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Author: Robert F. Engle
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 56
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Book Description
Author: Robert F. Engle
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 56
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Book Description
Author: John Hunter
Publisher: Springer
ISBN: 113731303X
Category : Business & Economics
Languages : en
Pages : 508
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Book Description
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.
Author: Colin P. Hargreaves
Publisher: Oxford University Press, USA
ISBN:
Category : Business & Economics
Languages : en
Pages : 336
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Book Description
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.
Author: Jean-Marie Dufour
Publisher: Springer Science & Business Media
ISBN: 3642487424
Category : Business & Economics
Languages : en
Pages : 248
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Book Description
This book contains eleven articles which provide empirical applications as well as theoretical extensions of some of the most exciting recent developments in time-series econometrics. The papers are grouped around three broad themes: (I) the modeling of multivariate times series; (II) the analysis of structural change; (III) seasonality and fractional integration. Since these themes are closely inter-related, several other topics covered are also worth stressing: vector autoregressive (VAR) models, cointegration and error-correction models, nonparametric methods in time series, and fractionally integrated models. Researchers and students interested in macroeconomic and empirical finance will find in this collection a remarkably representative sample of recent work in this area.
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.
Author: S. Burke
Publisher: Springer
ISBN: 0230005780
Category : Business & Economics
Languages : en
Pages : 253
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Book Description
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.
Author: Gebhard Kirchgässner
Publisher: Springer Science & Business Media
ISBN: 3642334369
Category : Business & Economics
Languages : en
Pages : 326
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Book Description
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.
Author: Helmut Lütkepohl
Publisher: Springer Science & Business Media
ISBN: 9783540569404
Category : Business & Economics
Languages : en
Pages : 576
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Book Description
This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
Author: Bernhard Pfaff
Publisher: Springer Science & Business Media
ISBN: 0387759670
Category : Business & Economics
Languages : en
Pages : 193
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Book Description
This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.
Author: Helmut Lütkepohl
Publisher: Cambridge University Press
ISBN: 1139454730
Category : Business & Economics
Languages : en
Pages : 351
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Book Description
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.
