Seasonal adjustment methods and real time trend-cycle estimation [electronic resource] / Estela Bee Dagum, Silvia Bianconcini.
Dagum, Estela Bee, author.; Bianconcini, Silvia, author.
2016
HB137
Available Online

Linked e-resources

Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks

Details

Title
Seasonal adjustment methods and real time trend-cycle estimation [electronic resource] / Estela Bee Dagum, Silvia Bianconcini.
Author
Dagum, Estela Bee, author.
ISBN
9783319318226 (electronic book)
3319318225 (electronic book)
9783319318202
Published
Switzerland : Springer, 2016.
Language
English
Description
1 online resource (xvi, 283 pages) : illustrations.
Call Number
HB137
Dewey Decimal Classification
338.5/4
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed July 5, 2016).
Added Author
Bianconcini, Silvia, author.
Series
Statistics for social and behavioral sciences.
Available in Other Form
Seasonal adjustment methods and real time trend-cycle prediction.
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
Introduction
Time Series Components
Part I: Seasonal Adjustment Methods
Seasonal Adjustment: Meaning, Purpose and Methods
Linear Filters Seasonal Adjustment Methods: Census Method II and its Variants
Seasonal Adjustment Based on ARIMA Decomposition: TRAMO-SEATS
Seasonal Adjustment Based on Structural Time Series Models
Part II: Trend-Cycle Estimation
Trend-Cycle Estimation
Further Developments on the Henderson Trend-Cycle Filter
A Unified View of Trend-Cycle Predictors in Reproducing Kernel Hilbert Spaces (RKHS)
Real Time Trend-Cycle Prediction
The Effect of Seasonal Adjustment on Real-Time Trend-Cycle Prediction
Glossary.

Browse Subjects

Show more subjects...

Statistics

from
to
Export