12 Weak Convergence of Markov Processes

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

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12 Weak Convergence of Markov Processes

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

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This chapter is in the book Solutions Manual for <i>Recursive Methods in Economic Dynamics</i>

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IRIGOYEN, Claudio, Rossi-Hansberg, Esteban and Wright, Mark L. J. "12 Weak Convergence of Markov Processes". Solutions Manual for Recursive Methods in Economic Dynamics, Cambridge, MA and London, England: Harvard University Press, 2002, pp. 198-211. https://doi.org/10.4159/9780674038967-013

IRIGOYEN, C., Rossi-Hansberg, E. & Wright, M. (2002). 12 Weak Convergence of Markov Processes. In Solutions Manual for Recursive Methods in Economic Dynamics (pp. 198-211). Cambridge, MA and London, England: Harvard University Press. https://doi.org/10.4159/9780674038967-013

IRIGOYEN, C., Rossi-Hansberg, E. and Wright, M. 2002. 12 Weak Convergence of Markov Processes. Solutions Manual for Recursive Methods in Economic Dynamics. Cambridge, MA and London, England: Harvard University Press, pp. 198-211. https://doi.org/10.4159/9780674038967-013

IRIGOYEN, Claudio, Rossi-Hansberg, Esteban and Wright, Mark L. J. "12 Weak Convergence of Markov Processes" In Solutions Manual for Recursive Methods in Economic Dynamics, 198-211. Cambridge, MA and London, England: Harvard University Press, 2002. https://doi.org/10.4159/9780674038967-013

IRIGOYEN C, Rossi-Hansberg E, Wright M. 12 Weak Convergence of Markov Processes. In: Solutions Manual for Recursive Methods in Economic Dynamics. Cambridge, MA and London, England: Harvard University Press; 2002. p.198-211. https://doi.org/10.4159/9780674038967-013

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Chapters in this book

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/10.4159/9780674038967-013

Chapters in this book

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

12 Weak Convergence of Markov Processes

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