State-space models with regime switching :: classical and Gibbs-sampling approaches with applications /
"Both state-space models and Markov-switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classi...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass. :
MIT Press,
©1999.
|
| Schriftenreihe: | MIT Press Ser.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | "Both state-space models and Markov-switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data."--Jacket |
| Beschreibung: | 1 online resource (xii, 297 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9780585087160 0585087164 9780262277112 0262277115 9780262112383 0262112388 |
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| 245 | 1 | 0 | |a State-space models with regime switching : |b classical and Gibbs-sampling approaches with applications / |c Chang-Jin Kim and Charles R. Nelson. |
| 260 | |a Cambridge, Mass. : |b MIT Press, |c ©1999. | ||
| 300 | |a 1 online resource (xii, 297 pages) : |b illustrations | ||
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| 490 | 1 | |a The MIT Press Ser. | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | 0 | |t State-Space Models and Markov Switching in Econometrics: A Brief History -- |t Computer Programs and Data -- |t The Classical Approach -- |t The Maximum Likelihood Estimation Method: Practical Issues -- |t Maximum Likelihood Estimation and the Covariance Matrix of OML -- |t The Prediction Error Decomposition and the Likelihood Function -- |t Parameter Constraints and the Covariance Matrix of OML -- |t State-Space Models and the Kalman Filter -- |t Time-Varying-Parameter Models and the Kalman Filter -- |t State-Space Models and the Kalman Filter -- |t Application 1: A Decomposition of Real GDP and the Unemployment Rate into Stochastic Trend and Transitory Components -- |t Application 2: An Application of the Time-Varying-Parameter Model to Modeling Changing Conditional Variance -- |t Application 3: Stock and Watson's Dynamic Factor Model of the Coincident Economic Indicators -- |t GAUSS Programs to Accompany Chapter 3 -- |t Markov-Switching Models -- |t Introduction: Serially Uncorrelated Data and Switching -- |t Serially Correlated Data and Markov Switching -- |t Issues Related to Markov-Switching Models -- |t Application 1: Hamilton's Markov-Switching Model of Business Fluctuations -- |t Application 2: A Unit Root in a Three-State Markov-Switching Model of the Real Interest Rate -- |t Application 3: A Three-State Markov-Switching Variance Model of Stock Returns -- |t GAUSS Programs to Accompany Chapter 4 -- |t State-Space Models with Markov Switching -- |t Specification of the Model -- |t The Basic Filter and Estimation of the Model -- |t Smoothing -- |t An Evaluation of the Kim Filter and Approximate MLE. |
| 520 | 1 | |a "Both state-space models and Markov-switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data."--Jacket | |
| 588 | 0 | |a Print version record. | |
| 546 | |a English. | ||
| 650 | 0 | |a Economics |x Mathematical models. |0 http://id.loc.gov/authorities/subjects/sh85040857 | |
| 650 | 0 | |a State-space methods. |0 http://id.loc.gov/authorities/subjects/sh85127512 | |
| 650 | 0 | |a Heteroscedasticity. |0 http://id.loc.gov/authorities/subjects/sh85060545 | |
| 650 | 0 | |a Sampling (Statistics) |0 http://id.loc.gov/authorities/subjects/sh85117056 | |
| 650 | 0 | |a Econometrics. |0 http://id.loc.gov/authorities/subjects/sh85040763 | |
| 650 | 0 | |a Markov processes. |0 http://id.loc.gov/authorities/subjects/sh85081369 | |
| 650 | 0 | |a Econometric models. |0 http://id.loc.gov/authorities/subjects/sh85040762 | |
| 650 | 2 | |a Markov Chains |0 https://id.nlm.nih.gov/mesh/D008390 | |
| 650 | 6 | |a Économie politique |x Modèles mathématiques. | |
| 650 | 6 | |a Méthodes de l'espace état. | |
| 650 | 6 | |a Hétéroscédasticité. | |
| 650 | 6 | |a Échantillonnage (Statistique) | |
| 650 | 6 | |a Économétrie. | |
| 650 | 6 | |a Processus de Markov. | |
| 650 | 6 | |a Modèles économétriques. | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Economics |x Theory. |2 bisacsh | |
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| 650 | 7 | |a Econometrics |2 fast | |
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| 650 | 7 | |a State-space methods |2 fast | |
| 653 | |a ECONOMICS/General | ||
| 700 | 1 | |a Nelson, Charles R. |0 http://id.loc.gov/authorities/names/n85281930 | |
