamical systems: a review

Bhattacharya

Majumdar

2003

Economic Theory

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This paper provides a review of some results on the stability of random dynamical systems and indicates a number of applications to stochastic growth models, linear and non-linear time series models, statistical estimation of invariant distributions, and random iterations of quadratic maps. Copyright Springer-Verlag Berlin/Heidelberg 2003Random dynamical systems, Stability, Splitting, Contractions, Stochastic growth, Time series, Estimation.,

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Dynamic Optimization Under Uncertainty: Non-convex Feasible Set

Cited by 36 publications

References 14 publications

Markov Processes Generated by Random Iterates of Monotone Maps: Theory and Applications

Markov Processes Generated by Random Iterates of Monotone Maps: Theory and Applications

Estimating the stationary distribution of a Markov chain

Random dynamical systems: a review

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