Estimating the underlying infant mortality rates for small populations: an historical study of US counties in 1970

David A. Swanson () and Jack Baker ()
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David A. Swanson: University of California Riverside
Jack Baker: HealthFitness Corporation

Journal of Population Research, 2019, vol. 36, issue 3, No 3, 233-244

Abstract: Abstract A method is presented for estimating the “underlying” infant mortality rates for areas with small populations. It is described and illustrated in a case study that estimates infant mortality rates for 2494 US counties that had less than 1000 births in 1970. The method’s validity is tested using a synthetic population in the form of a simulated data set generated from a model life table infant mortality rate, representing Level 23 of the West Family Model Life Table for both sexes. The test indicates that the method is capable of producing estimates that represent underlying rates. Although some judgment is needed with the method, it has sufficient transparency that estimates can be replicated. The results support the argument that the method can produce reasonable estimates of underlying infant mortality rates for small populations subject to high levels of stochastic variation.

Keywords: Beta model; Confidentiality; Intrinsic mortality regime; Monitoring health status; Policy; Stochastic uncertainty (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s12546-019-09225-w

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