Dynamic factor models:
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 ri...
Gespeichert in:
| Weitere beteiligte Personen: | , |
|---|---|
| Format: | E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Bingley, U.K.
Emerald
2016
|
| Schriftenreihe: | Advances in econometrics
v. 35 |
| Links: | https://doi.org/10.1108/S0731-9053201635 |
| Zusammenfassung: | 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. |
| Umfang: | 1 Online-Ressource (410 Seiten) Illustrationen |
| ISBN: | 9781785603525 (electronic bk.) |
| ISSN: | 0731-9053 |
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| spelling | Dynamic factor models edited by Eric Hillebrand, Siem Jan Koopman Bingley, U.K. Emerald 2016 1 Online-Ressource (410 Seiten) Illustrationen txt c cr Advances in econometrics 0731-9053 v. 35 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. Hillebrand, Eric Koopman, S. J. Erscheint auch als Druck-Ausgabe 9781785603532 |
| spellingShingle | Dynamic factor models |
| title | Dynamic factor models |
| title_auth | Dynamic factor models |
| title_exact_search | Dynamic factor models |
| title_full | Dynamic factor models edited by Eric Hillebrand, Siem Jan Koopman |
| title_fullStr | Dynamic factor models edited by Eric Hillebrand, Siem Jan Koopman |
| title_full_unstemmed | Dynamic factor models edited by Eric Hillebrand, Siem Jan Koopman |
| title_short | Dynamic factor models |
| title_sort | dynamic factor models |
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