Combining multiple imperfect data sources for small area estimation: a Bayesian model of provincial fertility rates in Cambodia

Junni L. Zhang and John Bryant

Statistical Theory and Related Fields, 2019, vol. 3, issue 2, 178-185

Abstract: Demographic estimation becomes a problem of small area estimation when detailed disaggregation leads to small cell counts. The usual difficulties of small area estimation are compounded when the available data sources contain measurement errors. We present a Bayesian approach to the problem of small area estimation with imperfect data sources. The overall model contains separate submodels for underlying demographic processes and for measurement processes. All unknown quantities in the model, including coverage ratios and demographic rates, are estimated jointly via Markov chain Monte Carlo methods. The approach is illustrated using the example of provincial fertility rates in Cambodia.

Date: 2019
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DOI: 10.1080/24754269.2019.1658062

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