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Investigation of Alternative Estimators for the Quarterly Financial Report

Carol Caldwell, Irene Evans, Andromache Howe, Michael Ikeda, Donald Luery, Terry Pennington, Mark Sands, Richard Sigman, Katherine Thompson

KEY WORDS:

ABSTRACT

This report presents the research procedures and resultant recommendations for estimation in the Quarterly Financial Report (QFR). The research was motivated by the upcoming QFR migration to the Economic Directorate's Standard Economic Processing System (StEPS). This evaluation study was conducted by an interdivision team comprised of representatives from the Company Statistics Division (CSD), the Economic Statistical Methods and Programming Division (ESMPD), and the Statistical Research Division (SRD).

The QFR estimator of total differs from traditional design-based estimators in that the weight assigned to each sample corporation is not based on its initial probability of selection. Instead, corporations in the enumerated industry are assigned weights equal to the ratio of the estimated total number of corporations in the type of industry at the time of enumeration to the number of sample corporations in that type of industry at the time of enumeration. Because the final QFR weight changes each quarter, the QFR estimator is referred to as a "variable weight estimator." There have been several investigations into the statistical properties of this variable weight estimator, but all prior studies have made simplifying assumptions. Instead, this workgroup attempted to account for all of the nuances of the QFR sample design and estimator via a Monte Carlo simulation study, comparing the existing estimator to several alternative variable weight estimators as well as to the Horvitz-Thompson estimator referred to by QFR as the "fixed weight estimator."

Ultimately, this study validated the current variable weight estimation method for QFR, showing it to have the lowest mean absolute error of the considered methods. Because of its sample design, the QFR has a coverage bias that is usually negative. The study found that none of the alternative variable weight estimators reduced the coverage bias compared to the current estimator, and that the coverage bias is approximately the same for the current estimator and the fixed weight estimator. Moreover, the quarter-to-quarter change estimates of sales constructed from the QFR variable weight estimates are more precise than the change estimates constructed from any of the considered alternative estimators, and the quarterly change in sales is a key economic statistic. Consequently, we recommend that QFR retain its current variable weight estimation methodology."

CITATION:

Source: U.S. Census Bureau, Statistical Research Division

Created: October 3, 2005
Last revised: October 3, 2005


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Source: U.S. Census Bureau | Statistical Research Division | (301) 763-3215 (or chad.eric.russell@census.gov) |   Last Revised: October 08, 2010