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Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation
ISBN-13:
9783319318226
Veröffentl:
2016
Seiten:
283
Autor:
Estela Bee Dagum
Serie:
Statistics for Social and Behavioral Sciences
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
Beschreibung:
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.
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.
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