Computational Methods for the Study of Dynamic Economies

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Overview

Macroeconomics increasingly uses stochastic dynamic general equilibrium models to understand theoretical and policy issues. Unless very strong assumptions are made, understanding the properties of particular models requires solving the model using a computer. This volume brings together leading contributors in the field who explain in detail how to implement the computational techniques needed to solve dynamic economics models. A broad spread of techniques are covered, and their application in a wide range of subjects discussed. The book provides the basics of a toolkit which researchers and graduate students can use to solve and analyse their own theoretical models.
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Product Details

  • ISBN-13: 9780198294979
  • Publisher: Oxford University Press
  • Publication date: 4/29/1999
  • Pages: 296
  • Lexile: 1500L (what's this?)
  • Product dimensions: 6.30 (w) x 9.30 (h) x 1.00 (d)

Meet the Author

Ramon Marimon is Professor at the European University Institute, Florence.

Andrew Scott is Associate Professor at the London Business School, and a Fellow of CEPR. A Fellow of All Souls College, Oxford, he has also been Visiting Professor at Harvard University.

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Table of Contents

Contributors
1 Introduction: From pipeline economics to computational economics 1
Pt. I Almost linear methods
2 Linear quadratic approximations: An introduction 13
3 A toolkit for analysing nonlinear dynamic stochastic models easily 30
4 Solving nonlinear rational expectations models by eigenvalue - eigenvector decompositions 62
Pt. II Nonlinear methods
5 Discrete state-space methods for the study of dynamic economies 95
6 Application of weighted residual methods to dynamic economic models 114
7 The parameterized expectations approach: Some practical issues 143
8 Finite-difference methods for continuous-time dynamic programming 172
Pt. III Solving some dynamic economies
9 Optimal fiscal policy in a linear stochastic economy 197
10 Computing models of social security 221
11 Computation of equilibria in heterogeneous-agent models 238
References 265
Subject index 275
Author index 279
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