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1. |
Record Nr. |
UNINA9910255030003321 |
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Autore |
Hunter John |
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Titolo |
Multivariate Modelling of Non-Stationary Economic Time Series [[electronic resource] /] / by John Hunter, Simon P. Burke, Alessandra Canepa |
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Pubbl/distr/stampa |
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London : , : Palgrave Macmillan UK : , : Imprint : Palgrave Macmillan, , 2017 |
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ISBN |
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Edizione |
[2nd ed. 2017.] |
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Descrizione fisica |
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1 online resource (XIII, 502 p.) |
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Collana |
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Palgrave Texts in Econometrics, , 2662-6594 |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Chapter 1. Introduction: Time Series, Common Trends and Equilibrium -- Chapter 2. Multivariate Time Series -- Chapter 3. Cointegration -- Chapter 4. Testing for Cointegration: Under Standard and Non-Standard Conditions -- Chapter 5. Structure and Evaluation -- Chapter 6. Testing in VECMs with Small Sample -- Chapter 7. Heteroscedasticity and Multivariate Volatility -- Chapter 8. Models with Alternative Orders of Integration -- Chapter 9. The Structural Analysis of Time Series. |
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Sommario/riassunto |
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This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists. |
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