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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Economists are increasingly using computer simulations to understand the implications of theoretical models and to make policy recommendations. Model solution techniques are required to deal with the role of dynamics and uncertainty in macroeconomics. These articles show how to use these techniques in the context of standard macroeconomic models.
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1. Introduction ; 2. Linear Quadratic Approximations: An Introduction ; 3. A Toolkit for Analyzing Nonlinear Dynamic Stochastic Models Easily ; 4. Solving Nonlinear Rational Expectations Models by Eigenvalue-Eigenvector Decompositions ; Part II. Non-Linear Methods ; 6. Application of Weighted Residual Methods to Dynamic Economic Models ; 7. The Parametrized Expectations Approach: Some Practical Issues ; 8. Finite-Difference Methods for Continuous-Time Dynamic Programming ; Part III. Solving some dynamic economies ; 10. Computing Models of Social Security ; 11. Computation of Equilibria in Heterogenous Agent Economies
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an excellent introduction to computational methods for the study of stochastic rational expectations models. Leading researchers in the field cover the main numerical techniques currently applied in the computation of business cycle and growth models. Possibly the greatest merit of this volume is to provide a basis for graduate students from which they can start their own research.
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`an excellent introduction to computational methods for the study of stochastic rational expectations models. Leading researchers in the field cover the main numerical techniques currently applied in the computation of business cycle and growth models. Possibly the greatest merit of this volume is to provide a basis for graduate students from which they can start their own research.' Dr Burkhard Heer, KYKLOS
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Provides an essential toolkit of computational techniques Accessible introduction to crucial techniques
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.
Les mer
Provides an essential toolkit of computational techniques Accessible introduction to crucial techniques

Produktdetaljer

ISBN
9780198294979
Publisert
1999
Utgiver
Vendor
Oxford University Press
Vekt
565 gr
Høyde
242 mm
Bredde
164 mm
Dybde
21 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
292

Biographical note

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.