Multiple time series models / Patrick T. Brandt, John T. Williams.

By:

Brandt, Patrick T

Contributor(s):

Williams, John T. (John Taylor), 1958-

Material type:

TextSeries: Sage university papers series. Quantitative applications in the social sciences ; ; no. 07-148.Publication details: Thousand Oaks, Calif. : Sage Publications, c2007.Description: xiii, 99 p. : ill. ; 22 cmISBN:

1412906563 (pbk.)
9781412906562

Subject(s):

Time-series analysis -- Mathematical models

DDC classification:

519.55 BRA W 23

LOC classification:

HA30.3 .B73 2007

Online resources:

Contents:

List of Figures List of Tables Series Editor?s Introduction Preface 1. Introduction to Multiple Time Series Models 1.1 Simultaneous Equation Approach 1.2 ARIMA Approach 1.3 Error Correction or LSE Approach 1.4 Vector Autoregression Approach 1.5 Comparison and Summary 2. Basic Vector Autoregression Models 2.1 Dynamic Structural Equation Models 2.2 Reduced Form Vector Autoregressions 2.3 Relationship of a Dynamic Structural Equation Model to a Vector Autoregression Model 2.4 Working With This Model 2.5 Specification and Analysis of VAR Models 2.6 Other Specification Issues 2.7 Unit Roots and Error Correction in VARs 2.8 Criticisms of VAR 3. Examples of VAR Analyses 3.1 Public Mood and Macropartisanship 3.2 Effective Corporate Tax Rates 3.3 Conclusion Appendix: Software for Multiple Time Series Models Notes References Index About the Authors

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Stack text books	All India Institute of Speech and Hearing		44/2		519.55 BRA W (Browse shelf(Opens below))					Available			14490

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Includes bibliographical references (p. 92-95) and index.

List of Figures
List of Tables
Series Editor?s Introduction
Preface
1. Introduction to Multiple Time Series Models
1.1 Simultaneous Equation Approach
1.2 ARIMA Approach
1.3 Error Correction or LSE Approach
1.4 Vector Autoregression Approach
1.5 Comparison and Summary
2. Basic Vector Autoregression Models
2.1 Dynamic Structural Equation Models
2.2 Reduced Form Vector Autoregressions
2.3 Relationship of a Dynamic Structural Equation Model to a Vector Autoregression Model
2.4 Working With This Model
2.5 Specification and Analysis of VAR Models
2.6 Other Specification Issues
2.7 Unit Roots and Error Correction in VARs
2.8 Criticisms of VAR
3. Examples of VAR Analyses
3.1 Public Mood and Macropartisanship
3.2 Effective Corporate Tax Rates
3.3 Conclusion
Appendix: Software for Multiple Time Series Models
Notes
References
Index
About the Authors

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