JSM 2004 - Toronto

Abstract #301009

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Activity Number: 73
Type: Topic Contributed
Date/Time: Monday, August 9, 2004 : 8:30 AM to 10:20 AM
Sponsor: Business and Economics Statistics Section
Abstract - #301009
Title: Bayesian Inference for Seasonal Adjustment with Sampling Error: Application to Estimates from Monthly Value of Construction Put-in-place Surveys
Author(s): William R. Bell*+ and Thuy T.T. Nguyen
Companies: U.S. Census Bureau and U.S. Census Bureau
Address: 4700 Silver Hill Rd., Washington, DC, 20233-9100,
Keywords: signal extraction ; sampling error model
Abstract:

The U.S. Census Bureau estimates "value of construction put in place" (VIP) each month using a variety of sources, including sample surveys, administrative records, and trade association data. Recently the VIP estimates were expanded to more levels of detail, but some of the resulting direct estimates have large sampling errors. The short length of the VIP time series (six years), coupled with the large sampling errors for some series, makes seasonal adjustment of these time series difficult. With model-based seasonal adjustment this difficulty manifests itself in large amounts of uncertainty about the model parameters. This paper examines use of Bayesian methods in model-based seasonal adjustment to recognize uncertainty about parameters in both the model for the true unobserved time series and in the sampling error model. The latter accounts for sampling error variances and autocorrelations of the VIP survey estimates. Because of the short length of the VIP time series, accounting for parameter uncertainty is important to judging the accuracy of the seasonal adjustments.

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