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Author | : K. Patterson |
Publisher | : Springer |
Total Pages | : 676 |
Release | : 2011-02-25 |
Genre | : Business & Economics |
ISBN | : 023029930X |
Download Unit Root Tests in Time Series Volume 1 Book in PDF, ePub and Kindle
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.
Author | : K. D. Patterson |
Publisher | : |
Total Pages | : |
Release | : 2011 |
Genre | : Econometrics |
ISBN | : |
Download Unit Root Tests in Time Series: Key concepts and problems Book in PDF, ePub and Kindle
Author | : K. Patterson |
Publisher | : Springer |
Total Pages | : 666 |
Release | : 2012-07-05 |
Genre | : Business & Economics |
ISBN | : 1137003316 |
Download Unit Root Tests in Time Series Volume 2 Book in PDF, ePub and Kindle
Testing for a Unit Root is now an essential part of time series analysis but the literature on the topic is so large that knowing where to start is difficult even for the specialist. This book provides a way into the techniques of unit root testing, explaining the pitfalls and nonstandard cases, using practical examples and simulation analysis.
Author | : Markku Lanne |
Publisher | : |
Total Pages | : 0 |
Release | : 2003 |
Genre | : |
ISBN | : |
Download Comparison of Unit Root Tests for Time Series with Level Shifts Book in PDF, ePub and Kindle
Unit root tests are considered for time series which have a level shift at a known point in time. The shift can have a very general nonlinear form, and additional deterministic mean and trend terms are allowed for. Prior to the tests, the deterministic parts and other nuisance parameters of the data generation process are estimated in a first step. Then, the series are adjusted for these terms and unit root tests of the Dickey-Fuller type are applied to the adjusted series. The properties of previously suggested tests of this sort are analysed and modifications are proposed which take into account estimation errors in the nuisance parameters. An important result is that estimation under the null hypothesis is preferable to estimation under local alternatives. This contrasts with results obtained by other authors for time series without level shifts.
Author | : Paramsothy Silvapulle |
Publisher | : |
Total Pages | : 30 |
Release | : 1995 |
Genre | : Monte Carlo method |
ISBN | : |
Download Unit Root Tests and Structural Breaks Book in PDF, ePub and Kindle
Author | : Francis X. Diebold |
Publisher | : |
Total Pages | : 110 |
Release | : 1988 |
Genre | : Econometric models |
ISBN | : |
Download Unit Roots in Economic Time Series Book in PDF, ePub and Kindle
Author | : K. Patterson |
Publisher | : Springer |
Total Pages | : 301 |
Release | : 2010-03-31 |
Genre | : Business & Economics |
ISBN | : 0230248454 |
Download A Primer for Unit Root Testing Book in PDF, ePub and Kindle
This book gives an authoritative overview of the literature on non-stationarity, integration and unit roots, providing direction and guidance. It also provides detailed examples to show how the techniques can be applied in practical situations and the pitfalls to avoid.
Author | : Junsoo Lee |
Publisher | : |
Total Pages | : 304 |
Release | : 1991 |
Genre | : Autocorrelation (Statistics) |
ISBN | : |
Download Unit Root Tests in the Presence of Autocorrelated Errors and Structural Change Book in PDF, ePub and Kindle
Author | : Xiao Zhong |
Publisher | : |
Total Pages | : 114 |
Release | : 2015 |
Genre | : Autoregression (Statistics) |
ISBN | : |
Download Essays on Unit Root Testing in Time Series Book in PDF, ePub and Kindle
"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.
Author | : K. Patterson |
Publisher | : Palgrave Macmillan |
Total Pages | : 550 |
Release | : 2012-07-06 |
Genre | : Business & Economics |
ISBN | : 9780230250260 |
Download Unit Root Tests in Time Series Volume 2 Book in PDF, ePub and Kindle
Testing for a Unit Root is now an essential part of time series analysis but the literature on the topic is so large that knowing where to start is difficult even for the specialist. This book provides a way into the techniques of unit root testing, explaining the pitfalls and nonstandard cases, using practical examples and simulation analysis.