| 758 | |i has work: |a State-space models with regime switching (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFRXVRPC78qmcPQRbJ6K7d |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
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| contents | State-Space Models and Markov Switching in Econometrics: A Brief History -- Computer Programs and Data -- The Classical Approach -- The Maximum Likelihood Estimation Method: Practical Issues -- Maximum Likelihood Estimation and the Covariance Matrix of OML -- The Prediction Error Decomposition and the Likelihood Function -- Parameter Constraints and the Covariance Matrix of OML -- State-Space Models and the Kalman Filter -- Time-Varying-Parameter Models and the Kalman Filter -- Application 1: A Decomposition of Real GDP and the Unemployment Rate into Stochastic Trend and Transitory Components -- Application 2: An Application of the Time-Varying-Parameter Model to Modeling Changing Conditional Variance -- Application 3: Stock and Watson's Dynamic Factor Model of the Coincident Economic Indicators -- GAUSS Programs to Accompany Chapter 3 -- Markov-Switching Models -- Introduction: Serially Uncorrelated Data and Switching -- Serially Correlated Data and Markov Switching -- Issues Related to Markov-Switching Models -- Application 1: Hamilton's Markov-Switching Model of Business Fluctuations -- Application 2: A Unit Root in a Three-State Markov-Switching Model of the Real Interest Rate -- Application 3: A Three-State Markov-Switching Variance Model of Stock Returns -- GAUSS Programs to Accompany Chapter 4 -- State-Space Models with Markov Switching -- Specification of the Model -- The Basic Filter and Estimation of the Model -- Smoothing -- An Evaluation of the Kim Filter and Approximate MLE. |
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| discipline | Wirtschaftswissenschaften |
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| id | ZDB-4-EBA-ocm43475778 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:15:00Z |
| institution | BVB |
| isbn | 9780585087160 0585087164 9780262277112 0262277115 9780262112383 0262112388 |
| language | English |
| oclc_num | 43475778 |
| open_access_boolean | |
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| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (xii, 297 pages) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 1999 |
| publishDateSearch | 1999 |
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| spelling | Kim, Chang-Jin, 1960- https://id.oclc.org/worldcat/entity/E39PBJhX3yXympFbfxD6dMwgrq http://id.loc.gov/authorities/names/n98082469 State-space models with regime switching : classical and Gibbs-sampling approaches with applications / Chang-Jin Kim and Charles R. Nelson. Cambridge, Mass. : MIT Press, ©1999. 1 online resource (xii, 297 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier text file The MIT Press Ser. Includes bibliographical references and index. State-Space Models and Markov Switching in Econometrics: A Brief History -- Computer Programs and Data -- The Classical Approach -- The Maximum Likelihood Estimation Method: Practical Issues -- Maximum Likelihood Estimation and the Covariance Matrix of OML -- The Prediction Error Decomposition and the Likelihood Function -- Parameter Constraints and the Covariance Matrix of OML -- State-Space Models and the Kalman Filter -- Time-Varying-Parameter Models and the Kalman Filter -- State-Space Models and the Kalman Filter -- Application 1: A Decomposition of Real GDP and the Unemployment Rate into Stochastic Trend and Transitory Components -- Application 2: An Application of the Time-Varying-Parameter Model to Modeling Changing Conditional Variance -- Application 3: Stock and Watson's Dynamic Factor Model of the Coincident Economic Indicators -- GAUSS Programs to Accompany Chapter 3 -- Markov-Switching Models -- Introduction: Serially Uncorrelated Data and Switching -- Serially Correlated Data and Markov Switching -- Issues Related to Markov-Switching Models -- Application 1: Hamilton's Markov-Switching Model of Business Fluctuations -- Application 2: A Unit Root in a Three-State Markov-Switching Model of the Real Interest Rate -- Application 3: A Three-State Markov-Switching Variance Model of Stock Returns -- GAUSS Programs to Accompany Chapter 4 -- State-Space Models with Markov Switching -- Specification of the Model -- The Basic Filter and Estimation of the Model -- Smoothing -- An Evaluation of the Kim Filter and Approximate MLE. "Both state-space models and Markov-switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data."