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Forecasting Non-stationary Economic Time Series

Forecasting Non-stationary Economic Time Series PDF Author: Michael P. Clements
Publisher: MIT Press
ISBN: 9780262531894
Category : Business & Economics
Languages : en
Pages : 398

Book Description
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.

Forecasting Non-stationary Economic Time Series

Forecasting Non-stationary Economic Time Series PDF Author: Michael P. Clements
Publisher: MIT Press
ISBN: 9780262531894
Category : Business & Economics
Languages : en
Pages : 398

Book Description
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.

Forecasting Non-stationary Economic Time Series

Forecasting Non-stationary Economic Time Series PDF Author: D. Couts
Publisher:
ISBN:
Category :
Languages : en
Pages : 21

Book Description


Modelling Non-Stationary Economic Time Series

Modelling Non-Stationary Economic Time Series PDF Author: S. Burke
Publisher: Springer
ISBN: 0230005780
Category : Business & Economics
Languages : en
Pages : 253

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.

Multivariate Modelling of Non-Stationary Economic Time Series

Multivariate Modelling of Non-Stationary Economic Time Series PDF Author: John Hunter
Publisher: Springer
ISBN: 113731303X
Category : Business & Economics
Languages : en
Pages : 508

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.

Forecasting Economic Time Series

Forecasting Economic Time Series PDF Author: Michael Clements
Publisher: Cambridge University Press
ISBN: 9780521634809
Category : Business & Economics
Languages : en
Pages : 402

Book Description
This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz. a non-constant, evolving economic system, and econometric models whose form and structure are unknown a priori. The authors find that conclusions which can be established formally for constant-parameter stationary processes and correctly-specified models often do not hold when unrealistic assumptions are relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject to structural breaks, Hendry and Clements show that significant insights can be gleaned. For example, a formal taxonomy of forecasting errors can be developed, the role of causal information clarified, intercept corrections re-established as a method for achieving robustness against forms of structural change, and measures of forecast accuracy re-interpreted.

Forecasting: principles and practice

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

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.

Forecasting Economic Time Series

Forecasting Economic Time Series PDF Author: Clive William John Granger
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 428

Book Description
This book has been updated to reflect developments in time series analysis and forecasting theory and practice, particularly as applied to economics. The second edition pays attention to such problems as how to evaluate and compare forecasts.

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

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.

Statistics in Volcanology

Statistics in Volcanology PDF Author: Heidy M. Mader
Publisher: Geological Society of London
ISBN: 9781862392083
Category : Nature
Languages : en
Pages : 304

Book Description
Statistics in Volcanology is a comprehensive guide to modern statistical methods applied in volcanology written by today's leading authorities. The volume aims to show how the statistical analysis of complex volcanological data sets, including time series, and numerical models of volcanic processes can improve our ability to forecast volcanic eruptions. Specific topics include the use of expert elicitation and Bayesian methods in eruption forecasting, statistical models of temporal and spatial patterns of volcanic activity, analysis of time series in volcano seismology, probabilistic hazard assessment, and assessment of numerical models using robust statistical methods. Also provided are comprehensive overviews of volcanic phenomena, and a full glossary of both volcanological and statistical terms. Statistics in Volcanology is essential reading for advanced undergraduates, graduate students, and research scientists interested in this multidisciplinary field.

Forecasting Economic Time Series

Forecasting Economic Time Series PDF Author: C. W. J. Granger
Publisher: Academic Press
ISBN: 1483273245
Category : Business & Economics
Languages : en
Pages : 353

Book Description
Economic Theory, Econometrics, and Mathematical Economics, Second Edition: Forecasting Economic Time Series presents the developments in time series analysis and forecasting theory and practice. This book discusses the application of time series procedures in mainstream economic theory and econometric model building. Organized into 10 chapters, this edition begins with an overview of the problem of dealing with time series possessing a deterministic seasonal component. This text then provides a description of time series in terms of models known as the time-domain approach. Other chapters consider an alternative approach, known as spectral or frequency-domain analysis, that often provides useful insights into the properties of a series. This book discusses as well a unified approach to the fitting of linear models to a given time series. The final chapter deals with the main advantage of having a Gaussian series wherein the optimal single series, least-squares forecast will be a linear forecast. This book is a valuable resource for economists.