Granger / Newbold / Shell Forecasting Economic Time Series

2. Auflage 2014
ISBN: 978-1-4832-7324-2
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 352 Seiten, Web PDF

Economic Theory, Econometrics, and Mathematical Economics, Second Edition: Forecasting Economic Time Series presents the developments in time series analysis and forecasting theory and practice. This book discusses the application of time series procedures in mainstream economic theory and econometric model building. Organized into 10 chapters, this edition begins with an overview of the problem of dealing with time series possessing a deterministic seasonal component. This text then provides a description of time series in terms of models known as the time-domain approach. Other chapters consider an alternative approach, known as spectral or frequency-domain analysis, that often provides useful insights into the properties of a series. This book discusses as well a unified approach to the fitting of linear models to a given time series. The final chapter deals with the main advantage of having a Gaussian series wherein the optimal single series, least-squares forecast will be a linear forecast. This book is a valuable resource for economists.

Autoren/Hrsg.

Granger, C. W. J.

Newbold, Paul

Shell, Karl

Inhaltsverzeichnis

1;Front Cover;1
2;Forecasting Economic Time Series;4
3;Copyright Page;5
4;Table of Contents;8
5;Dedication;6
6;PREFACE TO THE SECOND EDITION;12
7;PREFACE TO THE FIRST EDITION;14
8;CHAPTER ONE. INTRODUCTION TO THE THEORY OF TIME SERIES;16
8.1;1.1 Introducing Time Series;16
8.2;1.2 Covariances and Stationarity;18
8.3;1.3 Some Mathematical Tools;21
8.4;1.4 The Linear Cyclic Model;25
8.5;1.5 The Autoregressive Model;28
8.6;1.6 The Moving Average Model;36
8.7;1.7 The Mixed Autoregressive-Moving Average Model;40
8.8;1.8 Interpreting the Mixed Model;43
8.9;1.9 Filters;47
8.10;1.10 Deterministic Components;48
8.11;1.11 Wold's Decomposition;52
8.12;1.12 Nonstationary Processes;53
8.13;1.13 Integrated Processes;56
8.14;1.14 Models for Seasonal Time Series;58
9;CHAPTER TWO. SPECTRAL ANALYSIS;60
9.1;2.1 Introduction;60
9.2;2.2 Filters;68
9.3;2.3 The Spectrum of Some Common Models;70
9.4;2.4 Aliasing;72
9.5;2.5 The Cross Spectrum;73
9.6;2.6 Estimation of Spectral Functions;77
9.7;2.7 The Typical Spectral Shape and Its Interpretation;79
9.8;2.8 Seasonal Adjustment An Application of the Cross Spectrum;81
9.9;2.9 Advanced Spectral Techniques;86
10;CHAPTER THREE. BUILDING LINEAR TIME SERIES MODELS;91
10.1;3.1 Model Building Philosophy;91
10.2;3.2 Identification;92
10.3;3.3 Initial Estimates for Coefficients;102
10.4;3.4 The Autocorrelation Function as a Characteristic of Process Behavior;103
10.5;3.5 Estimation;106
10.6;3.6 Diagnostic Checking;111
10.7;3.7 Model Building for Seasonal Time Series;116
10.8;3.8 Time Series Model Building—An Overview;129
11;CHAFFER FOUR. THE THEORY OF FORECASTING;135
11.1;4.1 Some Basic Concepts;135
11.2;4.2 Generalized Cost Functions;139
11.3;4.3 Properties of Optimal, Single-Series Forecasts;142
11.4;4.4 Optimal Forecasts for Particular Models;147
11.5;4.5 A Frequency-Domain Approach;150
11.6;4.6 Expectations and Forecasts;155
11.7;4.7 Unbiased Forecasts;159
11.8;4.8 Invertibility;160
11.9;4.9 Types of Forecasts;164
12;CHAFER FIVE. PRACTICAL METHODS FOR UNIVARIATE TIME SERIES FORECASTING;166
12.1;5.1 Introduction;166
12.2;5.2 Box-Jenkins Forecasting Methods;167
12.3;5.3 Exponential Smoothing Methods;180
12.4;5.4 Stepwise Autoregression;193
12.5;5.5 A Fully Automatic Forecasting Procedure Based on the Combination of Forecasts;196
12.6;5.6 Comparison of Univariate Forecasting Procedures;196
13;CHAPTER SIX. FORECASTING FROM REGRESSION MODELS;202
13.1;6.1 Introduction;202
13.2;6.2 Single Equation Models;203
13.3;6.3 Simultaneous Equation Models;210
13.4;6.4 Danger of Spurious Regressions in Econometric Models;220
14;CHAPTER SEVEN. MULTIPLE SERIES MODELING AND FORECASTING;231
14.1;7.1 Introduction;231
14.2;7.2 Theoretical Models for Multiple Time Series;231
14.3;7.3 Causality and Feedback;235
14.4;7.4 Co-Integrated Series and Error-Correction Models;239
14.5;7.5 Properties of Optimal Multiseries Forecasts;241
14.6;7.6 Forecasting Aggregates;245
14.7;7.7 Rational Expectations;247
15;CHAPTER EIGHT. BUILDING MULTIPLE TIME SERIES FORECASTING MODELS;250
15.1;8.1 Introduction;250
15.2;8.2 Building Bivariate Models: Unidirectional Causality;250
15.3;8.3 Building Vector ARMA Models;259
15.4;8.4 Building Forecasting Models for Several Related Time Series;272
15.5;8.5 Testing for Causality;274
15.6;8.6 Testing for Co-Integration;277
16;CHAPTER NINE. THE COMBINATION AND EVALUATION OF FORECASTS;280
16.1;9.1 Typical Suboptimality of Economic Forecasts;280
16.2;9.2 The Combination of Forecasts;281
16.3;9.3 The Evaluation of Forecasts;291
16.4;9.4 A Survey of the Performance of Macroeconomic Forecasts;302
16.5;9.5 Econometric Forecasting and Time Series Analysis;307
16.6;9.6 Leading Indicators;309
17;CHAPTER TEN. FURTHER TOPICS;312
17.1;10.1 State-Space Representation, the Kalman Filter;312
17.2;10.2 Time-Varying Parameter Models;317
17.3;10.3 Nonlinear Models;318
17.4;10.4 Bilinear Models;320
17.5;10.5 Instantaneous Data Transformations;321
17.6;10.6 Forecasting White Noise;327
17.7;10.7 Predicting Variances: ARCH Models;329
17.8;10.8 Forecasting Unobserved Components;330
18;REFERENCES;332
19;AUTHOR INDEX;346
20;SUBJECT INDEX;350