Office of Survey Methods Research

Abstract

Stuart Scott, George Stamas, Thomas Sullivan, and Paul Chester (1994) "Seasonal Adjustment Of Hybrid Economic Time Series," Proceedings of the Section on Survey Research Methods, American Statistical Association, forthcoming.

Based on a sample of 380,000 employers, state industry employment is estimated monthly by the U.S. Bureau of Labor Statistics and seasonally adjusted with X-11-ARIMA. The estimates are revised annually to reflect employment counts available from administrative records of the Unemployment Insurance (UI) programs of each state. Thus, the overall time series is a hybrid of universe data up to the last benchmark and sample data afterward. As pointed out by Berger and Phillips (1993), there appear to be distortions in seasonal adjustment due to differing seasonal patterns in these data sources. The universe data dominate the historical data from which the factors are derived, but these factors then get applied to sample data. We compare seasonal factors from the two data sources, and use revision statistics to evaluate alternative approaches to seasonal adjustment . In addition, twelve-month change estimates are examined. When such estimates are across the last benchmark, the unadjusted estimate contains seasonality.

Last Modified Date: July 19, 2008

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