How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi

This paper assesses the reliability of poverty maps derived from remote-sensing data. Employing data for Malawi, it first obtains small area estimates of poverty by combining the Malawi household expenditure survey from 2010/11 with unit record pop...

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Main Authors:	Van Der Weide, Roy, Blankespoor, Brian, Elbers, Chris, Lanjouw, Peter
Format:	Working Paper
Language:	English English
Published:	World Bank, Washington, DC 2022
Subjects:	POVERTY MAPPING REMOTE SENSING DATA GEOGRAPHY OF POVERTY SMALL AREA POVERTY ESTIMATION POVERTY MONITORING TARGETING TRANSFERS
Online Access:	http://documents.worldbank.org/curated/en/099419209132236954/IDU0fcecbbc004dd3041cc088360d1c57c5ffe04 http://hdl.handle.net/10986/38009

id	okr-10986-38009
recordtype	oai_dc
spelling	okr-10986-380092022-09-15T05:10:47Z How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi Van Der Weide, Roy Blankespoor, Brian Elbers, Chris Lanjouw, Peter POVERTY MAPPING REMOTE SENSING DATA GEOGRAPHY OF POVERTY SMALL AREA POVERTY ESTIMATION POVERTY MONITORING TARGETING TRANSFERS This paper assesses the reliability of poverty maps derived from remote-sensing data. Employing data for Malawi, it first obtains small area estimates of poverty by combining the Malawi household expenditure survey from 2010/11 with unit record population census data from 2008. It then ignores the population census data and obtains a second poverty map for Malawi by combining the survey data with predictors of poverty derived from remote sensing data. This allows for a clean comparison between the two poverty maps. The findings are encouraging - although that assessment depends somewhat on the evaluation criteria employed. The two approaches reveal the same patterns in the geography of poverty. However, there are instances where the two approaches obtain markedly different estimates of poverty. Poverty maps obtained using remote sensing data may do well when the decision maker is interested in comparisons of poverty between assemblies of areas, yet may be less reliable when the focus is on estimates for specific small areas. 2022-09-14T16:50:24Z 2022-09-14T16:50:24Z 2022-09 Working Paper http://documents.worldbank.org/curated/en/099419209132236954/IDU0fcecbbc004dd3041cc088360d1c57c5ffe04 http://hdl.handle.net/10986/38009 English en Policy Research Working Papers;10171 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Policy Research Working Paper Publications & Research Malawi
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	English English
topic	POVERTY MAPPING REMOTE SENSING DATA GEOGRAPHY OF POVERTY SMALL AREA POVERTY ESTIMATION POVERTY MONITORING TARGETING TRANSFERS
spellingShingle	POVERTY MAPPING REMOTE SENSING DATA GEOGRAPHY OF POVERTY SMALL AREA POVERTY ESTIMATION POVERTY MONITORING TARGETING TRANSFERS Van Der Weide, Roy Blankespoor, Brian Elbers, Chris Lanjouw, Peter How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi
geographic_facet	Malawi
relation	Policy Research Working Papers;10171
description	This paper assesses the reliability of poverty maps derived from remote-sensing data. Employing data for Malawi, it first obtains small area estimates of poverty by combining the Malawi household expenditure survey from 2010/11 with unit record population census data from 2008. It then ignores the population census data and obtains a second poverty map for Malawi by combining the survey data with predictors of poverty derived from remote sensing data. This allows for a clean comparison between the two poverty maps. The findings are encouraging - although that assessment depends somewhat on the evaluation criteria employed. The two approaches reveal the same patterns in the geography of poverty. However, there are instances where the two approaches obtain markedly different estimates of poverty. Poverty maps obtained using remote sensing data may do well when the decision maker is interested in comparisons of poverty between assemblies of areas, yet may be less reliable when the focus is on estimates for specific small areas.
format	Working Paper
author	Van Der Weide, Roy Blankespoor, Brian Elbers, Chris Lanjouw, Peter
author_facet	Van Der Weide, Roy Blankespoor, Brian Elbers, Chris Lanjouw, Peter
author_sort	Van Der Weide, Roy
title	How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi
title_short	How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi
title_full	How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi
title_fullStr	How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi
title_full_unstemmed	How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi
title_sort	how accurate is a poverty map based on remote sensing data? : an application to malawi
publisher	World Bank, Washington, DC
publishDate	2022
url	http://documents.worldbank.org/curated/en/099419209132236954/IDU0fcecbbc004dd3041cc088360d1c57c5ffe04 http://hdl.handle.net/10986/38009
_version_	1764488305586470912

How Accurate Is a Poverty Map Based on Remote Sensing Data? : An Application to Malawi

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