Hamilton (2018) argues that one should never use the Hodrick-Prescott (HP) filter to detrend economic time series and proposes an alternative approach. This comment reconsiders Hamilton's case against the HP filter, emphasizing two simple points. First, in the empirical example Hamilton...

The COVID-19 pandemic has caused a substantial increase in house price growth and its seasonal amplitude. This change has presented challenges to traditional seasonal adjustment methods, such as the U.S. Census Bureau's X-12 method. This study tests for residual seasonality in three major...

This paper uses a seasonal long-memory model to capture the behaviour of the US Industrial Production Index (IPI) over the period 1919Q1-2022Q4. This series is found to display a large value of the periodogram at the zero, long-run frequency, and to exhibit an order of integration around 1. When...

In the last decade large data sets have become available, both in terms of the number of time series and with higher frequencies (weekly, daily and even higher). All series may suffer from seasonality, which hides other important fluctuations. Therefore time series are typically seasonally...

The Seasonal Autoregressive Integrated Moving Average (SARIMA) model is proposed for Osun State monthly rainfall data and the analysis was based on probability time series modeling approach. The Plot of the original data shows that the time series is stationary and the Augmented Dickey-Fuller...

Infra-monthly economic time series have become increasingly popular in official statistics in recent years. This evolution has been largely fostered by official statistics’ digital transformation during the last decade. The COVID-19 pandemic outbreak in 2020 has added fuel to the fire as many...