Dynamic factor models /:
This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.
Saved in:
| Other Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
United Kingdom :
Emerald Group Publishing Limited,
2016.
|
| Edition: | First edition. |
| Series: | Advances in econometrics ;
vol. 35. |
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications. |
| Physical Description: | 1 online resource |
| Bibliography: | Includes bibliographical references. |
| ISBN: | 9781785603525 1785603523 1785603531 9781785603532 |
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| 245 | 0 | 0 | |a Dynamic factor models / |c edited by Eric Hillebrand, Siem Jan Koopman. |
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| 505 | 0 | |a Front Cover; Dynamic Factor Models; Copyright page; Contents; List of Contributors; Editorial Introduction; Dynamic Factor Models: A Brief Retrospective; Notes; References; Part I: Methodology; An Overview of the Factor-augmented Error-Correction Model; 1. Introduction; 2. Factor-augmented error-correction model; 2.1. Representation of the FECM; 2.2. The FECM Form for Forecasting; 2.3. The FECM Form for Structural Analysis; 3. Data and empirical applications; 4. Forecasting macroeconomic variables; 4.1. Forecasting Results for the Euro Area; 4.2. Forecasting Results for the United States. | |
| 505 | 8 | |a 4.3. Robustness Check to I(1) Idiosyncratic Errors5. Transmission of Monetary Policy Shocks in the FECM; 6. Conclusions; Notes; Acknowledgements; References; Appendix A. Additional Forecasting Results; Estimation of VAR Systems from Mixed-Frequency Data: The Stock and the Flow Case; 1. Introduction; 2. Mixed-Frequency Estimators; 2.1 Extended Yule-Walker Estimators: The Stock Case; 2.2 Extended Yule-Walker Estimators: The General Case; 2.3 Maximum Likelihood Estimation and the EM Algorithm; 3. Projecting the MF Estimators on the Parameter Space. | |
| 505 | 8 | |a 3.1 Stabilization of the Estimated System Parameters3.2 Positive (Semi)-Definiteness of the Noise Covariance Matrix; 4. Asymptotic Properties of the XYW/GMM Estimators; 5. Simulations; 6. Outlook and Conclusions; Acknowledgments; References; Appendix; Modeling Yields at the Zero Lower Bound: Are Shadow Rates the Solution?; 1. Introduction; 2. A Standard Gaussian Term Structure Model; 2.1. The General Model; 2.2. The CR Model; 2.3. Negative Short-Rate Projections in Standard Models; 3. A Shadow-Rate Model; 3.1. The Option-Based Approach to the Shadow-Rate Model; 3.2. The B-CR Model. | |
| 505 | 8 | |a 3.3. Measuring the Effect of the ZLB3.4. Nonzero Lower Bound for the Short Rate; 4. Comparing Affine and Shadow-Rate Models; 4.1. Analysis of Parameter Estimates; 4.2. In-Sample Fit and Yield Volatility; 4.3. Forecast Performance; 4.3.1. Short-Rate Forecasts; 4.3.2. Yield Forecasts; 4.4. Decomposing 10-Year Yields; 4.5. Assessing Recent Shifts in Near-Term Monetary Policy Expectations; 5. Conclusion; Notes; Acknowledgments; References; Appendix A: How Good is the Option-Based Approximation?; Appendix B: Formula for Policy Expectations in AFNS and B-AFNS Models. | |
| 505 | 8 | |a Appendix C: Analytical Formulas for Averages of Policy Expectations and for Term Premiums in the CR ModelDynamic Factor Models for the Volatility Surface; 1. Introduction; 2. Volatility Surface Data; 2.1. Constructing the Volatility Surface; 2.2. Summary Statistics and Preliminary Analysis; 3. Models for the Volatility Surface; 3.1. General DFM; 3.2. Restricted Economic DFMs; 3.3. Spline-Based DFMs; 4. Main Results; 5. Robustness and Extensions; 5.1. Alternative Surface Construction; 5.2. Higher-Dimensional Models; 5.3. Alternative Factor Dynamics. | |
| 520 | |a This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications. | ||
| 650 | 0 | |a Macroeconomics. |0 http://id.loc.gov/authorities/subjects/sh85079443 | |
