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| Author | : Philip Hans Franses |
| Publisher | : Oxford University Press |
| Total Pages | : 162 |
| Release | : 2004 |
| Genre | : Business & Economics |
| ISBN | : 019924202X |
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 | : Philip Hans Franses |
| Publisher | : Oxford University Press, USA |
| Total Pages | : 256 |
| Release | : 1996 |
| Genre | : Business & Economics |
| ISBN | : |
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 | : |
| Total Pages | : 230 |
| Release | : |
| Genre | : ANALISIS DE SERIES DE TIEMPO. |
| ISBN | : |
| Author | : Philip Hans Franses |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2023 |
| Genre | : Cycles |
| ISBN | : 9781383033144 |
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 | : Philip Hans Franses |
| Publisher | : Cambridge University Press |
| Total Pages | : 300 |
| Release | : 1998-10-15 |
| Genre | : Business & Economics |
| ISBN | : 9780521586412 |
An introduction to time series models for business and economic forecasting.
| Author | : Masanao Aoki |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 262 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 3642455654 |
In seminars and graduate level courses I have had several opportunities to discuss modeling and analysis of time series with economists and economic graduate students during the past several years. These experiences made me aware of a gap between what economic graduate students are taught about vector-valued time series and what is available in recent system literature. Wishing to fill or narrow the gap that I suspect is more widely spread than my personal experiences indicate, I have written these notes to augment and reor ganize materials I have given in these courses and seminars. I have endeavored to present, in as much a self-contained way as practicable, a body of results and techniques in system theory that I judge to be relevant and useful to economists interested in using time series in their research. I have essentially acted as an intermediary and interpreter of system theoretic results and perspectives in time series by filtering out non-essential details, and presenting coherent accounts of what I deem to be important but not readily available, or accessible to economists. For this reason I have excluded from the notes many results on various estimation methods or their statistical properties because they are amply discussed in many standard texts on time series or on statistics.
| Author | : Terence C. Mills |
| Publisher | : Springer Nature |
| Total Pages | : 219 |
| Release | : 2021-07-29 |
| Genre | : Business & Economics |
| ISBN | : 3030763595 |
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 | : Marc Nerlove |
| Publisher | : |
| Total Pages | : 504 |
| Release | : 1979 |
| Genre | : Business & Economics |
| ISBN | : |
In this edition which has been reprinted with corrections, Nerlove and his co-authors illustrate techniques of spectral analysis and methods based on parametric models in the analysis of economic time series. The book provides a means and a method for incorporating economic intuition and theory in the formulation of time-series models useful in forecasting, in the formulation and estimation of distributed lag models, and in other applications, such as seasonal adjustment. Analysis of Economic Time Series is a useful primary text for graduate students and an attractive reference for researchers. Key Features * Presents a self-contained treatment of Fourier Analysis and complex variables, as well as Spectral Analysis of time series * Includes a detailed treatment of unobserved-components (UC) models and their time-series properties by means of covariance-generating transforms * Provides the formulation and maximum-likelihood estimation of ARMA and UC models in both time and frequency domains Integrates several topics in time-series analysis: * The formulation and estimation of distributed-lag models of dynamic economic behavior * The application of the techniques of spectral analysis in the study of behavior of economic time series * Unobserved-components models for economic time series and the closely related problem of seasonal adjustment * The complimentarities between time-domain and frequency-domain approaches to the analysis of economic time series * Historical contributions extending from the time of Charles Babbage and the Edinburgh Review to the present * Treats spectral analysis and Box-Jenkins models for an intuitive but rigorous point of view * Shows how these two types of analysis may be synthesized so that they complement one another * Describes a new type of model, based on a superposition of Box-Jenkins models, that captures the essential idea of the unobserved-components models long used in the analysis of economic time series * Applies multiple time-series techniques to the estimation of a novel dynamic model of the US cattle industry
| Author | : Haim Y Bleikh |
| Publisher | : Ashgate Publishing, Ltd. |
| Total Pages | : 149 |
| Release | : 2014-07-01 |
| Genre | : Business & Economics |
| ISBN | : 140944192X |
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 to provide statistics. An understanding of time series and the application and knowledge of related time series adjustment procedures is essential in areas such as risk management, business cycle analysis, and forecasting. 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 -- this is the first known published study to really deal with this issue of context.
| Author | : Clive William John Granger |
| Publisher | : |
| Total Pages | : 528 |
| Release | : 1977 |
| Genre | : Business & Economics |
| ISBN | : |
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.
