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Activity Number:
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196
- Time Series Methods with Seasonal, Monthly, and Daily Data
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #313363
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Title:
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Assessing the Contribution of Sampling Variance to Seasonal Adjustment Mean Squared Error
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Author(s):
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Osbert Pang* and William Bell
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Companies:
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U.S. Census Bureau and U.S. Census Bureau
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Keywords:
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Abstract:
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For many of the economic time series seasonally adjusted by the U.S. Census Bureau, the values being adjusted are actually estimates from data obtained via (repeated) survey samples. Thus, there is sampling error present in the series, which contributes to the error in the seasonal adjustment of those same series. Seasonal adjustment procedures (such as X-11 or SEATS) typically ignore the sampling error component that is present, treating the series as though the data were obtained via repeated censuses. Through simulation study, we attempt to assess just how much of an impact the sampling error in a series has on the seasonal adjustment error. We examine various alternative models for the sampling errors.
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Authors who are presenting talks have a * after their name.
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