| 650 | 0 | |a Macroeconomics |x Econometric models. |0 http://id.loc.gov/authorities/subjects/sh2008107159 | |
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| contents | Front Cover; Dynamic Factor Models; Copyright page; Contents; List of Contributors; Editorial Introduction; Dynamic Factor Models: A Brief Retrospective; Notes; References; Part I: Methodology; An Overview of the Factor-augmented Error-Correction Model; 1. Introduction; 2. Factor-augmented error-correction model; 2.1. Representation of the FECM; 2.2. The FECM Form for Forecasting; 2.3. The FECM Form for Structural Analysis; 3. Data and empirical applications; 4. Forecasting macroeconomic variables; 4.1. Forecasting Results for the Euro Area; 4.2. Forecasting Results for the United States. 4.3. Robustness Check to I(1) Idiosyncratic Errors5. Transmission of Monetary Policy Shocks in the FECM; 6. Conclusions; Notes; Acknowledgements; References; Appendix A. Additional Forecasting Results; Estimation of VAR Systems from Mixed-Frequency Data: The Stock and the Flow Case; 1. Introduction; 2. Mixed-Frequency Estimators; 2.1 Extended Yule-Walker Estimators: The Stock Case; 2.2 Extended Yule-Walker Estimators: The General Case; 2.3 Maximum Likelihood Estimation and the EM Algorithm; 3. Projecting the MF Estimators on the Parameter Space. 3.1 Stabilization of the Estimated System Parameters3.2 Positive (Semi)-Definiteness of the Noise Covariance Matrix; 4. Asymptotic Properties of the XYW/GMM Estimators; 5. Simulations; 6. Outlook and Conclusions; Acknowledgments; References; Appendix; Modeling Yields at the Zero Lower Bound: Are Shadow Rates the Solution?; 1. Introduction; 2. A Standard Gaussian Term Structure Model; 2.1. The General Model; 2.2. The CR Model; 2.3. Negative Short-Rate Projections in Standard Models; 3. A Shadow-Rate Model; 3.1. The Option-Based Approach to the Shadow-Rate Model; 3.2. The B-CR Model. 3.3. Measuring the Effect of the ZLB3.4. Nonzero Lower Bound for the Short Rate; 4. Comparing Affine and Shadow-Rate Models; 4.1. Analysis of Parameter Estimates; 4.2. In-Sample Fit and Yield Volatility; 4.3. Forecast Performance; 4.3.1. Short-Rate Forecasts; 4.3.2. Yield Forecasts; 4.4. Decomposing 10-Year Yields; 4.5. Assessing Recent Shifts in Near-Term Monetary Policy Expectations; 5. Conclusion; Notes; Acknowledgments; References; Appendix A: How Good is the Option-Based Approximation?; Appendix B: Formula for Policy Expectations in AFNS and B-AFNS Models. Appendix C: Analytical Formulas for Averages of Policy Expectations and for Term Premiums in the CR ModelDynamic Factor Models for the Volatility Surface; 1. Introduction; 2. Volatility Surface Data; 2.1. Constructing the Volatility Surface; 2.2. Summary Statistics and Preliminary Analysis; 3. Models for the Volatility Surface; 3.1. General DFM; 3.2. Restricted Economic DFMs; 3.3. Spline-Based DFMs; 4. Main Results; 5. Robustness and Extensions; 5.1. Alternative Surface Construction; 5.2. Higher-Dimensional Models; 5.3. Alternative Factor Dynamics. |
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| id | ZDB-4-EBU-ocn935323958 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:27:55Z |
| institution | BVB |
| isbn | 9781785603525 1785603523 1785603531 9781785603532 |
| language | English |
| oclc_num | 935323958 |
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| publishDate | 2016 |
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| publisher | Emerald Group Publishing Limited, |
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| series | Advances in econometrics ; |
| series2 | Advances in econometrics ; |
