Title: CAMPLET: Seasonal adjustment without revisions
Authors: Barend Abeln - Investment consultant (Netherlands) [presenting]
Jan Jacobs - University of Groningen (Netherlands)
Abstract: Seasonality in macroeconomic time series can `obscure' movements of other components in a series that are operationally more important for economic and econometric analyses. Indeed, in practice, one often prefers to work with seasonally adjusted data to assess the current state of the economy and its future course. A seasonal adjustment program called CAMPLET, an acronym of its tuning parameters, is presented which consists of a simple adaptive procedure to separate the seasonal and the non-seasonal component from an observed time series. Once this process is carried out there will be no need to revise these components at a later stage when new observations become available. Recently, two most widely used seasonal adjustment methods, Census X-12-ARIMA and TRAMO-SEATS, merged into X-13ARIMA-SEATS to become a new industry standard. The main features of CAMPLET are described, and a brief review of X13ARIMA-SEATS is provided. We compare and contrast CAMPLET with X-13ARIMA-SEATS. We evaluate the outcomes of both methods in a controlled simulation framework using a variety of processes.