Handbook of Computational Economics

Author:   Karl Schmedders (Department of Business Administration, University of Zurich, Switzerland) ,  Kenneth L. Judd (Hoover Institution, Stanford, CA, USA)
Publisher:   Elsevier Science & Technology
Volume:   3
ISBN:  

9780444529800


Pages:   688
Publication Date:   16 December 2013
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Handbook of Computational Economics


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Overview

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.

Full Product Details

Author:   Karl Schmedders (Department of Business Administration, University of Zurich, Switzerland) ,  Kenneth L. Judd (Hoover Institution, Stanford, CA, USA)
Publisher:   Elsevier Science & Technology
Imprint:   North-Holland
Volume:   3
Dimensions:   Width: 19.10cm , Height: 3.60cm , Length: 23.50cm
Weight:   1.380kg
ISBN:  

9780444529800


ISBN 10:   0444529802
Pages:   688
Publication Date:   16 December 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Learning About Learning in Dynamic Economic Models - David A. Kendrick, Hans M. Amman, & Marco P. Tucci On the Numerical Solution of Equilibria in Auction Models with Asymmetries within the Private-Values Paradigm - Timothy P. Hubbard & Harry Paarsch Analyzing Fiscal Policies in a Heterogeneous-Agent Overlapping Generations Economy - Shinichi Nishiyama & Kent Smetters On Formulating and Solving Portfolio Decision and Asset Pricing Problems - Yu Chen, Thomas F. Cosimano, & Alex A. Himonas Computational Methods for Derivatives with Early Exercise Features - Carl Chiarella, Boda Kang, Gunter Meyer, & Andrew Ziogas Solving and Simulating Models with Heterogeneous Agents and Aggregate Uncertainty - Yann Algan, Olivier Allais, Wouter J. den Haan, & Pontius Rendahl Numerical Methods for Large Scale Dynamic Economic Models - Lilia Maliar & Serguei Maliar Advances in Numerical Dynamic Programming and New Applications - Yongyang Cai & Kenneth L. Judd Accuracy of Numerical Errors - Adrian Peralta-Alva & Manuel S. Santos GPU Computing in Economics - Eric Aldrich Computing All Solutions to Polynomial Equations in Economics - Felix Kubler, Philipp Renner, & Karl Schmedders

Reviews

Volume 3 in the Handbook of Computational Economics series, which reviews the development of computational algorithms yielding approximate equilibrium solutions for analytically modeled dynamic economic systems, provides a useful complement to Volume 2 stressing the computational modeling of economic processes as open-ended dynamic systems of interacting agents. As noted in the Preface for Volume 2, the identification of potential equilibria, together with their basins of attraction, is essential for understanding the full capabilities of dynamic economic systems. --Leigh Tesfatsion, Iowa State University In 15 years computational methods have developed into indispensable tools for modern economic analysis. While traditional mathematical analysis is often limited to a rather abstract and simplified framework, recent computational tools allow researchers to tackle models and problems under much more general and realistic assumptions, such as agents' heterogeneity, nonlinearity, and large scale models. 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


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


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


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