The COVID-19 outbreak in 2020 has fostered in many countries the development of new weekly economic indices for the timely tracking of pandemic-related turmoils and other forms of rapid economic changes. Such indices often utilise information from daily and weekly economic time series that...

The establishment of common guidelines for seasonal adjustment within the European Statistical System is an essential step towards a better harmonisation and comparability of infra-annual statistics. Following the 2009 and 2015 editions which were widely accepted and implemented, the 2024...

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...

This paper summarizes and assesses several of the most popular methods to seasonally adjust weekly data. The industry standard approach, known as X-13ARIMA-SEATS, is suitable only for monthly or quarterly data. Given the increased availability and promise of non-traditional data at higher...

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...

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...

In this study, we analyze the effects of seasonal fluctuations on the aggregated price and quantity of goods in Japan. By analyzing monthly commodity-level data used to calculate Japan’s official Consumer Price Index, we demonstrate that a significant number of fresh foods are non-homogeneous...

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...

COVID-19 has hit the economy in an unprecedented way, abruptly changing the data generating process of many economic time series. This has triggered one of the highest policy interventions that we have ever seen. Policy assessment relies on real time monitoring of the economy using seasonally...

Infra-monthly time series have increasingly appeared on the radar of official statistics in recent years, mostly as a consequence of a general digital transformation process and the outbreak of the COVID-19 pandemic in 2020. Many of those series are seasonal and thus in need for seasonal...

The COVID-19 pandemic has increased the need for timely and granular information to assess the state of the economy in real time. Weekly and daily indices have been constructed using higher frequency data to address this need. Yet the seasonal and calendar adjustment of the underlying time...

Traffic fatalities are the leading cause of mortality in the United States despite being preventable. While several policies have been introduced to improve traffic safety and their effects have been well documented, the role of transitory health shocks or situational factors at explaining...

This paper examines the presence of seasonality in CPI in 36 OECD economies that provide monthly CPI data and reviews the properties of standard methods, namely X-13 and TRAMO-SEATS, in performing the adjustment. Evidence from statistical tests points to the presence of seasonality in headline...

Time series observed at higher frequencies than monthly frequency display complex seasonal patterns that result from the combination of multiple seasonal patterns (with annual, monthly, weekly and daily periodicities) and varying periods, due to the irregularity of the calendar. The paper deals...

The COVID19 crisis has a huge impact on economies all over the world. In this note we compare seasonal adjustments of X13 and CAMPLET before and after the COVID19 crisis. We show results of Quasi Real Time analyses for the quarterly series real GDP and the monthly series Consumption of...

The COVID-19 crisis has a huge impact on economies all over the world. In this note we compare seasonal adjustments of X13 and CAMPLET before and after the COVID19 crisis. We show results of Quasi Real Time analyses for the quarterly series real GDP and the monthly series Consumption of...

Seasonal adjustment procedures attempt to estimate the sample realizations of an unobservable economic time series in the presence of both seasonal factors and irregular factors. In this paper we consider a factor which has not been considered explicitly in previous treatments of seasonal...

Problem Definition. Firms that sell products over a limited selling season often have only imperfect information about (a) the exact timing of that season, (b) the demand volume to expect, and (c) the temporal distribution of demand over the selling season. Given these uncertainties, firms must...

The following paper discusses the analysis of some types of economic time series using an altered time scale, or operational time. It is argued that for some series, observations that are ordinarily thought of as equidistant in time are actually irregularly spaced in a more natural time scale....

We present a procedure to perform seasonal adjustment over daily sales data. The model adjusts daily information from the Immediate Supply of Information System for Value Added Tax declaration forms compiled by the Spanish Tax Agency. The procedure performs signal extraction and forecasting at...

The effect of the conventional model-based methods of seasonal adjustment is to nullify the elements of the data that reside at the seasonal frequencies and to attenuate the elements at the adjacent frequencies. It may be desirable to nullify some of the adjacent elements instead of merely...

The COVID-19 pandemic has increased the need for timely and granular information to assess the state of the economy in real time. Weekly and daily indices have been constructed using higher frequency data to address this need. Yet the seasonal and calendar adjustment of the underlying time...

This paper considers a general model which allows for both deterministic and stochastic forms of seasonality, including fractional (stationary and nonstationary) orders of integration, and also incorporating endogenously determined structural breaks. Monte Carlo analysis shows that the suggested...

This paper proposes a new univariate method to decompose a time series into a trend, a cyclical and a seasonal component: the Trend-Cycle filter (TC filter) and its extension, the Trend-Cycle-Season filter (TCS filter). They can be regarded as extensions of the Hodrick-Prescott filter (HP...

This note gives a fairly complete statistical description of the Hodrick-Prescott Filter (1997) which has been proposed in the context of my seasonal adjustment method (Schlicht 1981, 1984). A statistics estimator for the smoothing parameter is proposed that is asymptotically equivalent to the...

The production index is an important indicator for assessing the cyclical state of the economy. Unfortunately, the monthly time series is contaminated by many noisy components like seasonal variations, calendar and vacation effects. Only part of those nuisance components are explicitly...