Detrending, stylized facts and the business cycle

TLDR

Macroeconomic time series can be described by structural time‑series models, which also expose limitations of ARIMA and deterministic‑trend models with a single break. The study analyzes the consequences of the Hodrick–Prescott detrending technique. The authors use structural time‑series models to assess the effects of the Hodrick–Prescott filter and to account for seasonal and irregular movements that can distort cyclical components. The study shows that the Hodrick–Prescott filter can produce spurious cyclical behavior, as demonstrated by empirical examples.

Abstract

Abstract The stylized facts of macroeconomic time series can be presented by fitting structural time series models. Within this framework, we analyse the consequences of the widely used detrending technique popularised by Hodrick and Prescott (1980). It is shown that mechanical detrending based on the Hodrick–Prescott filter can lead investigators to report spurious cyclical behaviour, and this point is illustrated with empirical examples. Structural time‐series models also allow investigators to deal explicitly with seasonal and irregular movements that may distort estimated cyclical components. Finally, the structural framework provides a basis for exposing the limitations of ARIMA methodology and models based on a deterministic trend with a single break.