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Analysis of integrated and cointegrated time series with R / Bernhard Pfaff.

By: Pfaff, Bernhard.
Material type: materialTypeLabelBookSeries: Use R!. Publisher: New York : Springer, c2008Edition: 2nd ed.Description: xx, 188 p. : ill. ; 24 cm.ISBN: 9780387759661 (pbk.) :; 0387759662 (pbk.).Subject(s): Time-series analysis -- Computer programs | R (Computer program language)DDC classification: 330.0151955 Online resources: Table of contents only
Contents:
Univariate Analysis of Stationary Time Series Pages 3-21 Multivariate Analysis of Stationary Time Series Pages 23-51 Non-stationary Time Series Pages 53-71 Cointegration Pages 73-87 Testing for the Order of Integration Pages 91-105 Further Considerations Pages 107-118 Single-Equation Methods Pages 121-127 Multiple-Equation Methods Pages 129-159
Summary: The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. This book not only introduces the reader to this topic but enables him to conduct the various unit root tests and co-integration methods on his own by utilizing the free statistical programming environment R. The book encompasses seasonal unit roots, fractional integration, coping with structural breaks, and multivariate time series models. The book is enriched by numerous programming examples to artificial and real data so that it is ideally suited as an accompanying text book to computer lab classes. The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other. taken from Publisher's site.
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Item type Current location Call number Copy number Status Date due
Monograph Monograph Indian Institute of Management Udaipur
A4/2 		330.0151955 (Browse shelf) 1 Available

Includes bibliographical references (p. [169]-175) and indexes.

Univariate Analysis of Stationary Time Series
Pages 3-21
Multivariate Analysis of Stationary Time Series
Pages 23-51
Non-stationary Time Series
Pages 53-71
Cointegration
Pages 73-87
Testing for the Order of Integration
Pages 91-105
Further Considerations
Pages 107-118
Single-Equation Methods
Pages 121-127
Multiple-Equation Methods
Pages 129-159

The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. This book not only introduces the reader to this topic but enables him to conduct the various unit root tests and co-integration methods on his own by utilizing the free statistical programming environment R. The book encompasses seasonal unit roots, fractional integration, coping with structural breaks, and multivariate time series models. The book is enriched by numerous programming examples to artificial and real data so that it is ideally suited as an accompanying text book to computer lab classes.

The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other. taken from Publisher's site.

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