Seasonal adjustment by frequency determined filter procedures

Article type: Research Article

Authors: Nourney, Martin¹

Note: [1] Martin Nourney was born in 1930 and finished the study of mathematics and statistics at the universities at Kiel and Göttingen in 1956 with a degree in mathematics. In the Federal Statistical Office, Wiesbaden, he was first assigned to sampling problems in the agricultural sector. Since 1968, he is responsible for official sampling methods including mathematical methods of statistical analysis in the Federal Republic of Germany.

Abstract: For the purposes of monthly time series analysis the original data are assumed to be additively composed of a trend-cycle, a seasonal, a calender-effect, and a residual component, the last of which may include a few extreme values. The first mentioned two components are estimated by moving filter applications derived from approximating functions by a regression approach. The appropriateness of the filters is judged and controlled by their transforms into the frequency domain. While model 3 of this procedure was designed series-specifically, the improved model 4 provides adaptive and end-stable results by a uniform set of filters to both components where general optimization aspects had already been included. The mathematical models used, their specifications and development, and some features of the new model like practical simplicity and definiteness are indicated. A hint is given to the integrated identification of extreme values and estimation of calendar-effects which in future will both be performed before the eventual seasonal adjustment.

DOI: 10.3233/SJU-1984-2204

Journal: Statistical Journal of the United Nations Economic Commission for Europe, vol. 2, no. 2, pp. 161-168, 1984