Reducing Bias in Phone Survey Samples
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World Bank, Washington, DC
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Several developing countries are
currently implementing phone surveys in response to
immediate data needs to monitor the socioeconomic impact of
COVID-19. However, phone surveys are often subject to
coverage and non-response bias that can compromise the
representativeness of the sample and the external validity
of the estimates obtained from the survey. Using data from
high-frequency phone surveys in Ethiopia, Malawi, Nigeria,
and Uganda, this study investigates the magnitude and source
of biases present in these four surveys and explores the
effectiveness of techniques applied to reduce bias. Varying
levels of coverage and non-response bias are found in all
four countries. The successfully contacted samples in these
four countries were biased toward wealthier households with
higher living standards. Left unaddressed, this bias would
result in biased estimates from the interviewed sample that
do not fully reflect the situation of poorer households in
the country. However, phone survey biases can be
substantially reduced by applying survey weight adjustments
using information from the representative survey from which
the sample is drawn. Applying these methods to the four
surveys resulted in a substantial reduction in bias,
although the bias was not fully eradicated. This highlights
one of the potential advantages of drawing phone survey
samples from existing face-to-face, representative surveys
over random digit dialing or using lists from telecom
providers where such adjustment methods can be more limited.
Palabras clave
CORONAVIRUS, COVID-19, PANDEMIC IMPACT, SURVEY METHODOLOGY, NONRESPONSE BIAS, COVERAGE BIAS, WEIGHTING METHODS, SAMPLE REPRESENTATIVENESS