--Jacket Print version record. English. Economics Mathematical models. http://id.loc.gov/authorities/subjects/sh85040857 State-space methods. http://id.loc.gov/authorities/subjects/sh85127512 Heteroscedasticity. http://id.loc.gov/authorities/subjects/sh85060545 Sampling (Statistics) http://id.loc.gov/authorities/subjects/sh85117056 Econometrics. http://id.loc.gov/authorities/subjects/sh85040763 Markov processes. http://id.loc.gov/authorities/subjects/sh85081369 Econometric models. http://id.loc.gov/authorities/subjects/sh85040762 Markov Chains https://id.nlm.nih.gov/mesh/D008390 Économie politique Modèles mathématiques. Méthodes de l'espace état. Hétéroscédasticité. Échantillonnage (Statistique) Économétrie. Processus de Markov. Modèles économétriques. BUSINESS & ECONOMICS Economics Theory. bisacsh Econometric models fast Econometrics fast Economics Mathematical models fast Heteroscedasticity fast Markov processes fast Sampling (Statistics) fast State-space methods fast ECONOMICS/General Nelson, Charles R. http://id.loc.gov/authorities/names/n85281930 has work: State-space models with regime switching (Text) https://id.oclc.org/worldcat/entity/E39PCFRXVRPC78qmcPQRbJ6K7d https://id.oclc.org/worldcat/ontology/hasWork Print version: Kim, Chang-Jin, 1960- State-space models with regime switching. Cambridge, Mass. : MIT Press, ©1999 0262112388 (DLC) 98044193 (OCoLC)39897352 MIT Press Ser. FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=9231 Volltext |
| spellingShingle | Kim, Chang-Jin, 1960- State-space models with regime switching : classical and Gibbs-sampling approaches with applications / MIT Press Ser. State-Space Models and Markov Switching in Econometrics: A Brief History -- Computer Programs and Data -- The Classical Approach -- The Maximum Likelihood Estimation Method: Practical Issues -- Maximum Likelihood Estimation and the Covariance Matrix of OML -- The Prediction Error Decomposition and the Likelihood Function -- Parameter Constraints and the Covariance Matrix of OML -- State-Space Models and the Kalman Filter -- Time-Varying-Parameter Models and the Kalman Filter -- Application 1: A Decomposition of Real GDP and the Unemployment Rate into Stochastic Trend and Transitory Components -- Application 2: An Application of the Time-Varying-Parameter Model to Modeling Changing Conditional Variance -- Application 3: Stock and Watson's Dynamic Factor Model of the Coincident Economic Indicators -- GAUSS Programs to Accompany Chapter 3 -- Markov-Switching Models -- Introduction: Serially Uncorrelated Data and Switching -- Serially Correlated Data and Markov Switching -- Issues Related to Markov-Switching Models -- Application 1: Hamilton's Markov-Switching Model of Business Fluctuations -- Application 2: A Unit Root in a Three-State Markov-Switching Model of the Real Interest Rate -- Application 3: A Three-State Markov-Switching Variance Model of Stock Returns -- GAUSS Programs to Accompany Chapter 4 -- State-Space Models with Markov Switching -- Specification of the Model -- The Basic Filter and Estimation of the Model -- Smoothing -- An Evaluation of the Kim Filter and Approximate MLE. Economics Mathematical models. http://id.loc.gov/authorities/subjects/sh85040857 State-space methods. http://id.loc.gov/authorities/subjects/sh85127512 Heteroscedasticity. http://id.loc.gov/authorities/subjects/sh85060545 Sampling (Statistics) http://id.loc.gov/authorities/subjects/sh85117056 Econometrics. http://id.loc.gov/authorities/subjects/sh85040763 Markov processes. http://id.loc.gov/authorities/subjects/sh85081369 Econometric models. http://id.loc.gov/authorities/subjects/sh85040762 Markov Chains https://id.nlm.nih.gov/mesh/D008390 Économie politique Modèles mathématiques. Méthodes de l'espace état. Hétéroscédasticité. Échantillonnage (Statistique) Économétrie. Processus de Markov. Modèles économétriques. BUSINESS & ECONOMICS Economics Theory. bisacsh Econometric models fast Econometrics fast Economics Mathematical models fast Heteroscedasticity fast Markov processes fast Sampling (Statistics) fast State-space methods fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85040857 http://id.loc.gov/authorities/subjects/sh85127512 http://id.loc.gov/authorities/subjects/sh85060545 http://id.loc.gov/authorities/subjects/sh85117056 http://id.loc.gov/authorities/subjects/sh85040763 http://id.loc.gov/authorities/subjects/sh85081369 http://id.loc.gov/authorities/subjects/sh85040762 https://id.nlm.nih.gov/mesh/D008390 |
