The Rewards and Challenges of Seasonally Adjusting a Short Series: Seasonal Adjustment Research for the US Census Bureau's Quarterly Services Survey

• Activity Number: 413
• Type: Topic Contributed
• Date/Time: Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Rebecca J. Hutchinson*+ and Erica Wong
• Companies: U.S. Census Bureau and U.S. Census Bureau
• Keywords: seasonal adjustment ; economic indicator ; X-12 ; Quarterly Services Survey

Abstract

The Quarterly Services Survey (QSS) was introduced in 2004 as the Federal Government's first new economic indicator in nearly 30 years. The survey provides quarterly revenue estimates for technology-intensive, administrative, and health sectors of the service economy. As the time series has lengthened, the Census Bureau has researched the feasibility of seasonally adjusting the data. This paper describes research conducted to determine methods for producing seasonally adjusted estimates for QSS. Using X-12-ARIMA software diagnostics, we first identify those series that have a stable seasonal component. Then, we determine the industry levels at which the adjustment should be performed, the type of adjustment to be used, and the appropriate ARIMA model. This paper also summarizes the challenges that short data series pose to seasonal adjustment and to the X-12-ARIMA software.