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Modelling non-stationary economic ti...

Hunter, John.

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Modelling non-stationary economic time series

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modelling non-stationary economic time series/ by John Hunter, Simon P. Burke, Alessandra Canepa.
作者:	Hunter, John.
其他作者:	Burke, Simon P.
出版者:	London :Palgrave Macmillan UK : : 2017.,
面頁冊數:	xiii, 502 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Econometric models. -
電子資源:	http://dx.doi.org/10.1057/978-1-137-31303-4
ISBN:	9781137313034

Modelling non-stationary economic time series
Hunter, John.

Modelling non-stationary economic time series[electronic resource] /by John Hunter, Simon P. Burke, Alessandra Canepa. - 2nd ed. - London :Palgrave Macmillan UK :2017. - xiii, 502 p. :ill., digital ;24 cm. - Palgrave texts in econometrics. - Palgrave texts in econometrics..

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.

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.

ISBN: 9781137313034

Standard No.: 10.1057/978-1-137-31303-4doiSubjects--Topical Terms:

542933
Econometric models.

LC Class. No.: HB141

Dewey Class. No.: 330.0151955

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520 $a 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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