An Evaluation of Singular Spectrum Analysis-Based Seasonal Adjustment

In this paper, the Singular Spectrum Analysis (SSA) is presented and applied in the US air traffic emplacements for the period Jan. 1954 – Sept. 2011. I decompose the US air traffic emplacements in trend, cycle, seasonal and noise components. In turn, I apply several spectral criteria in order to evaluate the SSA as a seasonal adjustment filter. SSA detects, beyond trend, strong cycles and seasonal components and leaves as a residual a GARCH process. SSA performs quite well as a seasonal adjustment mechanism in the case of the GARCH process but it performs even better in the case of a simulated white noise process. SSA is a serious candidate in economics in dealing with filtering, denoising, smoothing and seasonal adjustment.