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Stephen J. Kaputa and Katherine J. Thompson

Abstract

The U.S. Census Bureau is investigating nonrespondent subsampling strategies for use in the 2017 Economic Census. In previous research, we developed an optimized allocation procedure for subsampling nonrespondents that selects larger systematic samples in domains with lower initial response. This article expands on our previous research by exploring improvements to the optimal allocation method; we investigate refinements to the previous procedure that incorporate measures of respondent balance with respect to the original sample. The revised allocation procedures have simultaneous objectives of allocating high proportions of sample in domains that indicate potential nonresponse bias and of equalizing response rates across domains. We examine the effects of the alternative allocation approaches on Horvitz-Thompson estimates via a simulation study using data from the 2014 Annual Survey of Manufactures.

Open access

Katherine Jenny Thompson and Stephen J. Kaputa

Abstract

The U.S. Census Bureau is investigating adaptive Nonresponse Follow-Up (NRFU) strategies for single unit businesses in the 2017 Economic Census. These collection protocols require a suite of viable alternative procedures that can be implemented. With business surveys, the majority of cognitive research and nonresponse follow-up procedures focus on collection methods that obtain valid response data from the larger businesses, and there is relatively little quantitative or qualitative research for small businesses. Moreover, the contact methods for small businesses are often constrained by budget limitations. Business programs at the U.S. Census Bureau rely on mailed reminder letters and supplemental promotional materials, with options for certified and bulk mailings. To explore the benefits and disadvantages of the proposed alternative nonresponse follow-up procedures for small businesses, we conducted a field experiment embedded in the 2014 Annual Survey of Manufactures, an annual program that has similar data collection procedures and sampling units as the Economic Census. This article describes the study and presents the results, then discusses how the recommended nonresponse follow-up procedures are implemented in an adaptive collection design test presently being conducted in the 2015 Annual Survey of Manufactures.

Open access

Mary H. Mulry, Stephen Kaputa and Katherine J. Thompson

Abstract

Recent research on the use of M-estimation methodology for detecting and treating verified influential values in economic surveys found that initial parameter settings affect effectiveness. In this article, we explore the basic question of how to develop initial settings for the M-estimation parameters. The economic populations that we studied are highly skewed and are consequently highly stratified. While we investigated settings for several parameters, the most challenging problem was to develop an “automatic” data-driven method for setting the initial value of the tuning constant φ, the parameter with the greatest influence on performance of the algorithm. Of all the methods that we considered, we found that methods defined in terms of the accuracy of published estimates can be implemented on a large scale and yielded the best performance. We illustrate the methodology with an empirical analysis of 36 consecutive months of data from 19 industries in the Monthly Wholesale Trade Survey.

Open access

Katherine J. Thompson, Polly Phipps, Darcy Miller and Ger Snijkers