| spelling | Dynamic factor models / edited by Eric Hillebrand, Siem Jan Koopman. First edition. United Kingdom : Emerald Group Publishing Limited, 2016. 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier Advances in econometrics ; vol. 35 Includes bibliographical references. Vendor-supplied metadata. Front Cover; Dynamic Factor Models; Copyright page; Contents; List of Contributors; Editorial Introduction; Dynamic Factor Models: A Brief Retrospective; Notes; References; Part I: Methodology; An Overview of the Factor-augmented Error-Correction Model; 1. Introduction; 2. Factor-augmented error-correction model; 2.1. Representation of the FECM; 2.2. The FECM Form for Forecasting; 2.3. The FECM Form for Structural Analysis; 3. Data and empirical applications; 4. Forecasting macroeconomic variables; 4.1. Forecasting Results for the Euro Area; 4.2. Forecasting Results for the United States. 4.3. Robustness Check to I(1) Idiosyncratic Errors5. Transmission of Monetary Policy Shocks in the FECM; 6. Conclusions; Notes; Acknowledgements; References; Appendix A. Additional Forecasting Results; Estimation of VAR Systems from Mixed-Frequency Data: The Stock and the Flow Case; 1. Introduction; 2. Mixed-Frequency Estimators; 2.1 Extended Yule-Walker Estimators: The Stock Case; 2.2 Extended Yule-Walker Estimators: The General Case; 2.3 Maximum Likelihood Estimation and the EM Algorithm; 3. Projecting the MF Estimators on the Parameter Space. 3.1 Stabilization of the Estimated System Parameters3.2 Positive (Semi)-Definiteness of the Noise Covariance Matrix; 4. Asymptotic Properties of the XYW/GMM Estimators; 5. Simulations; 6. Outlook and Conclusions; Acknowledgments; References; Appendix; Modeling Yields at the Zero Lower Bound: Are Shadow Rates the Solution?; 1. Introduction; 2. A Standard Gaussian Term Structure Model; 2.1. The General Model; 2.2. The CR Model; 2.3. Negative Short-Rate Projections in Standard Models; 3. A Shadow-Rate Model; 3.1. The Option-Based Approach to the Shadow-Rate Model; 3.2. The B-CR Model. 3.3. Measuring the Effect of the ZLB3.4. Nonzero Lower Bound for the Short Rate; 4. Comparing Affine and Shadow-Rate Models; 4.1. Analysis of Parameter Estimates; 4.2. In-Sample Fit and Yield Volatility; 4.3. Forecast Performance; 4.3.1. Short-Rate Forecasts; 4.3.2. Yield Forecasts; 4.4. Decomposing 10-Year Yields; 4.5. Assessing Recent Shifts in Near-Term Monetary Policy Expectations; 5. Conclusion; Notes; Acknowledgments; References; Appendix A: How Good is the Option-Based Approximation?; Appendix B: Formula for Policy Expectations in AFNS and B-AFNS Models. Appendix C: Analytical Formulas for Averages of Policy Expectations and for Term Premiums in the CR ModelDynamic Factor Models for the Volatility Surface; 1. Introduction; 2. Volatility Surface Data; 2.1. Constructing the Volatility Surface; 2.2. Summary Statistics and Preliminary Analysis; 3. Models for the Volatility Surface; 3.1. General DFM; 3.2. Restricted Economic DFMs; 3.3. Spline-Based DFMs; 4. Main Results; 5. Robustness and Extensions; 5.1. Alternative Surface Construction; 5.2. Higher-Dimensional Models; 5.3. Alternative Factor Dynamics. This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications. Macroeconomics. http://id.loc.gov/authorities/subjects/sh85079443 Macroeconomics Econometric models. http://id.loc.gov/authorities/subjects/sh2008107159 Macroéconomie. Econometrics. bicssc BUSINESS & ECONOMICS Economics Macroeconomics. bisacsh POLITICAL SCIENCE Economic Conditions. bisacsh Macroeconomics fast Macroeconomics Econometric models fast Hillebrand, Eric, editor. Koopman, S. J. (Siem Jan), editor. https://id.oclc.org/worldcat/entity/E39PBJtcMmxYthWRx97xxqDQbd http://id.loc.gov/authorities/names/n00008824 Print version: Hillebrand, Eric. Dynamic Factor Models. Bradford, West Yorkshire : Emerald Group Publishing Limited, ©2016 9781785603532 Advances in econometrics ; vol. 35. http://id.loc.gov/authorities/names/no98010995 |
