Representativeness of Individual-Level Data in COVID-19 Phone Surveys : Findings from Sub-Saharan Africa
The COVID-19 pandemic has created urgent demand for timely data, leading to a surge in mobile phone surveys for tracking the impacts of and responses to the pandemic. This paper assesses, and attempts to mitigate, selection biases in individual-lev...
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World Bank, Washington, DC
2021
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| Online Access: | http://documents.worldbank.org/curated/en/131501620912712969/Representativeness-of-Individual-Level-Data-in-COVID-19-Phone-Surveys-Findings-from-Sub-Saharan-Africa http://hdl.handle.net/10986/35609 |
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okr-10986-356092022-09-20T00:09:33Z Representativeness of Individual-Level Data in COVID-19 Phone Surveys : Findings from Sub-Saharan Africa Brubaker, Joshua Kilic, Talip Wollburg, Philip CORONAVIRUS COVID-19 SURVEY METHODOLOGY HOUSEHOLD SURVEY PHONE SURVEY SURVEY SAMPLING WEIGHTING METHODS The COVID-19 pandemic has created urgent demand for timely data, leading to a surge in mobile phone surveys for tracking the impacts of and responses to the pandemic. This paper assesses, and attempts to mitigate, selection biases in individual-level analyses based on phone survey data. The research uses data from (i) national phone surveys that have been implemented in Ethiopia, Malawi, Nigeria, and Uganda during the pandemic, and (ii) the pre-COVID-19 national face-to-face surveys that served as the sampling frames for the phone surveys. The availability of pre-COVID-19 face-to-face survey data permits comparisons of phone survey respondents with the general adult population. Phone survey respondents are more likely to be household heads or their spouses and non-farm enterprise owners, and on average, are older and better educated vis-à-vis the general adult population. To improve the representativeness of individual-level phone survey data, the household-level phone survey sampling weights are calibrated based on propensity score adjustments that are derived from a model of an individual’s likelihood of being interviewed as a function of individual- and household-level attributes. Reweighting improves the representativeness of the estimates for the phone survey respondents, moving them closer to those of the general adult population. This holds for women and men and a range of demographic, education, and labor market outcomes. However, reweighting increases the variance of the estimates and fails to overcome selection biases. Obtaining reliable data on men and women through phone surveys requires random selection of adult interviewees within sampled households. 2021-05-20T14:20:47Z 2021-05-20T14:20:47Z 2021-05-13 Working Paper http://documents.worldbank.org/curated/en/131501620912712969/Representativeness-of-Individual-Level-Data-in-COVID-19-Phone-Surveys-Findings-from-Sub-Saharan-Africa http://hdl.handle.net/10986/35609 English Policy Research Working Paper;No. 9660 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper Africa Africa Eastern and Southern (AFE) Africa Western and Central (AFW) Sub-Saharan Africa |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English |
| topic |
CORONAVIRUS COVID-19 SURVEY METHODOLOGY HOUSEHOLD SURVEY PHONE SURVEY SURVEY SAMPLING WEIGHTING METHODS |
| spellingShingle |
CORONAVIRUS COVID-19 SURVEY METHODOLOGY HOUSEHOLD SURVEY PHONE SURVEY SURVEY SAMPLING WEIGHTING METHODS Brubaker, Joshua Kilic, Talip Wollburg, Philip Representativeness of Individual-Level Data in COVID-19 Phone Surveys : Findings from Sub-Saharan Africa |
| geographic_facet |
Africa Africa Eastern and Southern (AFE) Africa Western and Central (AFW) Sub-Saharan Africa |
| relation |
Policy Research Working Paper;No. 9660 |
| description |
The COVID-19 pandemic has created urgent
demand for timely data, leading to a surge in mobile phone
surveys for tracking the impacts of and responses to the
pandemic. This paper assesses, and attempts to mitigate,
selection biases in individual-level analyses based on phone
survey data. The research uses data from (i) national phone
surveys that have been implemented in Ethiopia, Malawi,
Nigeria, and Uganda during the pandemic, and (ii) the
pre-COVID-19 national face-to-face surveys that served as
the sampling frames for the phone surveys. The availability
of pre-COVID-19 face-to-face survey data permits comparisons
of phone survey respondents with the general adult
population. Phone survey respondents are more likely to be
household heads or their spouses and non-farm enterprise
owners, and on average, are older and better educated
vis-à-vis the general adult population. To improve the
representativeness of individual-level phone survey data,
the household-level phone survey sampling weights are
calibrated based on propensity score adjustments that are
derived from a model of an individual’s likelihood of being
interviewed as a function of individual- and household-level
attributes. Reweighting improves the representativeness of
the estimates for the phone survey respondents, moving them
closer to those of the general adult population. This holds
for women and men and a range of demographic, education, and
labor market outcomes. However, reweighting increases the
variance of the estimates and fails to overcome selection
biases. Obtaining reliable data on men and women through
phone surveys requires random selection of adult
interviewees within sampled households. |
| format |
Working Paper |
| author |
Brubaker, Joshua Kilic, Talip Wollburg, Philip |
| author_facet |
Brubaker, Joshua Kilic, Talip Wollburg, Philip |
| author_sort |
Brubaker, Joshua |
| title |
Representativeness of Individual-Level Data in COVID-19 Phone Surveys : Findings from Sub-Saharan Africa |
| title_short |
Representativeness of Individual-Level Data in COVID-19 Phone Surveys : Findings from Sub-Saharan Africa |
| title_full |
Representativeness of Individual-Level Data in COVID-19 Phone Surveys : Findings from Sub-Saharan Africa |
| title_fullStr |
Representativeness of Individual-Level Data in COVID-19 Phone Surveys : Findings from Sub-Saharan Africa |
| title_full_unstemmed |
Representativeness of Individual-Level Data in COVID-19 Phone Surveys : Findings from Sub-Saharan Africa |
| title_sort |
representativeness of individual-level data in covid-19 phone surveys : findings from sub-saharan africa |
| publisher |
World Bank, Washington, DC |
| publishDate |
2021 |
| url |
http://documents.worldbank.org/curated/en/131501620912712969/Representativeness-of-Individual-Level-Data-in-COVID-19-Phone-Surveys-Findings-from-Sub-Saharan-Africa http://hdl.handle.net/10986/35609 |
| _version_ |
1764483411872841728 |