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Zusatztext 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. Informationen zum Autor 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. Klappentext Macroeconomics increasingly uses stochastic dynamic general equilibrium models to understand theoretical and policy issues. Unles 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. Zusammenfassung 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. Inhaltsverzeichnis 1Part 1.: Ramon Marimon and Andrew Scott: IntroductionAlmost Linear Methods 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.5: Craig Burnside: Non-Linear MethodsDiscrete State-Space Methods for the Study of Dynamic Economies 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.9: Thomas J. Sargent and Francois R. Velde: Solving some dynamic economiesOptimal Fiscal Policy in a Linear Stochastic Economy 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 ...
