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Activity Number: 171 - Predicting Attrition and Adaptive Strategies
Type: Contributed
Date/Time: Monday, July 31, 2017 : 10:30 AM to 12:20 PM
Sponsor: Survey Research Methods Section
Abstract #324654 View Presentation
Title: Refining an External-Factor Model of Government Survey Refusal Rates
Author(s): Luke Larsen* and Joanna Lineback and Benjamin Reist
Companies: U.S. Census Bureau and U.S. Census Bureau and U.S. Census Bureau
Keywords: official statistics ; time series models ; refusal rates ; autocorrelated error ; response rates ; Current Population Survey
Abstract:

Declining participation in government surveys is a concern for data users who rely on such programs for high-quality population and household statistics. In recent years, a rising trend in sampled persons who refuse to participate in government surveys is alarming, since increased unit non-response requires more reliance upon adjustment methods that - when used excessively - can generate bias and reduce data quality. While there are many factors that may affect one's decision to participate in a survey, the authors are concerned with the influence of economic and political conditions. In a prior analysis, the authors built upon an earlier paper (Harris-Kojetin and Tucker, 1999) to explore the relationships of these external factors with refusal rates of the monthly Current Population Survey (CPS). The time series regression model of the 1999 paper was replicated, and the scope of that model was expanded to 2015. However, analysis of the more recent data indicated that the model was not ideal for studying modern refusal patterns. In this follow-up paper, the authors consider new covariates for the model and devise an alternate construction of the autocorrelated error.


Authors who are presenting talks have a * after their name.

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