<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In the United States, government surveys’ refusal rates have been increasing at an alarming rate, despite traditional measures for mitigating nonresponse. Given this phenomenon, now is a good time to revisit the work of Harris-Kojetin and Tucker (1999). In that study, the authors explored the relation between economic and political conditions on Current Population Survey (CPS) refusal rates over the period 1960–1988.</p><p>They found evidence that economic and political factors are associated with survey refusals and acknowledged the need to extend this work as more data became available. In this study, our aim was to continue their analysis. First, we replicated their findings. Next, we ran the assumed underlying model on an extended time-period (1960–2015). Last, since we found that the model was not an ideal fit for the extended period, we revised it using available time series and incorporating information about the CPS sample design. In the extended, refined model, presidential approval, census year, number of jobs and not-in-labor-force rate were all significant predictors of survey refusal.</p></abstract>

In the United States, government surveys’ refusal rates have been increasing at an alarming rate, despite traditional measures for mitigating nonresponse. Given this phenomenon, now is a good time to revisit the work of Harris-Kojetin and Tucker (1999). In that study, the authors explored the relation between economic and political conditions on Current Population Survey (CPS) refusal rates over the period 1960–1988.They found evidence that economic and political factors are associated with survey refusals and acknowledged the need to extend this work as more data became available. In this study, our aim was to continue their analysis. First, we replicated their findings. Next, we ran the assumed underlying model on an extended time-period (1960–2015). Last, since we found that the model was not an ideal fit for the extended period, we revised it using available time series and incorporating information about the CPS sample design. In the extended, refined model, presidential approval, census year, number of jobs and not-in-labor-force rate were all significant predictors of survey refusal.

Continuing to Explore the Relation between Economic and Political Factors and Government Survey Refusal Rates: 1960–2015

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In the United States, government surveys’ refusal rates have been increasing at an alarming rate, despite traditional measures for mitigating nonresponse....

Continuing to Explore the Relation between Economic and Political Factors and Government Survey Refusal Rates: 1960–2015

Publié en ligne: 24 juil. 2020

Pages: 489 - 505

Reçu: 01 août 2018

Accepté: 01 nov. 2019

DOI: https://doi.org/10.2478/jos-2020-0026

Mots clés
Refusal rates, response rates, nonresponse, time series

© 2020 Luke J. Larsen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Continuing to Explore the Relation between Economic and Political Factors and Government Survey Refusal Rates: 1960–2015

Publié en ligne: 24 juil. 2020

Pages: 489 - 505

Reçu: 01 août 2018

Accepté: 01 nov. 2019

DOI: https://doi.org/10.2478/jos-2020-0026

Mots clésRefusal rates, response rates, nonresponse, time series

© 2020 Luke J. Larsen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Refusal rates, response rates, nonresponse, time series