Handbook of Computational Economics

Handbook of Computational Economics

by Karl Schmedders, Kenneth L. Judd
Released December 2013
Publisher(s): North Holland
ISBN: 9780080931784

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Book description

Handbook of Computational Economics summarizes recent advances in economic thought, revealing some of the potential offered by modern computational methods. With computational power increasing in hardware and algorithms, many economists are closing the gap between economic practice and the frontiers of computational mathematics. In their efforts to accelerate the incorporation of computational power into mainstream research, contributors to this volume update the improvements in algorithms that have sharpened econometric tools, solution methods for dynamic optimization and equilibrium models, and applications to public finance, macroeconomics, and auctions. They also cover the switch to massive parallelism in the creation of more powerful computers, with advances in the development of high-power and high-throughput computing.

Much more can be done to expand the value of computational modeling in economics. In conjunction with volume one (1996) and volume two (2006), this volume offers a remarkable picture of the recent development of economics as a science as well as an exciting preview of its future potential.

  • Samples different styles and approaches, reflecting the breadth of computational economics as practiced today
  • Focuses on problems with few well-developed solutions in the literature of other disciplines
  • Emphasizes the potential for increasing the value of computational modeling in economics

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributors
  6. Acknowledgments
  7. Introduction to the Series
  8. Introduction for Volume 3 of the Handbook of Computational Economics
  9. Chapter 1. Learning About Learning in Dynamic Economic Models
    1. Abstract
    2. 1 Introduction
    3. 2 The Framework
    4. 3 What We Have Learned
    5. 4 What We Hope to Learn
    6. 5 Algorithms and Codes
    7. 6 A Showcase on Active Learning
    8. 7 Learning with Forward Looking Variables
    9. 8 Other Applications of Active Learning
    10. 9 Summary
    11. References
  10. Chapter 2. On the Numerical Solution of Equilibria in Auction Models with Asymmetries within the Private-Values Paradigm
    1. Abstract
    2. 1 Motivation and Introduction
    3. 2 Theoretical Model
    4. 3 Primer on Relevant Numerical Strategies
    5. 4 Previous Research Concerning Numerical Solutions
    6. 5 Some Examples
    7. 6 Comparisons of Relative Performance and Potential Improvements
    8. 7 Summary and Conclusions
    9. Acknowledgments
    10. References
  11. Chapter 3. Analyzing Fiscal Policies in a Heterogeneous-Agent Overlapping-Generations Economy
    1. Abstract
    2. 1 Introduction
    3. 2 Existing Literature
    4. 3 Stylized Model Economy
    5. 4 Computational Algorithm
    6. 5 Calibration to the US Economy
    7. 6 Policy Experiments
    8. 7 Concluding Remarks
    9. References
  12. Chapter 4. On Formulating and Solving Portfolio Decision and Asset Pricing Problems
    1. Abstract
    2. 1 Introduction
    3. 2 Discrete Time Portfolio Decision Making
    4. 3 Discrete Time Asset Pricing
    5. 4 Continuous Time Portfolio Decision Problem
    6. 5 Continuous Time Asset Pricing
    7. 6 Conclusion
    8. Acknowledgments
    9. References
  13. Chapter 5. Computational Methods for Derivatives with Early Exercise Features
    1. Abstract
    2. 1 General Introduction
    3. 2 The Problem Statement—In the Case of Stochastic Volatility and Poisson Jump Dynamics
    4. 3 American Call Options Under Jump-Diffusion Processes
    5. 4 American Call Options under Jump-Diffusion and Stochastic Volatility Processes
    6. 5 Conclusion
    7. References
  14. Chapter 6. Solving and Simulating Models with Heterogeneous Agents and Aggregate Uncertainty
    1. Abstract
    2. 1 Introduction
    3. 2 Example Economy
    4. 3 Algorithms—Overview
    5. 4 Models with Nontrivial Market Clearing
    6. 5 Approximate Aggregation
    7. 6 Simulation with a Continuum of Agents
    8. 7 Accuracy
    9. 8 Comparison
    10. 9 Other Types of Heterogeneity
    11. 10 Concluding Comments
    12. Acknowledgments
    13. References
  15. Chapter 7. Numerical Methods for Large-Scale Dynamic Economic Models
    1. Abstract
    2. 1 Introduction
    3. 2 Literature Review
    4. 3 The Chapter at a Glance
    5. 4 Nonproduct Approaches to Representing, Approximating, and Interpolating Functions
    6. 5 Approximation of Integrals
    7. 6 Derivative-Free Optimization Methods
    8. 7 Dynamic Programming Methods for High-Dimensional Problems
    9. 8 Precomputation Techniques
    10. 9 Local (Perturbation) Methods
    11. 10 Parallel Computation
    12. 11 Numerical Analysis of a High-Dimensional Model
    13. 12 Numerical Results for the Multicountry Model
    14. 13 Conclusion
    15. Acknowledgments
    16. References
  16. Chapter 8. Advances in Numerical Dynamic Programming and New Applications
    1. Abstract
    2. 1 Introduction
    3. 2 Theoretical Challenges
    4. 3 Numerical Methods for Dynamic Programming
    5. 4 Tools from Numerical Analysis
    6. 5 Shape-preserving Dynamic Programming
    7. 6 Parallelization
    8. 7 Dynamic Portfolio Optimization with Transaction Costs
    9. 8 Dynamic Stochastic Integration of Climate and Economy
    10. 9 Conclusions
    11. Acknowledgments
    12. References
  17. Chapter 9. Analysis of Numerical Errors
    1. Abstract
    2. 1 Introduction
    3. 2 Dynamic Stochastic Economies
    4. 3 Numerical Solution of Simple Markov Equilibria
    5. 4 Recursive Methods for Non-optimal Economies
    6. 5 Numerical Experiments
    7. 6 Concluding Remarks
    8. References
  18. Chapter 10. GPU Computing in Economics
    1. Abstract
    2. 1 Introduction
    3. 2 Basics of GPGPU Computing
    4. 3 A Simple GPGPU Example
    5. 4 Example: Value Function Iteration
    6. 5 Example: A General Equilibrium Asset Pricing Model with Heterogeneous Beliefs
    7. 6 The Road Ahead
    8. 7 Conclusion
    9. References
  19. Chapter 11. Computing All Solutions to Polynomial Equations in Economics
    1. Abstract
    2. 1 Introduction
    3. 2 Gröbner Bases and Polynomial Equations
    4. 3 Applying Gröbner Bases to Economic Models
    5. 4 All-Solution Homotopy Methods
    6. 5 Applying Homotopy Methods
    7. 6 Conclusion
    8. Acknowledgments
    9. References
  20. Index

Product information

  • Title: Handbook of Computational Economics
  • Author(s): Karl Schmedders, Kenneth L. Judd
  • Release date: December 2013
  • Publisher(s): North Holland
  • ISBN: 9780080931784