Nonstationary Time Series Analysis And Cointegration
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Nonstationary Time Series Analysis And Cointegration
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Author : Colin P. Hargreaves
language : en
Publisher: Oxford University Press, USA
Release Date : 1994
Nonstationary Time Series Analysis And Cointegration written by Colin P. Hargreaves and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Business & Economics categories.
Nonstationary Time Series Analysis and Cointegration shows major developments in the econometric analysis of the long run (of nonstationarity and cointegration) - a field which has developed dramatically over the last twelve years to have a profound effect on econometric analysis in general. The papers here describe and evaluate new methods, provide useful overviews, and show detailed implementations helpful to practitioners. Papers include two substantive analyses of economic forecasting, based around an integral understanding of integration and cointegration and an evaluation of real business cycle models. There is an evaluation of different cointegration estimators and a new test for cointegration. There is a discussion of the effects of seasonality, looking at seasonal unit roots and at encompassing modelling with seasonally unadjusted versus adjusted data. A different style of nonstationarity is raised in a discussion of testing for inflationary bubbles and for time-varying transition probabilities in Hamilton's Markov switching model. This volume provides wide-ranging coverage of the literature, showing the importance of nonstationarity and cointegration.
Nonstationary Time Series Analysis And Cointegration
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Author : Hargreaves Colin P.
language : en
Publisher:
Release Date : 1994
Nonstationary Time Series Analysis And Cointegration written by Hargreaves Colin P. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
Introduction To Modern Time Series Analysis
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Author : Gebhard Kirchgässner
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-09
Introduction To Modern Time Series Analysis written by Gebhard Kirchgässner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-09 with Business & Economics categories.
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.
Multivariate Modelling Of Non Stationary Economic Time Series
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Author : John Hunter
language : en
Publisher: Springer
Release Date : 2017-05-08
Multivariate Modelling Of Non Stationary Economic Time Series written by John Hunter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-08 with Business & Economics categories.
This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists.
Modelling Non Stationary Economic Time Series
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Author : S. Burke
language : en
Publisher: Springer
Release Date : 2005-06-14
Modelling Non Stationary Economic Time Series written by S. Burke and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-06-14 with Business & Economics categories.
Co-integration, equilibrium and equilibrium correction are key concepts in modern applications of econometrics to real world problems. This book provides direction and guidance to the now vast literature facing students and graduate economists. Econometric theory is linked to practical issues such as how to identify equilibrium relationships, how to deal with structural breaks associated with regime changes and what to do when variables are of different orders of integration.
Forecasting Non Stationary Economic Time Series
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Author : Michael P. Clements
language : en
Publisher: MIT Press
Release Date : 1999
Forecasting Non Stationary Economic Time Series written by Michael P. Clements and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Business & Economics categories.
This text on economic forecasting asks why some practices seem to work empirically despite a lack of formal support from theory. After reviewing the conventional approach to forecasting, it looks at the implications for causal modelling, presents forecast errors and delineates sources of failure.
Analysis Of Integrated And Cointegrated Time Series With R
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Author : Bernhard Pfaff
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-03
Analysis Of Integrated And Cointegrated Time Series With R written by Bernhard Pfaff and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-03 with Business & Economics categories.
This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.
Applied Time Series Econometrics
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Author : Helmut Lütkepohl
language : en
Publisher: Cambridge University Press
Release Date : 2004-08-02
Applied Time Series Econometrics written by Helmut Lütkepohl and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-08-02 with Business & Economics categories.
Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.
The Econometric Analysis Of Non Stationary Spatial Panel Data
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Author : Michael Beenstock
language : en
Publisher: Springer
Release Date : 2019-03-27
The Econometric Analysis Of Non Stationary Spatial Panel Data written by Michael Beenstock and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-27 with Business & Economics categories.
This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.
Co Integration Error Correction And The Econometric Analysis Of Non Stationary Data
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Author : Anindya Banerjee
language : en
Publisher: Oxford University Press
Release Date : 1993-05-27
Co Integration Error Correction And The Econometric Analysis Of Non Stationary Data written by Anindya Banerjee and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-05-27 with Business & Economics categories.
This book provides a wide-ranging account of the literature on co-integration and the modelling of integrated processes (those which accumulate the effects of past shocks). Data series which display integrated behaviour are common in economics, although techniques appropriate to analysing such data are of recent origin and there are few existing expositions of the literature. This book focuses on the exploration of relationships among integrated data series and the exploitation of these relationships in dynamic econometric modelling. The concepts of co-integration and error-correction models are fundamental components of the modelling strategy. This area of time-series econometrics has grown in importance over the past decade and is of interest to econometric theorists and applied econometricians alike. By explaining the important concepts informally, but also presenting them formally, the book bridges the gap between purely descriptive and purely theoretical accounts of the literature. The asymptotic theory of integrated processes is described and the tools provided by this theory are used to develop the distributions of estimators and test statistics. Practical modelling advice, and the use of techniques for systems estimation, are also emphasized. A knowledge of econometrics, statistics, and matrix algebra at the level of a final-year undergraduate or first-year undergraduate course in econometrics is sufficient for most of the book. Other mathematical tools are described as they occur.