Search Results - subject_exact:"Saisonbereinigung"

Diagnostic tools for selecting the temporal resolution for seasonal adjustment

Ollech, Daniel; Stefan, Martin - 2026

Official statistics increasingly make use of higher-frequency time series. But when users ultimately are interested in a seasonally adjusted temporal aggregate of these data, we have to decide whether to perform seasonal adjustment or aggregation first. Consequently, we must weigh up the...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015587525

Redesigning the classical automatic selection of X-11 seasonal filters

Webel, Karsten - 2026

The classical X-11 seasonal adjustment method for monthly and quarterly time series is equipped with routines for data-driven selections of both Henderson trendcycle filters and 3 × k seasonal moving averages, currently involving up to three candidate filters in either case. Although these...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015607327

The R package deseats for data-driven trend and seasonality estimation in time series

Schulz, Dominik - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015626951

A semiparametric spatial FARIMA applied in the presence of spatial seasonality

Schulz, Dominik; Do, Thi Thu Huong; Feng, Yuanhua - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015626962

Selecting seasonal filters in X–13–ARIMA via cross-validation

Ollech, Daniel - 2026

Official statistics routinely employs the X-13-ARIMA method to seasonally adjust economic time series. A key step is choosing the length of the seasonal moving av- erage. Traditionally, this choice relies on ad hoc criteria and expert judgement. We propose a cross-validation-based filter...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015665401

The seasons they are a-changin' : a century of definitions and a way forward

Bryson, Carter; Cornwall, Gary - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015673567

Exercise book empirical economic research and econometrics

Winker, Peter; Funk, Christoph; Tönjes, Elena - 2026

This exercise book is aimed at students and teachers of economics and related subjects. It offers the opportunity to deepen skills in important methods of applied economic research and econometrics by solving different types of exercises. The book offers exercises in the areas of data, economic...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015637094

Revisions in concurrent seasonal adjustments of daily and weekly economic time series

Webel, Karsten - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015373330

Multiple seasonal autoregressive integrated moving average models

Lisi, Francesco; Grigoletto, Matteo - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015464756

Optimal time series forecasting through the GARMA model

Gadhi, Adel Hassan A.; Peiris, Shelton; Allen, David E.; … - 2025

This paper examines the use of machine learning methods in modeling and forecasting time series with long memory through GARMA. By employing rigorous model selection criteria through simulation study, we find that the hybrid GARMA-LSTM model outperforms traditional approaches in forecasting...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015408216

Modeling and forecasting time-series data with multiple seasonal periods using periodograms

Chudo, Solomon Buke; Terdik, Gyorgy - 2025

Applications of high-frequency data, including energy management, economics, and finance, frequently require time-series forecasting characterized by complex seasonality. Recognizing prevailing seasonal trends continues to be difficult, given that the majority of solutions depend on basic...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015437130

From noise to turning points : a new framework for seasonal adjustment in Armenia

Minasyan, Gevorg; Schipper, Stefan; Khachatryan, Lusya; … - 2025

This paper evaluates the transition from X12-ARIMA to X13-ARIMA-SEATS for the seasonal adjustment of Armenia's quarterly national accounts (QNA). We analyze the methodological advancements and their impact on key economic indicators, focusing on the precision and reliability of seasonally...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015416238

Seasonal adjustment of CPI and CPIH

Dixon, Huw; Michail, Monica George - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015402784

Structural periodic vector autoregressions

Dzikowski, Daniel; Jentsch, Carsten - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016084263

Learning and optimization with seasonal patterns

Chen, Ningyuan; Wang, Chun; Wang, Longlin - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015445449

Seasonal adjustment of CPIs during the COVID-19 pandemic and beyond

Arend, Tom - 2024

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015081758

Addressing complex seasonal patterns in hotel forecasting : a comparative study

Ampountolas, Apostolos - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015446365

Why you should never use the Hodrick-Prescott filter : a comment on Hamilton (The Review of Economics and Statistics, 2018)

Moura, Alban - 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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014529128

Seasonal adjustment of credit time series in the Bank of Italy

Di Paolo, Simone; Liberati, Danilo - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014520811

Driving under the influence of allergies : the effect of seasonal pollen on traffic fatalities

Danagoulian, Shooshan; Deza, Monica - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015182964

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Driving Under the Influence of Allergies : The Effect of Seasonal Pollen on Traffic Fatalities

Danagoulian, Shooshan; Deza, Monica - 2024

Book / Working Paper

Seasonal adjustment of weekly data

Mollins, Jeffrey; Lumb, Rachit - 2024

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015115015

A novel suggestion on how to adequately treat stochastic non-stationary seasonality in tourism export forecasting

Gunter, Ulrich; Smeral, Egon - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015670316

Konjunkturneutrale Arbeitslosigkeit in der Schweiz : Schätzung der konjunkturneutralen Arbeitslosenquote auf dem Schweizer Arbeitsmarkt

Zuchuat, Jeremy; Kaderli, Tabea; Lalive, Rafael - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015127227

