1. Research topics Item 4.4 Seasonal Adjustment Expert Group Duncan Elliott 7 December 2015

2. Overview Time series meeting (19-20 November, at Royal Statistical Society, London) Who? What was discussed? Outcomes List of research topics

3. Who? Attending Official Statistics Eurostat, National Bank of Belgium, Office for National Statistics, Statistics Canada, US Census Bureau Academia University of Bristol, University of Cambridge, University of Lancaster, University of Southampton Unable to attend but interested CBS Netherlands/University of Maastricht, ECB, INSEE, Istat, US Bureau of Labor Statistics

4. What was discussed? Lightning introductions (by institution) Brainstorming Prior adjustment, seasonal adjustment, forecasting, benchmarking, software, multivariate time series, structural time series models, big data and other time series issues Short questionnaire Advert break (by individuals) Prioritising research issues Prior adjustment, seasonal adjustment, forecasting, benchmarking

5. Outcomes Networking opportunity Exchange of ideas between academics and those involved in official statistics Notes on discussions held at the meeting to be posted on CROS portal and circulated to interested parties The start of a list of research topics

6. Research topics: prior adjustment 1 st : Minimizing the amount and complexity; new methods (eg non-Gaussian/Bayesian); premature outlier removal; piecewise analysis (different spans for different types of effects) 2 nd : Identifying spans for moving holidays; moving away from regARIMA; a principled approach to moving holidays; outliers in hierarchically aggregated sets 3 rd : Improve tests for choice of additive or multiplicative decomposition; weather effects; initial graphics and plotting; extend regARIMA for non-Guassian and automated choice of error distribution

7. Research topics: seasonal adjustment 1 st : Diagnostics on final series and defining “good enough"; consistency of revisions in barely seasonal series 2 nd : Revisions; additive/multiplicative/both or mixed decompositions; consistency of local and global seasonal adjustment; SEATS vs X11 or something else 3 rd : Identification of appropriate asymmetric end point filters; understanding and perceptions of seasonal adjustment by the public and policy makers; adjustment of multiple frequency series; signal-noise, estimation and removal of sampling error

8. Research topics: forecasting 1 st : Point, density or interval forecasts; communication of forecasts; big data for now/forecasting 2 nd : Scoring/validation; nowcasting effects in seasonal adjustment; mixed frequency/non-stationary forecasting; combing multiple forecasts 3 rd : Non-stationary forecasting and use of mixed frequency series; forecasting using related series (including different frequencies); backcasting; tools for evaluating and visualizing forecast variation

9. Research topics: benchmarking 1 st : Multivariate; relationship between benchmarking and seasonal adjustment 2 nd : Quality measures and diagnostics; binding and non-binding benchmarking 3 rd : Tests for suitability of benchmarking; issues around chainlinking and benchmarking; wavelets; choosing/scoring various methods

10. Some results from the questionnaire Total of 244 years of working on time series Most used software was R Top 3 Time Series Conferences: 1. JSM 2. ISF 3. Joint CFE and NBER 13 of 18 strongly agreed or agreed that trends should be included in time series publications by NSIs

12. Establishing a list of research topics Time series meeting provides a start Developing the list further? Addressing the list of research?