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Testing For Unit Roots In Seasonal Time Series With Long Period
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Book Synopsis Testing for Unit Roots in Seasonal Time Series with Long Period by :
Download or read book Testing for Unit Roots in Seasonal Time Series with Long Period written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Testing for seasonal unit roots has been discussed extensively in the literature. However, the test will be difficult if the time series has a long period, where the critical values for the test statistics are not available. We modify the seasonal unit roots test of Dickey, Hasza, and Fuller (1984) to investigate results for less typical, long period cases, and present some asymptotic normality properties. We also suggest an empirical adjustment to improve the normal approximation when the seasonal period is not sufficiently long. The basic idea is to use a double-index form for the seasonal time series with a long period, where d denotes the large lag number, so that the d "channels" will be independent for each i. By applying the Classical Central Limit Theorem for iid random variables, we can obtain the asymptotic result. The convergence is proved to be order independent with respect to m and d. An advantage of this technique is that one can make the adjustment and use a standard normal as a reference distribution instead of looking into the seasonal percentile tables when doing the seasonal unit roots test, no matter what kind of deterministic terms are included in the model as long as the number of the regressors is fixed. We also show that for an AR(p) model we still obtain the asymptotic normality of the unit root statistics.
Book Synopsis Testing for Unit Roots in Seasonal Time Series with Long Period by : Ying Zhang
Download or read book Testing for Unit Roots in Seasonal Time Series with Long Period written by Ying Zhang and published by . This book was released on 2008 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: long period, seasonal time series, unit roots test.
Book Synopsis Forecasting: principles and practice by : Rob J Hyndman
Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Book Synopsis Unit Root Tests in Time Series Volume 1 by : K. Patterson
Download or read book Unit Root Tests in Time Series Volume 1 written by K. Patterson and published by Springer. This book was released on 2011-02-25 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Testing for a unit root is now an essential part of time series analysis. This volume provides a critical overview and assessment of tests for a unit root in time series, developing the concepts necessary to understand the key theoretical and practical models in unit root testing.
Book Synopsis Essays on Unit Root Testing in Time Series by : Xiao Zhong
Download or read book Essays on Unit Root Testing in Time Series written by Xiao Zhong and published by . This book was released on 2015 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Unit root tests are frequently employed by applied time series analysts to determine if the underlying model that generates an empirical process has a component that can be well-described by a random walk. More specifically, when the time series can be modeled using an autoregressive moving average (ARMA) process, such tests aim to determine if the autoregressive (AR) polynomial has one or more unit roots. The effect of economic shocks do not diminish with time when there is one or more unit roots in the AR polynomial, whereas the contribution of shocks decay geometrically when all the roots are outside the unit circle. This is one major reason for economists' interest in unit root tests. Unit roots processes are also useful in modeling seasonal time series, where the autoregressive polynomial has a factor of the form (1-[zeta][superscript s]), and s is the period of the season. Such roots are called seasonal unit roots. Techniques for testing the unit roots have been developed by many researchers since late 1970s. Most such tests assume that the errors (shocks) are independent or weakly dependent. Only a few tests allow conditionally heteroskedastic error structures, such as Generalized Autoregressive Conditionally Heteroskedastic (GARCH) error. And only a single test is available for testing multiple unit roots. In this dissertation, three papers are presented. Paper I deals with developing bootstrap-based tests for multiple unit roots; Paper II extends a bootstrap-based unit root test to higher order autoregressive process with conditionally heteroscedastic error; and Paper III extends a currently available seasonal unit root test to a bootstrap-based one while at the same time relaxing the assumption of weakly dependent shocks to include conditional heteroscedasticity in the error structure"--Abstract, page iv.
Book Synopsis Unit Roots, Cointegration, and Structural Change by : G. S. Maddala
Download or read book Unit Roots, Cointegration, and Structural Change written by G. S. Maddala and published by Cambridge University Press. This book was released on 1998 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review of unit roots, cointegration and structural change from a best-selling author.
Book Synopsis Analysis of Integrated and Cointegrated Time Series with R by : Bernhard Pfaff
Download or read book Analysis of Integrated and Cointegrated Time Series with R written by Bernhard Pfaff and published by Springer Science & Business Media. This book was released on 2008-09-03 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.
Book Synopsis Testing for Seasonal Unit Roots with Temporally Aggregated Time Series by : Gabriel Pons
Download or read book Testing for Seasonal Unit Roots with Temporally Aggregated Time Series written by Gabriel Pons and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The temporal aggregation effect on seasonal unit roots and its implications for seasonal unit root testing are discussed. The aggregation effect allows to test with any HEGY-type method for integration at the harmonic frequencies through the Nyquist frequency of properly temporally aggregated series.
Book Synopsis Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles by : Gabriel Pons Rotger
Download or read book Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles written by Gabriel Pons Rotger and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The effects of systematic sampling and temporal aggregation on the seasonal cycle model (see Miron, 1993) and the seasonally integrated process (see Hylleberg et al., 1990) are discussed. The temporal aggregation theory is used to improve the sequential test for monthly seasonal unit roots of Rodrigues and Franses (2003). It is shown by simulation that the monthly sequential test has better finite sample properties than the BM test (see Beaulieu and Miron, 1993). The new test is applied to monthly US Industrial Production and, contrary to the BM test, rejects the presence of any seasonal unit root.
