Numerical methods in economics

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Bibliographic Information

Numerical methods in economics

Kenneth L. Judd

MIT Press, c1998

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Includes bibliographical references (p. [609]-622) and index

Description and Table of Contents

Description

To harness the full power of computer technology, economists need to use a broad range of mathematical techniques. In this book, Kenneth Judd presents techniques from the numerical analysis and applied mathematics literatures and shows how to use them in economic analyses. The book is divided into five parts. Part I provides a general introduction. Part II presents basics from numerical analysis on R^n, including linear equations, iterative methods, optimization, nonlinear equations, approximation methods, numerical integration and differentiation, and Monte Carlo methods. Part III covers methods for dynamic problems, including finite difference methods, projection methods, and numerical dynamic programming. Part IV covers perturbation and asymptotic solution methods. Finally, Part V covers applications to dynamic equilibrium analysis, including solution methods for perfect foresight models and rational expectation models. A website contains supplementary material including programs and answers to exercises.

Table of Contents

  • Part 1 Introduction: introduction
  • elementary concepts in numerical analysis. Part 2 Basics from numerical analysis on Rn: linear equations and iterative methods
  • optimization
  • nonlinear equations
  • approximation methods
  • numerical integration and differentiation
  • Monte Carlo and simulation methods
  • quasi-Monte Carlo methods. Part 3 Numerical methods for functional problems: finite-difference methods
  • projection methods for functional equations
  • numerical dynamic programming. Part 4 Perturbation methods: regular perturbation of simple systems
  • regular perturbations in multidimensional systems
  • advanced asymptotic methods. Part 5 Applications to dynamic equilibrium analysis
  • solution methods for perfect foresight models
  • solving rational expectations models.

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