Computational Methods for the Study of Dynamic Economies
Ramon Marimon and Andrew Scott
Abstract
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. It is based on lectures presented at the 7th Summer School of the European Economic Association on computational methods for the study of dynamic economies, held in 199 ... More
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. It is based on lectures presented at the 7th Summer School of the European Economic Association on computational methods for the study of dynamic economies, held in 1996. A broad spread of techniques is covered, and their application to a wide range of subjects discussed. The book provides the basics of a tool kit that researchers and graduate students can use to solve and analyse their own theoretical models. It is oriented towards economists who already have the equivalent of a first year of graduate studies or to any advanced undergraduates or researchers with a solid mathematical background. No competence with writing computer codes is assumed. After an introduction by the editors, it is arranged in three parts: I Almost linear methods; II Nonlinear methods; and III Solving some dynamic economies.
Keywords:
computational economics,
dynamic economics models,
dynamic economies,
general equilibrium models,
linear models,
Macroeconomics,
mathematical models,
nonlinear models,
stochastic dynamic general equilibrium models
Bibliographic Information
Print publication date: 2001 |
Print ISBN-13: 9780199248278 |
Published to Oxford Scholarship Online: November 2003 |
DOI:10.1093/0199248273.001.0001 |
Authors
Affiliations are at time of print publication.
Ramon Marimon, editor
European University Institute, Florence
Author Webpage
Andrew Scott, editor
London Business School
Author Webpage
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