Trends and Random Walks in Macroeconomic Time Series : Further Evidence from a New Approach PDF Download

Author: Perron, Pierre
Publisher: Montréal : Dép. de science économique, Université de Montréal
ISBN:
Category :
Languages : en
Pages : 49

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Author: Glenn D. Rudebusch
Publisher:
ISBN:
Category : Macroeconomics
Languages : en
Pages : 58

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Author: Charles R.. Nelson
Publisher:
ISBN:
Category :
Languages : en
Pages : 36

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Author: Denis Eugene Kwiatkowski
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 326

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Book Description

Author: Terence C. Mills
Publisher: Springer Nature
ISBN: 3030763595
Category : Business & Economics
Languages : en
Pages : 219

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Book Description
Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

Author: Glenn D. RUDEBUSCH
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: T. Mills
Publisher: Springer
ISBN: 0230595529
Category : Business & Economics
Languages : en
Pages : 184

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Book Description
Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. Terence Mills introduces these various approaches to allow students and researchers to appreciate the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

Author: Philip Hans Franses
Publisher: Cambridge University Press
ISBN: 9780521586412
Category : Business & Economics
Languages : en
Pages : 300

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Book Description
An introduction to time series models for business and economic forecasting.

Author: Terence C. Mills
Publisher: Cambridge University Press
ISBN: 9780521405744
Category : Business & Economics
Languages : en
Pages : 392

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Book Description
The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. This book clearly distinguishes itself from its competitors by emphasising the techniques of time series modelling rather than technical aspects such as estimation, and by the breadth of the models considered. It features many detailed real-world examples using a wide range of actual time series. It will be useful to econometricians and specialists in forecasting and finance and accessible to most practitioners in economics and the allied professions.

Author: Gebhard Kirchgässner
Publisher: Springer Science & Business Media
ISBN: 3642334350
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.