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Activity Number: 565 - Time Series in Government and National Statistics
Type: Topic Contributed
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Government Statistics Section
Abstract #307389 Presentation
Title: Dealing with Discontinuities in Survey Reporting Periods and Their Impact on Seasonal Adjustment of Time Series
Author(s): Charlotte Gaughan* and Atanaska Nikolova
Companies: Office for National Statistics and Office for National Statistics
Keywords: Time series discontinuity; seasonal adjustment; calendar effects; calendarization; trading day

Survey reporting periods refer to the dates when respondents are asked to provide data. While the methods for seasonal adjustment can be tailored to account for specific calendar effects arising from the nature of the survey reporting periods, discontinuities in the time series may arise if these periods are changed. This research looks into the case of UK Retail Sales Index, which has been historically based on a 4-4-5 week reporting period and will change to a calendar month period in 2019. A 4-4-5 reporting frequency does not feature trading day effects and causes artificial moving holidays and phase shifts that affect seasonality. The switch to a calendar month reporting will remove these anomalies and introduce a trading day effect, which will be difficult to estimate due to a short span. Possible procedures are assessed for calendarising the historic 4-4-5 series so they can be used for seasonal adjustment after the reporting period change. Methods include using a mixture of simulated and real values, temporal disaggregation, RegARIMA modelling for trading day estimation; splining, state-space modelling, and benchmarking for consistency between different frequencies.

Authors who are presenting talks have a * after their name.

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