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Seasonal adjustment or deseasonalization is a statistical method for removing the seasonal component of a time series. It is usually done when wanting to analyse the trend, and cyclical deviations from trend, of a time series independently of the seasonal components.
X-13ARIMA-SEATS, successor to X-12-ARIMA and X-11, is a set of statistical methods for seasonal adjustment and other descriptive analysis of time series data that are implemented in the U.S. Census Bureau's software package. [3]
The Mexican government declared that its economy technically had left the recession when the Mexican GDP grew by 2.93% in the third quarter of 2009. Mexico had been in a severe economic crisis for over a year prior to its economic rebound. The Mexican government also approved a $244 billion budget for 2010, a slight increase from 2009. [105]
Likewise, seasonal differencing is applied to a seasonal time-series to remove the seasonal component. From the perspective of signal processing, especially the Fourier spectral analysis theory, the trend is a low-frequency part in the spectrum of a series, while the season is a periodic-frequency part.
The seasonally adjusted PPP‑weighted real GDP for the G20‑zone, however, is a good indicator for the world GDP, and it was measured to have suffered a direct quarter on quarter decline during the three quarters from Q3‑2008 until Q1‑2009, which more accurately mark when the recession took place at the global level. [16]
The author of the Wall Street Journal article, Heather Haddon, didn't reply to my inquiry about why she appeared to use non-seasonally adjusted figures when the adjusted figures were more appropriate.
The seasonally adjusted annual rate (SAAR) is a rate that is adjusted to take into account typical seasonal fluctuations in data and is expressed as an annual total. SAARs are used for data affected by seasonality , when it could be misleading to directly compare different times of the year.
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