Dynamic Factor Models Vol: 35

Siem Jan Koopman
Vrije Universiteit (VU) Amsterdam, The Netherlands

Eric Hillebrand
Aarhus University, Denmark

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Product Details
08 Jan 2016
Emerald Group Publishing Limited
688 pages - 152 x 229 x 40mm
Advances in Econometrics
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.
PART I: METHODOLOGY An Overview of the Factor-Augmented Error-Correction Model - Anindya Banerjee, Massimiliano Marcellino and Igor Masten Estimation of VAR Systems from Mixed-Frequency Data: the Stock and the Flow Case - Lukas Koelbl, Alexander Braumann, Elisabeth Felsenstein and Manfred Deistler Modelling Yields at the Zero Lower Bound: Are Shadow Rates the Solution? - Jens H. E. Christensen and Glenn D. Rudebusch Dynamic Factor Models for the Volatility Surface - Michel Van Der Wel, Sait R. Ozturk and Dick Van Dijk PART II: FACTOR STRUCTURE AND SPECIFICATION Analyzing International Business and Financial Cycles Using Multi-Level Factor Models: a Comparison of Alternative Approaches - Jorg Breitung and Sandra Eickmeier Fast ML Estimation of Dynamic Bifactor Models: an Application to European Inflation - Gabriele Fiorentini, Alessandro Galesi and Enrique Sentana Country Shocks, Monetary Policy Expectations and ECB Decisions. a Dynamic Non-Linear Approach - Maximo Camacho, Danilo Leiva-Leon and Gabriel Perez-Quiros Modelling Financial Markets Comovements During Crises: a Dynamic Multi-Factor Approach - Martin Belvisi, Riccardo Pianeti and Giovanni Urga Specification and Estimation of Bayesian Dynamic Factor Models: a Monte Carlo Analysis with an Application to Global House Price Comovement - Laura E. Jackson, M. Ayhan Kose, Christopher Otrok and Michael T. Owyang Small-versus Big-Data Factor Extraction In Dynamic Factor Models: an Empirical Assessment - Pilar Poncela and Esther Ruiz PART III: INSTABILITY Regularized Estimation of Structural Instability In Factor Models: the US Macroeconomy and the Great Moderation - Laurent Callot and Johannes Tang Kristensen Dating Business Cycle Turning Points for the French Economy: an MS-DFM Approach - Catherine Doz and Anna Petronevich Common Faith or Parting Ways? a Time Varying Parameters Factor Analysis of Euro-Area Inflation - Davide Delle Monache, Ivan Petrella and Fabrizio Venditti PART IV: NOWCASTING AND FORECASTING Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models - Antonello D’Agostino, Domenico Giannone, Michele Lenza and Michele Modugno On the Selection of Common Factors for Macroeconomic Forecasting - Alessandro Giovannelli and Tommaso Proietti On the Design of Data Sets for Forecasting with Dynamic Factor Models - Gerhard Runstler
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
Editors Hillebrand and Koopman present students, academics, researchers, and professionals working in a wide variety of contexts with a collection of academic and expert contributions on the use of dynamic factor models (DFM) in the study of econometrics, macroeconomics, and finance. The editors have organized the contributions that make up the main body of their text in four parts devoted to methodology, factor structure and specification, instability, and nowcasting and forecasting. Eric Hillebrand is a faculty member of Aarhus University, Denmark. Siem Jan Koopman is a faculty member of VU University, The Netherlands. Distributed in North America by Turpin Distribution.

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