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.

Key Features

  • 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

Readership

Upper-division undergraduates, graduate students, and professionals worldwide working on economic analyses.

Table of Contents

Contributors

Acknowledgments

Introduction to the Series

Introduction for Volume 3 of the Handbook of Computational Economics

Chapter 1. Learning About Learning in Dynamic Economic Models

Abstract

1 Introduction

2 The Framework

3 What We Have Learned

4 What We Hope to Learn

5 Algorithms and Codes

6 A Showcase on Active Learning

7 Learning with Forward Looking Variables

8 Other Applications of Active Learning

9 Summary

References

Chapter 2. On the Numerical Solution of Equilibria in Auction Models with Asymmetries within the Private-Values Paradigm

Abstract

1 Motivation and Introduction

2 Theoretical Model

3 Primer on Relevant Numerical Strategies

4 Previous Research Concerning Numerical Solutions

5 Some Examples

6 Comparisons of Relative Performance and Potential Improvements

7 Summary and Conclusions

Acknowledgments

References

Chapter 3. Analyzing Fiscal Policies in a Heterogeneous-Agent Overlapping-Generations Economy

Abstract

1 Introduction

2 Existing Literature

3 Stylized Model Economy

4 Computational Algorithm

5 Calibration to the US Economy

6 Policy Experiments

7 Concluding Remarks

References

Chapter 4. On Formulating and Solving Portfolio Decision and Asset Pricing Problems

Abstract

1 Introduction

2 Discrete Time Portfolio Decision Making

3 Discrete Time Asset Pricing

4 Continuous Time Portfolio Decision Problem

5 Continuous Time Asset Pricing

6 Conclusion

Acknowledgments

References

Chapter 5. Computational Methods for Derivatives with Early Exercise Features

Abstract

1 General Introduction

2 The Problem Statement—In the Case of Stochastic Volatility and Pois

Details

No. of pages:
688
Language:
English
Copyright:
© 2014
Published:
Imprint:
North Holland
Electronic ISBN:
9780080931784
Print ISBN:
9780444529800

About the editors

Reviews

"...indispensable reference works which belong in every professional collection, and form ideal supplementary reading for graduate economics students on advanced courses."--Zentralblatt MATH, Sep-14

"In this volume the best experts show the breadth and depth of the state of the art of computational tools ready to accurately compute solutions and equilibria with a wide range of applications and models in macroeconomics and finance."  --Cars Hommes, University of Amsterdam

"Volume 3 of the Handbook of Computational Economics, which reviews the development of computational algorithms yielding approximate equilibrium solutions for analytically modeled dynamic economic systems, provides a useful complement to Volume 2, which introduced agent-based computational economic (ACE) modeling tools for the computational study of economic processes as open-ended dynamic systems of interacting agents.  Particular attention is focused on dynamic stochastic models that generalize traditional assumptions regarding agent heterogeneity, preference specifications, decision horizons, state-space characteristics, market imperfections, idiosyncratic risks, and aggregate uncertainty. Building on earlier simulation techniques, the computational algorithms incorporate recent advances in projection methods and perturbation techniques."   --Leigh Tesfatsion, Iowa State University