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Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation (Hardcover, 1st ed. 2016)
Loot Price: R4,659
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Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation (Hardcover, 1st ed. 2016)
Series: Statistics for Social and Behavioral Sciences
Expected to ship within 12 - 17 working days
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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.
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