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|a 3540262393 (acid - free paper)
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|a OHX
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|a QA280
|b .L874 2005
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|a 519.5/5
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|a Lütkepohl, Helmut
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|a New introduction to multiple time series analysis :
|b with 49 figures and 36 tables /
|c Helmut Lütkepohl.
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|a Berlin :
|b Springer,
|c c2005.
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| 300 |
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|a xxi, 764 p. :
|b ill. ;
|c 24 cm.
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|a Heavily revised version of author's: Introduction to multiple time series analysis, 1993.
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|a Includes bibliographical references (p. [713]-732) and indexes.
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|a Cover Preface Table of Contents 1 Introduction 1.1 Objectives of Analyzing Multiple Time Series 1.2 Some Basics 1.3 Vector Autoregressive Processes 1.4 Outline of the Following Chapters Part I Finite Order Vector Autoregressive Processes 2 Stable Vector Autoregressive Processes 2.1 Basic Assumptions and Properties of VAR Processes 2.2 Forecasting 2.3 Structural Analysis with VAR Models 2.4 Exercises 3 Estimation of Vector Autoregressive Processes 3.1 Introduction 3.2 Multivariate Least Squares Estimation 3.3 Least Squares Estimation with Mean-Adjusted Data and Yule-Walker Estimation 3.4 Maximum Likelihood Estimation 3.5 Forecasting with Estimated Processes 3.6 Testing for Causality. 3.7 The Asymptotic Distributions of Impulse Responses and Forecast Error Variance Decompositions 3.8 Exercises 4 VAR Order Selection and Checking the Model Adequacy 4.1 Introduction 4.2 A Sequence of Tests for Determining the VAR Order 4.3 Criteria for VAR Order Selection 4.4 Checking the Whiteness of the Residuals 4.5 Testing for Nonnormality 4.6 Tests for Structural Change 4.7 Exercises 5 VAR Processes with Parameter Constraints 5.1 Introduction 5.2 Linear Constraints 5.3 VAR Processes with Nonlinear Parameter Restrictions 5.4 Bayesian Estimation 5.5 Exercises Part II Cointegrated Processes 6 Vector Error Correction Models 6.1 Integrated Processes 6.2 VAR Processes with Integrated Variables 6.3 Cointegrated Processes, Common Stochastic Trends, and Vector Error Correction Models 6.4 Deterministic Terms in Cointegrated Processes 6.5 Forecasting Integrated and Cointegrated Variables 6.6 Causality Analysis 6.7 Impulse Response Analysis 6.8 Exercises 7 Estimation of Vector Error Correction Models 7.1 Estimation of a Simple Special Case VECM 7.2 Estimation of General VECMs 7.3 Estimating VECMs with Parameter Restrictions 7.4 Bayesian Estimation of Integrated Systems 7.5 Forecasting Estimated Integrated and Cointegrated Systems 7.6 Testing for Granger-Causality 7.7 Impulse Response Analysis 7.8 Exercises 8 Specification of VECMs 8.1 Lag Order Selection. 8.2 Testing for the Rank of Cointegration 8.3 Subset VECMs 8.4 Model Diagnostics 8.5 Exercises Part III Structural and Conditional Models 9 Structural VARs and VECMs 9.1 Structural Vector Autoregressions 9.2 Structural Vector Error Correction Models. 9.3 Estimation of Structural Parameters 9.4 Impulse Response Analysis and Forecast Error Variance Decomposition 9.5 Further Issues 9.6 Exercises 10 Systems of Dynamic Simultaneous Equations 10.1 Background. 10.2 Systems with Unmodelled Variables. 10.3 Estimation 10.4 Remarks on Model Specification and Model Checking 10.5 Forecasting 10.6 Multiplier Analysis 10.7 Optimal Control 10.8 Concluding Remarks on Dynamic SEMs 10.9 Exercises Part IV Infinite Order Vector Autoregressive Processes 11 Vector Autoregressive Moving Average Processes 11.1 Introduction 11.2 Finite Order Moving Average Processes 11.3 VARMA Processes 11.4 The Autocovariances and Autocorrelations of a VARMA(p, q) Process 11.5 Forecasting VARMA Processes 11.6 Transforming and Aggregating VARMA Processes 11.7 Interpretation of VARMA Models 11.8 Exercises 12 Estimation of VARMA Models 12.1 The Identification Problem 12.2 The Gaussian Likelihood Function 12.3 Computation of the ML Estimates 12.4 Asymptotic Properties of the ML Estimators 12.5 Forecasting Estimated VARMA Processes 12.6 Estimated Impulse Responses 12.7 Exercises 13 Specification and Checking the Adequacy of VARMA Models 13.1 Introduction 13.2 Specification of the Final Equations Form 13.3 Specification of Echelon Forms 13.4 Remarks on Other Specification Strategies for VARMA Models 13.5 Model Checking 13.6 Critique of VARMA Model Fitting 13.7 Exercises 14 Cointegrated VARMA Processes 14.1 Introduction 14.2 The VARMA Framework for I(1) Variables 14.3
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|a Time-series analysis
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|b 59b007506c5ad17d7e5a9c98
|c 952a
|d 9528
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