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Author: Philip Hans Franses Publisher: Oxford University Press, USA ISBN: Category : Business & Economics Languages : en Pages : 256
Book Description
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.
Author: Philip Hans Franses Publisher: Oxford University Press, USA ISBN: Category : Business & Economics Languages : en Pages : 256
Book Description
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.
Author: Philip Hans Franses Publisher: OUP Oxford ISBN: 0191529265 Category : Business & Economics Languages : en Pages : 166
Book Description
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.
Author: Philip Hans Franses Publisher: ISBN: 9781383033144 Category : Cycles Languages : en Pages : 0
Book Description
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.
Author: Terence C. Mills Publisher: Springer Nature ISBN: 3030763595 Category : Business & Economics Languages : en Pages : 219
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: Philip Hans Franses Publisher: ISBN: 9780191601286 Category : Econometric models Languages : en Pages : 147
Book Description
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.
Author: Clive William John Granger Publisher: Princeton University Press ISBN: 1400875528 Category : Business & Economics Languages : en Pages : 318
Book Description
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.
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.
Author: Haim Y. Bleikh Publisher: CRC Press ISBN: 1317010175 Category : Business & Economics Languages : en Pages : 148
Book Description
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.
Author: Philip Hans Franses
Author: Philip Hans Franses
Author: Philip Hans Franses
Author: Philip Hans Franses
Author: Philip Hans Franses
Author: Terence C. Mills
Author: Philip Hans Franses
Author: Philip Hans Franses
Author: Clive William John Granger
Author: Clive William John Granger
Author: Haim Y. Bleikh