13 Applications of Convergence Results for Markov Processes

Claudio IRIGOYEN; Esteban Rossi-Hansberg; Mark L. J Wright

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13 Applications of Convergence Results for Markov Processes

Claudio IRIGOYEN , Esteban Rossi-Hansberg und Mark L. J Wright

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Ein Kapitel aus dem Buch Solutions Manual for <i>Recursive Methods in Economic Dynamics</i>

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IRIGOYEN, Claudio, Rossi-Hansberg, Esteban and Wright, Mark L. J. "13 Applications of Convergence Results for Markov Processes". Solutions Manual for Recursive Methods in Economic Dynamics, Cambridge, MA and London, England: Harvard University Press, 2002, pp. 212-233. https://doi.org/10.4159/9780674038967-014

IRIGOYEN, C., Rossi-Hansberg, E. & Wright, M. (2002). 13 Applications of Convergence Results for Markov Processes. In Solutions Manual for Recursive Methods in Economic Dynamics (pp. 212-233). Cambridge, MA and London, England: Harvard University Press. https://doi.org/10.4159/9780674038967-014

IRIGOYEN, C., Rossi-Hansberg, E. and Wright, M. 2002. 13 Applications of Convergence Results for Markov Processes. Solutions Manual for Recursive Methods in Economic Dynamics. Cambridge, MA and London, England: Harvard University Press, pp. 212-233. https://doi.org/10.4159/9780674038967-014

IRIGOYEN, Claudio, Rossi-Hansberg, Esteban and Wright, Mark L. J. "13 Applications of Convergence Results for Markov Processes" In Solutions Manual for Recursive Methods in Economic Dynamics, 212-233. Cambridge, MA and London, England: Harvard University Press, 2002. https://doi.org/10.4159/9780674038967-014

IRIGOYEN C, Rossi-Hansberg E, Wright M. 13 Applications of Convergence Results for Markov Processes. In: Solutions Manual for Recursive Methods in Economic Dynamics. Cambridge, MA and London, England: Harvard University Press; 2002. p.212-233. https://doi.org/10.4159/9780674038967-014

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Kapitel in diesem Buch

Frontmatter i
Contents vii
Foreword ix
1 Introduction 1
2 An Overview 3
3 Mathematical Preliminaries 20
4 Dynamic Programming under Certainty 42
5 Applications of Dynamic Programming under Certainty 53
6 Deterministic Dynamics 80
7 Measure Theory and Integration 98
8 Markov Processes 131
9 Stochastic Dynamic Programming 147
10 Applications of Stochastic Dynamic Programming 171
11 Strong Convergence of Markov Processes 190
12 Weak Convergence of Markov Processes 198
13 Applications of Convergence Results for Markov Processes 212
14 Laws of Large Numbers 234
15 Pareto Optima and Competitive Equilibria 240
16 Applications of Equilibrium Theory 253
17 Fixed-Point Arguments 270
18 Equilibria in Systems with Distortions 284

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https://doi.org/10.4159/9780674038967-014

Kapitel in diesem Buch

Frontmatter i
Contents vii
Foreword ix
1 Introduction 1
2 An Overview 3
3 Mathematical Preliminaries 20
4 Dynamic Programming under Certainty 42
5 Applications of Dynamic Programming under Certainty 53
6 Deterministic Dynamics 80
7 Measure Theory and Integration 98
8 Markov Processes 131
9 Stochastic Dynamic Programming 147
10 Applications of Stochastic Dynamic Programming 171
11 Strong Convergence of Markov Processes 190
12 Weak Convergence of Markov Processes 198
13 Applications of Convergence Results for Markov Processes 212
14 Laws of Large Numbers 234
15 Pareto Optima and Competitive Equilibria 240
16 Applications of Equilibrium Theory 253
17 Fixed-Point Arguments 270
18 Equilibria in Systems with Distortions 284

13 Applications of Convergence Results for Markov Processes

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