Weather effects in energy seasonal adjustment : an application to France energy consumption

Bruguet, Marie; Thomas, Arthur; Le Saout, Ronan - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016062012

Multivariate trend-cycle-seasonal decompositions with correlated innovations

Tian, Jing; Jacobs, Jan; Osborn, Denise R. - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015130539

ESS guidelines on seasonal adjustment : 2024 edition

2024 - 2024 edition

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015276078

Seasonal temperature variability and economic cycles

Linsenmeier, Manuel - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014558686

Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model

He, Changli; Kang, Jian; Silvennoinen, Annastiina; … - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015073960

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Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model

He, Changli; Kang, Jian; Teräsvirta, Timo; Zhang, Shuhua - 2019

Book / Working Paper

Seasonal Adjustment of Daily Data With CAMPLET

Mulder, Machiel; Abeln, Barend; Jacobs, Jan - 2023

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014256893

Forecasting monthly inflation in Bangladesh : a Seasonal Autoregressive Moving Average (SARIMA) approach

Hassan, Abir; Alam, Mahbubul Md; Faeique, Azmaine - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014486900

Seasonal Adjustment in House Price Indices in the COVID-19 Period : A Study of Residual Seasonality

Karamon, Kadiri - 2023

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014347813

Seasonality and consumer confidence

Zélity, Balázs - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015133076

Show one more version 1

Seasonality and consumer confidence

Zélity, Balázs - 2022

Book / Working Paper

Towards seasonal adjustment of infra-monthly time series with JDemetra+

Webel, Karsten; Smyk, Anna - 2023

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014336194

Modelling seasonal fractionally integrated process with volatility and structural change

Dhliwayo, Lawrence; Matarise, Florance; Chimedza, Charles - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015399331

Impact of Seasonal Level Shift (SLS) on time series forecasting

Shahid, Hayat; Urooj, Amena; Asghar, Zahid - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014279614

The Effect of Seasonality on Elementary Index

Inoue, Toshikatsu - 2023

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014255422

Persistence and seasonality in the US industrial production index

Caporale, Guglielmo Maria; Gil-Alaña, Luis A.; Poza, Carlos - 2023

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014427486

Economic analysis using higher-frequency time series : challenges for seasonal adjustment

Ollech, Daniel - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014226362

Show 2 more versions 2

Economic analysis using higher frequency time series : challenges for seasonal adjustment

Ollech, Daniel - 2021

Book / Working Paper

Economic Analysis Using Higher Frequency Time Series : Challenges for Seasonal Adjustment

Ollech, Daniel - 2022

Book / Working Paper

The seasonality of lottery-like stock returns

Gould, John; Yang, Wenling; Singh, Ranjodh B.; Yeo, Ben - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014246716

Der neue Lkw-Maut-Grenzfahrtenindex

Bolz, Maria; Linz, Stefan; Goebels, Claus; Cox, Michael - 2022

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013408697

Quantile regression-based seasonal adjustment

Caporin, Massimiliano; Elseidi, Mohammed - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014312057

Der Lkw-Maut-Fahrleistungsindex für Bundesländer: ein neuer Konjunkturindikator für die regionale Industrieaktivität

Bolz, Maria; Linz, Stefan; Goebels, Claus; May, Lisa; … - 2022

Persistent link: https://ebvufind01.dmz1.zbw.eu/10012872595

Seasonality in Covid-19 Times

Bógalo, Juan; Llada, Martín; Poncela, Pilar; Senra, Eva - 2022

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013323805

Tourism demand with subtle seasonality : recognition and forecasting

Wang, Haiyan; Hu, Tao; Wu, Huihui - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014384549

A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series

Webel, Karsten - 2022

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013336397

Part 3 Seasons

2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015491021

Why you should never use the Hodrick-Prescott filter : comment

Moura, Alban - 2022

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013400174

Trading time seasonality in electricity futures

Størdal, Ståle; Ewald, Christian; Lien, Gudbrand; … - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014477808

Seasonal Adjustment Without Revisions : A Real-Time Approach

Abeln, Barend; Jacobs, Jan - 2023

Chapter 1. Introduction -- Chapter 2. CAMPLET: Seasonal adjustment without revisions -- Chapter 3. Seasonal adjustment of economic tendency survey data -- Chapter 4. Residual Seasonality: A Comparison of X13 and CAMPLET -- Chapter 5. COVID-19 and Seasonal Adjustment -- Chapter 6. Seasonal...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013551782

Der neue Lkw-Maut-Grenzfahrtenindex

Bolz, Maria; Linz, Stefan; Goebels, Claus; Cox, Michael - 2022

Das Bundesamt für Güterverkehr berechnet aus digitalen Prozessdaten, die im Zuge der Erhebung der Lkw-Maut anfallen, den Lkw-Maut-Grenzfahrtenindex. Dieser könnte frühzeitig Anhaltspunkte zur konjunkturellen Entwicklung in Deutschland liefern. Aufgrund des hohen Bedarfs an aktuellen...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013401869