GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project

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 app...

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Main Author:	van der Weide, Roy
Format:	Policy Research Working Paper
Language:	English en_US
Published:	World Bank Group, Washington, DC 2014
Subjects:	CAPITA CONSUMPTION DEVELOPMENT RESEARCH ESTIMATORS GEOGRAPHIC TARGETING HOUSEHOLD INCOME INCOME INDEPENDENT VARIABLES MATRICES MATRIX POVERTY ALLEVIATION POVERTY INDICATORS PREDICTION PROBABILITIES PROBABILITY RA RESEARCH METHODS RESEARCH WORKING PAPERS SAMPLE SIZE STANDARD ERRORS STATA SURVEY DATA TARGETING YIELDS
Online Access:	http://documents.worldbank.org/curated/en/2014/09/20197348/gls-estimation-empirical-bayes-prediction-linear-mixed-models-heteroskedasticity-sampling-weights-background-study-povmap-project http://hdl.handle.net/10986/20332

id	okr-10986-20332
recordtype	oai_dc
spelling	okr-10986-203322021-04-23T14:03:55Z GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project van der Weide, Roy CAPITA CONSUMPTION DEVELOPMENT RESEARCH ESTIMATORS GEOGRAPHIC TARGETING HOUSEHOLD INCOME INCOME INDEPENDENT VARIABLES MATRICES MATRIX POVERTY ALLEVIATION POVERTY INDICATORS PREDICTION PROBABILITIES PROBABILITY RA RESEARCH METHODS RESEARCH WORKING PAPERS SAMPLE SIZE STANDARD ERRORS STATA SURVEY DATA TARGETING YIELDS 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. 2014-10-02T19:40:15Z 2014-10-02T19:40:15Z 2014-09 http://documents.worldbank.org/curated/en/2014/09/20197348/gls-estimation-empirical-bayes-prediction-linear-mixed-models-heteroskedasticity-sampling-weights-background-study-povmap-project http://hdl.handle.net/10986/20332 English en_US Policy Research Working Paper;No. 7028 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank Group, Washington, DC Publications & Research :: Policy Research Working Paper Publications & Research
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	English en_US
topic	CAPITA CONSUMPTION DEVELOPMENT RESEARCH ESTIMATORS GEOGRAPHIC TARGETING HOUSEHOLD INCOME INCOME INDEPENDENT VARIABLES MATRICES MATRIX POVERTY ALLEVIATION POVERTY INDICATORS PREDICTION PROBABILITIES PROBABILITY RA RESEARCH METHODS RESEARCH WORKING PAPERS SAMPLE SIZE STANDARD ERRORS STATA SURVEY DATA TARGETING YIELDS
spellingShingle	CAPITA CONSUMPTION DEVELOPMENT RESEARCH ESTIMATORS GEOGRAPHIC TARGETING HOUSEHOLD INCOME INCOME INDEPENDENT VARIABLES MATRICES MATRIX POVERTY ALLEVIATION POVERTY INDICATORS PREDICTION PROBABILITIES PROBABILITY RA RESEARCH METHODS RESEARCH WORKING PAPERS SAMPLE SIZE STANDARD ERRORS STATA SURVEY DATA TARGETING YIELDS van der Weide, Roy GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project
relation	Policy Research Working Paper;No. 7028
description	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.
format	Publications & Research :: Policy Research Working Paper
author	van der Weide, Roy
author_facet	van der Weide, Roy
author_sort	van der Weide, Roy
title	GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project
title_short	GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project
title_full	GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project
title_fullStr	GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project
title_full_unstemmed	GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project
title_sort	gls estimation and empirical bayes prediction for linear mixed models with heteroskedasticity and sampling weights : a background study for the povmap project
publisher	World Bank Group, Washington, DC
publishDate	2014
url	http://documents.worldbank.org/curated/en/2014/09/20197348/gls-estimation-empirical-bayes-prediction-linear-mixed-models-heteroskedasticity-sampling-weights-background-study-povmap-project http://hdl.handle.net/10986/20332
_version_	1764445053663576064

GLS Estimation and Empirical Bayes Prediction for Linear Mixed Models with Heteroskedasticity and Sampling Weights : A Background Study for the POVMAP Project

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