| title | State-space models with regime switching : classical and Gibbs-sampling approaches with applications / |
| title_alt | State-Space Models and Markov Switching in Econometrics: A Brief History -- Computer Programs and Data -- The Classical Approach -- The Maximum Likelihood Estimation Method: Practical Issues -- Maximum Likelihood Estimation and the Covariance Matrix of OML -- The Prediction Error Decomposition and the Likelihood Function -- Parameter Constraints and the Covariance Matrix of OML -- State-Space Models and the Kalman Filter -- Time-Varying-Parameter Models and the Kalman Filter -- Application 1: A Decomposition of Real GDP and the Unemployment Rate into Stochastic Trend and Transitory Components -- Application 2: An Application of the Time-Varying-Parameter Model to Modeling Changing Conditional Variance -- Application 3: Stock and Watson's Dynamic Factor Model of the Coincident Economic Indicators -- GAUSS Programs to Accompany Chapter 3 -- Markov-Switching Models -- Introduction: Serially Uncorrelated Data and Switching -- Serially Correlated Data and Markov Switching -- Issues Related to Markov-Switching Models -- Application 1: Hamilton's Markov-Switching Model of Business Fluctuations -- Application 2: A Unit Root in a Three-State Markov-Switching Model of the Real Interest Rate -- Application 3: A Three-State Markov-Switching Variance Model of Stock Returns -- GAUSS Programs to Accompany Chapter 4 -- State-Space Models with Markov Switching -- Specification of the Model -- The Basic Filter and Estimation of the Model -- Smoothing -- An Evaluation of the Kim Filter and Approximate MLE. |
| title_auth | State-space models with regime switching : classical and Gibbs-sampling approaches with applications / |
| title_exact_search | State-space models with regime switching : classical and Gibbs-sampling approaches with applications / |
| title_full | State-space models with regime switching : classical and Gibbs-sampling approaches with applications / Chang-Jin Kim and Charles R. Nelson. |
| title_fullStr | State-space models with regime switching : classical and Gibbs-sampling approaches with applications / Chang-Jin Kim and Charles R. Nelson. |
| title_full_unstemmed | State-space models with regime switching : classical and Gibbs-sampling approaches with applications / Chang-Jin Kim and Charles R. Nelson. |
| title_short | State-space models with regime switching : |
| title_sort | state space models with regime switching classical and gibbs sampling approaches with applications |
| title_sub | classical and Gibbs-sampling approaches with applications / |
| topic | Economics Mathematical models. http://id.loc.gov/authorities/subjects/sh85040857 State-space methods. http://id.loc.gov/authorities/subjects/sh85127512 Heteroscedasticity. http://id.loc.gov/authorities/subjects/sh85060545 Sampling (Statistics) http://id.loc.gov/authorities/subjects/sh85117056 Econometrics. http://id.loc.gov/authorities/subjects/sh85040763 Markov processes. http://id.loc.gov/authorities/subjects/sh85081369 Econometric models. http://id.loc.gov/authorities/subjects/sh85040762 Markov Chains https://id.nlm.nih.gov/mesh/D008390 Économie politique Modèles mathématiques. Méthodes de l'espace état. Hétéroscédasticité. Échantillonnage (Statistique) Économétrie. Processus de Markov. Modèles économétriques. BUSINESS & ECONOMICS Economics Theory. bisacsh Econometric models fast Econometrics fast Economics Mathematical models fast Heteroscedasticity fast Markov processes fast Sampling (Statistics) fast State-space methods fast |
| topic_facet | Economics Mathematical models. State-space methods. Heteroscedasticity. Sampling (Statistics) Econometrics. Markov processes. Econometric models. Markov Chains Économie politique Modèles mathématiques. Méthodes de l'espace état. Hétéroscédasticité. Échantillonnage (Statistique) Économétrie. Processus de Markov. Modèles économétriques. BUSINESS & ECONOMICS Economics Theory. Econometric models Econometrics Economics Mathematical models Heteroscedasticity Markov processes State-space methods |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=9231 |
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