Handbook of Computational Economics - 1st Edition - ISBN: 9780444529800, 9780080931784

Handbook of Computational Economics, Volume 3

1st Edition

Editors: Karl Schmedders Kenneth Judd
eBook ISBN: 9780080931784
Hardcover ISBN: 9780444529800
Imprint: North Holland
Published Date: 13th December 2013
Page Count: 688
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Table of Contents



Introduction to the Series

Introduction for Volume 3 of the Handbook of Computational Economics

Chapter 1. Learning About Learning in Dynamic Economic Models


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


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


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



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


1 Introduction

2 Existing Literature

3 Stylized Model Economy

4 Computational Algorithm

5 Calibration to the US Economy

6 Policy Experiments

7 Concluding Remarks


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


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



Chapter 5. Computational Methods for Derivatives with Early Exercise Features


1 General Introduction

2 The Problem Statement—In the Case of Stochastic Volatility and Poisson Jump Dynamics

3 American Call Options Under Jump-Diffusion Processes

4 American Call Options under Jump-Diffusion and Stochastic Volatility Processes

5 Conclusion


Chapter 6. Solving and Simulating Models with Heterogeneous Agents and Aggregate Uncertainty


1 Introduction

2 Example Economy

3 Algorithms—Overview

4 Models with Nontrivial Market Clearing

5 Approximate Aggregation

6 Simulation with a Continuum of Agents

7 Accuracy

8 Comparison

9 Other Types of Heterogeneity

10 Concluding Comments



Chapter 7. Numerical Methods for Large-Scale Dynamic Economic Models


1 Introduction

2 Literature Review

3 The Chapter at a Glance

4 Nonproduct Approaches to Representing, Approximating, and Interpolating Functions

5 Approximation of Integrals

6 Derivative-Free Optimization Methods

7 Dynamic Programming Methods for High-Dimensional Problems

8 Precomputation Techniques

9 Local (Perturbation) Methods

10 Parallel Computation

11 Numerical Analysis of a High-Dimensional Model

12 Numerical Results for the Multicountry Model

13 Conclusion



Chapter 8. Advances in Numerical Dynamic Programming and New Applications


1 Introduction

2 Theoretical Challenges

3 Numerical Methods for Dynamic Programming

4 Tools from Numerical Analysis

5 Shape-preserving Dynamic Programming

6 Parallelization

7 Dynamic Portfolio Optimization with Transaction Costs

8 Dynamic Stochastic Integration of Climate and Economy

9 Conclusions



Chapter 9. Analysis of Numerical Errors


1 Introduction

2 Dynamic Stochastic Economies

3 Numerical Solution of Simple Markov Equilibria

4 Recursive Methods for Non-optimal Economies

5 Numerical Experiments

6 Concluding Remarks


Chapter 10. GPU Computing in Economics


1 Introduction

2 Basics of GPGPU Computing

3 A Simple GPGPU Example

4 Example: Value Function Iteration

5 Example: A General Equilibrium Asset Pricing Model with Heterogeneous Beliefs

6 The Road Ahead

7 Conclusion


Chapter 11. Computing All Solutions to Polynomial Equations in Economics


1 Introduction

2 Gröbner Bases and Polynomial Equations

3 Applying Gröbner Bases to Economic Models

4 All-Solution Homotopy Methods

5 Applying Homotopy Methods

6 Conclusion





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


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


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"...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

Ratings and Reviews

About the Editors

Karl Schmedders Editor

Affiliations and Expertise

Department of Business Administration, University of Zurich, Switzerland

Kenneth Judd Editor

Affiliations and Expertise

Hoover Institution, Stanford, CA, USA