van der Weide, Roy2014-10-022014-10-022014-09https://hdl.handle.net/10986/20332This 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.en-USCC BY 3.0 IGOCAPITA CONSUMPTIONDEVELOPMENT RESEARCHESTIMATORSGEOGRAPHIC TARGETINGHOUSEHOLD INCOMEINCOMEINDEPENDENT VARIABLESMATRICESMATRIXPOVERTY ALLEVIATIONPOVERTY INDICATORSPREDICTIONPROBABILITIESPROBABILITYRARESEARCH METHODSRESEARCH WORKING PAPERSSAMPLE SIZESTANDARD ERRORSSTATASURVEY DATATARGETINGYIELDS10.1596/1813-9450-7028