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Results of Evaluation of AGGIES for ACES

Maria Garcia and Katherine J. Thompson

KEY WORDS: data editing, Fellegi-Holt model, error localization

ABSTRACT

The U. S. Census Bureauís Annual Capital Expenditures Survey (ACES) collects data about domestic capital expenditures in non-farm businesses operating within the United States. Analysts manually edit the ACES data using a specified set of editing rules. Although individual edits are straightforward, the hierarchical combination of edits are complicated with several nested levels of simultaneous balance requirements. We investigate the feasibility of replacing the current ACES editing procedures with an automated system based on National Agricultural Statistics Service's generalized edit and imputation system (AGGIES). The AGGIES system solves simultaneous linear-inequality edits using Chernikova-type algorithms for determining the minimum number of fields to change so that a record satisfies all edits. These algorithms can simultaneously deal with a large number of mathematical constraints and have been successfully applied in Statistics Canada's Generalized Edit and Imputation System and Statistics Netherlands' CherryPI system.

CITATION:

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

Created: November 29, 2000


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