Computational Methods for the Study of Dynamic Economies

• Provides an essential toolkit of computational techniques
• Accessible introduction to crucial techniques

Readership: Graduate students and researchers in macroeconomics; advisors on economic policy.

Edited by Ramon Marimon, European University Institute, Florence, and Andrew Scott, London Business School

Review(s) from previous edition

"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

1: Ramon Marimon and Andrew Scott: Introduction
2: Javier Diaz-Gimenez: Linear Quadratic Approximations: An Introduction
3: Harald Uhlig: A Toolkit for Analyzing Nonlinear Dynamic Stochastic Models Easily
4: Alfonso Novales, Emilio Dominguez, Javier Perez and Jesus Ruiz: Solving Nonlinear Rational Expectations Models by Eigenvalue-Eigenvector Decompositions
Part II.: Craig Burnside: Non-Linear Methods
6: Ellen McGratten: Application of Weighted Residual Methods to Dynamic Economic Models
7: Albert Marcet and Guido Lorenzoni: The Parametrized Expectations Approach: Some Practical Issues
8: Graham V. Candler: Finite-Difference Methods for Continuous-Time Dynamic Programming
Part III.: Thomas J. Sargent and Francois R. Velde: Solving some dynamic economies
10: Douglas H. Joines, Ayse Imrohoroglu and Selo Imrohoroglu: Computing Models of Social Security
11: Jose Victor Rios-Rull: Computation of Equilibria in Heterogenous Agent Economies