Economic Dynamics: Theory and Computation

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The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems.

This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field.

New for the second edition:
  • “Programming-language agnostic” presentation using pseudocode.
  • New chapter 1 covering conceptual issues concerning Markov chains such as ergodicity and stability.
  • New focus in chapter 2 on algorithms and techniques for program design and high-performance computing.
  • New focus on household problems rather than optimal growth in material on dynamic programming.
  • Solutions to many exercises, code, and other resources available on a supplementary website.

Author(s): John Stachurski
Edition: 2
Publisher: The MIT Press
Year: 2022

Language: English
Commentary: Converted to PDF
Pages: 373
City: London
Tags: dynamics, steady state, Markov chains, dynamic programming

Preface
Common Symbols
Part I: Introduction to Dynamics
Chapter 1: Introduction
Chapter 2: Programming
Chapter 3: Analysis in Metric Space
Chapter 4: Introduction to Dynamics
Chapter 5: Further Topics for Finite MCs
Chapter 6: Infinite State Space
Part II: Advanced Techniques
Chapter 7: Integration
Chapter 8: Density Markov Chains
Chapter 9: Measure-Theoretic Probability
Chapter 10: Stochastic Dynamic Programming
Chapter 11: Stochastic Dynamics
Chapter 12: More Stochastic Dynamic Programming
Part III: Appendixes
Appendix A: Real Analysis
Appendix B: Chapter Appendixes
Bibliography
Index