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Alison Livingston

Doctor of Philosophy, (Statistics)
Study Completed: 2019
College of Sciences


Thesis Title
Some Diagnostic Techniques for Small Area Estimation: With Applications to Poverty Mapping

Read article at Massey Research Online: MRO icon

Small area estimation (SAE) techniques borrow strength through regression-type models to provide reliable estimates at finer geographical levels. An important application is poverty mapping, whereby aid organisations distribute billions of dollars every year using small area estimates of poverty measures as an input. However diagnostic techniques to ensure these estimates are correct has been largely unresearched. Mrs Livingston developed three specific statistical diagnostic techniques to highlight any unusual poverty predictions, as well as ensuring these final estimates are reliable and meaningful. The diagnostics developed can be applied to a wide range of SAE methods. By way of illustration, the proposed methods were applied to SAE poverty measures in Cambodia and Nepal and were used in real time to identify unreliable predictions, where if left unchecked would have led to a gross misallocation of resources.

Professor Stephen Haslett
Professor Geoff Jones

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