New Introduction to Multiple Time Series Analysis

ISBN-13: 9783540262398 / Angielski / Miękka / 2006 / 764 str.

Helmut L]tkepohl; Helmut Lutkepohl

Opis

When I worked on my Introduction to Multiple Time Series Analysis (Lutk ] ]- pohl (1991)), a suitable textbook for this ?eld was not available. Given the great importance these methods have gained in applied econometric work, it is perhaps not surprising in retrospect that the book was quite successful. Now, almost one and a half decades later the ?eld has undergone substantial development and, therefore, the book does not cover all topics of my own courses on the subject anymore. Therefore, I started to think about a serious revision of the book when I moved to the European University Institute in Florence in 2002. Here in the lovely hills of ToscanyIhadthetimetothink about bigger projects again and decided to prepare a substantial revision of my previous book. Because the label Second Edition was already used for a previous reprint of the book, I decided to modify the title and thereby hope to signal to potential readers that signi?cant changes have been made relative to my previous multiple time series book.

Spis treści

Introduction.- Finite Order Vector Autoregressive Processes: Stable Vector Autoregressive Processes.- Estimation of Vector Autoregressive Processes.- VAR Order Selection and Checking the Model Adequacy.- VAR Processes with Parameter Constraints. Cointegrated Processes: Vector Error Correction Models.- Estimation of Vector Error Correction Models.- Specification of VECMs. Structural and Conditional Models: Structural VARs and VECMs.- Systems of Dynamic Simultaneous Equations. Infinite Order Vector Autoregressive Processes: Vector Autoregressive Moving Average Processes.- Estimation of VARMA Models.- Specification and Checking the Adequacy of VARMA.- Cointegrated VARMA Processes.- Fitting Finite Order VAR Models to Infinite Order Processes. Time Series Topics: Multivariate ARCH and GARCH Models.- Periodic VAR Processes and Intervention Models.- State Space Models. Appendices: Vectors and Matrices.- Multivariate Normal and Related Distributions.- Stochastic Convergence and Asymptotic Distributions.- Evaluating Properties of Estimators and Test Statistics by Simulation and Resampling Techniques.