Computational Macroeconomics for the Open Economy

(Hardback)

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How to use nonlinear dynamic models in policy analysis.Policymakers need quantitative as well as qualitative answers to pressing policy questions. Because of advances in computational methods, quantitative estimates are now derived from coherent nonlinear dynamic macroeconomic models embodying measures of risk and calibrated to capture specific characteristics of real-world situations. This text shows how such models can be made accessible and operational for confronting policy issues. The book starts with a simple setting based on market-clearing price flexibility. It gradually incorporates departures from the simple competitive framework in the form of price and wage stickiness, taxes, rigidities in investment, financial frictions, and habit persistence in consumption. Most chapters end with computational exercises; the Matlab code for the base model can be found in the appendix. As the models evolve, readers are encouraged to modify the codes from the first simple model to more complex extensions. Computational Macroeconomics for the Open Economy can be used by graduate students in economics and finance as well as policy-oriented researchers.

Reviews

"Dynamic equilibrium models are at the center of modern research in open macroeconomics. However, graduate students and policy researchers often find it difficult to get started in this literature. Lim and McNelis' book fills this gap by providing an excellent introduction to the construction and solution of dynamic equilibrium models for small open economics. The authors carefully analyze a prototype economy, which they enrich in each chapter with new aspects, thus allowing the reader to learn the field naturally as the book progresses. Extensive documentation of the code used in the computations and numerous exercises complement the main discussion. Systematic yet concise, this monograph will become a popular reference for both students and researchers in the field."--Jesus Fernandez-Villaverde, Department of Economics University ofPennsylvania -- Jesus Fernandez-Villaverde "Lim and McNelis provide a manual that allows the diligent reader interested in open economy macroeconomics to move quickly to the frontier of research. This is not a book to gather dust on the bookshelf. It is a book to be first pored over carefully and then put to use."-- Timothy J. Kehoe, Department of Economics, University of Minnesota -- Tim Kehoe "Dynamic equilibrium models are at the center of modern research in open macroeconomics. However, graduate students and policy researchers often find it difficult to get started in this literature. Lim and McNelis' book fills this gap by providing an excellent introduction to the construction and solution of dynamic equilibrium models for small open economics. The authors carefully analyze a prototype economy, which they enrich in each chapter with new aspects, thus allowing the reader to learn the field naturally as the book progresses. Extensive documentation of the code used in the computations and numerous exercises complement the main discussion. Systematic yet concise, this monograph will become a popular reference for both students and researchers in the field." -- Jesus Fernandez-Villaverde , Department of Economics University of Pennsylvania "Lim and McNelis provide a manual that allows the diligent reader interested in open economy macroeconomics to move quickly to the frontier of research. This is not a book to gather dust on the bookshelf. It is a book to be first pored over carefully and then put to use." -- Timothy J. Kehoe , Department of Economics, University of Minnesota

Author Bio

G. C. Lim is Professorial Research Fellow at the Melbourne Institute of Applied Economic and Social Research, University of Melbourne. She is the coauthor of Dynamic Economic Models in Discrete Time- Theory and Empirical Applications and An Introduction to Dynamic Economic Models (both with Brian Ferguson). Paul D. McNelis is Robert Bendheim Chair of Economic and Financial Policy at Fordham University Graduate School of Business Administration. He is the author of Neural Networks in Finance- Gaining Predictive Edge in the Market.