Time Series Analysis And Adjustment

Author : Haim Y. Bleikh,Warren L.Young
Publisher : CRC Press
Page : 148 pages
File Size : 40,5 Mb
Release : 2016-02-24
Category : Business & Economics
ISBN : 9781317010173

Get Book

Time Series Analysis and Adjustment by Haim Y. Bleikh,Warren L.Young Pdf

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 : William R. Bell,Scott H. Holan,Tucker S. McElroy
Publisher : CRC Press
Page : 544 pages
File Size : 42,7 Mb
Release : 2018-11-14
Category : Mathematics
ISBN : 9781439846582

Get Book

Economic Time Series by William R. Bell,Scott H. Holan,Tucker S. McElroy Pdf

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

Author : Estela Bee Dagum,Silvia Bianconcini
Publisher : Springer
Page : 283 pages
File Size : 49,9 Mb
Release : 2016-06-20
Category : Business & Economics
ISBN : 9783319318226

Get Book

Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation by Estela Bee Dagum,Silvia Bianconcini Pdf

This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.

Author : Haim Y. Bleikh,Warren L.Young
Publisher : CRC Press
Page : 149 pages
File Size : 47,5 Mb
Release : 2016-02-24
Category : Business & Economics
ISBN : 9781317010180

Get Book

Time Series Analysis and Adjustment by Haim Y. Bleikh,Warren L.Young Pdf

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 : Rob J Hyndman,George Athanasopoulos
Publisher : OTexts
Page : 380 pages
File Size : 49,7 Mb
Release : 2018-05-08
Category : Business & Economics
ISBN : 9780987507112

Get Book

Forecasting: principles and practice by Rob J Hyndman,George Athanasopoulos Pdf

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.

Author : Terence C. Mills
Publisher : Cambridge University Press
Page : 392 pages
File Size : 49,6 Mb
Release : 1990
Category : Business & Economics
ISBN : 0521405742

Get Book

Time Series Techniques for Economists by Terence C. Mills Pdf

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 : George E. P. Box,Gwilym M. Jenkins,Gregory C. Reinsel
Publisher : Unknown
Page : 628 pages
File Size : 54,7 Mb
Release : 1994
Category : Business & Economics
ISBN : UOM:39015040387949

Get Book

Time Series Analysis by George E. P. Box,Gwilym M. Jenkins,Gregory C. Reinsel Pdf

This is a complete revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970. It focuses on practical techniques throughout, rather than a rigorous mathematical treatment of the subject. It explores the building of stochastic (statistical) models for time series and their use in important areas of application forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control. Features sections on: recently developed methods for model specification,such as canonical correlation analysis and the use of model selection criteria; results on testing for unit root nonstationarity in ARIMA processes; the state space representation of ARMA models and its use for likelihood estimation and forecasting; score test for model checking; and deterministic components and structural components in time series models and their estimation based on regression-time series model methods.

Author : Marc Nerlove,David M. Grether,José L. Carvalho
Publisher : Academic Press
Page : 495 pages
File Size : 52,8 Mb
Release : 2014-05-10
Category : Business & Economics
ISBN : 9781483218885

Get Book

Analysis of Economic Time Series by Marc Nerlove,David M. Grether,José L. Carvalho Pdf

Analysis of Economic Time Series: A Synthesis integrates several topics in economic time-series analysis, including the formulation and estimation of distributed-lag models of dynamic economic behavior; the application of spectral analysis in the study of the behavior of economic time series; and unobserved-components models for economic time series and the closely related problem of seasonal adjustment. Comprised of 14 chapters, this volume begins with a historical background on the use of unobserved components in the analysis of economic time series, followed by an Introduction to the theory of stationary time series. Subsequent chapters focus on the spectral representation and its estimation; formulation of distributed-lag models; elements of the theory of prediction and extraction; and formulation of unobserved-components models and canonical forms. Seasonal adjustment techniques and multivariate mixed moving-average autoregressive time-series models are also considered. Finally, a time-series model of the U.S. cattle industry is presented. This monograph will be of value to mathematicians, economists, and those interested in economic theory, econometrics, and mathematical economics.

Author : Harry Myer Rosenblatt
Publisher : Unknown
Page : 60 pages
File Size : 54,5 Mb
Release : 1965
Category : Seasonal variations
ISBN : PSU:000070961911

Get Book

Spectral Analysis and Parametric Methods for Seasonal Adjustment of Economic Time Series by Harry Myer Rosenblatt Pdf

Author : William W. S. Wei
Publisher : Pearson
Page : 648 pages
File Size : 48,9 Mb
Release : 2018-03-14
Category : Time-series analysis
ISBN : 0134995368

Get Book

Time Series Analysis Univariate and Multivariate Methods by William W. S. Wei Pdf

With its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Time Series Analysis is a thorough introduction to both time-domain and frequency-domain analyses of univariate and multivariate time series methods, with coverage of the most recently developed techniques in the field.

Author : Anders Milhoj
Publisher : Unknown
Page : 0 pages
File Size : 44,5 Mb
Release : 2013
Category : Computers
ISBN : 1612901700

Get Book

Practical Time Series Analysis Using SAS by Anders Milhoj Pdf

Anders Milhøj's Practical Time Series Analysis Using SAS explains and demonstrates through examples how you can use SAS for time series analysis. It offers modern procedures for forecasting, seasonal adjustments, and decomposition of time series that can be used without involved statistical reasoning. The book teaches, with numerous examples, how to apply these procedures with very simple coding. In addition, it also gives the statistical background for interested readers. Beginning with an introductory chapter that covers the practical handling of time series data in SAS using the TIMESERIES and EXPAND procedures, it goes on to explain forecasting, which is found in the ESM procedure; seasonal adjustment, including trading-day correction using PROC X12; and unobserved component models using the UCM procedure. This book is part of the SAS Press program.

Author : Eric Ghysels,Denise R. Osborn
Publisher : Cambridge University Press
Page : 258 pages
File Size : 40,6 Mb
Release : 2001-06-18
Category : Business & Economics
ISBN : 052156588X

Get Book

The Econometric Analysis of Seasonal Time Series by Eric Ghysels,Denise R. Osborn Pdf

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.

Author : Steven Durlauf,L. Blume
Publisher : Springer
Page : 417 pages
File Size : 53,8 Mb
Release : 2016-04-30
Category : Business & Economics
ISBN : 9780230280830

Get Book

Macroeconometrics and Time Series Analysis by Steven Durlauf,L. Blume Pdf

Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.

Author : Víctor Gómez
Publisher : Springer Nature
Page : 355 pages
File Size : 45,7 Mb
Release : 2019-10-04
Category : Computers
ISBN : 9783030207908

Get Book

Linear Time Series with MATLAB and OCTAVE by Víctor Gómez Pdf

This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book ‘Multivariate Time Series With Linear State Space Structure’, by the same author, if they require more details.

Author : Paul S.P. Cowpertwait,Andrew V. Metcalfe
Publisher : Springer Science & Business Media
Page : 262 pages
File Size : 53,8 Mb
Release : 2009-05-28
Category : Mathematics
ISBN : 9780387886985

Get Book

Introductory Time Series with R by Paul S.P. Cowpertwait,Andrew V. Metcalfe Pdf

This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation. Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence enhances understanding of both the time series model and the R function used to fit the model to data. Finally, the model is used to analyse observed data taken from a practical application. By using R, the whole procedure can be reproduced by the reader. All the data sets used in the book are available on the website http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/. The book is written for undergraduate students of mathematics, economics, business and finance, geography, engineering and related disciplines, and postgraduate students who may need to analyse time series as part of their taught programme or their research.