The Importance of Trend-Cycle Analysis for National Statistics Institutes

Abstract

Seasonal adjustment is a widely applied statistical method. National Statistics Institutes around the world apply seasonal adjustment methods, such as X-12-ARIMA or TRAMO-SEATS, on a regular basis to help users interpret movements in the time series and aid in decision making. The seasonal adjustment process decomposes the original time series into three main components: a trend-cycle, seasonal and irregular. By definition the seasonally adjusted estimates still contain a degree of volatility as they are just a combination of the trend-cycle and irregular. Typically, as an analytical product, the seasonally adjusted estimates are published alongside the time series of the original estimates. In most countries the trend-cycle estimates are not published. Some countries, such as Australia, regularly publish trend-cycle as additional analytical product alongside the original and seasonally adjusted estimates to inform users. This paper presents the case for the regular calculation and production of trend- cycle estimates at National Statistics Institutes to help inform and educate users about the longer term signals in the time series.