GLS estimation and empirical bayes prediction for linear mixed models with Heteroskedasticity and sampling weights: a background study for the POVMAP project

Roy van der Weide ()

No 7028, Policy Research Working Paper Series from The World Bank

Abstract: This note adapts results by Huang and Hidiroglou (2003) on Generalized Least Squares estimation and Empirical Bayes prediction for linear mixed models with sampling weights. The objective is to incorporate these results into the poverty mapping approach put forward by Elbers et al. (2003). The estimators presented here have been implemented in version 2.5 of POVMAP, the custom-made poverty mapping software developed by the World Bank.

Keywords: Statistical&Mathematical Sciences; Crops and Crop Management Systems; Poverty Monitoring&Analysis; Science Education; Scientific Research&Science Parks (search for similar items in EconPapers)
Date: 2014-09-01
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (9)

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