Sample Size, Lag Order and Critical Values of Seasonal Unit Root Tests

Sample Size, Lag Order and Critical Values of Seasonal Unit Root Tests PDF Author:
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ISBN:
Category :
Languages : en
Pages :

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Sample Size, Lag Order and Critical Values of Seasonal Unit Root Tests

Sample Size, Lag Order and Critical Values of Seasonal Unit Root Tests PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Lag Order and Critical Values of Unit Root Tests

Lag Order and Critical Values of Unit Root Tests PDF Author: Yin-Wong Cheung
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 48

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Unit Roots, Cointegration, and Structural Change

Unit Roots, Cointegration, and Structural Change PDF Author: G. S. Maddala
Publisher: Cambridge University Press
ISBN: 9780521587822
Category : Business & Economics
Languages : en
Pages : 528

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Book Description
A comprehensive review of unit roots, cointegration and structural change from a best-selling author.

Seasonal Unit Root Tests Under Structural Breaks

Seasonal Unit Root Tests Under Structural Breaks PDF Author: Uwe Hassler
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
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.

Time Series Models for Business and Economic Forecasting

Time Series Models for Business and Economic Forecasting PDF Author:
Publisher: Cambridge University Press
ISBN: 0521817706
Category :
Languages : en
Pages : 313

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Time Series Models for Business and Economic Forecasting

Time Series Models for Business and Economic Forecasting PDF Author: Philip Hans Franses
Publisher: Cambridge University Press
ISBN: 1139952129
Category : Business & Economics
Languages : en
Pages : 421

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Book Description
With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. Downloadable datasets are available online.

Critical Values for Unit Root Tests in Seasonal Time Series

Critical Values for Unit Root Tests in Seasonal Time Series PDF Author: Philip Hans Franses
Publisher:
ISBN:
Category :
Languages : en
Pages : 25

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The Econometric Analysis of Seasonal Time Series

The Econometric Analysis of Seasonal Time Series PDF Author: Eric Ghysels
Publisher: Cambridge University Press
ISBN: 9780521565882
Category : Business & Economics
Languages : en
Pages : 258

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Book Description
Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.

Forecasting: principles and practice

Forecasting: principles and practice PDF Author: Rob J Hyndman
Publisher: OTexts
ISBN: 0987507117
Category : Business & Economics
Languages : en
Pages : 380

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Book Description
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.

Asymptotic Theory for Econometricians

Asymptotic Theory for Econometricians PDF Author: Halbert White
Publisher: Academic Press
ISBN: 1483294420
Category : Business & Economics
Languages : en
Pages : 241

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Book Description
This book is intended to provide a somewhat more comprehensive and unified treatment of large sample theory than has been available previously and to relate the fundamental tools of asymptotic theory directly to many of the estimators of interest to econometricians. In addition, because economic data are generated in a variety of different contexts (time series, cross sections, time series--cross sections), we pay particular attention to the similarities and differences in the techniques appropriate to each of these contexts.