ENGLISH

Economic Dynamics: Theory and Computation

Book information

Publisher
The MIT Press
Year
2022
ISBN
0262012774, 9780262012775, 9780262544771, 9780262372442, 9780262372459
Language
english
Format
PDF
Filesize
37 MB (39288300 bytes)
Edition
2
Pages
373\309
Topic
Economy\\Mathematical Economics
Time added
2023-01-17 13:02:10

Description

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. 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

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