A Note on the Optimum Allocation of Resources to Follow up Unit Nonrespondents in Probability Surveys

Tam Siu-Ming (), Holmberg Anders () and Wang Summer ()
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Tam Siu-Ming: Australian Bureau of Statistics, Canberra, Australia. 45, Benjamin Way, Belconnen, ACT 2617, Australia.
Holmberg Anders: Australian Bureau of Statistics, Canberra, Australia. 45, Benjamin Way, Belconnen, ACT 2617, Australia.
Wang Summer: Australian Bureau of Statistics, Canberra, Australia. 45, Benjamin Way, Belconnen, ACT 2617, Australia.

Journal of Official Statistics, 2023, vol. 39, issue 3, 421-433

Abstract: Common practice to address nonresponse in probability surveys in National Statistical Offices is to follow up every non respondent with a view to lifting response rates. As response rate is an insufficient indicator of data quality, it is argued that one should follow up non respondents with a view to reducing the mean squared error (MSE) of the estimator of the variable of interest. In this article, we propose a method to allocate the nonresponse follow-up resources in such a way as to minimise the MSE under a quasi-randomisation framework. An example to illustrate the method using the 2018/19 Rural Environment and Agricultural Commodities Survey from the Australian Bureau of Statistics is provided.

Keywords: Data quality; nonresponse follow-up; propensity score; weighting adjustment (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:39:y:2023:i:3:p:421-433:n:2

DOI: 10.2478/jos-2023-0020

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