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Hector Najera

Researcher at University of Bristol

Publications -  10
Citations -  152

Hector Najera is an academic researcher from University of Bristol. The author has contributed to research in topics: Population & Poverty. The author has an hindex of 4, co-authored 5 publications receiving 70 citations.

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Reliability, Population Classification and Weighting in Multidimensional Poverty Measurement: A Monte Carlo Study

TL;DR: A Monte Carlo study based on factor mixture models is used to draw up a series of uni-and multidimensional poverty measures with different reliabilities and predefined groups and shows that low reliability results in a high proportion of the poor group erroneously classified as part of the not poor group.
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Towards an EU measure of child deprivation

TL;DR: A new measure of child material and social deprivation in the European Union which includes age appropriate child-specific information available from the thematic deprivation modules included in the 2009 and 2014 waves of the “EU Statistics on Income and Living Conditions” (EU-SILC).
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Within-country migration and obesity dynamics: analysis of 94,783 women from the Peruvian demographic and health surveys

TL;DR: Exposure to urban environments and migration are associated with higher odds of obesity, and the length of exposure to urban settings shows a steady effect over time.
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Small-area estimates of stunting. Mexico 2010: Based on a hierarchical Bayesian estimator.

TL;DR: The first small-area estimates of stunting for the Mexican municipalities are produced by applying a hierarchical Bayesian estimator using data from a nationally representative survey and the sample of the National Housing and Population Census 2010.
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Does measurement invariance hold for the official Mexican multidimensional poverty measure? A state-level analysis 2012

TL;DR: The results suggest that partial strong MI holds for the official measure and MI is violated when the thresholds are adjusted, and this article uses these two measures and the method as an illustration of why it is vital to introduce MI tests into poverty measurement.