Clyde Tucker

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1 The opinions expressed here are those of the authors and not necessarily those of the authors’ institutions. We thank the following people for help and support: Atar Baer, Mick Couper, Jim Esposito, Sarah Jerstad, Yun-Chiao Kang, Dominic Perri, Stanley Presser, Linda Stinson, Deborah Stone, Tim Triplett, Clyde Tucker, Beth Webb and Gordon Willis.
Previous research by Tucker et al. (2010), working with the Consumer Expenditure Survey (CE), explores the factor structure of measurement error indicators such as: interview length, extent and type of records used, the monthly patterns of reporting, reporting of income, attempt history information, and response behavior across multiple interviews in a(More)
Introduction Surveys of businesses, organizations, and institutions—so-called “establishment surveys”—provide key data for some of the Nation’s most important measures of economic health. However, the quality of the data depends on respondent cooperation; thus, survey nonresponse is a major challenge for a survey. Increasing concern about this challenge to(More)
This paper makes estimates of the level of underreporting of consumer expenditures. The paper examines reporting in particular commodity categories and attempts only to make estimates of underreporting among those that report at least one expenditure in the category. The measure of the level of underreporting in a category by a particular responding unit is(More)
Government surveys often accept reports from proxy respondents. For example, the Current Population Survey (CPS), used to measure unemployment, uses proxy information about the employment status of other household members. The Consumer Expenditure Program, which provides the cost weights in the Consumer Price Index, accepts proxy reports about the(More)
Recently, a trend toward increased nonresponse in government surveys has resulted in concern about the effect of nonresponse on data quality and statistical estimates. Several recent studies have examined this issue in the context of describing nonresponse, and identifying ways to reduce nonresponse (Christianson, & Tortora, 1995; Osmint, McMahon, & Ware(More)
Previous research by Tucker et al. (2005) and Tucker et al. (2006) attempts to identify a latent construct that predicts the amount of measurement error in expenditure reports on the Consumer Expenditure Interview Survey (CEIS). While this work was successful in identifying a construct that predicts measurement error in expenditure reports, it is more(More)