Elements of Time Series Econometrics
Elements of Time Series Econometrics

Author: Evžen Kočenda

Publisher:

Published: 2007

Total Pages: 0

ISBN-13: 9788024613703

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This book presents the numerous tools for the econometric analysis of time series. The text is designed with emphasis on the practical application of theoretical tools. Accordingly, material is presented in a way that is easy to understand. In many cases, intuitive explanation and understanding of the studied phenomena are offered. Essential concepts are illustrated by clear-cut examples. The attention of readers is drawn to numerous applied works where the use of specific techniques is best illustrated. Such applications are chiefly connected with issues of recent economic transition and European integration. The outlined style of presentation makes the book also a rich source of references. The text is divided into four major sections. The first section, "The Nature of Time Series," gives an introduction to time series analysis. The second section, "Difference Equations," describes briefly the theory of difference equations, with an emphasis on results that are important for time series econometrics. The third section, "Univariate Time Series," presents the methods commonly used in univariate time series analysis, the analysis of time series of one single variable. The fourth section, "Multiple Time Series," deals with time series models of multiple interrelated variables. Appendices contain an introduction to simulation techniques and statistical tables.

Elements of Time Series Econometrics : An Applied Approach
Elements of Time Series Econometrics : An Applied Approach

Author: Evžen Kočenda

Publisher: Karolinum Press

Published: 2014-03-01

Total Pages: 220

ISBN-13: 8024623153

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This book presents the numerous tools for the econometric analysis of time series. The text is designed with emphasis on the practical application of theoretical tools. Accordingly, material is presented in a way that is easy to understand. In many cases intuitive explanation and understanding of the studied phenomena are offerd. Essential concepts are illustrated by clear-cut examples. The attention of readers is drawn to numerous applied works where the use of specific techniques is best illustrated. Such applications are chiefly connected with issues of recent economic transition and European integration. The outlined style of presentation makes the book also a rich source of references. The text is divided into four major sections. The first section, "The Nature of Time Series?, gives an introduction to time series analysis. The second section, "Difference Equations?, describes briefly the theory of difference equations with an emphasis on results that are important for time series econometrics. The third section, "Univariate Time Series?, presents the methods commonly used in univariate time series analysis, the analysis of time series of one single variable. The fourth section, "Multiple Time Series?, deals with time series models of multiple interrelated variables. Appendices contain an introduction to simulation techniques and statistical tables.

The Econometric Analysis of Seasonal Time Series
The Econometric Analysis of Seasonal Time Series

Author: Eric Ghysels

Publisher: Cambridge University Press

Published: 2001-06-18

Total Pages: 258

ISBN-13: 9780521565882

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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, Structural Time Series Models and the Kalman Filter
Forecasting, Structural Time Series Models and the Kalman Filter

Author: Andrew C. Harvey

Publisher: Cambridge University Press

Published: 1990

Total Pages: 574

ISBN-13: 9780521405737

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A synthesis of concepts and materials, that ordinarily appear separately in time series and econometrics literature, presents a comprehensive review of theoretical and applied concepts in modeling economic and social time series.

Forecasting: principles and practice
Forecasting: principles and practice

Author: Rob J Hyndman

Publisher: OTexts

Published: 2018-05-08

Total Pages: 380

ISBN-13: 0987507117

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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.

Time Series Models for Business and Economic Forecasting
Time Series Models for Business and Economic Forecasting

Author: Philip Hans Franses

Publisher: Cambridge University Press

Published: 2014-04-24

Total Pages: 421

ISBN-13: 1139952129

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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.

Time Series Analysis by State Space Methods
Time Series Analysis by State Space Methods

Author: James Durbin

Publisher: OUP Oxford

Published: 2012-05-03

Total Pages: 369

ISBN-13: 0191627194

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This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series. Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations. Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.