SAPW 2022

4th Seasonal Adjustment Practitioners Workshop 2022

June 8 and 9

4th Seasonal Adjustment Practitioners Workshop - Program

Many of the speakers have provided their slides for downloading - the links are provided below.

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Session 1 - Tutorial

Identifying Seasonality
Tucker S. McElroy and Kathleen M. McDonald-Johnson (U.S. Census Bureau)

Session 2 - Modeling Applications Supporting Seasonal Adjustment

Methodology for Choosing the Seasonal Adjustment Models of Economic Series: A Study of Monthly Trade, Industry and Services Series in Brazil
Manoela Cabo, Carla Mello, Marcelo Barboza, Felipe Figueiredo (IBGE Brazilian Institute of Geography and Statistics, Rio de Janeiro, Brazil)

Outlier Methodology for Seasonal Adjustment
Jamas Enright (Statistics New Zealand)

Joint Modeling of Longitudinal Processes and Mortality via Mixed Effects State Space Models with Applications to Dialysis Data
Ming Hu, Ya Luo, Yuedong Wang (University of California, Santa Barbara)

Seasonality Tests for Weekly and Other Non-Integer Seasonal Time Series
Daniel Ollech (Bundesbank)

Concurrent Session 3a - Special Topics in Seasonal Adjustment and Modeling

Bayesian Dependent Functional Mixture Estimation for Area and Time-Indexed Data: An Application for the Prediction of Monthly County Employment
Matt Williams (RTI International) and Terrance D. Savitsky (U. S. Bureau of Labor Statistics)

Indirect Seasonal Adjustment Application of Chained Indices for Türkiye
Gülsüm Merve GÖKÇİN, Osman SERT, Özlem YİĞİT, Fatma Aydan KOCACAN NURAY (TurkStat)

Removing Residual Seasonality from GDP
Tucker McElroy (US Census Bureau), Baoline Chen (Bureau of Economic Analysis), Osbert Pang (US Census Bureau)

Concurrent Session 3b - Lightning Sessions

Comparing R and Python Interfaces to X-13ARIMA-SEATS
Michael Boldin (Lehigh University)
SAS Code to Generate Temporary Change Regressors with Distinct Decay Rate
Eric Valentine (U.S. Census Bureau)

Negative Transportation Volumes? COVID-19 Issues Seasonally Adjusting Transportation Data Series
Theresa Firestine (Department of Transportation)

Experience with Seasonal Adjustment of Composite Series
Richard Penny (Statistics New Zealand)

The sautilities R Package
Brian Monsell (Bureau of Labor Statistics)

Session 4 - Model Selection and Seasonality

Model Selection in an Annual Review: A Machine Learning Inspired Approach
Yingfu Xie (Statistics Sweden)

Restating the Case for Complete, Model-Based Seasonal Adjustments of Economic Data and Reporting Both NSA and SA Detail
Michael Boldin (Lehigh University)

Holiday Variable Generating Routines Within Our In-House Versions of the Census Method
Hideki Furuya (SKANIOGLOS Investment Advisory Company)

Effects of Different Temporary Change Decay Rates in Retail Sales Time Series
Eric Valentine (U.S. Census Bureau)

Jdemetra +, Lesson Learned on Direct vs Indirect SA Tool on an Italian Case Study
Matteo Cardelli, Maria Saiz, Maria Liviana Mattonetti (Istituto Nazionale di Statistica – Istat)

Concurrent Session 5a - Pandemic Issues

Special Outlier Treatment Technique in Seasonal Adjustment for Handling the Effect of COVID-19
Gábor Lovics, Beáta Horváth, and Mária Pécs (HCSO, Budapest, Hungary)

Mitigating the Effects of the COVID-19 Pandemic on Seasonally Adjusted Price Indexes
Marie Rogers, Jonathan Weinhagen, Jeff Wilson, and Blake Hoarty (Bureau of Labor Statistics)

Identifying and Adjusting for Sudden Changes in Seasonal Patterns
Demetra Lytras (U.S. Census Bureau)

Trend and Cycle Decomposition for Macroeconomic Variables After the COVID Pandemic
Ferdinando Biscosi (GOPA Luxembourg), Stefano Grassi (University of Rome ’Tor Vergata’), Gian Luigi Mazzi (Senior Consultant), Francesco Ravazzolo (BI Norwegina Business School and Free University of Bozen-Bolzano), Rosa Ruggeri Cannata (Europena commission | Eurostat), Piotr Ronkowski (Europena commission | Eurostat), and Hionia Vlachou (GOPA Luxembourg)

Concurrent Session 5b - Trends

MSEs of X-11 Trend Filters
William Bell (U.S. Census Bureau)

Trend-Cycle Extraction and Moving Average Manipulations in R with the rjdfilters Package

Alain Quartier-la-Tente (INSEE)

Trend-Cycle Estimation in Topsy-Turvy Times
Steve Matthews, Statistics Canada