Dynamic Factor Models

Siem Jan Koopman

ISBN 10: 1785603531 / ISBN 13: 9781785603532

Published by Emerald Publishing Limited, GB, 2016

About this Item

Dynamic factor models (DFM) constitute an active and growing area of research, both in econometrics, in macroeconomics, and in finance. Many applications lie at the center of policy questions raised by the recent financial crises, such as the connections between yields on government debt, credit risk, inflation, and economic growth. This volume collects a key selection of up-to-date contributions that cover a wide range of issues in the context of dynamic factor modeling, such as specification, estimation, and application of DFMs. Examples include further developments in DFM for mixed-frequency data settings, extensions to time-varying parameters and structural breaks, for multi-level factors associated with subsets of variables, in factor augmented error correction models, and in many other related aspects. A number of contributions propose new estimation procedures for DFM, such as spectral expectation-maximization algorithms and Bayesian approaches. Numerous applications are discussed, including the dating of business cycles, implied volatility surfaces, professional forecaster survey data, and many more.

Seller Inventory # LU-9781785603532

Bibliographic Details

• Title: Dynamic Factor Models
• Publisher: Emerald Publishing Limited, GB
• Publication Date: 2016
• Language: English
• ISBN 10: 1785603531
• ISBN 13: 9781785603532
• Binding: Hardback
• Condition: New
• Weight: 666 grams

About this title

Synopsis

Dynamic factor models (DFM) constitute an active and growing area of research, both in econometrics, in macroeconomics, and in finance. Many applications lie at the center of policy questions raised by the recent financial crises, such as the connections between yields on government debt, credit risk, inflation, and economic growth. This volume collects a key selection of up-to-date contributions that cover a wide range of issues in the context of dynamic factor modeling, such as specification, estimation, and application of DFMs. Examples include further developments in DFM for mixed-frequency data settings, extensions to time-varying parameters and structural breaks, for multi-level factors associated with subsets of variables, in factor augmented error correction models, and in many other related aspects. A number of contributions propose new estimation procedures for DFM, such as spectral expectation-maximization algorithms and Bayesian approaches. Numerous applications are discussed, including the dating of business cycles, implied volatility surfaces, professional forecaster survey data, and many more.

About the Author

Edited by Eric Hillebrand, Department of Economics and Business Economics and CREATES, Aarhus University, Aarhus, Denmark Siem Jan Koopman, Department of Econometrics, Vrije Universiteit Amsterdam, The Netherlands, Tinbergen Institute and CREATES