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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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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Hardcover. Condición: new. Hardcover. 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 arecovered, 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 theoreticalmodels. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9780198294979
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