| spellingShingle | Dynamic factor models / Advances in econometrics ; Front Cover; Dynamic Factor Models; Copyright page; Contents; List of Contributors; Editorial Introduction; Dynamic Factor Models: A Brief Retrospective; Notes; References; Part I: Methodology; An Overview of the Factor-augmented Error-Correction Model; 1. Introduction; 2. Factor-augmented error-correction model; 2.1. Representation of the FECM; 2.2. The FECM Form for Forecasting; 2.3. The FECM Form for Structural Analysis; 3. Data and empirical applications; 4. Forecasting macroeconomic variables; 4.1. Forecasting Results for the Euro Area; 4.2. Forecasting Results for the United States. 4.3. Robustness Check to I(1) Idiosyncratic Errors5. Transmission of Monetary Policy Shocks in the FECM; 6. Conclusions; Notes; Acknowledgements; References; Appendix A. Additional Forecasting Results; Estimation of VAR Systems from Mixed-Frequency Data: The Stock and the Flow Case; 1. Introduction; 2. Mixed-Frequency Estimators; 2.1 Extended Yule-Walker Estimators: The Stock Case; 2.2 Extended Yule-Walker Estimators: The General Case; 2.3 Maximum Likelihood Estimation and the EM Algorithm; 3. Projecting the MF Estimators on the Parameter Space. 3.1 Stabilization of the Estimated System Parameters3.2 Positive (Semi)-Definiteness of the Noise Covariance Matrix; 4. Asymptotic Properties of the XYW/GMM Estimators; 5. Simulations; 6. Outlook and Conclusions; Acknowledgments; References; Appendix; Modeling Yields at the Zero Lower Bound: Are Shadow Rates the Solution?; 1. Introduction; 2. A Standard Gaussian Term Structure Model; 2.1. The General Model; 2.2. The CR Model; 2.3. Negative Short-Rate Projections in Standard Models; 3. A Shadow-Rate Model; 3.1. The Option-Based Approach to the Shadow-Rate Model; 3.2. The B-CR Model. 3.3. Measuring the Effect of the ZLB3.4. Nonzero Lower Bound for the Short Rate; 4. Comparing Affine and Shadow-Rate Models; 4.1. Analysis of Parameter Estimates; 4.2. In-Sample Fit and Yield Volatility; 4.3. Forecast Performance; 4.3.1. Short-Rate Forecasts; 4.3.2. Yield Forecasts; 4.4. Decomposing 10-Year Yields; 4.5. Assessing Recent Shifts in Near-Term Monetary Policy Expectations; 5. Conclusion; Notes; Acknowledgments; References; Appendix A: How Good is the Option-Based Approximation?; Appendix B: Formula for Policy Expectations in AFNS and B-AFNS Models. Appendix C: Analytical Formulas for Averages of Policy Expectations and for Term Premiums in the CR ModelDynamic Factor Models for the Volatility Surface; 1. Introduction; 2. Volatility Surface Data; 2.1. Constructing the Volatility Surface; 2.2. Summary Statistics and Preliminary Analysis; 3. Models for the Volatility Surface; 3.1. General DFM; 3.2. Restricted Economic DFMs; 3.3. Spline-Based DFMs; 4. Main Results; 5. Robustness and Extensions; 5.1. Alternative Surface Construction; 5.2. Higher-Dimensional Models; 5.3. Alternative Factor Dynamics. Macroeconomics. http://id.loc.gov/authorities/subjects/sh85079443 Macroeconomics Econometric models. http://id.loc.gov/authorities/subjects/sh2008107159 Macroéconomie. Econometrics. bicssc BUSINESS & ECONOMICS Economics Macroeconomics. bisacsh POLITICAL SCIENCE Economic Conditions. bisacsh Macroeconomics fast Macroeconomics Econometric models fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85079443 http://id.loc.gov/authorities/subjects/sh2008107159 |
| 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 |
| topic | Macroeconomics. http://id.loc.gov/authorities/subjects/sh85079443 Macroeconomics Econometric models. http://id.loc.gov/authorities/subjects/sh2008107159 Macroéconomie. Econometrics. bicssc BUSINESS & ECONOMICS Economics Macroeconomics. bisacsh POLITICAL SCIENCE Economic Conditions. bisacsh Macroeconomics fast Macroeconomics Econometric models fast |
| topic_facet | Macroeconomics. Macroeconomics Econometric models. Macroéconomie. Econometrics. BUSINESS & ECONOMICS Economics Macroeconomics. POLITICAL SCIENCE Economic Conditions. Macroeconomics Macroeconomics Econometric models |
| work_keys_str_mv | AT hillebranderic dynamicfactormodels AT koopmansj dynamicfactormodels |