Periodic Time Series Models

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OUP Oxford, Mar 25, 2004 - Business & Economics - 162 pages
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This book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book presents a large number of empirical results. The first part of the book deals with model selection, diagnostic checking and forecasting of univariate periodic autoregressive models. Tests for periodic integration, are discussed, and an extensive discussion of the role of deterministic regressors in testing for periodic integration and in forecasting is provided. The second part discusses multivariate periodic autoregressive models. It provides an overview of periodic cointegration models, as these are the most relevant. This overview contains single-equation type tests and a full-system approach based on generalized method of moments. All methods are illustrated with extensive examples, and the book will be of interest to advanced graduate students and researchers in econometrics, as well as practitioners looking for an understanding of how to approach seasonal data.
 

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Contents

Introduction
1
12 Readership
3
13 Why periodic models?
5
14 Outline of this book
8
Properties of seasonal time series
11
22 Typical features of seasonal time series
17
23 Summary and outlook
25
Univariate periodic time series models
27
43 Testing for unit roots
77
44 Forecasting trending time series
92
45 Effects of neglecting periodicity
97
46 Conclusion
99
Multivariate periodic time series models
103
51 Notation and representation
104
52 Useful representations in practice
108
53 Cointegration testing single equation approach
111

31 Representation
28
32 Stationarity in periodic autoregressions
34
33 Model selection and parameter estimation
39
34 Forecasting
46
35 Effects of neglecting periodicity
48
36 Periodic conditional heteroskedasticity
54
37 Discussion
58
Periodic models for trending data
61
41 Representation of unit roots
64
42 Intercepts and deterministic trends
72
54 Cointegration testing fullsystem approach
117
55 Discussion
122
Critical values of the Dickey and Fuller statistics
125
Critical values of the Johansen trace statistics
126
Critical values of the Boswijk and Franses statistic
129
References
131
Author Index
141
Subject Index
145
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About the author (2004)

Philip Hans Franses is Professor of Applied Econometrics and Professor of Marketing Research at Erasmus University, Rotterdam. He is the author of a number of books, including Periodicity and Stochastic Trends in Economic Time Series (OUP, 1996). Richard Paap is a Postdoctoral Researcher at the Econometric Institute in Erasmus University, Rotterdam.

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