Book Synopsis Time Series Analysis Univariate and Multivariate Methods by : William W. S. Wei
Download or read book Time Series Analysis Univariate and Multivariate Methods written by William W. S. Wei and published by Pearson. This book was released on 2018-03-14 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Time Series Analysis is a thorough introduction to both time-domain and frequency-domain analyses of univariate and multivariate time series methods, with coverage of the most recently developed techniques in the field.
Book Synopsis Seasonal Unit Root Tests Under Structural Breaks by : Uwe Hassler
Download or read book Seasonal Unit Root Tests Under Structural Breaks written by Uwe Hassler and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, several seasonal unit root tests are analysed in the context of structural breaks at known time and a new break corrected test is suggested. We show that the widely used HEGY test, as well as an LM variant thereof, are asymptotically robust to seasonal mean shifts of finite magnitude. In finite samples, however, experiments reveal that such tests suffer from severe size distortions and power reductions when breaks are present. Hence, a new break corrected LM test is proposed to overcome this problem. Importantly, the correction for seasonal mean shifts bears no consequence on the limiting distributions, thereby maintaining the legitimacy of canonical critical values. Moreover, although this test assumes a breakpoint a priori, it is robust in terms of misspecification of the time of the break. This asymptotic property is well reproduced in finite samples. Based on a Monte-Carlo study, our new test is compared with other procedures suggested in the literature and shown to hold superior finite sample properties.
Book Synopsis Seasonal Unit Root Tests: A Comparison by :
Download or read book Seasonal Unit Root Tests: A Comparison written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Three major regression-based seasonal unit root tests: the DHF test introduced by Dickey et al (1984), the HEGY test proposed by Hylleberg et al. (1990) and the Kunst test introduced by Kunst (1997) are compared. The regression model for the DHF test is a reduced form of that for the Kunst test. We modify the Kunst test by using the t-statistic instead of Kunst's proposed joint F-statistic to study the influence of additional variables in the Kunst model. Also, we modify the HEGY test to test the presence of all four quarterly unit roots against the presence of roots 1 and -1. Through the comparison between the DHF test and the modified HEGY test, we find that the DHF test does not have asymptotic power one when the series only have some of the seasonal unit roots but not all of them. We call this case of partial unit roots. The asymptotic distributions derived in the paper provide the explanation of this limitation for the DHF test. Using simulation, we find that the probability that the DHF test will lead researchers to accept the seasonal unit root null hypothesis increases when the series contains more partial unit roots. For the DHF test, the test power depends on the augmented model. We derive limits of the related estimates from two augmented models for the DHF test. Both estimates are inconsistent. The test statistic obtained from the augmented model suggested by Ghysels et al. (1992) has relatively low power. For the HEGY/Kunst test, most limiting distributions for the test statistics depend on the lag augmentation but the test statistics have few problems caused by inconsistent estimates. However, the augmented models for the HEGY/Kunst test have more variables than those for the DHF test. Based on our simulation study results, the inclusion of more variables results in more loss in power when a redundant variable is included, and more sensitivity to the size distortion when the augmented lag length is less than the true lag length.
Book Synopsis Critical Values for Unit Root Tests in Seasonal Time Series by : Philip Hans Franses
Download or read book Critical Values for Unit Root Tests in Seasonal Time Series written by Philip Hans Franses and published by . This book was released on 1994 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Unit Root Tests and Structural Breaks by : Paramsothy Silvapulle
Download or read book Unit Root Tests and Structural Breaks written by Paramsothy Silvapulle and published by . This book was released on 1995 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Testing for Seasonal Unit Roots with Temporally Aggregated Time Series by : Gabriel Pons Rotger
Download or read book Testing for Seasonal Unit Roots with Temporally Aggregated Time Series written by Gabriel Pons Rotger and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis SAS for Forecasting Time Series, Third Edition by : John C. Brocklebank, Ph.D.
Download or read book SAS for Forecasting Time Series, Third Edition written by John C. Brocklebank, Ph.D. and published by SAS Institute. This book was released on 2018-03-14 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.
Book Synopsis The Asymptotic and Finite Sample Behaviour of Seasonal Unit Root Tests Under the Presence of a Break in the Deterministic Seasonal Pattern by : Artur C.B da Silva Lopes
Download or read book The Asymptotic and Finite Sample Behaviour of Seasonal Unit Root Tests Under the Presence of a Break in the Deterministic Seasonal Pattern written by Artur C.B da Silva Lopes and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies the asymptotic behaviour of the HEGY tests for quarterly data, for nonseasonal and seasonal autoregressive unit roots, when the time series being analysed is trend and deterministic seasonal stationary but exhibits a change in the seasonal pattern. Our results show that, asymptotically, the HEGY test statistics are not biased towards the acceptance of the seasonal and nonseasonal unit root hypotheses. Just under some combinations of the parameters the rejection of the false null hypothesses may require a larger sample size. Therefore, our results are also useful to understand and to predict the finite sample power properties of the tests statistics under several circumstances.
