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.
The second edition offers a “programming-language agnostic” presentation using pseudocode. A completely rewritten chapter 1 covers conceptual issues concerning Markov chains such as ergodicity and stability, and chapter 2 now focuses on algorithms and techniques for program design and high-performance computing. The coverage of dynamic programming now emphasizes household problems rather than optimal growth. A supplementary website offers solutions to many exercises, code, and other resources.
“Beautifully written by a star in the field, this delightfully novel and thorough treatment of stochastic dynamic modeling builds on well-known results and synthesizes the latest developments. A must-read for any economist or researcher who wants to learn the tools of dynamic stochastic modeling and apply these tools in their own research.”
William A. Brock, Vilas Research Professor Emeritus, University of Wisconsin, Madison; Research Professor, University of Missouri, Columbia
“Graduate macroeconomics courses are becoming more technically sophisticated every year. There are very few books that introduce the necessary mathematical techniques to understand modern macroeconomics that are comprehensible to the nonmathematician. This book helps fill that void. It is easy to read but does not shy away from difficult material. More than just an introduction to dynamics for the mathematically challenged graduate student, it will also be an invaluable aid to the researcher as a reference book on stochastic dynamics.”
Roger Farmer, Department of Economics, University of California, Los Angeles, UCLA