Download or read book Periodicity and Stochastic Trends in Economic Time Series written by Philip Hans Franses and published by Oxford University Press, USA. This book was released on 1996 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a self-contained account of periodic models for seasonally observed economic time series with stochastic trends. Two key concepts are periodic integration and periodic cointegration. Periodic integration implies that a seasonally varying differencing filter is required to remove a stochastic trend. Periodic cointegration amounts to allowing cointegration paort-term adjustment parameters to vary with the season. The emphasis is on useful econrameters and shometric models that explicitly describe seasonal variation and can reasonably be interpreted in terms of economic behaviour. The analysis considers econometric theory, Monte Carlo simulation, and forecasting, and it is illustrated with numerous empirical time series. A key feature of the proposed models is that changing seasonal fluctuations depend on the trend and business cycle fluctuations. In the case of such dependence, it is shown that seasonal adjustment leads to inappropriate results.
Download or read book Periodicity Stochastic Trends in Economic Time Series written by Philip Hans Franses and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides a self-contained account of periodic models for seasonally observed economic time series with stochastic trends. The analysis considers econometric theory, Monte Carlo simulation and forecasting, and it is illuminated with empirical time series.
Download or read book Periodic Time Series Models written by Philip Hans Franses and published by OUP Oxford. This book was released on 2004-03-25 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book presents a large number of empirical results. The first part of the book deals with model selection, diagnostic checking and forecasting of univariate periodic autoregressive models. Tests for periodic integration, are discussed, and an extensive discussion of the role of deterministic regressors in testing for periodic integration and in forecasting is provided. The second part discusses multivariate periodic autoregressive models. It provides an overview of periodic cointegration models, as these are the most relevant. This overview contains single-equation type tests and a full-system approach based on generalized method of moments. All methods are illustrated with extensive examples, and the book will be of interest to advanced graduate students and researchers in econometrics, as well as practitioners looking for an understanding of how to approach seasonal data.
Download or read book Periodicity and Stochastic Trends in Economic Time Series written by Philip Hans Franses and published by . This book was released on with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modelling Trends and Cycles in Economic Time Series written by Terence C. Mills and published by Springer Nature. This book was released on 2021-07-29 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Periodic Time Series Models written by Philip Hans Franses and published by . This book was released on 2004 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this insightful, modern study of the use of periodic models in the description and forecasting of economic data the authors investigate such areas as seasonal time series, periodic time series models, periodic integration and periodic cointegration.
Download or read book Economic Time Series written by William R. Bell and published by CRC Press. This book was released on 2018-11-14 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time s
Download or read book Spectral Analysis of Economic Time Series PSME 1 written by Clive William John Granger and published by Princeton University Press. This book was released on 2015-12-08 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for time series data. New methods for analyzing series containing no trends have been developed by communication engineering, and much recent research has been devoted to adapting and extending these methods so that they will be suitable for use with economic series. This book presents the important results of this research and further advances the application of the recently developed Theory of Spectra to economics. In particular, Professor Hatanaka demonstrates the new technique in treating two problems-business cycle indicators, and the acceleration principle existing in department store data. Originally published in 1964. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Download or read book Forecasting Economic Time Series written by Clive William John Granger and published by . This book was released on 1977 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Forecasting Non stationary Economic Time Series written by Michael P. Clements and published by MIT Press. This book was released on 1999 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Periodic Time Series Models written by Philip Hans Franses and published by Oxford University Press. This book was released on 2004 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this insightful, modern study of the use of periodic models in the description and forecasting of economic data the authors investigate such areas as seasonal time series, periodic time series models, periodic integration and periodic cointegration.
Download or read book Forecasting Economic Time Series written by Michael Clements and published by Cambridge University Press. This book was released on 1998-10-08 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book A Continuous Time Econometric Model of the United Kingdom with Stochastic Trends written by Albert Rex Bergstrom and published by Cambridge University Press. This book was released on 2007-04-16 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents a continuous time macroeconometric model of the United Kingdom incorporating stochastic trends. It describes the model in detail to permit a rigorous mathematical analysis of its steady-state and stability properties, thus providing a valuable check on the capacity of the model to generate plausible long-run behaviour.
Download or read book Time Series Analysis and Adjustment written by Haim Y. Bleikh and published by CRC Press. This book was released on 2016-02-24 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyze economic and financial data on behalf of economic and financial institutions and provide statistics to whomsoever requires them. Such analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory and focused on modelling. An understanding of time series and the application and understanding of related time series adjustment procedures is essential in areas such as risk management, business cycle analysis, and forecasting. Dealing with economic data involves grappling with things like varying numbers of working and trading days in different months and movable national holidays. Special attention has to be given to such things. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to uncover hidden patterns in the data and then to generate accurate forecasts. The case studies in this book demonstrate that time series adjustment methods can be efficaciously applied and utilized, for both analysis and forecasting, but they must be used in the context of reasoned statistical and economic judgment. The authors believe this is the first published study to really deal with this issue of context.
Download or read book Seasonal Adjustment when Both Deterministic and Stochastic Seasonality are Present written by David A. Pierce and published by . This book was released on 1976 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Modern Time Series Analysis written by Gebhard Kirchgässner and published by Springer Science & Business Media. This book was released on 2012-10-09 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Time Series Models for Business and Economic Forecasting written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2014-04-24 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
